True. However, very excited for Grok3 on that massive cluster
LLMS
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ChatGPT vs Competitors: Comparing AI Chatbot Solutions
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I default to ChatGPT and then try the others to see how they compare.
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Elon Musk Launches Free Grok 2 AI Tier on X Platform
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Elon Musk goes into AI battle! There is now a free tier for Grok 2 on X, which is certainly sufficient for everyday use. If you own premium, you have even more access to Grok 2 and probably soon Grok 3 as well. You can say what you like: X makes absolutely great deals on its
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Grok vs ChatGPT: Performance Comparison on Practical Tasks
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Just found one thing Grok fails on that ChatGPT answers properly. We rented a manual transmission Opal in Spain. I tried many things and couldn’t figure out how to put it in reverse. ChatGPT’s first suggestion was right. Grok didn’t even suggest it. Do you have others? Oh
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Full o1 and Sora Release Expected at November 21 DevDay
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Full o1 and Sora on Devday November 21?
— Chubby♨️ (@kimmonismus) 10 novembre 2024
How can this post be ignored? Hensen Juang is a reliable Person who says in 14 days we see a "new dawn".
After seeing more and more leaks, I expect Sora and Full o1.
According to research, a dev day is planned for November 21 in… https://t.co/v5JcZwpmcEFull o1 and Sora on Devday November 21? How can this post be ignored? Hensen Juang is a reliable Person who says in 14 days we see a "new dawn". After seeing more and more leaks, I expect Sora and Full o1.
According to research, a dev day is planned for November 21 in -
Fine-tuning LLMs to learn from tools and adaptive problem-solving
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9). Adapting while Learning – proposes a two-part fine-tuning approach that first helps LLMs learn from tool-generated solutions and then trains them to determine when to solve problems directly versus when to use tools; testing on math, climate science, and epidemiology
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Personalization Framework for Large Language Models
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10). Personalization of LLMs – presents a comprehensive framework for understanding personalized LLMs; introduces taxonomies for different aspects of personalization and unifying existing research across personalized text generation and downstream applications.
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LLM Numerical Understanding: Fine-tuning Improves Processing Ability
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7). Number Understanding of LLMs – provides a comprehensive analysis of the numerical understanding and processing ability (NUPA) of LLMs; finds that naive finetuning can improve NUPA a lot on many but not all tasks…
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WebRL Self-Evolving Framework Boosts Open LLM Web Agents
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8). WebRL – proposes a self-evolving online curriculum RL framework to bridge the gap between open and proprietary LLM-based web agents; it improves the success rate of Llama-3.1-8B from 4.8% to 42.4%, and from 6.1% to 43% for GLM4-9B; the open models significantly surpass the
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Multi-Expert Prompting: Aggregating LLM Responses for Better Outputs
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6). Multi-expert Prompting with LLMs – improves LLM responses by simulating multiple experts and aggregating their responses; it guides an LLM to fulfill input instructions by simulating multiple experts and selecting the best response among individual and aggregated views.