Utilizing Tech - The Podcast Series about New and Emerging Technologies

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 l...

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...

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...

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...

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 A...

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 o...

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 inform...

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...

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 thi...

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...

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 sing...

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, machi...

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...

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 N etworking 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 ne...

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...

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 applicat...

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 discus...

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....

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 de...

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 l...

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 imp...

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...

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 th...

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. On...

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 learn...