Really awesome to see LLM research happening in india
LLMS
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Game-Changing Smartphone Trends Defining 2025 with AI
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8 Game-Changing Smartphone Trends That Will Define 2025 #AI innovation and sustainability dominate 2025's #smartphone #trends, with #LLM-powered #assistants and eco-friendly #designs leading the way. Discover how multi-screen displays, revolutionary batteries, and enhanced
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Using GPT-4 for PDF text extraction and summarization
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I've had great success using GPT-4 to extract text and summarize key points from PDFs.
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Ollama Model Interaction Gradio App for Text and Image Analysis
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Ollama-Model-Interaction A simple Gradio-based app for interacting with @ollama models, supporting image analysis, text completion, and model pulling
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TokenFormer: Efficient Transformer Architecture Scaling from 124M to 1.4B Parameters
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TokenFormer, a new model architecture from @cvml_mpiinf and @PKU1898
, scales from 124M to 1.4B parameters by treating parameters as tokens, maintaining Transformer performance with lower cost. Talk to the team @haiyang73756134 @ferjadnaeem @xyongqin @janericlenssen @fedassa here! -
Mistral Releases Batch API and Moderation API for Cost Efficiency
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Today we are releasing a Batch API and a Moderation API ! The batch API allows to process high-volume requests to all Mistral models at 50% lower cost. https://
mistral.ai/news/batch-api/ https://
mistral.ai/news/mistral-m
oderation/
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Mistral Launches Moderation and Batch APIs
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Moderation API – https://
mistral.ai/news/mistral-m
oderation/
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Batch API – -
Building Reliable LLM Applications with Gradio Playground
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In his talk at Lllamapalooza NYC, @dawoodnyc
, co-founder of @Gradio (Acq. by @huggingface
) shared insights into building reliable applications with large language models (LLMs), specifically focusing on the Gradio Playground, powered by Cerebras Inference Check out the -
LLMs as Operating Systems: Agent Memory Course with Letta AI
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New short course: LLMs as Operating Systems: Agent Memory, created with @Letta_AI, and taught by its founders @charlespacker and @sarahwooders.
— Andrew Ng (@AndrewYNg) 7 novembre 2024
An LLM's input context window has limited space. Using a longer input context also costs more and results in slower processing. So,… pic.twitter.com/Akw6uPPIbqNew short course: LLMs as Operating Systems: Agent Memory, created with @Letta_AI
, and taught by its founders @charlespacker and @sarahwooders
. An LLM's input context window has limited space. Using a longer input context also costs more and results in slower processing. So, -
Berkeley Research on AI Evaluations and Agent Systems
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Two of the things we spend the most time thinking about are evals and agents This new research from @sh_reya and Ankush Garg at Berkeley touches on BOTH those things Includes an example notebook for how to run on your LangGraph app!