Professor Stephen Bach offers an exceptionally clear description of the three training phases required to make LLMs perform. https://
snorkel.ai/large-language
-model-training-three-phases-shape-llm-training/
… #largelanguagemodels #llmtraining #genai
LLMS
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Three Training Phases Required for LLM Performance
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NVIDIA GTC24 AI Day for VCs: Generative AI and LLM Trends
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Understand trends within the #generativeAI and LLM ecosystem from the perspective of NVIDIA, portfolio startups, and investors. Don't miss AI Day for VC's in person at #GTC24: https://
nvda.ws/4bRUhW9 -
Perfect Memory Retrieval Enhances AI Performance
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100% the perfect memory retrieval goes a long way too.
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Cohere and Redis Enable Vector Data Retrieval Pipelines
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Businesses can now build data retrieval pipelines with Cohere and @RedisInc
. With the release of Redis Vector Library, Redis customers can seamlessly use Cohere’s Embed v3 model to transform their text data into embeddings. Full guide here: -
Citing AI Models with Dates for Research Reproducibility
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If you are writing a paper on AI, cite the model number but also the date range in which you used it. These systems are being continually improved and tuned. However, the lack of clear changes or versioning makes replicability hard sometimes (along with inherent LLM randomness)
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Testing ChatGPT’s Response to Unknown Input
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Just out of curiosity, I plugged it into ChatGPT to see how it would respond…
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Survey Paper Overview: Understanding LLM Architecture and Design
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If you want a resource for learning more about LLMs this survey paper provides a very nice overview. There’s several useful diagrams, including the one below which shows a breakdown of how LLMs are built.
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Self-corrective coding assistant with LangGraph and AlphaCodium
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Building a self-corrective coding assistant from scratch with LangGraph Code generation / analysis is one of the most important LLM applications. @itamar_mar and team recently released AlphaCodium, which showed that code generation can be improved by using a flow paradigm to
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RAG Cheatsheet: Complete Guide with GitHub and Research Papers
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Download the full 5-page PDF => RAG (Retrieval Augmented Generation) Cheatsheet (with links to GitHub and research papers): https://
linkedin.com/feed/update/ur
n:li:activity:7164902842330275840/
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#AI #GenerativeAI #DeepLearning #Semantic #KnowledgeGraphs #GraphDB #VectorDB #LLMs #MachineLearning #DataScience -
Gemini Pro 1.0 Now Available as Multimodal Base Bot
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Now available: Gemini Pro 1.0 as a base bot! This multimodal bot accepts text, image, and video input, and has been upgraded with overall quality improvements, including improved reasoning, better latency, and multilingual support. We look forward to seeing what you build! pic.twitter.com/bjD8KeFZXw
— Poe (@poe_platform) 28 février 2024Now available: Gemini Pro 1.0 as a base bot! This multimodal bot accepts text, image, and video input, and has been upgraded with overall quality improvements, including improved reasoning, better latency, and multilingual support. We look forward to seeing what you build!