Computer scientists as rogue art historians
04/12/23 • 43 min
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What can art historians and computer scientists learn from one another? Actually, a lot! Amanda Wasielewski joins us to talk about how she discovered that computer scientists working on computer vision were actually acting like rogue art historians and how art historians have found machine learning to be a valuable tool for research, fraud detection, and cataloguing. We also discuss the rise of generative AI and how we this technology might cause us to ask new questions like: “What makes a photograph a photograph?”
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Featuring:
- Amanda Wasielewski – Website, X
- Chris Benson – Website, GitHub, LinkedIn, X
- Daniel Whitenack – Website, GitHub, X
Show Notes:
Something missing or broken? PRs welcome!
What can art historians and computer scientists learn from one another? Actually, a lot! Amanda Wasielewski joins us to talk about how she discovered that computer scientists working on computer vision were actually acting like rogue art historians and how art historians have found machine learning to be a valuable tool for research, fraud detection, and cataloguing. We also discuss the rise of generative AI and how we this technology might cause us to ask new questions like: “What makes a photograph a photograph?”
Changelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!
Sponsors:
- Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com
- Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs.
- Typesense – Lightning fast, globally distributed Search-as-a-Service that runs in memory. You literally can’t get any faster!
Featuring:
- Amanda Wasielewski – Website, X
- Chris Benson – Website, GitHub, LinkedIn, X
- Daniel Whitenack – Website, GitHub, X
Show Notes:
Something missing or broken? PRs welcome!
Previous Episode
Accelerated data science with a Kaggle grandmaster
Daniel and Chris explore the intersection of Kaggle and real-world data science in this illuminating conversation with Christof Henkel, Senior Deep Learning Data Scientist at NVIDIA and Kaggle Grandmaster. Christof offers a very lucid explanation into how participation in Kaggle can positively impact a data scientist’s skill and career aspirations. He also shared some of his insights and approach to maximizing AI productivity uses GPU-accelerated tools like RAPIDS and DALI.
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Sponsors:
- Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com
- Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs.
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Featuring:
- Christof Henkel – GitHub, LinkedIn, X
- Chris Benson – Website, GitHub, LinkedIn, X
- Daniel Whitenack – Website, GitHub, X
Show Notes:
- Christof Henkel | Kaggle
- NVIDIA Kaggle Grandmasters
- Kaggle
- NVIDIA RAPIDS
- NVIDIA Data Loading Library (DALI)
Something missing or broken? PRs welcome!
Next Episode
Capabilities of LLMs 🤯
Large Language Model (LLM) capabilities have reached new heights and are nothing short of mind-blowing! However, with so many advancements happening at once, it can be overwhelming to keep up with all the latest developments. To help us navigate through this complex terrain, we’ve invited Raj - one of the most adept at explaining State-of-the-Art (SOTA) AI in practical terms - to join us on the podcast.
Raj discusses several intriguing topics such as in-context learning, reasoning, LLM options, and related tooling. But that’s not all! We also hear from Raj about the rapidly growing data science and AI community on TikTok.
Changelog++ members support our work, get closer to the metal, and make the ads disappear. Join today!
Sponsors:
- Fastly – Our bandwidth partner. Fastly powers fast, secure, and scalable digital experiences. Move beyond your content delivery network to their powerful edge cloud platform. Learn more at fastly.com
- Fly.io – The home of Changelog.com — Deploy your apps and databases close to your users. In minutes you can run your Ruby, Go, Node, Deno, Python, or Elixir app (and databases!) all over the world. No ops required. Learn more at fly.io/changelog and check out the speedrun in their docs.
Featuring:
- Rajiv Shah – Website, GitHub, LinkedIn, X
- Chris Benson – Website, GitHub, LinkedIn, X
- Daniel Whitenack – Website, GitHub, X
Show Notes:
- Solving AI Tasks with ChatGPT and its Friends in HuggingFace | GitHub
- Generative Agents: Interactive Simulacra of Human Behavior
- Wolfram ChatGPT
- Comparing LLMs
- LangChain
- Learn about LLMs:
- Learning Prompting
- Getting Started with Transformers:
- Training your own LLM Models:
- Dolly blog post
- Illustrating Reinforcement Learning from Human Feedback
Something missing or broken? PRs welcome!
Practical AI - Computer scientists as rogue art historians
Transcript
Welcome to another episode of Practical AI. This is Daniel Whitenack. I'm a data scientist with SIL International, and I'm joined as always by my co-host, Chris Benson, who is a tech strategist at Lockheed Martin. How're you doing, Chris?
Chris Benson:Doing well, Daniel. How are you today?
Daniel Whitenack:I'm actually super-excited for this conversation, because I don't know about you,
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