Chris Benson Avatar

Chris Benson

Chris Benson is Principal Artificial Intelligence Strategist at Lockheed Martin. He came to Lockheed Martin from Honeywell SPS, where he was Chief Scientist for Artificial Intelligence & Machine Learning. Chris built and operationalized Honeywell’s first dedicated AI team from the ground up. Before that he was on the AI Team at Accenture.

As a strategist and thought leader, Chris is among the world’s most in-demand professional keynote speakers on artificial intelligence, machine learning, emerging technologies, and visionary futurism. His inspirational keynotes are known for their passion, energy, and clarity. He is a seasoned storyteller who delights in captivating his audiences with inspiring narratives and insightful analysis at conferences, broadcasts, interviews, forums, and corporate events around the world.

Chris is an innovative hands-on solutions architect for artificial intelligence and machine learning - and the emerging technologies they intersect - robotics, IoT, augmented reality, blockchain, mobile, edge, and cloud.

He is Co-Host of the Practical AI podcast, which reaches thousands of AI enthusiasts each week, and is also the Founder & Organizer of the Atlanta Deep Learning Meetup - one of the largest AI communities in the world.

Chris and his family are committed animal advocates who are active in animal rescue, and strive to make strategic improvements on specific animal welfare issues through advocacy for non-partisan, no-kill, and vegan legislation and regulation.

Chris Benson’s opinions are his own.

https://chrisbenson.com

Atlanta · Twitter · GitHub · LinkedIn · Website
271 episodes

Practical AI Practical AI #299

Sidekick is an AI Shopify expert

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2024-12-11T22:15:00Z #ai +2 🎧 13,845

Today, Chris explores Shopify Magic and other AI offerings with Mike Tamir, Distinguished ML Engineer and Head of Machine Learning, and Matt Colyer, Director of Product Management for Sidekick. They talk about how Shopify uses generative AI and LLMs to enhance their products, and they take a deeper dive into Sidekick, a first-of-its-kind, AI-enabled commerce assistant that understands a merchant’s business (products, orders, customers) and has been trained to know all about Shopify.

Practical AI Practical AI #298

Full-duplex, real-time dialogue with Kyutai

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2024-12-04T16:00:00Z #ai 🎧 19,020

Kyutai, an open science research lab, made headlines over the summer when they released their real-time speech-to-speech AI assistant (beating OpenAI to market with their teased GPT-driven speech-to-speech functionality). Alex from Kyutai joins us in this episode to discuss the research lab, their recent Moshi models, and what might be coming next from the lab. Along the way we discuss small models and the AI ecosystem in France.

Practical AI Practical AI #297

Clones, commerce & campaigns

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2024-11-29T17:30:00Z #ai +1 🎧 19,589

Chris and Daniel dive into what Trump’s impending second term could mean for AI companies, model developers, and regulators, unpacking the potential shifts in policy and innovation. Next, they discuss the latest models, like Qwen, that blur the performance gap between open and closed systems. Finally, they explore new AI tools for meeting clones and AI-driven commerce, sparking a conversation about the balance between digital convenience and fostering genuine human connections.

Practical AI Practical AI #296

scikit-learn & data science you own

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2024-11-19T21:00:00Z #ai +1 🎧 23,576

We are at GenAI saturation, so let’s talk about scikit-learn, a long time favorite for data scientists building classifiers, time series analyzers, dimensionality reducers, and more! Scikit-learn is deployed across industry and driving a significant portion of the “AI” that is actually in production. :probabl is a new kind of company that is stewarding this project along with a variety of other open source projects. Yann Lechelle and Guillaume Lemaitre share some of the vision behind the company and talk about the future of scikit-learn!

Practical AI Practical AI #295

Creating tested, reliable AI applications

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2024-11-13T19:30:00Z #ai 🎧 24,191

It can be frustrating to get an AI application working amazingly well 80% of the time and failing miserably the other 20%. How can you close the gap and create something that you rely on? Chris and Daniel talk through this process, behavior testing, and the flow from prototype to production in this episode. They also talk a bit about the apparent slow down in the release of frontier models.

Practical AI Practical AI #294

AI is changing the cybersecurity threat landscape

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2024-11-05T19:40:00Z #ai +3 🎧 24,254

This week, Chris is joined by Gregory Richardson, Vice President and Global Advisory CISO at BlackBerry, and Ismael Valenzuela, Vice President of Threat Research & Intelligence at BlackBerry. They address how AI is changing the threat landscape, why human defenders remain a key part of our cyber defenses, and the explain the AI standoff between cyber threat actors and cyber defenders.

Practical AI Practical AI #293

The path towards trustworthy AI

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2024-10-29T19:00:00Z #ai +2 🎧 24,777

Elham Tabassi, the Chief AI Advisor at the U.S. National Institute of Standards & Technology (NIST), joins Chris for an enlightening discussion about the path towards trustworthy AI. Together they explore NIST’s ‘AI Risk Management Framework’ (AI RMF) within the context of the White House’s ‘Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence’.

Practical AI Practical AI #292

Big data is dead, analytics is alive

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2024-10-24T15:30:00Z #ai +1 🎧 25,964

We are on the other side of “big data” hype, but what is the future of analytics and how does AI fit in? Till and Adithya from MotherDuck join us to discuss why DuckDB is taking the analytics and AI world by storm. We dive into what makes DuckDB, a free, in-process SQL OLAP database management system, unique including its ability to execute lighting fast analytics queries against a variety of data sources, even on your laptop! Along the way we dig into the intersections with AI, such as text-to-sql, vector search, and AI-driven SQL query correction.

Practical AI Practical AI #291

Practical workflow orchestration

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2024-10-15T20:00:00Z #ai +1 🎧 28,469

Workflow orchestration has always been a pain for data scientists, but this is exacerbated in these AI hype days by agentic workflows executing arbitrary (not pre-defined) workflows with a variety of failure modes. Adam from Prefect joins us to talk through their open source Python library for orchestration and visibility into python-based pipelines. Along the way, he introduces us to things like Marvin, their AI engineering framework, and ControlFlow, their agent workflow system.

Practical AI Practical AI #290

Towards high-quality (maybe synthetic) datasets

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2024-10-09T13:30:00Z #ai +1 🎧 27,080

As Argilla puts it: “Data quality is what makes or breaks AI.” However, what exactly does this mean and how can AI team probably collaborate with domain experts towards improved data quality? David Berenstein & Ben Burtenshaw, who are building Argilla & Distilabel at Hugging Face, join us to dig into these topics along with synthetic data generation & AI-generated labeling / feedback.

Practical AI Practical AI #288

GraphRAG (beyond the hype)

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2024-09-25T18:30:00Z #ai +1 🎧 30,467

Seems like we are hearing a lot about GraphRAG these days, but there are lots of questions: what is it, is it hype, what is practical? One of our all time favorite podcast friends, Prashanth Rao, joins us to dig into this topic beyond the hype. Prashanth gives us a bit of background and practical use cases for GraphRAG and graph data.

Practical AI Practical AI #287

Pausing to think about scikit-learn & OpenAI o1

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2024-09-17T19:00:00Z #ai +1 🎧 28,240

Recently the company stewarding the open source library scikit-learn announced their seed funding. Also, OpenAI released “o1” with new behavior in which it pauses to “think” about complex tasks. Chris and Daniel take some time to do their own thinking about o1 and the contrast to the scikit-learn ecosystem, which has the goal to promote “data science that you own.”

Practical AI Practical AI #282

Only as good as the data

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2024-08-14T21:15:00Z #ai +1 🎧 30,502

You might have heard that “AI is only as good as the data.” What does that mean and what data are we talking about? Chris and Daniel dig into that topic in the episode exploring the categories of data that you might encounter working in AI (for training, testing, fine-tuning, benchmarks, etc.). They also discuss the latest developments in AI regulation with the EU’s AI Act coming into force.

Practical AI Practical AI #281

Gaudi processors & Intel's AI portfolio

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2024-08-07T13:45:00Z #ai 🎧 29,502

There is an increasing desire for and effort towards GPU alternatives for AI workloads and an ability to run GenAI models on CPUs. Ben and Greg from Intel join us in this episode to help us understand Intel’s strategy as it related to AI along with related projects, hardware, and developer communities. We dig into Intel’s Gaudi processors, open source collaborations with Hugging Face, and AI on CPU/Xeon processors.

Practical AI Practical AI #278

The first real-time voice assistant

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2024-07-18T12:45:00Z #ai +1 🎧 26,727

In the midst of the demos & discussion about OpenAI’s GPT-4o voice assistant, Kyutai swooped in to release the first real-time AI voice assistant model and a pretty slick demo (Moshi). Chris & Daniel discuss what this more open approach to a voice assistant might catalyze. They also discuss recent changes to Gartner’s ranking of GenAI on their hype cycle.

Practical AI Practical AI #277

Vectoring in on Pinecone

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2024-07-10T17:30:00Z #ai +2 🎧 25,969

Daniel & Chris explore the advantages of vector databases with Roie Schwaber-Cohen of Pinecone. Roie starts with a very lucid explanation of why you need a vector database in your machine learning pipeline, and then goes on to discuss Pinecone’s vector database, designed to facilitate efficient storage, retrieval, and management of vector data.

Practical AI Practical AI #274

The perplexities of information retrieval

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2024-06-19T16:30:00Z #ai +2 🎧 26,844

Daniel & Chris sit down with Denis Yarats, Co-founder & CTO at Perplexity, to discuss Perplexity’s sophisticated AI-driven answer engine. Denis outlines some of the deficiencies in search engines, and how Perplexity’s approach to information retrieval improves on traditional search engine systems, with a focus on accuracy and validation of the information provided.

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