All tags
Topic: "model-speed"
Western Open Models get Funding: Cohere $500m @ 6.8B, AI2 gets $152m NSF+NVIDIA grants
gpt-5 o3 command-a gemma-3-270m imagen-4 dinov3 openai perplexity-ai ai2 nvidia cohere meta-ai-fair google hugging-face ollama unsloth model-speed funding ai-infrastructure on-device-ai quantization embedding-models image-generation self-supervised-learning vision dense-prediction benchmarking instruction-following model-optimization model-release challenge joelle_pineau fchollet awnihannun _philschmid osanseviero
OpenAI's GPT-5 achieved a speedrun of Pokemon Red 3x faster than o3. Perplexity raised $200M at a $20B valuation. AI2 secured $75M NSF grants and $77M from NVIDIA for AI infrastructure projects like Olmo and Molmo. Cohere raised $500M and hired Joelle Pineau from meta-ai-fair, boosting models like Command A. Google released the Gemma 3 270M on-device tiny LLM with INT4 QAT checkpoints and large embedding tables, and made Imagen 4 generally available with a fast version at $0.02/image. Meta-ai-fair introduced DINOv3, a family of self-supervised vision foundation models with high-resolution dense features and strong performance on benchmarks like COCO detection and ADE20K segmentation, under a permissive license. A $150,000 MiniMax AI Agent Challenge is ongoing with 200+ prizes, encouraging AI project builds by August 25.
Claude 3 just destroyed GPT 4 (see for yourself)
claude-3 claude-3-opus claude-3-sonnet claude-3-haiku gpt-4 anthropic amazon google claude-ai multimodality vision long-context model-alignment model-evaluation synthetic-data structured-output instruction-following model-speed cost-efficiency benchmarking safety mmitchell connor-leahy
Claude 3 from Anthropic launches in three sizes: Haiku (small, unreleased), Sonnet (medium, default on claude.ai, AWS, and GCP), and Opus (large, on Claude Pro). Opus outperforms GPT-4 on key benchmarks like GPQA, impressing benchmark authors. All models support multimodality with advanced vision capabilities, including converting a 2-hour video into a blog post. Claude 3 offers improved alignment, fewer refusals, and extended context length up to 1 million tokens with near-perfect recall. Haiku is noted for speed and cost-efficiency, processing dense research papers in under three seconds. The models excel at following complex instructions and producing structured outputs like JSON. Safety improvements reduce refusal rates, though some criticism remains from experts. Claude 3 is trained on synthetic data and shows strong domain-specific evaluation results in finance, medicine, and philosophy.