interesting. Now give us GPT 4.5 ffs. @apples_jimmy @futuristflower
GENERATIVE AI
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The Trade-off Between Browsing Capability and LLM Creative Magic
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Browsing is great for information retrieval and massively reduces hallucinations, but I feel that it is easy for models that browse to lose some of the “magic” of large language models. What I mean by magic is when language models give rich, organic responses reflecting the
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AI Features Rollout Across Devices and Consumer Hardware
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I wrote about giants like Samsung, Google, Qualcomm, Microsoft — along with startups like OpenAI and Rabbit — already are bringing to market new AI features for smartphones, laptops, TVs, cars, XR headsets, handheld gadgets and even grocery carts.
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AlphaGeometry Impresses IMO Legend with Elegant Math Solutions
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Last month, I showed #AlphaGeometry solution to my Olympiad math teacher, Dr Le Ba Khanh Trinh, who was quite legendary in Vietnam as he ranked #1 at IMO 1979 with a special prize given for solving a geometry problem that year so elegantly. Dr. Le was quite impressed as the
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AlphaGeometry Solves IMO 2015 Problem with Neural Assistance
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In case you wonder how an #AlphaGeometry solution looks like, check out the full solution (109 step!) here. In this IMO 2015, problem #3, the symbolic component asked for help from the neural language models 3 times (the auxiliary constructions in blue) before succeeding 🙂
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Fine-tune Zephyr-7B for Customer Service Intent Detection
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ICYMI: We recently released a new #LLM tutorial for #finetuning open-source #Zephyr-7B to determine the intent of customer service tickets. Sample data, code and notebooks included. Check it out to get started! https://
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Stanford AI Tool Helps Composers with Anticipatory Music Transformer
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In this video, @Stanford scholar @jwthickstun demos the Anticipatory Music Transformer, a new AI tool for composers:
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Flow Engineering Boosts Code Generation Performance Significantly
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Prompt engineering (or rather "Flow engineering") intensifies for code generation. Great reading and a reminder of how much alpha there is (pass@5 19% to 44%) in moving from a naive prompt:answer paradigm to a "flow" paradigm, where the answer is constructed iteratively.
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GTC24 Conference Explores RAG and AI Innovation Potential
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Exciting #GTC24 Announcement! Attend enlightening sessions led by visionary CEOs, data scientists, and industry experts to explore the potential of retrieval-augmented generation (#RAG). Register now to revolutionize your AI projects: https://
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Free Webinar on RAG Systems, ChatLLMs, and AI Agents
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We at http://
Abacus.AI are hosting a free webinar on RAG systems, ChatLLMs, & AI Agents next week! We kick-off with a brief overview of LLMs and and recent developments in the AI landscape and also cover/provide a demonstration on the following: •Chat/Data/DocLLMs –