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AI Engineer World's Fair: Second Run, Twice The Fun
gemini-2.5-pro google-deepmind waymo tesla anthropic braintrust retrieval-augmentation graph-databases recommendation-systems software-engineering-agents agent-reliability reinforcement-learning voice image-generation video-generation infrastructure security evaluation ai-leadership enterprise-ai mcp tiny-teams product-management design-engineering robotics foundation-models coding web-development demishassabis
The 2025 AI Engineer World's Fair is expanding with 18 tracks covering topics like Retrieval + Search, GraphRAG, RecSys, SWE-Agents, Agent Reliability, Reasoning + RL, Voice AI, Generative Media, Infrastructure, Security, and Evals. New focuses include MCP, Tiny Teams, Product Management, Design Engineering, and Robotics and Autonomy featuring foundation models from Waymo, Tesla, and Google. The event highlights the growing importance of AI Architects and enterprise AI leadership. Additionally, Demis Hassabis announced the Gemini 2.5 Pro Preview 'I/O edition', which leads coding and web development benchmarks on LMArena.
not much happened to end the week
gemini deepseek-r1 o1 chatgpt gpt-4 claude-3.5-sonnet o1-preview o1-mini gpt4o qwq-32b google-deepmind deeplearningai amazon tesla x-ai alibaba ollama multimodality benchmarking quantization reinforcement-learning ai-safety translation reasoning interpretability model-comparison humor yoshua-bengio kevinweil ylecun
AI News for 11/29/2024-11/30/2024 covers key updates including the Gemini multimodal model advancing in musical structure understanding, a new quantized SWE-Bench for benchmarking at 1.3 bits per task, and the launch of the DeepSeek-R1 model focusing on transparent reasoning as an alternative to o1. The establishment of the 1st International Network of AI Safety Institutes highlights global collaboration on AI safety. Industry updates feature Amazon's Olympus AI model, Tesla's Optimus, and experiments with ChatGPT as a universal translator. Community reflections emphasize the impact of large language models on daily life and medical AI applications. Discussions include scaling sparse autoencoders to gpt-4 and the need for transparency in reasoning LLMs. The report also notes humor around ChatGPT's French nickname.
s{imple|table|calable} Consistency Models
llama-3-70b llama-3-405b llama-3-1 stable-diffusion-3.5 gpt-4 stability-ai tesla cerebras cohere langchain model-distillation diffusion-models continuous-time-consistency-models image-generation ai-hardware inference-speed multilingual-models yang-song
Model distillation significantly accelerates diffusion models, enabling near real-time image generation with only 1-4 sampling steps, as seen in BlinkShot and Flux Schnell. Research led by Yang Song introduced simplified continuous-time consistency models (sCMs), achieving under 10% FID difference in just 2 steps and scaling up to 1.5B parameters for higher quality. On AI hardware, Tesla is deploying a 50k H100 cluster potentially capable of completing GPT-4 training in under three weeks, while Cerebras Systems set a new inference speed record on Llama 3.1 70B with their wafer-scale AI chips. Stability AI released Stable Diffusion 3.5 and its Turbo variant, and Cohere launched new multilingual models supporting 23 languages with state-of-the-art performance. LangChain also announced ecosystem updates.
DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing
bitnet-b1.58 llama-3.1-nemotron-70b-instruct gpt-4o claude-3.5-sonnet uc-berkeley deepmind openai microsoft nvidia archetype-ai boston-dynamics toyota-research google adobe openai mistral tesla meta-ai-fair model-optimization on-device-ai fine-tuning large-corpus-processing gpu-acceleration frameworks model-benchmarking rohanpaul_ai adcock_brett david-patterson
UC Berkeley's EPIC lab introduces innovative LLM data operators with projects like LOTUS and DocETL, focusing on effective programming and computation over large data corpora. This approach contrasts GPU-rich big labs like Deepmind and OpenAI with GPU-poor compound AI systems. Microsoft open-sourced BitNet b1.58, a 1-bit ternary parameter LLM enabling 4-20x faster training and on-device inference at human reading speeds. Nvidia released Llama-3.1-Nemotron-70B-Instruct, a fine-tuned open-source model outperforming GPT-4o and Claude-3.5-sonnet. These developments highlight advances in model-optimization, on-device-ai, and fine-tuning.
Somebody give Andrej some H100s already
gpt-2 openai fineweb meta-ai-fair nvidia tesla cuda fine-tuning training-time gpu-acceleration convolutional-neural-networks real-time-processing ai-safety ai-regulation andrej-karpathy yann-lecun elon-musk francois-chollet svpino mervenoyann
OpenAI's GPT-2 sparked controversy five years ago for being "too dangerous to release." Now, with FineWeb and llm.c, a tiny GPT-2 model can be trained in 90 minutes for $20 using 8xA100 GPUs, with the full 1.6B model estimated to take 1 week and $2.5k. The project is notable for its heavy use of CUDA (75.8%) aiming to simplify the training stack. Meanwhile, a Twitter debate between Yann LeCun and Elon Musk highlighted the importance of convolutional neural networks (CNNs) in real-time image processing for autonomous driving, with LeCun emphasizing scientific research's role in technological progress. LeCun also criticized AI doomsday scenarios, arguing for cautious optimism about AI safety and regulation.
DeepSeek-V2 beats Mixtral 8x22B with >160 experts at HALF the cost
deepseek-v2 llama-3-120b llama-3-400b gpt-4 mistral phi claude gemini mai-1 med-gemini deepseek-ai mistral-ai microsoft openai scale-ai tesla nvidia google-deepmind mixture-of-experts multi-head-attention model-inference benchmarking overfitting robotics teleoperation open-source multimodality hallucination-detection fine-tuning medical-ai model-training erhartford maximelabonne bindureddy adcock_brett drjimfan clementdelangue omarsar0 rohanpaul_ai
DeepSeek V2 introduces a new state-of-the-art MoE model with 236B parameters and a novel Multi-Head Latent Attention mechanism, achieving faster inference and surpassing GPT-4 on AlignBench. Llama 3 120B shows strong creative writing skills, while Microsoft is reportedly developing a 500B parameter LLM called MAI-1. Research from Scale AI highlights overfitting issues in models like Mistral and Phi, whereas GPT-4, Claude, Gemini, and Llama maintain benchmark robustness. In robotics, Tesla Optimus advances with superior data collection and teleoperation, LeRobot marks a move toward open-source robotics AI, and Nvidia's DrEureka automates robot skill training. Multimodal LLM hallucinations are surveyed with new mitigation strategies, and Google's Med-Gemini achieves SOTA on medical benchmarks with fine-tuned multimodal models.