Vanishing Gradients
Hugo Bowne-Anderson, Sebastian Raschka, PhD, Alex Strick van Linschoten, Hamel Husain, Eleanor Berger, Bryan Bischof, John Berryman, Antaripa SahaEverything you wanted to know about data, ML, and AI, but were too afraid to ask.
| Platform |  | Pricing | Only free issues | Publishes | Twice weekly |
|---|---|---|---|---|---|
| Issues | 84 | Founded | 2 years ago | Last Issue | 10 days ago |
| Active | |||||
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hugobowne.substack.comLatest Issues
Beyond Navier–Stokes: Who Controls Scientific Discovery?
Is the current furore in mathematics the canary in the coalmine for experimental science and knowledge work?
Science without understanding?
I recently went back to Dresden for the 25th birthday of the Max Planck Institute (MPI) for Cel...
Chip Huyen Used 1,409 Agents on One Project
People spent the past few years declaring data science dead. Then we started building agents that produce mountains of noisy data and plausible-looking answers.
Someone has to figure out whether any of it works. Hamel Husain calls this the...
How Evals Are Central To Harness Engineering
Today’s post comes from Antaripa Saha, a machine learning practitioner who worked directly with production evals at Quotient AI.
She makes the case that evals belong at the center of harness engineering. A harness gives an agent tools, mem...
How to Build a Search Agent and Prove It Works
“Just adding reasoning to a dumb retrieval system gives me a 15% improvement”
— Doug Turnbull (Search expert, led Search at Reddit and Shopify)
John Berryman and Doug Turnbull started with BM25, a widely used keyword-search method that ra...
RAG Isn’t Dead. It’s Sleeping.
Doug Turnbull asked ChatGPT to list his posts about BM25. It returned titles and summaries for articles he had never written.
Classic RAG addressed that failure by retrieving documents before asking the model to answer. But the architectur...
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Authors
The writers behind this newsletter.
I help teams build with AI. I’m an independent data and AI consultant who’s advised and taught engineers from Netflix, Meta, and Amazon, and written about data science and AI for publications such as Harvard Business Review and VentureBeat.
I'm an LLM research engineer 10+ years of experience in artificial intelligence. My expertise lies in AI & LLM research focusing on code-driven implementations. I am also the author of "Build a Large Language Model From Scratch" (amzn.to/4fqvn0D).
ML Engineer @ ZenML
I am a machine learning engineer with over 20 years of experience. More about me @ https://hamel.dev
I lead ai at Theory Ventures.
I was an early product engineer on GitHub Copilot. And I wrote a couple of books! One on Prompt Engineering (https://amzn.to/4gChsFf) and one on Relevant Search (https://amzn.to/3TXmDHk)
ML Engineer working on evals and search.
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