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Company: "modular"
not much happened today
dflash nemo-automodel claude openai broadcom qualcomm modular nvidia skypilot modal anthropic hugging-face hardware inference performance-optimization model-training agent-ux security capability-based-security open-source fine-tuning infrastructure model-optimization gdb kimmonismus scaling01 clattner_llvm karpathy gallabytes dabit3 kentonvarda random_walker jubbaonjeans victormustar
OpenAI announced Jalapeño, its first custom AI chip for LLM inference, built with Broadcom, aiming to control more of the AI stack and improve compute economics with a fast 9-month design cycle. Community analysis suggests Jalapeño features 216GB HBM3E, ~7.1–7.4 TB/s bandwidth, and ~10 PFLOPS FP4 performance, signaling hyperscaler-style inference silicon as a new standard. Meanwhile, Qualcomm is acquiring Modular, with Mojo open-sourcing on track, indicating rising competition in vertically integrated inference stacks beyond NVIDIA/CUDA. On infrastructure, NVIDIA's NeMo AutoModel boosts training throughput for MoE models by 3.4–3.7x, and startups like SkyPilot and Modal advance unified and open-source inference solutions. Custom training of DFLASH models yields 30–50% decode gains. In UX, Anthropic's Slack-native Claude agent shifts agent interaction from tools to coworkers, raising new security and cost concerns around identity, permissions, and lock-in, with debates on capability-based security and attribution. Hugging Face responded with its self-hosted Slack coding agent Moon Bot.
ALL of AI Engineering in One Place
claude-3-sonnet claude-3 openai google-deepmind anthropic mistral-ai cohere hugging-face adept midjourney character-ai microsoft amazon nvidia salesforce mastercard palo-alto-networks axa novartis discord twilio tinder khan-academy sourcegraph mongodb neo4j hasura modular cognition anysphere perplexity-ai groq mozilla nous-research galileo unsloth langchain llamaindex instructor weights-biases lambda-labs neptune datastax crusoe covalent qdrant baseten e2b octo-ai gradient-ai lancedb log10 deepgram outlines crew-ai factory-ai interpretability feature-steering safety multilinguality multimodality rag evals-ops open-models code-generation gpus agents ai-leadership
The upcoming AI Engineer World's Fair in San Francisco from June 25-27 will feature a significantly expanded format with booths, talks, and workshops from top model labs like OpenAI, DeepMind, Anthropic, Mistral, Cohere, HuggingFace, and Character.ai. It includes participation from Microsoft Azure, Amazon AWS, Google Vertex, and major companies such as Nvidia, Salesforce, Mastercard, Palo Alto Networks, and more. The event covers 9 tracks including RAG, multimodality, evals/ops, open models, code generation, GPUs, agents, AI in Fortune 500, and a new AI leadership track. Additionally, Anthropic shared interpretability research on Claude 3 Sonnet, revealing millions of interpretable features that can be steered to modify model behavior, including safety-relevant features related to bias and unsafe content, though more research is needed for practical applications. The event offers a discount code for AI News readers.