Interconnects

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Evaluating and uncovering open LLMs
When choosing a model, we're stuck in the middle between classic NLP benchmarks (e.g. MMLU) and qualitative chatbot ranking. Neither are exactly what we…
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Nathan Lambert
2
Code: green pastures for LLMs
Both code-generation and code-training seem central to LLM progress, present and future.
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Nathan Lambert
Unfortunately, OpenAI and Google have moats
While everyone went crazy over a leaked memo, no one took the time to think through how companies have worked in the internet era.
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Nathan Lambert
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Behind the curtain: what it feels like to work in AI right now
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21
Unfortunately, OpenAI and Google have moats
 • Nathan Lambert
3
Predicting machine learning moats
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6
Beyond human data: RLAIF needs a rebrand
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3
The RLHF battle lines are drawn
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Specifying hallucinations
The future of LLM errors and the need for a discourse around the specification of unexpected outputs.
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Nathan Lambert
6
Beyond human data: RLAIF needs a rebrand
Reinforcement learning from computational feedback: how a promising method is being ignored because of a confusing launch.
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Nathan Lambert
3
The next chapter: Interconnects
Democratizing Automation is now Interconnects. Doubling down on making the most important links in AI.
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Nathan Lambert
Growing needs for accessing state-of-the-art reward models
The rewards assigned by these models will control the subjective experience of users; the subjective experience controls their decision-making.
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Nathan Lambert
8
Behind the curtain: what it feels like to work in AI right now
Fear, FOMO, and the scientific exodus driven by ChatGPT
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Nathan Lambert
21
The implicit dynamics of optimizing costs vs. rewards vs. preferences
With the emergence of reinforcement learning from human feedback, we've been applying old techniques with a new guiding function (🤫 RLHF).
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Nathan Lambert
GPT4: The quiet parts and the state of ML
Checking in on the state of the ML field: technical progress, societal implications, and more.
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Nathan Lambert
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Interconnects
Interconnects
Linking important ideas of AI. The interface of systems and society. The border between high-level and technical thinking. Most Wednesday mornings.
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