Meta
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meta-models/Muse-Glimmer-30B
New image-text-to-text model. Tags: muse_glimmer, image-text-to-text, conversational, arxiv:2504.13181, arxiv:2602.06036, license:apache-2.0, eval-results
2026 BAIR Graduate Showcase
Congratulations to the Berkeley Artificial Intelligence Research (BAIR) Lab class of 2026! This year, BAIR celebrates another remarkable group of Ph.D. graduates whose curiosity, creativity, and perseverance have pushed the frontiers of artificial intelligence and machine learning. Their work spans the breadth of modern AI — robotics and embodied intelligence, large language models and reasoning, computer vision, generative modeling, AI…
Plan, divide, and conquer: How weak models excel at long context tasks
As context windows grow, LLM performance degrades in unexpected ways. We show how a "Divide & Conquer" framework — breaking long documents into parallel chunks with a planner, workers, and manager — lets smaller models like Llama-3-70B and Qwen-72B outperform GPT-4o single-shot.
What do LLMs think when you don't tell them what to think about?
What do language models generate when you don't tell them what to generate? New research reveals that LLM families have distinct 'knowledge priors'—GPT models default to code and math, Llama favors narratives, DeepSeek generates religious content, and Qwen outputs exam questions.
Claude Code costs up to $200 a month. Goose does the same thing for free.
The artificial intelligence coding revolution comes with a catch: it's expensive. Claude Code , Anthropic's terminal-based AI agent that can write, debug, and deploy code…
Together AI and Meta partner to bring PyTorch Reinforcement Learning to the AI Native Cloud
Build, train, and deploy advanced AI agents with integrated reinforcement learning on the Together platform.
Minions: where local and cloud LLMs meet
Avanika Narayan, Dan Biderman, and Sabri Eyuboglu from Christopher Ré's Stanford Hazy Research lab, along with Avner May, Scott Linderman, James Zou, have developed a way to shift a substantial portion of LLM workloads to consumer devices by having small on-device models (such as Llama 3.2 with Ollama) collaborate with larger models in the cloud (such as GPT-4o).
Tool support
Ollama now supports tool calling with popular models such as Llama 3.1. This enables a model to answer a given prompt using tool(s) it knows about, making it possible for models to perform more complex tasks or interact with the outside world.
Llama 3 is not very censored
Compared to Llama 2, Llama 3 feels much less censored. Meta has substantially lowered false refusal rates. Llama 3 will refuse less than 1/3 of the prompts previously refused by Llama 2.