How the GapEncoder works https://
bit.ly/49pcJ7F
#AI #MachineLearning #DeepLearning #LLMs #DataScience
LLMS
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GapEncoder: How This AI Technique Works
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ChatLLM Teams: Interactive Data Analysis Across Multiple Formats
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Interact with many data modalities (PDF/text, images, dashboards,…) using @AbacusAI ChatLLM Teams. This video highlights DataLLM, which allows you to chat with (ask questions to) your data! Sign up for FREE TRIAL here: https://t.co/ATIFqtJ0Di
— Kirk Borne (@KirkDBorne) 10 décembre 2024
———#LLMs #GenAI #AI #GenerativeAI pic.twitter.com/Xk06kJgPOAInteract with many data modalities (PDF/text, images, dashboards,…) using @AbacusAI ChatLLM Teams. This video highlights DataLLM, which allows you to chat with (ask questions to) your data! Sign up for FREE TRIAL here: http://
chatllm.abacus.ai/?token=kirk
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#LLMs #GenAI #AI #GenerativeAI -
DeepSeek-V2.5-1210 with Live Search Support
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BREAKING : DeepSeek got a model upgrade to DeepSeek-V2.5-1210 along with live search support A new Search toggle is now available on the prompt bar.
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LLMs Drive Vector Embeddings and Vector Databases Popularity
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The rise of #LLMs has made vector embeddings and #VectorDB immensely popular and useful, particularly in #AI, #GenerativeAI, and #LLMOps applications. @bindureddy from @abacusai explains in this “RAG – Vector Retrieval – Comprehensive Study”…
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Preference Optimization Algorithms for Large Language Models NeurIPS
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We will be presenting “Discovering Preference Optimization Algorithms with and for Large Language Models” at #NeurIPS2024 https://
sakana.ai/llm-squared/ https://
openreview.net/forum?id=erjQD
J0z9L
… If you are around, please swing by on Thurs Dec 12th, from 11am to 2pm to chat! https://
neurips.cc/virtual/2024/p
oster/94244
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DeepSeek-V2.5-1210 Model Weights Released on Hugging Face
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Model weights: https://
huggingface.co/deepseek-ai/De
epSeek-V2.5-1210
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DeepSeek-V2.5-1210 Upgrade Achieves 82.8% on MATH-500
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Let’s gooo! The whale is back w/ DeepSeek-V2.5-1210 an upgraded version of DeepSeek-V2.5, offering improvements in: > 74.8% to 82.8% on MATH-500
> 29.2% to 34.38% on LiveCodebench
> writing and Reasoning: notable improvements in internal tests
> optimised file upload and -
Densing Law of LLMs: Capability Density and Training Quality
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Densing Law of LLMs https://
arxiv.org/pdf/2412.04315
v2
… introducing the concept of “capability density” to evaluate the training quality of large language models (LLMs) and describe the trend of LLMs that considers both effectiveness and efficiency. -
Create Swarm of Agents with Haystack Framework
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Create a Swarm of Agents | Haystack https://
bit.ly/3ODkE80 #AI #MachineLearning #DeepLearning #LLMs #DataScience -
Comparing π_0 Robot Training Data to Qwen LLM Training Scale
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Thanks Kevin! Using your conversion rate, that works out to π_0 trained on 1 person-year of robot data vs. Qwen trained on 120,000 person-years of LLM data: