AI - AI Dynamics

→ View original post on X — @alliekmiller

AI Expert Shares Insights on Technology and Venture Capital

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@alliekmiller

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19 December 2022 19h34

Thanks for reading this far. I've worked in artificial intelligence for startups and 2 of the 5 largest cloud providers and have been an angel investor in the space for 5+ years. Follow me @alliekmiller for more insights on AI, tech, business, and venture capital.

→ View original post on X — @levelsio

Building Furniture Recognition System with Machine Learning

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@levelsio

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19 December 2022 18h43

Really really really hard problem to solve, need a massive database of furniture objects and then recognize them, I have no idea how to that, tried to learn it but it's very difficult

→ View original post on X — @cerebras

Cerebras CS-2 Python API Achieves 470x Faster Performance

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@cerebras

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19 December 2022 18h29

At #SC22, Dr. Dirk Van Essendelft from the National Energy Technology Laboratory presented a Python API to build applications that run on Cerebras CS-2 systems with impressive results – 470x faster than the Joule supercomputer! Watch his lecture:

Anthropic Hiring Research Engineers and Scientists for AI Evaluation

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19 December 2022 17h57

We’re also actively hiring research engineers/scientists to develop evaluations and to find/fix flaws with LMs/RLHF. If you’re interested, we’d encourage you to apply!
Research engineer: https://
jobs.lever.co/Anthropic/436c
a148-6440-460f-b2a2-3334d9b142a5
…
Research scientist: https://
jobs.lever.co/Anthropic/eb9e
6d83-626c-4f59-8a0e-fa7c413b2014
…

Language Models Augmenting Evaluation Authors for Faster Assessment

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19 December 2022 17h57

We’re excited about the potential of LMs to augment evaluation authors, so that they can run more (and larger) evaluations more quickly. We encourage you to read our paper for more results/details: https://
anthropic.com/model-written-
evals.pdf
…
Generated data:

Interactive Visualizations for Model-Written Dataset Evaluations Released

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19 December 2022 17h57

To help readers understand our evaluations better, we created interactive visualizations showcasing the diversity of each of the model-written datasets: https://t.co/yc9oP9n9uV pic.twitter.com/R5IH7nTJw4
— Anthropic (@AnthropicAI) 19 décembre 2022

To help readers understand our evaluations better, we created interactive visualizations showcasing the diversity of each of the model-written datasets: https://
evals.anthropic.com/model-written/

RLHF Training Shows Inverse Scaling Issues in Model Behavior

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19 December 2022 17h57

We also find some of the first instances of inverse scaling for RL from Human Feedback (RLHF), where more RLHF training makes behavior worse. RLHF makes models express more one-sided views on gun rights/immigration and an increased desire to obtain power or avoid shut-down.

Large Language Models More Sycophantic Than Small Ones

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19 December 2022 17h57

Using these LM-written evals, we found many new instances of "inverse scaling," where larger LMs are worse than smaller ones. For example, larger LMs are more sycophantic, repeating back a user's views as their own in 75-98% of conversations.

LM-written data verified by human evaluators for quality

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19 December 2022 17h57

We verified LM-written data with human evaluators, who agreed with the data’s labels and rated the examples favorably on both diversity and relevance to the tested behavior. We’ve released our evaluations at