AI for science is already here! 20% of researchers say they use LLMs as a scientific search engine, or for brainstorming, or literature reviews, or even to help write manuscripts. Awesome paper published in Nature @Richvn / JM Perkel
LLMS
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Building RAG-Based LLM Applications for Production
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Building RAG-based LLM Applications for Production (Part 1) https://
bit.ly/3raSWaB
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Major LLM Project Videos Coming Soon to Channel
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Everyone right now…😅
— Louis-François Bouchard 🎥🤖 (@Whats_AI) 1 octobre 2023
Stay tuned for a lot of new videos coming in the next 10 days on my channel for a project we’ve been working on for months now… Useful to anyone involved with large language models (LLMs) and want to use them!#ai #llm #llms #gpt #chatgpt #languagemodels pic.twitter.com/n2vPlEm92NEveryone right now… Stay tuned for a lot of new videos coming in the next 10 days on my channel for a project we’ve been working on for months now… Useful to anyone involved with large language models (LLMs) and want to use them! #ai #llm #llms #gpt #chatgpt #languagemodels
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ChatGPT Voice Speed Control and Text Mode Switching Features
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Need ChatGPT voice 2x speed Plus jump in and out of text mode
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MentalLlaMa: Open-Source LLM for Mental Health Analysis
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9/ MentalLlaMa – an open-source LLM series for interpretable mental health analysis with instruction-following capability; proposes a multi-task and multi-source interpretable mental health instruction dataset on social media with 105K data samples.
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Logical Chain-of-Thought Framework Improves LLM Reasoning
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10/ Logical Chain-of-Thought in LLMs – a new neurosymbolic framework to improve zero-shot chain-of-thought reasoning in LLMs; leverages principles from symbolic logic to verify and revise reasoning processes to improve the reasoning capabilities of LLMs.
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LLM Alignment Survey: Comprehensive Review of Safety and Interpretability
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7/ LLM Alignment Survey – a comprehensive survey paper on LLM alignment; topics include Outer Alignment, Inner Alignment, Mechanistic Interpretability, Attacks on Aligned LLMs, Alignment Evaluation, Future Directions, and Discussions.
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Qwen LLM Demonstrates RLHF Strength in Tool Use and Planning
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8/ Qwen LLM – proposes a series of LLMs demonstrating the strength of RLHF on tasks involving tool use and planning capabilities for creating language agents.
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LlaVA-RLHF Achieves GPT-4 Level Performance on Multimodal Tasks
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6/ LlaVA-RLHF – adapts factually augmented RLHF to aligning large multimodal models; this approach alleviates the reward hacking in RLHF and improves performance on the LlaVA-Bench dataset with the 94% performance level of the text-only GPT-4.
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Graph Neural Prompting Enhances LLMs Knowledge Learning
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3/ Graph Neural Prompting with LLMs – proposes a plug-and-play method to assist pre-trained LLMs in learning beneficial knowledge from knowledge graphs (KGs).