LangChain v0.0.45 Redis Cache support from @sjwhitmore Documentation improvements (one from @dheeraja486
, one highlighted by @altryne
) .gitignore improvements from @gojira
LLMS
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LangChain v0.0.45 Release: Redis Cache and Documentation Updates
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Three Stages of Humanity’s Growing Disconnection from Reality
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Stages in humanity’s disconnection from reality:
1. Reality TV
2. Social media
3. Chatbots -
Large language models used to write Twitter code deployment
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Maybe he started using large language models to write Twitter’s code, and deployed straight to prod
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ChatGPT Sparks Google Code Red Alert on AI Search Competition
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Searching is different from question/answering, and even though #ChatGPT still has plenty of room for improvement, it seems that its release definitely stirred things up at Google! Google’s management to declare a "code red" https://
nytimes.com/2022/12/21/tec
hnology/ai-chatgpt-google-search.html
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Google’s AI Model Announcements Lag Behind Meta and OpenAI
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True, honestly, IDK why they are running behind in the industry. since BERT they haven't announced any significant model release. while even meta, openai are moving really fast, even though google has more access to the world's data than any other org.
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Unavoidable difficulty of logprobs for completion sequences in classification
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The number of logprobs returned per token isn’t the issue here, it’s the unavoidable difficulty of getting logprobs for different completion sequences. In a classification context you need to assign class labels to individual tokens during training.
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Humor: RLHF works because practitioners are fast
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This is how RLHF works btw the people doing it are just really fast.
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LLM Emergent Properties and Their Staggering Economic Implications
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The emergent properties of LLM’s continue to astound me. The implications for work and the economy are staggering. It’s a growing focus for us at the @DigEconLab https://
t.co/mA2n7p48kR -
ML Startups Focus on LLM Application Layer Next Three Years
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This is my bet too. And one I’ve talked about a lot. Next 3 years of ML startups and AI/ML VC will be focused on the application layer of LLMs (even the compute-optimal mini-LLMs like chinchilla). Buckle up.