AI - AI Dynamics

→ View original post on X — @yoheinakajima

Data Privacy and Tech Company Trust in AI Models

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@yoheinakajima

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16 March 2023 19h48

Technically, I'm having the model predict tokens based on tokens it's calculating from the sensitive data – which is different from "feeding sensitive data to the model". Though if your question is around whether we can trust tech cos not to use the sensitive data for purposes

→ View original post on X — @erictopol

AI Research Reveals Rising Colon Cancer Cases Young Adults

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@erictopol

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16 March 2023 19h37

Why are so many young people getting colon cancer? https://
science.org/doi/10.1126/sc
ience.ade7114
… @ScienceMagazine w/ @ScienceVisuals by @GiannakisLab @KimmieNgMD @DFarberYoungCRC @DanaFarber

→ View original post on X — @learnopencv

GPT-4 as a Multiplier: Amplifying Engineering Capabilities

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@learnopencv

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16 March 2023 19h36

GPT-4 should be thought of as a multiplier to your capabilities. If you are a 1x engineer, you can become 10x. If you are a 0x engineer, you will stay at 0 or may even go negative. I just asked GPT-4 to write OpenCV code for Photometric Stereo, and it produced beautiful code.

GPT-3.5-Turbo Praised for Academic Research with 10x Price Reduction

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16 March 2023 19h36

I also think gpt-3.5-turbo is great for academic research, with a 10x reduction in price

Llama Model Enables Emergence Research with Strong Performance

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16 March 2023 19h36

And by the way, I think Llama is great for enabling emergence research to be done, strong performance and multiple model sizes.

Emergent Behavior in Language Models: Scaling, Prediction, and Optimization

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16 March 2023 19h36

6. Studying emergent behavior in language models. – How/why does scaling unlock emergence?
– Can we predict future emergent capabilities?
– How do we get these abilities in smaller models?

Understanding How Language Models and Prompting Work

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16 March 2023 19h36

5. Why language models / prompting works. We still don’t have a great understanding of how in-context learning works, or why chain-of-thought/reasoning works. We can learn a great deal by only looking at inputs and outputs (as do we do with humans in psychology).

Building Evaluations for Frontier Language Models

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16 March 2023 19h36

2. Building evaluations. Many benchmarks get quickly saturated, and we need more to evaluate the frontier of language models. In addition, it’s still an open question of how to evaluate language models generally. The new OpenAI evals library could be good: https://
github.com/openai/evals

Prompting Research: Just the Beginning for Language Model Guidance

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16 March 2023 19h36

1. Prompting research. Maybe hot take, but I think we’ve just reached the tip of the iceberg on the best ways to prompt language models. As language model capabilities increase, the degrees of freedom for guiding a particular generation via a good prompt will increase.