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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
237 episodes

Practical AI Practical AI #257

Leading the charge on AI in National Security

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2024-02-20T15:15:00Z #ai +2 🎧 17,109

Chris & Daniel explore AI in national security with Lt. General Jack Shanahan (USAF, Ret.). The conversation reflects Jack’s unique background as the only senior U.S. military officer responsible for standing up and leading two organizations in the United States Department of Defense (DoD) dedicated to fielding artificial intelligence capabilities: Project Maven and the DoD Joint AI Center (JAIC).

Together, Jack, Daniel & Chris dive into the fascinating details of Jack’s recent written testimony to the U.S. Senate’s AI Insight Forum on National Security, in which he provides the U.S. government with thoughtful guidance on how to achieve the best path forward with artificial intelligence.

Practical AI Practical AI #256

Gemini vs OpenAI

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2024-02-14T20:00:00Z #ai +2 🎧 22,016

Google has been releasing a ton of new GenAI functionality under the name “Gemini”, and they’ve officially rebranded Bard as Gemini. We take some time to talk through Gemini compared with offerings from OpenAI, Anthropic, Cohere, etc.

We also discuss the recent FCC decision to ban the use of AI voices in robocalls and what the decision might mean for government involvement in AI in 2024.

Practical AI Practical AI #255

Data synthesis for SOTA LLMs

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2024-02-06T22:00:00Z #ai +1 🎧 20,961

Nous Research has been pumping out some of the best open access LLMs using SOTA data synthesis techniques. Their Hermes family of models is incredibly popular! In this episode, Karan from Nous talks about the origins of Nous as a distributed collective of LLM researchers. We also get into fine-tuning strategies and why data synthesis works so well.

Practical AI Practical AI #254

Large Action Models (LAMs) & Rabbits 🐇

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2024-01-30T21:00:00Z #ai +2 🎧 23,925

Recently the release of the rabbit r1 device resulted in huge interest in both the device and “Large Action Models” (or LAMs). What is an LAM? Is this something new? Did these models come out of nowhere, or are they related to other things we are already using? Chris and Daniel dig into LAMs in this episode and discuss neuro-symbolic AI, AI tool usage, multimodal models, and more.

Practical AI Practical AI #251

AI predictions for 2024

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2024-01-10T19:30:00Z #ai +1 🎧 28,779

We scoured the internet to find all the AI related predictions for 2024 (at least from people that might know what they are talking about), and, in this episode, we talk about some of the common themes. We also take a moment to look back at 2023 commenting with some distance on a crazy AI year.

Practical AI Practical AI #250

Open source, on-disk vector search with LanceDB

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2023-12-19T19:40:00Z #ai +3 🎧 27,339

Prashanth Rao mentioned LanceDB as a stand out amongst the many vector DB options in episode #234. Now, Chang She (co-founder and CEO of LanceDB) joins us to talk through the specifics of their open source, on-disk, embedded vector search offering. We talk about how their unique columnar database structure enables serverless deployments and drastic savings (without performance hits) at scale. This one is super practical, so don’t miss it!

Practical AI Practical AI #249

The state of open source AI

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2023-12-12T19:45:00Z #oss +1
🎧 28,408

The new open source AI book from PremAI starts with “As a data scientist/ML engineer/developer with a 9 to 5 job, it’s difficult to keep track of all the innovations.” We couldn’t agree more, and we are so happy that this week’s guest Casper (among other contributors) have created this resource for practitioners.

During the episode, we cover the key categories to think about as you try to navigate the open source AI ecosystem, and Casper gives his thoughts on fine-tuning, vector DBs & more.

Practical AI Practical AI #246

Generating product imagery at Shopify

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2023-11-21T18:45:00Z #ai +1 🎧 26,049

Shopify recently released a Hugging Face space demonstrating very impressive results for replacing background scenes in product imagery. In this episode, we hear the backstory technical details about this work from Shopify’s Russ Maschmeyer. Along the way we discuss how to come up with clever AI solutions (without training your own model).

Practical AI Practical AI #245

AI trailblazers putting people first

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2023-11-14T17:45:00Z #ai +2 🎧 24,442

According to Solana Larsen: “Too often, it feels like we have lost control of the internet to the interests of Big Tech, Big Data — and now Big AI.” In the latest season of Mozilla’s IRL podcast (edited by Solana), a number of stories are featured to highlight the trailblazers who are reclaiming power over AI to put people first. We discuss some of those stories along with the issues that they surface.

Practical AI Practical AI #244

Government regulation of AI has arrived

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2023-11-07T14:00:00Z #ai +2 🎧 28,451

On Monday, October 30, 2023, the U.S. White House issued its Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. Two days later, a policy paper was issued by the U.K. government entitled The Bletchley Declaration by Countries Attending the AI Safety Summit, 1-2 November 2023. It was signed by 29 countries, including the United States and China, the global leaders in AI research.

In this Fully Connected episode, Daniel and Chris parse the details and highlight key takeaways from these documents, especially the extensive and detailed executive order, which has the force of law in the United States.

Practical AI Practical AI #243

Self-hosting & scaling models

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2023-10-31T18:00:00Z #ai +2 🎧 28,757

We’re excited to have Tuhin join us on the show once again to talk about self-hosting open access models. Tuhin’s company Baseten specializes in model deployment and monitoring at any scale, and it was a privilege to talk with him about the trends he is seeing in both tooling and usage of open access models. We were able to touch on the common use cases for integrating self-hosted models and how the boom in generative AI has influenced that ecosystem.

Practical AI Practical AI #242

Deep learning in Rust with Burn 🔥

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2023-10-24T20:40:00Z #ai +2 🎧 28,639

It seems like everyone is interested in Rust these days. Even the most popular Python linter, Ruff, isn’t written in Python! It’s written in Rust. But what is the state of training or inferencing deep learning models in Rust? In this episode, we are joined by Nathaniel Simard, the creator burn. We discuss Rust in general, the need to have support for AI in multiple languages, and the current state of doing “AI things” in Rust.

Practical AI Practical AI #240

Generative models: exploration to deployment

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2023-10-03T19:00:00Z #ai +2 🎧 34,585

What is the model lifecycle like for experimenting with and then deploying generative AI models? Although there are some similarities, this lifecycle differs somewhat from previous data science practices in that models are typically not trained from scratch (or even fine-tuned). Chris and Daniel give a high level overview in this effort and discuss model optimization and serving.

Practical AI Practical AI #238

Fine-tuning vs RAG

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2023-09-06T12:30:00Z #ai +1 🎧 36,604

In this episode we welcome back our good friend Demetrios from the MLOps Community to discuss fine-tuning vs. retrieval augmented generation. Along the way, we also chat about OpenAI Enterprise, results from the MLOps Community LLM survey, and the orchestration and evaluation of generative AI workloads.

Practical AI Practical AI #237

Automating code optimization with LLMs

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2023-08-29T21:30:00Z #ai +1 🎧 32,621

You might have heard a lot about code generation tools using AI, but could LLMs and generative AI make our existing code better? In this episode, we sit down with Mike from TurinTech to hear about practical code optimizations using AI “translation” of slow to fast code. We learn about their process for accomplishing this task along with impressive results when automated code optimization is run on existing open source projects.

Practical AI Practical AI #236

The new AI app stack

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2023-08-23T12:00:00Z #ai +2 🎧 34,277

Recently a16z released a diagram showing the “Emerging Architectures for LLM Applications.” In this episode, we expand on things covered in that diagram to a more general mental model for the new AI app stack. We cover a variety of things from model “middleware” for caching and control to app orchestration.

Practical AI Practical AI #235

Blueprint for an AI Bill of Rights

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2023-08-09T16:20:00Z #ai +3 🎧 32,238

In this Fully Connected episode, Daniel and Chris kick it off by noting that Stability AI released their SDXL 1.0 LLM! They discuss its virtues, and then dive into a discussion regarding how the United States, European Union, and other entities are approaching governance of AI through new laws and legal frameworks. In particular, they review the White House’s approach, noting the potential for unexpected consequences.

Practical AI Practical AI #234

Vector databases (beyond the hype)

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2023-08-01T18:30:00Z #ai +1 🎧 36,379

There’s so much talk (and hype) these days about vector databases. We thought it would be timely and practical to have someone on the show that has been hands on with the various options and actually tried to build applications leveraging vector search. Prashanth Rao is a real practitioner that has spent and huge amount of time exploring the expanding set of vector database offerings. After introducing vector database and giving us a mental model of how they fit in with other datastores, Prashanth digs into the trade offs as related to indices, hosting options, embedding vs. query optimization, and more.

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