Matt Shaffer @_w_x_b_
https://t.co/zfA2V8cQPo Data scientist/software engineer/roboticist teaching machines to learn responsibly for the benefit of humankind. DiscoverMatt.com San Francisco Bay Area, CA Joined February 2014-
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New research on grokking suggests that Softmax Collapse (SC) from numerical instability & Naive Loss Minimization (NLM) are key hurdles to generalization. Proposed StableMax & ⊥Grad show promise in addressing these. openreview.net/forum?id=TvfkS… github.com/LucasPrietoAl/…
"Action precedes motivation". - @3blue1brown You don't have to be a 2024 graduate to appreciate this. If you reframe the advice as being directed at startups finding their way it might be just as relevant. youtube.com/watch?v=W3I3kA…
"LLMs are not genies that grant wishes. They are idiot savants that you can make on your computer." bit.ly/LocalLLaMA-com…
Losing track of all the recent large language model (LLM) developments? Here's is another comprehensive LLM model zoo, available as table and dependency graph: crfm.stanford.edu/ecosystem-grap…
Visualizing S&P 500 Performance in 2022, by Sector ift.tt/21Pjo6t
"One of the messages here is that all of these components: compliance, closed loop operation and accurate enough perception are needed to make such an end-to-end manipulation system work" youtu.be/HL7G08rzHsI
No matter how good an artist you are, who hasn't dreamed of doing this?
No matter how good an artist you are, who hasn't dreamed of doing this?
Full of insights for people searching for jobs -- but also companies looking to hire.
Full of insights for people searching for jobs -- but also companies looking to hire.
Wondered how that table tennis playing robot actually works? As a table tennis player as well as AI researcher, I had to understand more! I made a short video explaining the system, w/ focus on the reinforcement learning aspect: youtu.be/ktkbxWcYiF8
Counterintuitively, this research suggests the educated may need to be even more careful when interpreting data. "Critically, we showed that this association was causal: visualizing the same data in a more beautiful way caused people to trust it more" psyarxiv.com/dnr9s

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