All tags
Topic: "image-segmentation"
not much happened today
rstar-math o1-preview qwen2.5-plus qwen2.5-coder-32b-instruct phi-4 claude-3.5-sonnet openai anthropic alibaba microsoft cohere langchain weights-biases deepseek rakuten rbc amd johns-hopkins math process-reward-model mcts vision reasoning synthetic-data pretraining rag automation private-deployment multi-step-workflow open-source-dataset text-embeddings image-segmentation chain-of-thought multimodal-reasoning finetuning recursive-self-improvement collaborative-platforms ai-development partnerships cuda triton ai-efficiency ai-assisted-coding reach_vb rasbt akshaykagrawal arankomatsuzaki teortaxestex aidangomez andrewyng
rStar-Math surpasses OpenAI's o1-preview in math reasoning with 90.0% accuracy using a 7B LLM and MCTS with a Process Reward Model. Alibaba launches Qwen Chat featuring Qwen2.5-Plus and Qwen2.5-Coder-32B-Instruct models enhancing vision-language and reasoning. Microsoft releases Phi-4, trained on 40% synthetic data with improved pretraining. Cohere introduces North, a secure AI workspace integrating LLMs, RAG, and automation for private deployments. LangChain showcases a company research agent with multi-step workflows and open-source datasets. Transformers.js demos released for text embeddings and image segmentation in JavaScript. Research highlights include Meta Meta-CoT for enhanced chain-of-thought reasoning, DeepSeek V3 with recursive self-improvement, and collaborative AI development platforms. Industry partnerships include Rakuten with LangChain, North with RBC supporting 90,000 employees, and Agent Laboratory collaborating with AMD and Johns Hopkins. Technical discussions emphasize CUDA and Triton for AI efficiency and evolving AI-assisted coding stacks by Andrew Ng.
Apple Intelligence Beta + Segment Anything Model 2
llama-3-405b llama-3 segment-anything-model meta-ai-fair apple image-segmentation memory-attention video-processing pretraining cloud-tpus post-training synthetic-data instruction-following reasoning writing benchmarking bindureddy maximelabonne reach_vb
Meta advanced its open source AI with a sequel to the Segment Anything Model, enhancing image segmentation with memory attention for video applications using minimal data and compute. Apple Intelligence delayed its official release to iOS 18.1 in October but launched developer previews on MacOS Sequoia, iOS 18, and iPadOS 18, accompanied by a detailed 47-page paper revealing extensive pretraining on 6.3T tokens and use of Cloud TPUs rather than Apple Silicon. The paper highlights improvements in instruction following, reasoning, and writing through post-training and synthetic data. Benchmarks show Apple’s model scores lower than Llama 3, but with trusted human evaluations. Additionally, Meta released Llama 3.1 with a 405B parameter model, marking a significant open-source frontier model release.