Reflexion: Language Agents with Verbal Reinforcement Learning Shinn et al.: https://
arxiv.org/abs/2303.11366 #AIGgents #DeepLearning #ReinforcementLearning
LLMS
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Language Agents with Verbal Reinforcement Learning Study
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Chunking Techniques for Better AI Context Organization
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it definitely does this and as @bwatson suggests, chunking tends to help for this kind of use case it's also not as important to me that it gets every last detail—more just giving me a zoomed out view that helps me organize myself
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GPT-4 Excellence in Note Organization and Content Synthesis
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I will never not be amazed at how good GPT-4 is at turning a twisted jumble of notes into something clean, organized, and comprehensible…
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Groq Sponsors Imagine Nation ELC 2023 with LPU Demo
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We are proud to sponsor @ACTIAC
's Imagine Nation ELC 2023. Our Public Sector Team members would love to show you our #LLM demo running on our Language Processing Units™ (LPUs™). #ImagineNationELC #LPU #LanguageProcessingUnit #GenAI -
Open-source Framework for Autonomous Language Agents
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Agents: An Open-source Framework for Autonomous Language Agents Zhou et al.: https://
arxiv.org/abs/2309.07870 #ArtificialIntelligence #DeepLearning #MachineLearning -
Learning Agents Getting Started Course Guide
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Learning Agents – Getting Started | Course https://
bit.ly/3EAtXQR
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LLM Latency Emerges as Primary Challenge for Users
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“The No. 1 thing we’re hearing from people right now is that on LLMs, latency is the problem,” Ross said. Read more in this week's article in the EE Times by Sally Ward Foxton.
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Handling Large Documents Exceeding Context Windows
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ah. curious to see approaches to large documents that wont fit in the context window 🙂
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Study reveals behavior gaps in large language models
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Should we delegate important tasks to AI? A new benchmark study reveals behavior gaps in large language models.
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Interactive Virtual Panel on LLMs: Open-source vs Commercial Solutions
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Don't miss our interactive virtual panel with #LLM experts from @llama_index
, Bank of America & @predibase Topics: Open-source vs. commercial LLMs High-value use cases Tips for customization (#RAG, #finetuning) Overcoming common pitfalls https://
pbase.ai/3PDq4Qz