Chris Benson
Cohost @ Practical AI Podcast • Principal AI / Autonomy Research Engineer specializing in fully autonomous UxS swarming with embodied intelligence.
Appears in 335 Episodes
🌍 AI in Africa - Radiant Earth
In the second of the “AI in Africa” spotlight episodes, we welcome guests from Radiant Earth to talk about machine learning for earth observation. They give us a glimp...
OpenAI and Hugging Face tooling
The time has come! OpenAI’s API is now available with no waitlist. Chris and Daniel dig into the API and playground during this episode, and they also discuss some of ...
Friendly federated learning 🌼
This episode is a follow up to our recent Fully Connected show discussing federated learning. In that previous discussion, we mentioned Flower (a “friendly” federated ...
AI-generated code with OpenAI Codex
Recently, GitHub released Copilot, which is an amazing AI pair programmer powered by OpenAI’s Codex model. In this episode, Natalie Pistunovich tells us all about Code...
Zero-shot multitask learning
In this Fully-Connected episode, Daniel and Chris ponder whether in-person AI conferences are on the verge of making a post-pandemic comeback. Then on to BigScience fr...
Analyzing the 2021 AI Index Report
Each year we discuss the latest insights from the Stanford Institute for Human-Centered Artificial Intelligence (HAI), and this year is no different. Daniel and Chris ...
Photonic computing for AI acceleration
There are a lot of people trying to innovate in the area of specialized AI hardware, but most of them are doing it with traditional transistors. Lightmatter is doing s...
Eureka moments with natural language processing
When is the last time you had a eureka moment? Chris had a chat with Nicholas Mohnacky, CEO and Cofounder of bundleIQ, where they use natural language processing algor...
🌍 AI in Africa - Makerere AI Lab
This is the first episode in a special series we are calling the “Spotlight on AI in Africa”. To kick things off, Joyce and Mutembesa from Makerere University’s AI Lab...
Federated Learning 📱
Federated learning is increasingly practical for machine learning developers because of the challenges we face with model and data privacy. In this fully connected epi...
The mathematics of machine learning
Tivadar Danka is an educator and content creator in the machine learning space, and he is writing a book to help practitioners go from high school mathematics to mathe...
Balancing human intelligence with AI
Polarity Mapping is a framework to “help problems be solved in a realistic and multidimensional manner” (see here for more info). In this week’s fully connected episod...
Trends in data labeling
Any AI play that lacks an underlying data strategy is doomed to fail, and a big part of any data strategy is labeling. Michael, from Label Studio, joins us in this epi...
Stellar inference speed via AutoNAS
Yonatan Geifman of Deci makes Daniel and Chris buckle up, and takes them on a tour of the ideas behind his amazing new inference platform. It enables AI developers to ...
Anaconda + Pyston and more
In this episode, Peter Wang from Anaconda joins us again to go over their latest “State of Data Science” survey. The updated results include some insights related to d...
Exploring a new AI lexicon
We’re back with another Fully Connected episode – Daniel and Chris dive into a series of articles called ‘A New AI Lexicon’ that collectively explore alternate narrati...
SLICED - will you make the (data science) cut?
SLICED is like the TV Show Chopped but for data science. Competitors get a never-before-seen dataset and two-hours to code a solution to a prediction challenge. Meg an...
AI is creating never before heard sounds! 🎵
AI is being used to transform the most personal instrument we have, our voice, into something that can be “played.” This is fascinating in and of itself, but Yotam Man...
Building a data team
Inspired by a recent article from Erik Bernhardsson titled “Building a data team at a mid-stage startup: a short story”, Chris and Daniel discuss all things AI/data te...
Towards stability and robustness
9 out of 10 AI projects don’t end up creating value in production. Why? At least partly because these projects utilize unstable models and drifting data. In this episo...