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Utilizing AI - The Enterprise AI Podcast

Utilizing AI - The Enterprise AI Podcast

By Utilizing AI
AI is getting real, moving out of academia and hyperscale and into the enterprise. Businesses are adopting AI in strategically, and IT companies are deploying AI technologies in their products. This podcast focuses on practical applications of artificial intelligence and machine learning in the modern enterprise datacenter and cloud infrastructure. Hosted by Stephen Foskett of GestaltIT.com, Chris Grundemann of chrisgrundemann.com, and Frederic Van Haren, of HighFens Inc.
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09: Deploying AI Models in the Enterprise with @DataCereal

Utilizing AI - The Enterprise AI Podcast

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3x28: Revisiting Utilizing AI Season 3
Frederic Van Haren and Stephen Foskett look back on all the subjects covered during Season 3 of Utilizing AI. The podcast covered many topics, from religious and ethical implications of AI to the technology that enables machine learning, but one topic that stands out is data science. If data is the key to AI, then the collection, management, organization, and sharing of data is a critical element of making AI projects possible. We also continue our “three questions” tradition by bringing in open-ended questions from Rich Harang of Duo Security, Sunil Samel of Akridata, Adi Gelvan of Speedb, Bin Fan of Alluxio, Professor Katina Michael, and David Kanter of MLCommons. Three Questions: Stephen's Question: Can you think of an application for ML that has not yet been rolled out but will make a major impact in the future? Frederic's Question: What market is going to benefit the most from AI technology in the next 12 months Rich Harang Senior Technical Lead, Duo Security: In an alternate timeline where we didn't develop automatic-differentiation and put it on top of GUPs do this entire deep learning hardware family that we depend on now never got invented. What would the dominat AI/ ML technology be and what would have been different?  Sunil Samel, VP of Pusiness Development, Akriadata: How will new technologies like AI help marginalized members of the communities. Folks like senior citizens, minorities, pepole with disabilities, veterans trying to reenter civilian life? Adi Gelvan, CEO and Co-Founder of Speedb: What do you think the risks of AI are and what is your recommended solution? Bin Fan, Founding Member, Alluxio: Im wondering if AI can help with a humanitarian crisis happening in the future? Katina Michael, Professor, School for the Future of Innovation in Society, Arizona State University: If AI was to self replicate what would be the first thing it would do? David Kanter, Executive Director of MLCommons: what s a problem in the AI world where you are held back by the lack of good publicly available data? Hosts: Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren.  Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 4/25/2022 Tags: @SFoskett, @FredericVHaren,
28:28
April 25, 2022
3x27: Benchmarking AI with MLPerf
How fast is your machine learning infrastructure, and how do you measure it? That's the topic of this episode, featuring David Kanter of MLCommons, Frederic Van Haren, and Stephen Foskett. MLCommons is focused on making machine learning better for everyone through metrics, datasets, and enablement. The goal for MLPerf is to come up with a fair and representative benchmark to allow the makers of ML systems to demonstrate the performance of their solutions. They focus on real data from a reference ML model that defines correctness, review the performance of a solution, and post the results. MLPerf started with training then added inferencing, which is the focus for users of ML. We must also consider factors like cost and power use when evaluating a system, and a reliable bench Links: MLCommons.org Connect-Converge.com Three Questions: Frederic: Is it possible to create a truly unbiased AI? Stephen: How big can ML models get? Will today's hundred-billion parameter model look small tomorrow or have we reached the limit? Andy Hock, Cerebras: What AI application would you build or what AI research would you conduct if you were not constrained by compute? Gests and Hosts David Kanter is the Executive Director of MLCommons. You can connect with David on Twitter at @TheKanter and on LinkedIn. You can also send David an email at david@mlcommons.org.  Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 4/12/2022 Tags: @SFoskett, @FredericVHaren, 
43:28
April 12, 2022
3x26: DataOps - Putting the Data in Data Science
The quality of an AI application depends on the quality of the data that feeds it. Sunil Samel joins Frederic Van Haren and Stephen Foskett to discuss DataOps and the importance of data quality. When we consider data-centric AI, we must consider all aspects of the data pipeline, from storing, transporting, and understanding to controlling access and cost. We must look at the data needed to train our models, think about the desired outcomes, and consider the sources and pipeline needed to get that result. We must also decide how to define quality: Do we need a variety of data sources? Should we reject some data? How does the modality of the data type change this definition? Is there bias in what is included and excluded? Data pipelines are usually simple, ingesting and storing data from the source, slicing and preparing it, and presenting it for processing. But DataOps recognizes that the data pipeline can get very complicated and requires understanding of all these steps as well as adaptation from development to production. Three Questions: Frederic: Do you think we should expect another AI winter? Stephen: When will we see a full self-driving car that can drive anywhere, any time? Mike O'Malley, Seneca Global: Can you give an example where an AI algorithm went terribly wrong and gave a result that clearly wasn’t correct? Gests and Hosts Sunil Samel, VP of Products at Akridata. Connect with Sunil on LinkedIn or email him at sunil.samel@akridata.com. Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 3/29/2022 Tags: @SFoskett, @FredericVHaren
37:16
March 29, 2022
3x25: The Unique Challenges of ML Training Data with Bin Fan
Machine learning is unlike any other enterprise application, demanding massive datasets  from distributed sources. In this episode, Bin Fan of Alluxio discusses the unique challenges of distributed heterogeneous data to support ML workloads with Frederic Van Haren and Stephen Foskett. The systems supporting AI training are unique, with GPUs and other AI accelerators distributed across multiple machines, each accessing the same massive set of small files. Conventional storage solutions are not equipped to serve parallel access to such a large number of small files, and they often become a bottleneck to performance in machine learning training. Another issue is moving data across silos, storage systems and protocols, which is impossible with most solutions. Three Questions: Frederic: What areas are blocking us today to further improve and accelerate AI? Stephen: How big can ML models get? Will today's hundred-billion parameter model look small tomorrow or have we reached the limit? Sara E. Berger: With all of the AI that we have in our day-to-day, where should be the limitations? Where should we have it, where shouldn't we have it, where should be the boundaries? Gests and Hosts Bin Fan, Founding Member of Alluxio Inc. Connect with Bin on LinkedIn and on Twitter @BinFan. Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 3/15/2022 Tags: @SFoskett, @FredericVHaren, @BinFan, @Alluxio
35:33
March 15, 2022
3x24: Challenges of Building Successful ML Programs
With so many AI tools available, it can be a challenge to integrate everything into a productive platform. Orly Amsalem of cnvrg.io joins Frederic Van Haren and Stephen Foskett to discuss the challenges of managing data and resources for AI training, development, management, and deployment. Orly discusses her journey from software development to AI and the challenges people face. Many in the AI community are following the same path, and are looking for tools like cnvrg to help them bring AI to their day to day work. AL blueprints, provided by cnvrg and the community, can help developers and data scientists get started with AI projects. In a recent survey, only 10% of developers said training was their main challenge; nearly every one said that deploying a model to production was the biggest. Orly then discusses the main bottlenecks to MLOps in production and how to break through and normalize AI in the enterprise. Links: "Five Ways to Shift to AI-First" Three Questions: Frederic: When do you think AI will diagnose a patient as accurately as (or better than) a human doctor? Stephen: Is MLOps a lasting trend or just a step on the way for ML and DevOps becoming normal? Eitan Medina, Habana Labs: If you should choose something for AI to do for you in your day-today life, what would it be? Gests and Hosts Orly Amsalem, VP of AI Innovation & Business Development at cnvrg.io. Read "Five Ways to Shift to AI-First" here.  Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 3/01/2022 Tags: @SFoskett, @FredericVHaren, @cnvrg_io
38:27
March 01, 2022
3x23: How Algorithmic Bias in ML Affects Marketing
As machine learning is used to market and sell, we must consider how biases in models and data can impact society. Arizona State University Professor Katina Michael joins Frederic Van Haren and Stephen Foskett to discuss the many ways in which algorithms are skewed. Even a perfect model will produce biased answers when fed input data with inherent biases. How can we test and correct this? Awareness is important, but companies and governments should take active interest in detecting bias in models and data. Links: "Algorithmic bias in machine learning-based marketing models" Three Questions: Frederic: When will AI be able to reliably detect when a person is lying? Stephen: Is it possible to create a truly unbiased AI? Tom Hollingsworth of Gestalt IT: Can AI ever recognize that it is biased and learn how to overcome it? Gests and Hosts Katina Michael, Professor in the School for the Future of Innovation in Society and School of Computing and Augmented Intelligence at Arizona State University. Read here paper here in the Journal of Business Research. You can find more about her at KatinaMichael.com.  Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 2/21/2022 Tags: @SFoskett, @FredericVHaren
39:25
February 21, 2022
3x22: The State of AI and the Enterprise
With AI technology changing so quickly, we often need to step back and take a big picture look at the market. In this episode, Manoj Suvarna of Deloitte joins Frederic Van Haren and Stephen Foskett to discuss the many products and applications of AI in the enterprise. It is important for business executives to survey the many ways that AI and data science are being applied across the enterprise and try to find ways to leverage this work in other areas. Deloitte recently conducted a survey of companies around the world to get a sense of the many ways AI is being adopted. 92% of those surveyed said that AI is a competitive area these days, and 83% realize the value of multiple ecosystems. A majority of businesses see AI as a strategic differentiator that they want to invest in, while most of the rest are trying to determine the value of AI to the business. Links: "State of AI and the Enterprise, Fourth Edition"  Three Questions: Frederic: Do you believe AI products and models should be regulated by an independent organization? Stephen: Are there any jobs that will be completely eliminated by AI in the next five years? Amanda Kelly of Streamlit: What is a tool that you were personally using a few years ago but you find you are not using anymore? Gests and Hosts Manoj Suvarna, Managing Director, AI Ecosystems, Deloitte. Connect with Manoj on LinkedIn or on Twitter at @MSuvarna Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 2/15/2022 Tags: @SFoskett, @FredericVHaren, @MSuvarna
41:23
February 15, 2022
3x21: Under the Hood of the Data Engine with Speedb
Data is the most important element of artificial intelligence, but how is that data managed and stored? In this episode of Utilizing AI, Adi Gelvan of Speedb goes deep under the hood to take a look at the data engine along with Frederic Van Haren and Stephen Foskett. Facebook's RocksDB provides the basic storage for many webscale projects, managing metadata in a massive scale. Because of the inherent limits of RocksDB, most cloud applications shard data across many data engines. But Speedb takes a different approach, bringing more advanced storage technology to build a compatible data engine. A good data engine can massively improve overall performance, and data scientists and AI engineers would be wise to consider the storage engine, not just the processing components and models. Three Questions: Frederic Van Haren: In what areas will AI have little to no impact? Stephen: Is AI just a new aspect of data science or is it truly a unique field? Rob Telson of BrainChip: Where do you see AI having the most beneficial impact on our society? Gests and Hosts Adi Gelvan, Co-Founder and CEO of Speedb. Find out more at  www.speedb.io or reach out to Adi at adi@speedb.io.  Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 2/08/2022 Tags: @SFoskett, @FredericVHaren, @speedb_io
36:30
February 08, 2022
3x20: GPUs and AI accelerators - What is the difference?
AI is everywhere, and so are AI accelerators, from CPU to GPU to special-purpose hardware. Eitan Medina, Chief Operating Officer of Habana Labs, an Intel Company, joins Frederic Van Haren and Stephen Foskett to discuss the various specialized AI processors being developed today. Habana Labs has created a special-purpose AI training and inferencing processor with many unique features. Since deep learning is done at scale today, it makes sense to integrate enterprise networking with an accelerator like Habana Gaudi to increase overall system performance thanks to rDMA over Ethernet (RoCE) technology. Habana Gaudi is optimized for matrix math and also includes a fully-programmable vector core for Tensor processing. In October 2021, Amazon AWS launched the new DL1 instance based on Habana Gaudi, offering more performance than many GPU-based instances for a much lower total cost. Habana is very developer-focused as well, working with partners, data scientists, and end users to expand the accessibility of the platform in channels like GitHub and their own developer forum. Habana will soon introduce a 7 nm Gaudi 2 processor with much-improved performance and power efficiency. Habana Labs is also making their hardware more accessible thanks to their SynapseAPI and recently acquired cnvrg.io to bring a higher-level MLOps pipeline to AI. Three Questions: Frederic: At what point in time do you believe AI will be able to show compassion (like humans) if ever? Stephen: How big can ML models get? Will today's hundred-billion parameter model look small tomorrow or have we reached the limit? Edward Cui Founder of Graviti: Which will be more important in the future: Bigger and bigger ML or smaller ML? Gests and Hosts Eitan Medina, Chief Operating Officer of Habana Labs, an Intel Company. Visit habana.ai to learn more. Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 2/01/2022 Tags: @SFoskett, @FredericVHaren, @HabanaLabs
42:24
February 01, 2022
3x19: How AI Can Help in Medical Care and Pain Management with Sara E. Berger
Among many surprising applications, AI can be used for pain management and medical care. Neuroscientist Sara E. Berger of IBM joins Chris Grundemann and Stephen Foskett to discuss applications of machine learning in medical care. Pain management is a deeply personal field, but there are so many different data points that it can be difficult to see patterns that lead to positive outcomes. Machine learning can assist in sorting and selecting treatments, bringing in different sensors and data types to help patients. The more we see pain in a multi-disciplinary lens, and the more understanding we bring, the better the outcome for patients. Three Questions: Chris: How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Stephen: Is it possible to create a truly unbiased AI? Sriram Chandrasekaran, Professor at the University of Michigan: What do you think is the biggest AI technology that you can think of that will transform medicine in the future? Gests and Hosts Sara E. Berger, Research Staff Member at IBM and Neuroscientist. Connect with Sara on LinkedIn.  Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 1/25/2022 Tags: @IBM, @SFoskett, @ChrisGrundemann 
40:54
January 25, 2022
3x18: AI Everywhere, Even in Surprising Places with BrainChip
BrainChip's neuromorphic AI technology has long been the talk of the industry, and now the Akida processor is available for purchase. We invited Rob Telson, VP of Worldwide Sales for BrainChip, to return to the Utilizing AI podcast to give Chris Grundemann and Stephen Foskett an update on the Akida processor. As of today, Akida is available for use by developers and hobbyists to explore neuromorphic compute at the edge. BrainChip enables five sensor modalities: Vision, hearing, touch, olfactory, and taste. BrainChip's architecture allows incremental on-chip learning at extremely low power, potentially bringing this capability to some surprising places, from home appliances to the factory floor. Another differentiator of the BrainChip solution is its event-based architecture, which can trigger based on events rather than sending a continual stream of data. As of today, the BrainChip Akida AKD1000 PCIe development board is available for purchase so everyone can try out the technology. Three Questions: Chris: When will we see a full self-driving car that can drive anywhere, any time? Stephen: Are there any jobs that will be completely eliminated by AI in the next five years? Girard Kavelines: What is it that scares you about AI in today's industry? Links: shop.brainchipinc.com Gests and Hosts Rob Telson, Vice President, Worldwide Sales, BrainChip. You can find out more information at shop.brainchip.com. For questions you can email sales@brainchip.com. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 1/18/2022 Tags: @BrainChip_inc, @SFoskett, @ChrisGrundemann 
37:25
January 18, 2022
3x17: Why the Heck Even Use Deep Learning?
Although it’s a powerful tool, deep learning is perhaps over-used in modern applications. In this episode of the Utilizing AI podcast, Rich Harang joins Chris Grundemann and Stephen Foskett to discuss the various reasons people use AI, both good and bad. In a November Twitter thread, Rich posited that the following conditions were required to use AI for real: The cost of errors must be extremely low, the decision needs to be possible but expensive, there needs to be the same kind of decision frequently, there needs to be a benefit and be better than a simple rule, you have to not care how it got the answer, the base rate must be close to even, you need a steady stream of data for training, and you must match the size and cost of the model to the application. On the other hand, these same considerations can point us to problem sets that make a great match for DL, and we should focus on using the right tool for the job. Three Questions: Chris Grundemann: Are there any jobs that will be completely eliminated by AI in the next five years? Stephen Foskett: How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Adam Probst of ZenML: What percentage of companies will be using ML in five years? Links: Rich’s Twitter Thread: https://twitter.com/rharang/status/1465340190919217153 Sara Hooker’s Paper, “The Hardware Lottery”: https://hardwarelottery.github.io Gests and Hosts Rich Harang, Senior Technical Lead at Duo Security. Connect with Rich on Twitter at @RHarang. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 1/11/2022 Tags: @RHarang, @SFoskett, @ChrisGrundemann 
41:20
January 11, 2022
3x16: Utilizing AI in 2022 with Chris Grundemann and Frederic Van Haren
AI is now widespread, and companies are starting to look at the real-world impact of machine learning. In this special episode of the Utilizing AI podcast, the three hosts look forward to AI in 2022 and revisit some of our guest questions from season three. First, we turn to the specific markets and verticals served by AI applications. We feel that datasets and models will increasingly be focused on specific business uses instead of being general-purpose tools. Next, we consider how the AI industry is increasingly concerned about ethics, bias, and privacy of data. Industry leaders like Timnit Gebru and Cynthia Rudin are showing how important social responsibility is to artificial intelligence. Finally we turn to the continuing progress seen in AI technology. New methodologies, larger models, and increasingly critical real-time applications are transforming the technology, and ML hardware and instructions are everywhere from mobile devices to the datacenter and the cloud. "Three" Questions: Chris from Tony Pikeday: Can AI ever teach us to be more human? Frederic from Sriam Chandrasakren: What do you think is the biggest AI technology that will transform medicine in the future? Chris from Leon Adato: What responsibility do you think IT folks have to insure the things that we build are etihical? Frederic from Amanda Kelly: What is a tool that you were personally using a few years ago but you find you are not using anymore? Chris from Ben Taylor: Are you living up to your potential legacy? Frederic from Girard Kavelines: What scares you the most about AI? Stephen from Chris: What do you think will be the most surprising thing to come out of AI in the next three years?  Stephen from Frederic: When do you think AI will be able to automatically identify if an AI model is ethical or not? Stephen from Chris: What do you think is the most over hyped application of AI people are talking about today? Hosts Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 1/4/2022 Tags: @ChrisGrundemann, @SFoskett, @FredericVHaren  
35:12
January 04, 2022
3x15: Utilization of Shadow AI with Run: AI
Shadow IT is as old as our profession, so it's no surprise that shadow AI is becoming a major issue. In this episode of Utilizing AI, Ronen Dar and Gijsbert Janssen van Doorn join Frederic Van Haren and Stephen Foskett to discuss resource utilization and shadow AI. One of the biggest issues with shadow IT is the low utilization of these resources that can come when they are purchased and used by a single corporate group or application. This is true both on-premises and in the cloud. But even if enterprise IT operations and infrastructure groups can come to understand AI, they must offer a compelling AI solution if they will be able to get control. The easiest way to do this is to deploy a much larger centralized solution than any group could procure on their own and deliver it with a flexible cloud-like access method. Another issue with shadow AI is that it often relies on a single individual and is difficult to reproduce, put into production, or scale. Three Questions: Frederic: Is it possible to create a truly unbiased AI? Stephen: Is MLOps a lasting trend or just a step on the way for ML and DevOps becoming normal? Tony Paikeday, Nvidia: Can AI ever teach us to be more human? Guests and Hosts Ronen Dar, CTO and Co-Founder of Run: AI. Connect with Ronen on LinkedIn. Gijsbert Janssen van Doorn, Director of Technical Product Marketing at Run: AI. Connect with Gijsbert on LinkedIn.  Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 12/21/2021 Tags: @runailabs, @SFoskett, @FredericVHaren  
40:44
December 21, 2021
3x14: What Scares InfoSec About AI? With Girard Kavelines
AI is coming fast to the information security world, both in terms of tools and threats. In this episode, InfoSec professional Girard Kavelines discusses the reality of AI in security with Chris Grundemann and Stephen Foskett. With AI assistance on both sides of the security divide, will we see an escalation of attack and defense? On the defense side, threats have evolved to advanced attacks that look like system processes and legitimate connections, and machine learning can help process more data than ever before. ML-based systems can also judge unknown threats that a rules-based system would never catch. On the other hand, we are already seeing AI used to generate more effective attacks, from phishing to fuzzing APIs. Three Questions: Chris Grundemann: Are there any jobs that will be completely eliminated by AI in the next five years? Stephen Foskett: Can you think of any fields that have not yet been touched by AI? Amanda Kelly, Streamlit: What is a tool that you were personally using a few years ago but you are not using anymore? Links: TechHouse570- Cisco Champion Highlights Gests and Hosts Girard Kavelines, Founder of TechHouse570. Connect with Girard on LinkedIn and on Twitter at @GKavelines. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 12/14/2021 Tags: @GKavelines, @SFoskett, @ChrisGrundemann 
34:22
December 14, 2021
3x13: AI is a Creativity Maximizer with Ben Taylor of DataRobot
Many of the tasks we perform on a daily basis are beneath our abilities, and these are the ideal targets for AI. In this episode, Ben Taylor of DataRobot joins Frederic Van Haren and Stephen Foskett to talk about AI as a creativity maximizer. Business people too often get stuck in a process rather than innovating, from office work to manufacturing to R&D, and all of these can be augmented by AI-based tools. The most successful companies have hundreds or thousands of AI initiatives across the entire business to help identify opportunities for the technology to help employees be more successful. There is an inherent push and pull between small tactical projects and big strategic ones, and we have to consider the level of effort and the impact of AI projects. Three Questions Frederic: When will we see a full self-driving car that can drive anywhere, any time? Stephen: Is AI just a new aspect of data science or is it truly a unique field? Mike O'Malle, SVP, Seneca Global: Can you give an example where an AI algorithm went terribly wrong and gave a result that clearly wasn’t correct? Guests and Hosts Ben Taylor, Chief AI Evangelist, DataRobot and host of the More Intelligent Tomorrow podcast. Connect with Ben on LinkedIn or on Twitter at @BenTaylorData Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 12/07/2021 Tags: @DataRobot ,@BenTaylorData, @FredericVHaren, @SFoskett
39:03
December 07, 2021
3x12: Democratizing Unstructured Data at Scale with Edward Cui of Graviti
Machine learning applications require massive datasets, but it can be challenging to build and store large amounts of unstructured data. In this episode of Utilizing AI, Edward Cui of Graviti discusses his creation of an open repository for unstructured data with Frederic Van Haren and Stephen Foskett. Coming from Uber's self-driving organization, Cui realized the value of data and the challenge of storing massive amounts of unstructured data, so he created the Graviti platform and made it available for free to open datasets. These datasets enable development of a variety of applications, from agriculture and environmental science to gaming and robotics. To address the challenge of data sharing and quality, Graviti is working with the Linux Foundation on the OpenBytes project. Three Questions Frederic: Are there any jobs that will be completely eliminated by AI in the next five years? Stephen: When will we see a full self-driving car that can drive anywhere, any time? Tom Hollingsworth, Gestalt IT: Can AI ever recognize that it's biased and learn how to overcome it? Guests and Hosts  Edward Cui, Founder of Graviti. You can follow Graviti on LinkedIn or twitter at @graviti_ai. You can also email Graviti at contact@graviti.com. Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 11/30/2021 Tags: @graviti_ai, @FredericVHaren, @SFoskett
38:39
November 30, 2021
3x11: Putting Data Science Into Everyone's Hands with Amanda Kelly of Streamlit
Data science and machine learning developments can't have an impact if they don't get into everyone's hands. In this episode, Amanda Kelly of Streamlit joins Chris Grundemann and Stephen Foskett to talk about the challenges and opportunities in bringing data science to everyone's hands. How can we enable marketing, sales, marketing, and other elements of the business to access data and make informed decisions themselves? Data science teams have to meet business people where they are to better answer their questions rather than trying to create a perfect model in a vacuum. Streamlit helps to productize python scripts with a complete and flexible front-end and easy deployment, making it easy to share and iterate. These micro apps foster collaboration and interaction between data science and the business. Three Questions Stephen: Is AI just a new aspect of data science or is it truly a unique field? Chris: Can you think of an application for ML that has not yet been rolled out but will make a major impact in the future? Leon Adato: What responsibility do you think IT folks have to insure the things that we build are ethical? Gests and Hosts Amanda Kelly, Co-Founder of Streamlit.  Follow her thoughts on the Streamlit Blog.  Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 11/16/2021 Tags: @streamlit, @SFoskett, @ChrisGrundemann
37:58
November 16, 2021
3x10: Democratizing Data Infrastructure for ML with Melisa Tokmak of Scale AI
Data is the most important component of AI implementation, but most companies neglect data infrastructure and focus too much on the ML models. In this episode of the Utilizing AI podcast, Melisa Tokmak of Scale AI joins Frederic Van Haren and Stephen Foskett to discuss the democratization of data infrastructure to support machine learning projects. Enterprises often don't have a good understanding of their data, and this can undermine the success of an AI project, and this must be addressed before the project can proceed. Companies also must consider the quality of their data, beginning with a definition of the metrics that will properly assess the data foundation for their ML models. Three Questions Frederic: Will we ever see a Hollywood-style “artificial mind” like Mr. Data or other characters? Stephen: How big can ML models get? Will today's hundred-billion parameter model look small tomorrow or have we reached the limit? Alexandrine Royer: What do you think is one of the biggest ethical challenges that comes with AI that often goes under-discussed and should be more present in conversations surrounding the deployment of AI models? Guests and Hosts Melisa Tokmak, GM at Scale AI. Connect with Melisa on LinkedIn or on Twitter @MelisaTokmak.  Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 11/09/2021 Tags: @MelisaTokmak, @scale_AI, @SFoskett, @FredericVHaren  
44:54
November 09, 2021
3x09: Focusing MLOps on the Data Scientist with Adam Probst of ZenML
Many data scientists and ML engineers have faced the challenge of putting AI models into production, and this is the core of MLOps. In this episode, Adam Probst, Co-Founder of ZenML, joins Frederic Van Haren and Stephen Foskett to discuss the challenges of putting ML models into production.  Machine learning pipelines are inherently complex and fragile and require feedback and tuning, and this requires a new approach with continuous improvement and tight integration. Although reminiscent of DevOps, MLOps demands even more collaboration between IT operations, developers and data scientists, and lines of business. ZenML prepares ready-to-use MLOps infrastructure to these groups so they can focus on the model rather than the platform. Three Questions Stephen: How big can ML models get? Will today's hundred-billion parameter model look small tomorrow or have we reached the limit? Frederic: Is MLOps a lasting trend or just a step on the way for ML and DevOps becoming normal? Zach DeMeyer: What's the most innovative use of AI you've seen in the real world? Guests and Hosts Adam Probst, Co-Founder, ZenML. Connect with ZenML on GitHub, LinkedIn and on Twitter @zenml_io.  Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 11/02/2021 Tags: @zenml_io, @SFoskett, @FredericVHaren           
37:45
November 02, 2021
3X08: The Invisible Workers Behind the AI Algorithms with Alexandrine Royer
AI is spreading around the world, both in terms of technology and workforces. Many tasks that support artificial intelligence are being outsourced globally, with many workers exploited or mistreated as they take up the opportunities offered by the information economy. In this episode, Alexandrine Royer, Student Fellow at the Leverhulme Center for the Future of Intelligence, joins Chris Grundemann and Stephen Foskett to discuss the prospects for global AI workers. The situation is akin to globalization of manufacturing or shipping, with powerful corporations exploiting differing regulations and approaches around the world. Given this situation, collective action and advocacy might be the only way for workers to improve their situation. Three Questions Stephen: How long will it take for a conversational AI to pass the Turing test and fool an average person? Chris: Are there any jobs that will be completely eliminated by AI in the next five years? Tony Paikeday, Senior Director of AI Systems at NVIDIA: Can AI ever teach us to be more human? Links   The urgent need for regulating global ghost work (brookings.edu)   The wellness industry’s risky embrace of AI-driven mental health care (brookings.edu) Guests and Hosts Alexandrine Royer, Student Fellow at the Leverhulme Center for the Future of Intelligence. Connect with Alexandrine on LinkedIn.  Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 10/26/2021 Tags: @SFoskett, @ChrisGrundemann
35:18
October 26, 2021
3X07: The Trillion-Parameter ML Model with Cerebras Systems
Demand for AI compute is growing faster than conventional systems architecture can match, so companies like Cerebras Systems are building massive special-purpose processing units. In this episode, Andy Hock, VP of Product for Cerebras Systems, joins Frederic Van Haren and Stephen Foskett to discuss this new class of hardware. The Cerebras Wafer-Scale Engine (WSE-2) has 850,000 processors on a single chip the size of a dinner plate, along with 40 GB of SRAM and supporting interconnects. But Cerebras also has a software stack that integrates with standard ML frameworks like PyTorch and TensorFlow. Although the trillion-parameter model is a real need for certain applications, platforms need to be flexible to support both massive-scale and more mainstream workloads, and this is a focus for Cerebras as well. Three Questions Frederic's Question: How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Stephen's Question: Will we ever see a Hollywood-style “artificial mind” like Mr. Data or other characters? Leon Adato, host of the Technically Religious Podcast: I'm curious, what responsibility do you think IT folks have to insure the things that we build are ethical? Guests and Hosts Andy Hock, VP of Product at Cerebras Systems. Connect with Andy on LinkedIn. Follow Cerebras Systems on Twitter at @CerebrasSystems. Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 10/19/2021 Tags: @CerebrasSystems, @SFoskett, @FredericVHaren
40:15
October 19, 2021
3x06: Fighting Nightmare Bacteria Using AI with Sriram Chandrasekaran
It is sometimes hard to see how AI technology benefits society, but applications like drug discovery really bring the power home. Sriram Chandrasekaran, Assistant Professor of Biochemical Engineering at the University of Michigan, is using machine learning to assess the properties of drug candidates to fight antibiotic-resistant bacteria. Presented with millions of different potential drugs, machine learning can identify the few most useful to be tested clinically. Because it tries everything and anything without preconceived biases, ML can uncover novel combinations that researchers might never notice. We also discuss specifics of the AI environment, including the preference for random forests to deep learning, privacy concerns, bias in datasets, and the interplay between domain expertise and data science. Three Questions Stephen's Question: Can you think of an application for ML that has not yet been rolled out but will make a major impact in the future? Chris's Question: How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Zach DeMeyer, Gestalt IT: What's the most innovative use of AI you've seen in the real world Guests and Hosts Sriram Chandrasekaran, Assistant Professor of Biomedical Engineering at University of Michigan. Connect with Sriram on LinkedIn or on Twitter at @sriram_lab. You can also email Sriram at csriram@umich.edu. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 10/12/2021 Tags: @sriram_lab , @SFoskett, @ChrisGrundemann
35:28
October 12, 2021
3x05: The Philosophical and Religious Aspects of AI
In this episode, we consider the moral and ethical dimensions of artificial intelligence. Leon Adato, host of the Technically Religious podcast, joins Frederic Van Haren and Stephen Foskett to consider the boundaries of technology and the choices we make. Leon suggests that the unintentional, unconscious, and undetectable impact of AI is the key consideration, not the science fiction questions of AI and religion. Many religions seek to apply the lessons of the past to new technologies and situations, and these can provide a unique insight into the question of the way we as a society should proceed. We must also re-evaluate the systems we put in place to ask if the machine is doing what we wanted it to do and what the side effects are. Three Questions Can you think of any fields that have not yet been touched by AI? Will we ever see a Hollywood-style “artificial mind” like Mr. Data or other characters? Tom Hollingsworth: Can AI ever recognize that it's biased and learn how to overcome it? Guests and Hosts Leon Adato, Head Geek at SolarWinds and host of the Technically Religious podcast. Follow Leon at adatosystems.com. You can also connect with Leon on LinkedIn or on Twitter @LeonAdato.  Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 10/05/2021 Tags: @LeonAdato, @SFoskett, @FredericVHaren
39:46
October 05, 2021
3x04: How AI and ML are used in Network Management with Tom Hollingsworth of Gestalt IT
Local and wide-area networks can get complex very quickly, so it's no surprise that AI-powered network management is making a huge impact in the enterprise. In this episode, Tom Hollingsworth, who runs Networking Field Day for Gestalt IT, joins Chris Grundemann and Stephen Foskett to discuss applications of AI in network monitoring and management. Solutions like Mist from Juniper Networks give network administrators the ability to ask questions get insight using the power of machine learning. This proactive observability stance allows network administrators to answer difficult questions rather than just keeping things running. AI truly has become a co-pilot for network engineers, helping transform their career once they embrace it. Another use of AI in networking is exemplified by Forward Networks, which can model and test networking concepts before they are pushed to a live environment. Another company, HPE's Aruba, is leveraging AI in edge computing while their Net Insight suggesting best practices. SD-WAN companies are also using AI to accelerate applications, and AI is finding applications in wireless networks. Finally we take on "AI washing" and the need to be skeptical when companies say their solutions use AI. Three Questions Is MLOps a lasting trend or just a step on the way for ML and DevOps becoming normal? Are there any jobs that will be completely eliminated by AI in the next five years? Tony Paikeday of NVIDIA asks, can AI ever teach us to be more human? Guests and Hosts Tom Hollingsworth, Event Lead for Networking Field Day. Follow Tom's thoughts at networkingnerd.net and Gestaltit.com. You can also connect with Tom on Twitter at @NetworkingNerd.  Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 9/28/2021 Tags: @GestaltIT, @TechFieldDay, @SFoskett, @ChrisGrundemann, @NetworkingNerd
35:12
September 28, 2021
3x03: Platform Considerations For Deploying AI At Scale with Tony Paikeday of NVIDIA
Enterprises are working to simplify the process of deploying and managing systems to support AI applications. That's what NVIDIA's DGX architecture is designed to do, and what we'll talk about on this episode. Frederic Van Haren and Stephen Foskett are joined by Tony Paikeday, Senior Director, AI Systems at NVIDIA, to discuss the tools needed to operationalize AI at scale. Although many NVIDIA DGX systems have been purchased by data scientists or directly by lines of business, it is also a solution that CIOs have embraced. The system includes NVIDIA GPUs of course but also CPU, storage, and connectivity and all of this is held together with software that makes it easy to use as a unified solution. AI is a unique enterprise workload in that it requires high storage IOPS and low storage and network latency. Another issue is balancing these needs to scale performance in a linear manner as more GPUs are used, and this is why NVIDIA relies on NVLink and NVSwitch as well as DPU and InfiniBand to connect the largest systems Three Questions  How big can ML models get? Will today's hundred-billion parameter model look small tomorrow or have we reached the limit? Will we ever see a Hollywood-style “artificial mind” like Mr. Data or other characters? Can you give an example where an AI algorithm went terribly wrong and gave a result that clearly wasn’t correct? *Question asked by Mike O'Malley of SenecaGlobal. Guests and Hosts Tony Paikeday, Senior Director Senior Director, AI systems at NVIDIA. Connect with Tony on LinkedIn or on Twitter at @TonyPaikeday.  Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 9/21/2021 Tags: @TonyPaikeday, @nvidia, @SFoskett, @FredericVHaren
41:51
September 21, 2021
3x02: Using AI to Assess Risk with Mike O'Malley of SenecaGlobal
Machine learning excels at finding needles in haystacks, even unexpected ones, and this helps organizations to assess risks. In this first episode of season 3, Utilizing AI hosts Stephen Foskett and Chris Grundemann discuss risk analysis with Mike O'Malley of SenecaGlobal. ML is extremely good at detecting outliers and adapting to changing patterns, and this can yield excellent results in applications like financial pattern recognition. But AI lacks real understanding, and this can limit the use cases for ML. Three Questions Are there any jobs that will be completely eliminated by AI in the next five years? What’s the strangest or most amusing application for ML that you have encountered? Can you think of any fields that have not yet been touched by AI? Guests and Hosts Mike O'Malley, SVP at SenecaGlobal. Connect with Mike on LinkedIn.  Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 9/14/2021 Tags: @senecaglobal, @SFoskett, @ChrisGrundemann
29:28
September 14, 2021
3x01: A Look Back at Season 2
Welcome back to another season of Utilizing AI! In this first episode of season 3, we are taking a look at some of the most memorable moments of season 2. We started season 2 by talking about AI as a co-pilot in the first few episodes and this theme continued throughout the season. AI making our jobs easier was a common discussion we had through the course of the season. Another common discussion had throughout the season was how to make implementing AI easier through tools and platforms. We also discussed the duality of working in AI vs. working on AI. Having AI be more accessible and easier to use was yet another common theme we saw throughout season 2. Some of the most memorable guests that have stuck with our host and co-hosts include Saiph Savage, Sofia Trejo, Ayodele Odubela, and Anti Raman. Speaking of guests, Frederic Van Haren, who is one of our show’s co-hosts, was an early season 2 guest. Our most listened to episode was the discussion we had with BrainChip. Three Questions This season, we are continuing with our three questions tradition but we’re throwing in a twist! We are offering the opportunity for our guests and our listeners to pose questions that we may use in a future episode. Each guest will be asked to record a question that may be used to ask a future guest. We also want to offer our listeners the opportunity to become a part of the podcast. If you would like your question asked, send us an email at Host@Utilizing-AI.com and let us know you would like to participate! Hosts Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.  Date: 9/7/2021 Tags:  @SFoskett, @ChrisGrundemann, @FredericVHaren           
42:48
September 07, 2021
2x31: Taking Artificial Intelligence on the Road with Christophe Couvreur of Cerence
Most people think AI in vehicles means autonomous driving, but there are a lot of other applications for the technology. Ever since Mercedes-Benz introduced Linguatronic voice response in the 1990s, vehicles have included verbal control and feedback mechanisms. In this episode, Christophe Couvreur discusses the lessons of bringing AI to vehicles based on his experience at Nuance spin-off, Cerence. As these systems have improved, they have reached the so-called uncanny valley, where people become frustrated by their limitations despite tremendous advancement over the last decade or so. Looking beyond voice response, we can see many driver assistance technologies added to vehicles in the future, and many of these will be ML powered as well. Three Questions: When will we see a full self-driving car that can drive anywhere, any time? How long will it take for a conversational AI to pass the Turing test and fool an average person? How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Guests and Hosts Christophe Couvreur, VP of Product at Cerence Inc. Connect with Christophe on LinkedIn here and the company page Cerence.com. Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.           Date: 8/3/2021 Tags: @CerenceInc, @SFoskett, @FredericVHaren
40:51
August 03, 2021
2x30: Bringing AI to the Executive Suite with Josh Epstein of AtScale
Businesses have long tried to use data to drive decisions, but over the last few years new big data and AI capabilities have appeared. In this episode, Josh Epstein of AtScale discusses the opportunities that enterprise AI brings to drive business decisions. Although executives might not know the details of AI models, they can certainly benefit from the forecasts and recommendations these tools deliver. One benefit of these systems is that they can bring in more diverse data to uncover real value from areas typically outside the sight of executives. Three Questions Are there any jobs that will be completely eliminated by AI in the next five years? Will we ever see a Hollywood-style “artificial mind” like Mr. Data or other characters? Can you think of an application for ML that has not yet been rolled out but will make a major impact in the future? Guests and Hosts Josh Epstein, Chief Marketing Officer at AtScale. Connect with Josh on LinkedIn. Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.         Date: 7/27/2021 Tags: @AtScale, @SFoskett, @FredericVHaren
37:01
July 27, 2021
2x29: How AI Can Help Displaced Workers with Saiph Savage
Although we usually focus on the ways AI can displace workers, this technology can also create new jobs and help them. In this episode, Saiph Savage joins Chris Grundemann and Stephen Foskett to discuss the many ways AI can help displaced workers. One new type of job created by AI is in the area of model training, and this can help develop digital skills and improve the lives of workers. Digital labor platforms tend to be opaque, however, and we must audit them to understand the wages paid, exposure to negative content, and invisible labor workers do to continue to use these tools. Yet despite these shortcomings, many workers report positive experiences, in terms of life/work balance, opportunity, and flexibility. Researchers like Savage are monitoring these opportunities and developing tools to help workers and policymakers fairly judge the costs and benefits of participating. Ultimately, these jobs can become a stepping stone to digital careers and further opportunities. References Saiph Savage’s Super Turker paper  Flexible Work and Personal Digital Infrastructures  Turker Tales: Integrating Tangential Play into Crowd Work  “Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass” by Mary L. Gray and Siddharth Suri (book) Three Questions How long will it take for a conversational AI to pass the Turing test and fool an average person? Are there any jobs that will be completely eliminated by AI in the next five years? Can you think of any fields that have not yet been touched by AI? Guests and Hosts Saiph Savage, Assistant Professor at Northeastern University. Connect with Saiph on LinkedIn or on Twitter at @Saiphcita. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.       Date: 7/20/2021 Tags: @Saiphcita, @SFoskett, @ChrisGrundemann
39:31
July 20, 2021
2x28: Offloading ML Processing to Storage Devices with NGD Systems
Today’s storage devices (disks and SSDs) have processors and memory already, and this is the concept of computational storage. If drives can process data locally, they can relieve the burden of communication and processing and help reduce the amount of data that gets to the CPU or GPU. In this episode, Vladimir Alves and Scott Shadley join Chris Grundemann and Stephen Foskett to discuss the AI implications of computational storage. Modern SSDs already process data, including encryption and compression, and they are increasingly taking on applications like machine learning. Just as industrial IoT and edge computing is taking on ML processing, so too are storage devices. Current applications for ML on computational storage include local processing of images and video for recognition and language processing, but these devices might even be able to execute ML training locally as in the case of federated learning. Three Questions Are there any jobs that will be completely eliminated by AI in the next five years? Can you think of any fields that have not yet been touched by AI? How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Guests and Hosts Vladimir Alves, CTO and Co-Founder at NGD Systems. Connect with Vladimir on LinkedIn. Scott Shadley, VP of Marketing at NGD System. Connect with Scott on LinkedIn or on Twitter @SMShadley. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.     Date: 7/13/2021 Tags: @SFoskett, @ChrisGrundemann, @SMShadley, @NGDSystems
37:55
July 13, 2021
2x27: How the ML Community Has Evolved in 2021 with Demetrios Brinkmann and David Aponte
The MLOps community has grown dramatically recently, with security, a data-centric approach, ethical implications, and a growing and diverse community rising in 2021. In this episode, MLOps Community managers Demetrios Brinkmann and David Aponte join Steph Locke and Stephen Foskett to discuss what has changed over the last year. It seems that a new ML company is launching every week, and the MLOps Community provides a great way to learn about these. We are also seeing a push and pull between open source and cloud platforms, and concern about lock-in and technical debt. Data science and machine learning are merging, with greater focus on data quality and quantity when training models. Three Questions Is MLOps a lasting trend or just a step on the way for ML and DevOps becoming normal? Can you think of an application for ML that has not yet been rolled out but will make a major impact in the future? How big can ML models get? Will today’s hundred-billion parameter model look small tomorrow or have we reached the limit? Companies Mentioned  Microsoft, Tecton, Scale AI Sara Williams Talk D. Sculley interview Guests and Hosts Demetrios Brinkmann, Community Coordinator at MLOps Community. Connect with Demetrios on LinkedIn, on Twitter at @DPBrinkm or at mlops.community. David Aponte, Community Coordinator at MLOps Community. Connect with David on LinkedIn.  Steph Locke, Data Scientist and CEO of Nightingale HQ. Connect with Steph on LinkedIn or on Twitter @TheStephLocke. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.   Date: 7/6/2021 Tags: @SFoskett, @TheStephLocke, @DPBrinkm, @MLOpsCommunity
51:51
July 06, 2021
2x26: The Global Imbalance of AI Investment with Sofia Trejo
Look at a list of the top companies in the world, and most are focused in the United States, China, and Europe, and this causes an imbalance of investment in AI. With most companies building AI infrastructure and applications located in Silicon Valley and similar areas, how will the rest of the world catch up? Sofia Trejo joins Chris Grundemann and Stephen Foskett to discuss the implications of this imbalance, which causes an AI divide. Companies like Facebook, Google, and Amazon increasingly centralize global data through their internet access initiatives, and all are also deeply involved in developing cloud and AI applications. This poses issues for developing countries, which are increasingly dependent on these companies and susceptible to disinformation and misinformation campaigns. Most discussions of bias focus on a first-world context and do not take into account the challenges faced by developing countries, and the same is true of AI development. We must stop thinking that the solution is technological and focus instead on education and digital literacy before AI gets out of control. Three Questions Is it possible to create a truly unbiased AI? Can you think of any fields that have not yet been touched by AI? Can you think of an application for ML that has not yet been rolled out but will make a major impact in the future? Guests and Hosts Sofia Trejo, PhD in Mathematics, Specialist in AI Ethics. Connect with Sofia on LinkedIn.  Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.   Date: 6/29/2021 Tags: @SFoskett, @ChrisGrundemann
37:07
June 29, 2021
2x25: AI Is Going to Be Everywhere and in Everything With David Klee
AI is everywhere these days, powering applications from the enterprise to industrial, medical, education, and mobility. In this episode, David Klee joins Chris Grundemann and Stephen Foskett to discuss the ubiquity of AI technology today. Although not all applications of machine learning have been compelling, we are starting to see novel uses that allow us to do things we could never do before. One exciting application is in root cause analysis across the entire application stack, which has never before been possible. Three Questions Will we ever see a Hollywood-style “artificial mind” like Mr. Data or other characters? When will we see a full self-driving car that can drive anywhere, any time? How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Guests and Hosts David Klee, Founder of SQLibrium & Heraflux Technologies. Connect with David at LinkedIn and on Twitter at @KleeGeek Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.   Date: 6/22/2021 Tags: @SFoskett, @ChrisGrundemann, @KleeGeek, @SQLibrium, @HeraFlux
31:47
June 22, 2021
2x24: MLOps Is About Quality Not Technology with Steph Locke
MLOps is similar to DevOps but focused on ML, and focuses on improving quality of delivery for artificial intelligence applications. In this episode, Stephen Foskett discusses MLOps with Steph Locke, CEO of Nightingale HQ. DevOps is very much a cultural shift for software development, while MLOps in practice tends to be more of a team sport, with software developers, data scientists, machine learning experts, and IT infrastructure and operations. Another benefit of MLOps is the improvement of efficiency that results from having all these diverse groups collaborate on application development and deployment. Three Questions How long will it take for a conversational AI to pass the Turing test and fool an average person? Are there any jobs that will be completely eliminated by AI in the next five years? How big can ML models get? Will today’s hundred-billion parameter model look small tomorrow or have we reached the limit? Guests and Hosts Steph Locke, Data Scientist and CEO of Nightingale HQ. Connect with Steph on LinkedIn or on Twitter @TheStephLocke. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.   Date: 6/15/2021 Tags: @SFoskett, @TheStephLocke, @NightingaleHQAI
31:14
June 15, 2021
2x23: Overcoming the Obstacles of AI Application Development with Snorkel AI
Developers of AI applications face many obstacles, but the chief challenge is simply that these are different from traditional software development projects. 85% of businesses say they are looking to adopt AI but a similar percentage of data science projects never reach production. Too many organizations approach AI application development similarly to other software projects. Another issue is focusing on the machine learning model rather than the data set that will be used. Devang Sachdev of Snorkel AI suggests being data-focused instead, and reducing and optimizing models instead of continually expanding the number of parameters. Another issue is the manual process of developing training data, which is time-consuming and error-prone. Finally, we must consider a process of iteration over models and training data to ensure quality. Machine learning is an excellent tool but it requires a re-think in how a company approaches software development. Three Questions Is it possible to create a truly unbiased AI? Can you think of an application for ML that has not yet been rolled out but will make a major impact in the future? How big can ML models get? Will today’s hundred-billion parameter model look small tomorrow or have we reached the limit? Guests and Hosts Devang Sachdev, VP of Marketing at Snorkel AI. Connect with Devang on LinkedIn or on Twitter at @DevangSachdev. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.   Date: 6/08/2021 Tags: @SFoskett, @ChrisGrundemann, @SnorkelAI, @DevangSachdev
34:47
June 08, 2021
2x22: Microsoft is Democratizing AI with Steph Locke
Microsoft plays a large role in enterprise IT applications, from the desktop to the datacenter to the Azure cloud, and the company is active in the world of AI as well. But most of Microsoft’s work has gone unnoticed, with high-profile cloud AI and ML applications at companies like Google and Uber getting all the press. In this episode, Steph Locke joins Chris Grundemann and Stephen Foskett to discuss the place of AI inside the Microsoft ecosystem. Microsoft has built AI into search and Cortana and has also produced an AI Builder and ML workspace in Azure that allows developers to produce their own chatbots, recognize images, and more. Steph also discusses the AI-related announcements at Microsoft Build last week. We finish up with a deep discussion of accessibility and diversity and potential solutions from hiring to training to awareness. Three Questions Can you think of an application for ML that has not yet been rolled out but will make a major impact in the future? Is it possible to create a truly unbiased AI? Will we ever see a Hollywood-style “artificial mind” like Mr. Data or other characters? Guests and Hosts Steph Locke, Data Scientist and CEO of Nightingale HQ. Connect with Steph on LinkedIn or on Twitter @TheStephLocke. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.   Date: 6/1/2021 Tags: @SFoskett, @ChrisGrundemann, @TheStephLocke, @NightingaleHQAI
40:08
June 01, 2021
2x21: The Intersection of 5G and AI with EdgeQ
You might think that 5G and AI are completely unrelated, but these new technologies support each other. Both are expressions of information theory, and both use similar mathematics under the hood. Both 5G and AI are also disruptive to existing business models and enable new applications. EdgeQ develops processors that leverage machine learning to improve customer experience in 5G and enable customers to develop their own AI solutions on-chip. 5G is bringing the edge closer to the cloud and it enables seamless deployment of AI across the network. Three Questions When will we see a full self-driving car that can drive anywhere, any time? When will we have video-focused ML in the home that operates like the audio-based AI assistants like Siri or Alexa? How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices?Guest Information Guests and Hosts Vinay Ravuri, CEO / Founder at EdgeQ Inc. Connect with Vinay on LinkedIn or Twitter at @EdgeQ_Inc Frederic Van Haren, Founder at HighFens Inc., Consultancy & Services. Connect with Frederic on Highfens.com or on Twitter at @FredericVHaren Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.   Date: 5/2/2021 Tags: @SFoskett, @EdgeQ_Inc, @FredericVHaren
37:28
May 25, 2021
2x20: Expanding ML Models Beyond Current Limits with Groq
Machine learning models have grown tremendously in recent years, with some having hundreds of billions of data points, and we wonder how big they can get. How do we deploy even bigger models, whether it’s in the cloud or using captive infrastructure? Models are getting bigger and bigger, then are distilled and annealed, and then grow bigger still. In this episode, Dennis Abts of Groq discusses the scalability of ML models with Stephen Foskett and Chris Grundemann. HPC architecture and concepts are coming to the enterprise, enabling us to work with unthinkable amounts of data. But we are also reducing precision and complexity of models to reduce their size. The result is that businesses will be able to work with ever-larger data sets in the future. Three Questions How long will it take for a conversational AI to pass the Turing test and fool an average person? Will we ever see a Hollywood-style “artificial mind” like Mr. Data or other characters? How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Guests and Hosts Dennis Abts, Chief Architect at Groq. Connect with Dennis on LinkedIn or on Twitter @DennisAbts Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.     Date: 5/18/2021 Tags: @SFoskett, @ChrisGrundemann, @DennisAbts, @GroqInc
40:44
May 18, 2021
2x19: Running AI Everywhere and In Everything with Intel
AI processing is appearing everywhere, running on just about any kind of infrastructure, from the cloud to the edge to end-user devices. Although we might think AI processing requires massive centralized resources, this is not necessarily the case. Deep learning training might need centralized resources, but the topic goes way beyond this, and it is likely that most production applications will use CPUs to process data in-place. Simpler machine learning applications don’t need specialized accelerators and Intel has been building specialized hardware support into their processors for a decade. DL Boost on Xeon is competitive with discrete GPUs thanks to specialized instructions and optimized software libraries. Three Questions How long will it take for a conversational AI to pass the Turing test and fool an average person? Is it possible to create a truly unbiased AI? How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Guests and Hosts Eric Gardner, Director of AI Marketing at Intel. Connect with Eric on LinkedIn or on Twitter @DataEric. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett.   Date: 5/11/2021 Tags: @SFoskett, @ChrisGrundemann, @DataEric, @IntelBusiness
31:37
May 11, 2021
2x18: Taking Machine Learning on the Road with IBM and B-Plus
Development of autonomous vehicles is an excellent example of machine learning applied to industrial IoT. In this episode, Alexander Noack of b-plus and Frank Kräemer of IBM Germany join Chris Grundemann and Stephen Foskett to discuss data collection on the road, central processing, and AI model training. Machine learning is part of the development of autonomous vehicle development and is also used in production in vehicles. It is also used to filter data and enhance processing, and this is the same concept found in many edge and industrial use cases. Edge computing is relevant beyond AI, and these technologies are complementary, with the edge moving right into vehicles, factories, retail outlets, medical facilities, and more. Three Questions When will we see a full self-driving car that can drive anywhere, any time? Are there any jobs that will be completely eliminated by AI in the next five years? How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Guests and Hosts Frank Kräemer, Systems Architect at IBM Germany. Connect with Frank on LinkedIn or on Twitter @IBM. Alexander Noack, Managing Director at b-plus. Connect with Alexander on LinkedIn.  Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 5/4/2021 Tags: @SFoskett, @ChrisGrundemann, @IBM
34:34
May 04, 2021
2x17: How AI Drives the Need for Next-Generation Infrastructure Architectures with Liqid
We are on the cusp of a totally new architecture for enterprise IT, and this change toward composability is being driven by applications like AI. Instead of designing around fixed-configuration servers, disaggregation allows the use of pools of resources, and composability allows dynamic allocation of these resources as needed for different applications. When it comes to AI workloads, organizations can deploy a set of expensive GPUs and then allocate these as needed to various tasks, and redeploy these when that task (ML training, for example) is done. That’s what Liqid is delivering for their customers, and why we invited CEO and Co-Founder Sumit Puri and Chief AI Architect Josiah Clark to join Stephen Foskett and Chris Grundemann for this episode of Utilizing AI. Three Questions Are there any jobs that will be completely eliminated by AI in the next five years? Can you think of any fields that have not yet been touched by AI? How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices? Guests and Hosts Sumit Puri, CEO and Co-Founder at Liqid. Connect with Sumit on LinkedIn or on Twitter at @WeAreLiqid. Josiah Clark, Chief AI Architect at Liqid. Connect with Josiah on LinkedIn. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 4/27/2021 Tags: @SFoskett, @ChrisGrundemann, @WeAreLiqid
38:15
April 27, 2021
2x16: Optimizing ML at the Edge for Industrial IoT with Sastry Malladi of FogHorn
Industrial cameras and sensors are generating more data than ever, and companies are increasingly moving machine learning to the edge to meet it. This is the market for FogHorn, so we invited Co-Founder Sastry Malladi to join Chris Grundemann and Stephen Foskett to discuss the implications of this challenge. Industrial IoT, also called operational technology, is the use of distributed connected sensors and devices in industrial environments, from factories to oil rigs to retail. Any solution to this problem must be oriented towards the staff and skills found in these environments and must reflect the data inputs and outputs found there. Another concern is cyber security, since these environments are increasingly being targeted by attackers. Machine learning can be brought in to control industrial processes and monitor sensors locally, with low latency and high accuracy, reducing risk and increasing profitability. These environments also benefit from transfer learning, periodic re-training, and closed-loop machine learning to keep them optimized and functional Three Questions Is machine learning a product or a feature? When will we have video-focused ML in the home that operates like the audio-based AI assistants like Siri or Alexa? Are there any jobs that will be completely eliminated by AI in the next five years? Guests and Hosts Sastry Malladi, CTO and Co-Founder at FogHorn. Connect with Sastry on LinkedIn or on Twitter at @M_Sastry. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 4/20/2021 Tags: @SFoskett, @ChrisGrundemann, @M_Sastry, @FogHorn_IoT
32:09
April 20, 2021
2x15: Enabling AI Applications through Datacenter Connectivity with Nvidia
AI applications typically require massive volumes of data and multiple devices within the datacenter. Nvidia acquired Mellanox to bring them industry-leading networking products to enable next-generation applications, including artificial intelligence. Kevin Deierling joins Chris Grundemann and Stephen Foskett to discuss the Nvidia vision for a datacenter-wide compute unit with integrated networking to bring all of these components together. This represents a continuous evolution of computing, from supercomputers to HPC to big data to AI, all of which have required more compute, memory, and storage resources than any one device and require the connectivity to bring it all together. Three Questions How long will it take for a conversational AI to pass the Turing test and fool an average person? When will we have video-focused ML in the home that operates like the audio-based AI assistants like Siri or Alexa? Are there any jobs that will be completely eliminated by AI in the next five years? Guests and Hosts Kevin Deierling, SVP Nvidia Networking. Connect with Kevin on LinkedIn or find him on Twitter at @TechseerKD. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 4/13/2021 Tags: @SFoskett, @ChrisGrundemann, @TechseerKD, @Nvidia
32:49
April 13, 2021
2x14: Using ML to Optimize ML with Luis Ceze of OctoML
Training and optimizing a machine learning model takes a lot of compute resources, but what if we used ML to optimize ML? Luis Ceze created Apache Tensor Virtual Machine (TVM) to optimize ML models and has now founded a company, OctoML, to leverage this technology. Fundamentally, machine learning relies on linear algebra, but how should we pick the fastest approach for each model? Today this is done with human intuition, but TVM builds machine learning models to predict the best approaches to try. It also creates an executable so the model can run best on various target hardware platforms. It can also help select the right target platform for a given model. Three Questions How long will it take for a conversational AI to pass the Turing test and fool an average person? Is machine learning a product or a feature? Can you think of any fields that have not yet been touched by AI? Guests and Hosts Luis Ceze, CEO of OctoML. Find Luis on Twitter at @LuisCeze. Chris Grundemann, Gigaom Analyst and Managing Director at Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 4/6/2021 Tags: @SFoskett, @ChrisGrundemann, @LuisCeze, @OctoML
30:57
April 06, 2021
2x13: AI Needs Non-Traditional Storage Solutions with James Coomer of DDN
AI applications have large data volumes with lots of clients and conventional storage systems aren’t a good fit. In this episode, James Coomer from DDN talks about the lessons they have learned building storage systems to support AI applications. Inferencing requires terabytes or petabytes of data, often large files and streaming data. For example, autonomous driving applications generate hundreds of terabytes of data per vehicle drive, resulting in petabytes of data to ingest and process. DDN’s parallel filesystem goes a step further than NFS with an intelligent client that directs I/O to leverage all network links and storage endpoints available. Deep learning loves data, and a smart client can make the whole application faster. Because data is the biggest AI challenge today, an advanced storage solution can really help deliver AI solutions in the enterprise. Although most companies realize that finding expertise (data scientists, etc) is a major challenge, building infrastructure to support them is just as critical. Guests and Hosts James Coomer is Senior Vice President for Products at DDN. Connect with James on LinkedIn or learn more on Twitter at @DDN_Limitless. Andy Thurai, technology influencer and thought leader. Find Andy’s content at theFieldCTO.com and on Twitter at @AndyThurai. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 3/30/2021 Tags: @SFoskett, @AndyThurai, @DDN_Limitless
36:46
March 30, 2021
2x12: Balancing Data Security and Data Processing with Arti Raman of Titaniam
AI and analytics needs access to massive volumes of data, but we are constantly reminded of the importance of securing data. How can data be protected at rest and in flight while still enabling access? That’s what Titaniam is enabling, and this episode of Utilizing AI features CEO Arti Raman, who tells us how they are able to provide access to data without leaving it wide open. They provide granular access according to the needs of the application, enabling access for processing on demand. This approach also protects data in use by researchers and developers, since they can not access the clear text data even while their system is processing it. This has practical applications for medical applications or when dealing with personally identifiable information (PII) in the face of GDPR and CCPA. Guests and Hosts: Arti Raman is CEO and Founder of Titaniam. Connect with Arthi on LinkedIn and learn more on Twitter at @TitaniamLabs. Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 3/23/2021 Tags: @SFoskett, @ChrisGrundemann, @TitaniamLabs
33:34
March 23, 2021
2x11: Using AI to Assess Unstructured Data with Concentric
Most organizations have a vast amount of so-called unstructured data, and this poses a major risk for operations. But what if there was an AI-powered application that could sift through all this data, categorize it, and determine the risk profile for everything? That’s the promise of Concentric IO, and the premise for this episode of Utilizing AI with their CEO, Karthik Krishnan. The company uses a deep learning model trained on a vast pool of data from the Internet to create “Concentric Mind” which can identify documents across many business verticals, and this is continually tuned based on the results at each new customer environment. It also includes a language model to identify clusters of documents thematically. Guests and Hosts: Karthik Krishnan is CEO of Concentric. Connect with Karthik on Twitter at @KK_Karthik. Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 3/16/2021 Tags: @SFoskett, @ChrisGrundemann, @KK_Karthik, @IncConcentric
36:57
March 16, 2021
2x10: AI and Analytics Are Driving a New Kind of Storage with Brad King of Scality
Big data really wasn't all that big until modern analytics and machine learning applications appeared, but now storage solutions have to scale capacity and performance like never before. In this episode, Brad King, Co-Founder of Scality, joins Chris Grundemann and Stephen Foskett to discuss this new demand for scalable storage by AI applications. Applications like autonomous driving, log analysis, and travel booking are driving massive need for storage as AI applications detect anomalies and support business intelligence. Scality had to tune their system to handle the massive scale of data supporting these applications, with up to a petabyte of log data being added and deleted in a single day. AI-driven tools are enabling customers to do what they never could do, and it requires a balanced infrastructure stack to make it possible. Brad suggests that companies implementing AI applications need to find a system that scales with their needs and has API-driven data access, preferably with an object-based storage model. Guests and Hosts: Brad King is Co-Founder and CTO of Scality. Connect with Brad on Twitter at @Baslking. Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 3/9/2021 Tags: @SFoskett, @ChrisGrundemann, @Scality, @Baslking
34:29
March 09, 2021
2x09: Building Transparency and Fighting Bias in AI with Ayodele Odubela
When it comes to AI, it's garbage in, garbage out: A model is only as good as the data used. In this episode of Utilizing AI, Ayodele Odubela joins Chris Grundemann and Stephen Foskett to discuss practical ways companies can eliminate bias in AI. Data scientists have to focus on building statistical parity to ensure that their data sets are representative of the data to be used in applications. We consider the sociological implications for data modeling, using lending and policing as examples for biased data sets that can lead to errors in modeling. Rather than just believing the answers, we must consider whether the data and the model are unbiased. Guests and Hosts: Ayodele Odubela of @CometML is an ML instructor, founder, and author. Connect with Ayodele on Twitter at @DataSciBae. Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 3/2/2021 Tags: @SFoskett, @ChrisGrundemann, @DataSciBae
31:29
March 02, 2021
2x08: Algorithmic Bias and Subjective Decision Making with Alf Rehn
Biases can creep into any data set, and these can cause trouble when this data is used to train an AI model. Alf Rehn, Professor of Innovation, Design, and Management at the University of Southern Denmark, joins Andy Thurai and Stephen Foskett to discuss the lessons he has learned about algorithmic bias based on his work with the Velux Foundations Algorithms, Data and Democracy project. Society is directing artificial intelligence to solving some problems and ignoring others, and this can create biases as surely as data selection in model training. Can we ever truly eliminate bias? If not how do we work against it? Can we keep the genie in the bottle even if we want to? And can machines ever make sound, ethical subjective decisions? Guests and Hosts Alf Rehn, Professor of Innovation, Design and Management at the University of Southern Denmark. Find Alf on Twitter as @AlfRehn or at AlfRehn.com Andy Thurai, technology influencer and thought leader. Find Andy’s content at theFieldCTO.com and on Twitter at @AndyThurai Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 2/23/2021 Tags: @SFoskett, @AndyThurai, @AlfRehn
33:35
February 23, 2021
2x07: Improving AI with Transfer Learning Featuring Frederic Van Haren
Productive use of AI requires the application of existing models to new applications through a process called transfer learning. In this episode, High-Performance Computing and AI Expert Frederic van Haren joins Stephen Foskett to discuss the topic of transfer learning and what it means, from voice recognition to autonomous driving and enterprise applications. Transfer learning is analogous to the way teachers impart knowledge and experience to their students, and represents a feedback loop that improves the model over time. This is a valuable concept for applications like language processing but requires a feedback mechanism or it is something of a dead end. One challenge for machine learning is that models do not truly understand the world the way people do, but they can fool us into thinking that they do because of their uncanny ability to match patterns the way we would. Over time, we all must develop a better understanding of this technology even as it is being widely deployed around us. Guests and Hosts Frederic Van Haren, CTO and Founder of HighFens. Find Frederic on Twitter as FredericVHaren. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 2/16/2021 Tags: @SFoskett, @FredericVHaren
37:35
February 16, 2021
2x06: Moving AI To the Edge with BrainChip
BrainChip is developing a novel ultra low power “neuromorphic” AI processor that can be embedded in literally any electronic device, rather than centralizing learning in high performance processors. Today’s edge devices are applying exiting models to process inputs but can’t actually learn in the field, but on-chip learning and inference could radically alter the capabilities of devices in automotive, home, medical, and other remote locations. BrainChip is able to reduce power thanks to the neuromorphic self-learning approach and also because they reduce precision down to 4 bits or less. This loses some accuracy, but only a little. The company also creates a mesh of cores that have access to local memory, enabling flexibility of processing. Guests and Hosts Lou DiNardo, President and CEO of BrainChip. Connect with Lou on LinkedIn Andy Thurai, technology influencer and thought leader. Find Andy’s content at theFieldCTO.com and on Twitter at @AndyThurai Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 2/9/2021 Tags: @SFoskett, @AndyThurai, @BrainChip_Inc
31:55
February 09, 2021
2x05: How AI Can Save IT Operations From Drowning in Data with Josh Atwell from Splunk
AI is impacting IT operations more quickly than expected, and companies like Splunk are leveraging it to augment staff capabilities. Josh Atwell joins Andy Thurai and Stephen Foskett to discuss practical application of AI to help keep IT operations from drowning in data as applications are distributed in containers and the cloud. The key to using AI for operations is to leverage it to assist staff to process the volume and velocity of data, not replace them. Guests and Hosts Josh Atwell is Senior Technology Advocate at Splunk. Find Josh on Twitter as @Josh_Atwell and learn more about Splunk at Splunk.com Andy Thurai, technology influencer and thought leader. Find Andy’s content at theFieldCTO.com and on Twitter at @AndyThurai Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 2/2/2021 Tags: @SFoskett, @AndyThurai, @Josh_Atwell, @Splunk
30:50
February 02, 2021
2x04: Talking To Business People About AI with Ken Grohe of Weka
Ken Grohe of Weka discusses various business use cases for AI-enabled applications with Chris Grundemann and Stephen Foskett. AI is coming into practical use right now in applications like autonomous vehicles, drug development and healthcare, and retail. High-performance scalable storage is necessary for many ML training applications, and can be key to advanced applications in life sciences and others with massive data sets. The Chief Data Officer, and data scientists in general, are the future of the business, and AI is enabling the growth of this field. Guests and Hosts Ken Grohe, President and Chief Revenue Officer of Weka. Find Ken on LinkedIn and Twitter as @LeverageGTM and learn more about Weka at Weka.IO Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 1/26/2021 Tags: @SFoskett, @ChrisGrundemann, @LeverageGTM, @WekaIO
34:51
January 26, 2021
2x03: Deploying AI in the Business with Per Nyberg of Stradigi AI
Per Nyberg of Stradigi AI discusses "blue collar" AI applications with Stephen Foskett.  What problems can businesses solve with AI technology? Machine learning can find anomalies and outliers in manufacturing and finance, look for relationships in data, and cutting through the complexity of multi-disciplinary data. Consider customer churn: Machine learning can discover features in profiles that might not be visible even to an expert. Data scientists and AI experts must learn to present AI technology to average business people in terms they can understand, and this has lead to a "haves/have nots" situation where some companies or business units don't have access to this technology. We also need to reduce the science fiction appeal of AI and express what it can't do. Guests and Hosts Per Nyberg is Chief Commercial Officer for Stradigi AI. Find Per on LinkedIn to continue the conversation and connect on Twitter as @_PerNyberg or @StradigiAI Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 1/19/2021 Tags: @SFoskett, @_PerNyberg, @StradigiAI
28:20
January 19, 2021
2x02: The Last Mile - Connecting AI to Enterprise Applications with Monte Zweben
There are many “last mile” items on the enterprise checklist, and companies are struggling to connect everything together. In this episode, Monte Zweben, CEO of Splice Machine, discusses feature stores with Andy Thurai and Stephen Foskett. Data engineers maintain data pipelines, data scientists maintain the data store, and machine learning engineers are trying to create models and package them so they will be useful. One idea is to store a model in a relational database, store records in a feature table, and enable the database to trigger a model based on this data. That’s what Splice Machines is implementing - in-database ML deployment. SQL is making a comeback in ML, with scale-out solutions providing a more familiar and usable environment than leading noSQL databases. Monte believes that SQL will be the dominant data paradigm for machine learning, modeling, experimentation, and deployment. After all, SQL is the dominant language of enterprise data scientists. Guests and Hosts Monte Zweben is CEO of Splice Machine. Find Monte on Twitter as @MZweben and Splice Machine as @SpliceMachine. Andy Thurai, technology influencer and thought leader. Find Andy’s content at theFieldCTO.com and on Twitter at @AndyThurai. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 1/12/2021 Tags: @SFoskett, @AndyThurai, @MZweben, @SpliceMachine
36:32
January 12, 2021
2x01: AI-Driven Information Security with Steve Salinas
AI will be part of everything we do in the future, not replacing us but augmenting our work, and this is especially true in information security. In this, the first episode of Season 2 of Utilizing AI, Steve Salinas joins Chris Grundemann and Stephen Foskett to discuss AI as a “co-pilot.” Enterprise security saw an explosion of threats in the last decade, outstripping the ability of information security professionals to identify and prevent intrusions. The goal of enterprise AI in security is to help identify threats both known and unknown through deep learning as well as simpler pattern-matching machine learning. Of course, if AI is a co-pilot inside the company it will also be used by intruders, and adversarial machine learning is rising. The industry needs to be ready for anything! We finish the episode with a new feature: Three questions about the future of AI! Guests and Hosts Steve Salinas is an Information Security Product Marketing Professional. You can find Steve Twitter as @So_Cal_Aggie or on LinkedIn as StevetheMarketingGuy Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 1/5/2021 Tags: @SFoskett, @ChrisGrundemann, @So_Cal_Aggie
30:23
January 05, 2021
18: Merging Data Science and AI with Mel Greer of @Intel
Just as data analytics transformed business intelligence so is artificial intelligence transforming data science. In this episode, Mel Greer of Intel joins Chris Grundemann and Stephen Foskett to discuss this transformation, which is impacting business of all sorts including Intel itself. Intel's strategy has evolved, and their hardware platforms are following, with the company developing hardware and software to serve AI-driven data analytics. The conversation then turns to the challenges of implementing unbiased AI, from explainable AI to diversity of data and thought within businesses. Hosts and Guests Mel Greer, Chief Data Scientist, Americas, at Intel. Connect with Mel on LinkedIn. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann Date: 12/22/2020 Tags: @SFoskett, @ChrisGrundemann, @IntelAI, @Intel
33:17
December 22, 2020
17: Building a Hybrid Cloud Platform To Support AI Projects with Red Hat @OpenShift
In this episode, we ask Red Hat about the platform requirements for AI applications in production. What makes AI applications special and how does this change the infrastructure required to support these? The demand for flexibility, scalability, and distribution seems to match the capabilities of a hybrid cloud, and this is emerging as the preferred model for AI infrastructure. Red Hat is supporting the container-centric hybrid cloud with OpenShift, and containers are also critical to AI workloads.  Red Hat has production customers in healthcare, manufacturing, and financial industries deploying ML workloads in production right now. Episode Hosts and Guests Abhinav Joshi, Senior Manager, Product Marketing, OpenShift Business Unit, Red Hat. Find Abhinav on Twitter at @Abhinav_Joshi. Tushar Katarki, Senior Manager, Product Management, OpenShift Business Unit, Red Hat. Find Tushar on Twitter at @TKatarki. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann Date: 12/15/2020 Tags: @SFoskett, @ChrisGrundemann, @Abhinav_Joshi, @TKatarki, @RedHat, @OpenShift
40:28
December 15, 2020
16: As AI is Transforming Our Tools, It’s Also Transforming Us with @ChrisGrundemann
In this episode, Stephen Foskett and Chris Grundemann discuss the impact of AI on the future of work. How will our everyday lives be transformed by the widespread application of AI? What about the datacenter? Do AI-enabled network management tools mean we lose jobs? We already rely on AI-enabled tools, from Siri to Marvis, and maybe this is the template for the future of work with AI. Not everyone needs to be a data scientist or programmer, we just need to see AI as a co-worker. Episode Hosts and Guests Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann. Date: 12/8/2020 Tags: @SFoskett, @ChrisGrundemann
24:09
December 08, 2020
15: Applying the Lessons of Data Science to Artificial Intelligence with @YvesMulkers
We begin by taking a look at the world of data and analytics in the enterprise. Data architects like Yves have been involved in enterprise IT applications for decades, but the world really took off with the advent of data warehouses and the field of data science. Now AI and ML are impacting the field in many ways, and we discuss how this world has changed. Data scientists come from a statistics background, while modelers come from software engineering. How do the tools interact and intersect? What is Yves excited about and what frightens him? How does the infrastructure support all this? We finish with a look at what the future looks like: We will see a lot of evolution in science and medicine for data and ML, and this technology will be found everywhere in the datacenter and the cloud. Key questions covered include the following: How did the world of data and analytics evolve in the enterprise? How has AI/ML impacted the job of the data scientist? How can the data modelers, software developers, and IT Ops work together? Episode Hosts and Guests Yves Mulkers, Data & Analytics Strategist. Find Yves on Twitter at @YvesMulkers. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Date: 12/1/2020 Tags: @SFoskett, @YvesMulkers
31:02
December 01, 2020
14: Three Reasons AI is Getting Real with @WirelessBob
AI, machine learning, and neural networks are not new ideas. So what changed now? Over the last 5-6 years, advances in software, hardware, and scale have brought machine learning to the forefront, enabling new products and technologies. In this episode, Bob Friday, CTO of Mist, a Juniper Company, discusses the changes that have enabled his company and others to bring AI to the enterprise. We focus on four key questions: When did you start to see that AI was going to be a major force in the enterprise networking world? How have Google and other companies enabled AI through advances in open source software? How about hardware? There have been many advances over the last decade, from GP-GPUs to faster and lower-latency networking in storage. How has this enabled AI? How are large neural networks enabling AI in the enterprise? Episode Hosts and Guests Bob Friday, CTO of Mist, a Juniper Company. Find bob on Twitter at @WirelessBob. Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett. Andy Thurai, technology influencer and thought leader. Find Andy’s content at theFieldCTO.com and on Twitter at @AndyThurai. Date: 11/24/2020 Tags: @SFoskett, @AndyThurai, @WirelessBob, @JuniperNetworks
27:44
November 24, 2020
13: Will Nvidia Dominate the Market for AI Hardware
Matt Bryson of Wedbush securities joins Stephen Foskett for a discussion of AI hardware companies, focusing on the biggest player, Nvidia. Stephen and Matt start with a look at Nvidia: Just how big is Nvidia in the enterprise AI market? Then we turn to other major player in this space, Intel, which is strong in the inference market with their Xeon processors but obviously wants a bigger piece of the special-purpose processor market. AMD has had success in the cloud but doesn’t seem focused on the AI space. Then we look at the world of AI hardware startups. How will they compete with Nvidia, Intel, and AMD, when they just don’t have the same resources? Companies like BrainChip and Cerebras are trying to be more efficient and go after the gaps in the market rather than compete directly with Nvidia. Then there’s the crossover between AI and HPC, which is an opportunity for AMD, Tachyum, and others. We also see an opportunity for AI at the edge, which brings to mind companies like Apple and Huawei who are adding AI processing to chips used in client systems. We also need to consider companies like Amazon and Google that are creating their own AI solutions and Microsoft using GraphCore. But does AI live in the cloud or will next-generation hardware platforms like Liqid be more compelling? Finally we turn to the pending acquisition of Arm by Nvidia, and what that means if it goes through and if it doesn’t. Episode Hosts and Guests Matt Bryson, Senior Vice President at Wedbush Securities, can be found on LinkedIn at LinkedIn.com/in/Matt-Bryson-3105071/ Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 11/17/2020 Tags: @SFoskett, @Nvidia, @Intel, @AMD, @BrainChip_Inc, @CerebrasSystems, @Tachyum
26:03
November 17, 2020
12: Why Do Most Enterprise AI Projects Fail? @BeyondMindsAI
Most enterprise IT projects fail, and it has been this way for decades, and this discussion with Roey Mechrez of BeyondMinds considers why this is the case. One of the primary reasons is the trade-off between building custom solutions and buying off the shelf products. This is doubly different with AI since the success of a model depends on the data and training, not to mention the maintenance and updates needed as issues arise. Data science teams need to invest significant time and model into infrastructure, rather than just jumping in to train the model. This is a similar challenge to DevOps, but the added dimension of models and data makes MLOps even more challenging. Episode Hosts and Guests Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett Andy Thurai, technology influencer and thought leader. Find Andy's content at theFieldCTO.com and on Twitter at @AndyThurai Roey Mechrez, CTO at BeyondMinds. Find Roey on Twitter at @BeyondMindsAI Date: 11/10/2020 Tags: @SFoskett, @AndyThurai, @BeyondMindsAI
33:02
November 10, 2020
11: Is Kubeflow the Real Deal? Featuring @AponteAnalytics and @DPBrinkm
David Aponte and Demetrios Brinkmann discuss the future of Kubeflow with Stephen Foskett and Andy Thurai. Kubeflow is getting a lot of attention, but contributions and community seem to be lagging. Is this really the future of machine learning or just another dead-end open source project? Will product vendors pile on top, redirect the project, or kill development? The open source community tends to gravitate to quality projects, and it will develop Kubeflow (or not) based on the usefulness of the solution. Episode Hosts and Guests David Aponte, Machine Learning Engineer. Find David online at LinkedIn.com/in/AponteAnalytics and on Twitter at @AponteAnalytics Demetrios Brinkmann, Community Coordinator for @MLOpsCommunity. Find Demetrios online at LinkedIn.com/in/DPBrinkm and on Twitter at @DPBrinkm Andy Thurai, technology influencer and thought leader. Find Andy’s content at theFieldCTO.com and on Twitter at @AndyThurai Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett Date: 11/3/2020 Tags: @SFoskett, @AndyThurai, @AponteAnalytics, @DPBrinkm, @MLOpsCommunity
34:41
November 03, 2020
10: Bringing DevOps Principles to MLOps with @GaetCast
Stephen Foskett and Andy Thurai discuss the parallels between DevOps and MLOps with Gaetan Castelein of Tecton. We are in the middle of a shift in analytics and software engineering, with DevOps and continuous deployment, and this is colliding with the development of data analytics and big data. Machine Learning allows organizations to handle this explosion of data and build new applications and automate new business processes, but MLOps must be converged with big data and DevOps tooling to make this a reality. One key enabler of this transformation is the creation of an ML feature store, which stores curated features for machine learning pipelines. Feature stores typically enable users to build features, have standardized feature definitions, run models using these curated features, and manage MLOps. This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett Andy Thurai, technology influencer and thought leader. Find Andy's content at theFieldCTO.com and on Twitter at @AndyThurai Gaetan Castelein, VP of Marketing at Tecton (@TectonAI). Find Gaetan on Twitter at @GaetCast Date: 10/27/2020 Tags: @SFoskett, @AndyThurai, @GaetCast, @TectonAI
30:17
October 27, 2020
09: Deploying AI Models in the Enterprise with @DataCereal
Stephen Foskett discusses the practicalities involved in packaging, deploying, and operating AI models with Manasi Vartak of Verta. Deploying an AI model in production is a challenge, just like it was in the past with software. Once a company has an AI model to deploy, they must validate its results, create scaffolding code to make it consumable, optimize the data pipelines, instrument it, and assign operators. This is what Manasi and Verta have developed, and the world of AIOps parallels that of DevOps but with some unique twists. The data component of AI models presents a unique challenge not found in some other enterprise applications, and it is important to continually test the model to ensure that it hasn't drifted off target as data changes. Previously, training models was the main challenge for AI, but now it's all about getting things into production. That's why we started this podcast and why we created AI Field Day! This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett Manasi Vartak, CEO and Founder of Verta (@VertaAI). Find Manasi on Twitter at @DataCereal Date: 10/20/2020 Tags: @SFoskett, @DataCereal, @VertaAI
29:05
October 20, 2020
08: What Does AI Mean For the Future of Networking with @ChrisGrundemann
Stephen Foskett and Andy Thurai are joined by Chris Grundemann to discuss how AI is used in enterprise networking, and how it is changing the industry. They begin with a discussion of AI in enterprise networking, connecting it with software-defined networking and other trends. What network management tasks can be improved through the use of AI? Grundemann looks to using the technology in root cause analysis and fault correlation as well as prediction of network events. The discussion then turns to the ways that AI workloads will change the workload or demand on networking. AI systems demand data, throughput, and low latency, and the networking must adapt to support these workloads. This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett     Andy Thurai, technology influencer and thought leader. Find Andy's content at theFieldCTO.com and on Twitter at @AndyThurai Chris Grundemann a Gigaom Analyst and VP of Client Success at Myriad360. Connect with Chris on ChrisGrundemann.com on Twitter at @ChrisGrundemann Date: 10/13/2020 Tags: @SFoskett, @AndyThurai, ChrisGrundemann
22:46
October 13, 2020
07: The Seductive Appeal of AI with @JCEFidel
Stephen Foskett is joined by Josh Fidel, a technologist and futurist who has been inspired by applications for AI. Starting with a discussion of GPT-3, the AI text generation engine, the discussion ranges widely from AI Weirdness to James Yu's Singular to technological determinism to the Melbourne Monolith. Applications of AI are everywhere today, and Fidel's background as an enterprise technologist and futurist gives him a unique perspective. AI is generating compelling content, and we all must be ready to absorb and understand it. How will businesses use machine-generated text? It is likely that we will have to push back on too-broad uses of AI technology in the interest of truth and usefulness, rather than simply applying AI to every task at hand. This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett   Josh Fidel, futurist and technical architect. Find Josh on Twitter at @JCEFidel. Date: 10/06/2020 Tags: @SFoskett, @JCEFidel
30:05
October 06, 2020
06: Ethics and Bias in AI with @DataChick
Stephen Foskett is joined by Karen Lopez, an expert and speaker on data management, data quality, and data analysis. Karen focuses on the quality of the data underlying AI systems and the ethics of using this data. She discusses concerns about data reuse, consent for use, and how changes of data cat impact the outcome of models. We also consider the impact of pervasive data collection, and how this flood of data can impact the outcome of AI models. We finish with a discussion of outliers and missing data, and how this can affect the integrity of artificial intelligence applications. This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett Karen Lopez, Senior Project Manager and Architect at InfoAdvisors. Find Karen's writing at DataModel.com and on Twitter at @Datachick Date: 09/29/2020 Tags: @SFoskett, @Datachick
26:58
September 29, 2020
05: Building AI and Machine Learning Infrastructure with @GMinks
Stephen Foskett is joined by Gina Rosenthal, an expert on enterprise IT infrastructure and operations. Gina has made her career in enterprise IT infrastructure and has worked with many of the largest vendors. In this episode, she considers how vendors approach artificial intelligence, what applications they are delivering, and what this means in the enterprise. The conversation turns to ethics and risks of AI applications and how business should approach building AI models. As AI applications are deployed in the line of business, IT infrastructure organizations need to be prepared to handle the demands of these systems with next-generation cloud platforms. This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett Gina Rosenthal, Founder of Digital Sunshine Solutions. Find Gina on Twitter at @GMinks Date: 09/22/2020 Tags: @SFoskett, @GMinks
25:59
September 22, 2020
04: Is Enterprise IT Operations Really Ready for AI with @RayLucchesi
Stephen Foskett is joined by Ray Lucchesi, an expert on enterprise IT infrastructure and operations. Ray has seen many technologies come and go, but he's impressed by AI. Why does he think it's more reality than hype and how does he think it will affect the datacenter going forward? How are product vendors using AI and ML technology today, from storage to security to systems management? What will AI mean to datacenter infrastructure and the future of CPU and GPU hardware? Stephen Foskett can be found at GestaltIT.com and on Twitter @SFoskett. Ray Lucchesi can be found online at SilvertonConsulting.com and on Twitter @RayLucchesi. This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett Ray Lucchesi, President of Silverton Consulting. Find Ray on Twitter at @RayLucchesi Date: 09/15/2020 Tags: @SFoskett, @RayLucchesi
23:14
September 15, 2020
03: How is Machine Learning Affecting IT Operations with @MLOpsCommunity
Stephen Foskett discusses practical aspects of enterprise AI with David Aponte and Demetrios Brinkmann. AI offers promise to help IT operations departments deal with the flood of data, since ML is so good at finding needles in haystacks. But is it true or just vendor hype? Are current vendors able to work in this space or do we need a new kind of product or vendor to develop AI models? Does the new data demand a different type of infrastructure? And how are AIOps related to DevOps? Find Stephen online at GestaltIT.com and on Twitter at @SFoskett. Find David Aponte online at LinkedIn.com/in/AponteAnalytics. Find Demetrios Brinkmann online at LinkedIn.com/in/DPBrinkm and on Twitter at @MLOpsCommunity This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett David Aponte, Machine Learning Engineer. Find David online at LinkedIn.com/in/AponteAnalytics Demetrios Brinkmann, Community Coordinator. Find Demetrios online at LinkedIn.com/in/DPBrinkm and on Twitter at @MLOpsCommunity Date: 09/08/2020 Tags: @SFoskett, @MLOpsCommunity, DavidAponte, DemetriosBrinkmann
29:11
September 08, 2020
02: Ethical and Moral AI with @AndyThurai
Stephen Foskett and Andy Thurai discuss the ethics and morality of AI. Taking a cue from an article written by Andy for AI Trends, we focus on the various biases that can influence AI, and how to prevent these from interfering with the results. Andy recommends modeling knowing that biases would come into the input data, recognizing limitations in technology and data, teaching human values and validating AI models, and setting an ethical tone in the organization creating the AI model. Like people, AI models can only be as unbiased as their environment and training, and it is critical to recognize these limits when deploying them. This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett Andy Thurai, technology influencer and thought leader. Find Andy's content at theFieldCTO.com and on Twitter at @AndyThurai Date: 09/01/2020 Tags: @SFoskett, @AndyThurai
28:52
September 01, 2020
01: AI is Getting Real with @AndyThurai
In this pilot episode of Utilizing AI, Stephen Foskett and Andy Thurai discuss the reason for the podcast and consider where we go from here. AI is getting real, moving out of academia and hyperscale and into the enterprise. Businesses are adopting AI in strategically, and IT companies are deploying AI technologies in their products. This trend is quite obvious to Stephen at Gestalt IT, as many Tech Field Day companies present AI-enabled products for network monitoring and management, security, mobility, and much more. Today's infrastructure applications are focused on applying machine learning to large datasets, finding needles in haystacks. But tomorrow will see much more exciting applications. This episode features: Stephen Foskett, publisher of Gestalt IT and organizer of Tech Field Day. Find Stephen's writing at GestaltIT.com and on Twitter at @SFoskett Andy Thurai, technology influencer and thought leader. Find Andy's content at theFieldCTO.com and on Twitter at @AndyThurai Date: 08/28/2020 Tags: @SFoskett, @AndyThurai
22:53
August 28, 2020