All tags
Model: "deepseek-r1"
not much happened today
gemini-2.5-flash gemini-2.0-flash mistral-medium-3 llama-4-maverick claude-3.7-sonnet qwen3 pangu-ultra-moe deepseek-r1 o4-mini x-reasoner google-deepmind mistral-ai alibaba huawei openai microsoft deepseek model-performance reasoning cost-analysis reinforcement-learning chain-of-thought multilinguality code-search model-training vision model-integration giffmana artificialanlys teortaxestex akhaliq john__allard
Gemini 2.5 Flash shows a 12 point increase in the Artificial Analysis Intelligence Index but costs 150x more than Gemini 2.0 Flash due to 9x more expensive output tokens and 17x higher token usage during reasoning. Mistral Medium 3 competes with Llama 4 Maverick, Gemini 2.0 Flash, and Claude 3.7 Sonnet with better coding and math reasoning at a significantly lower price. Alibaba's Qwen3 family supports reasoning and multilingual tasks across 119 languages and includes a Web Dev tool for app building. Huawei's Pangu Ultra MoE matches DeepSeek R1 performance on Ascend NPUs, with new compute and upcoming V4 training. OpenAI's o4-mini now supports Reinforcement Fine-Tuning (RFT) using chain-of-thought reasoning. Microsoft's X-REASONER enables generalizable reasoning across modalities post-trained on general-domain text. Deep research integration with GitHub repos in ChatGPT enhances codebase search and reporting. The AI Engineer World's Fair offers an Early Bird discount for upcoming tickets.
Qwen 3: 0.6B to 235B MoE full+base models that beat R1 and o1
qwen-3 qwen3-235b-a22b qwen3-30b-a3b deepseek-r1 o1 o3-mini grok-3 gemini-2.5-pro alibaba google-deepmind deepseek mistral-ai mixture-of-experts reinforcement-learning benchmarking model-release model-architecture long-context multi-agent-systems inference dataset-release awnihannun prince_canuma actuallyisaak oriolvinyalsml iscienceluvr reach_vb teortaxestex omarsar0
Qwen 3 has been released by Alibaba featuring a range of models including two MoE variants, Qwen3-235B-A22B and Qwen3-30B-A3B, which demonstrate competitive performance against top models like DeepSeek-R1, o1, o3-mini, Grok-3, and Gemini-2.5-Pro. The models introduce an "enable_thinking=True" mode with advanced soft switching for inference scaling. The release is notable for its Apache 2.0 license and broad inference platform support including MCP. The dataset improvements and multi-stage RL post-training contribute to performance gains. Meanwhile, Gemini 2.5 Pro from Google DeepMind shows strong coding and long-context reasoning capabilities, and DeepSeek R2 is anticipated soon. Twitter discussions highlight Qwen3's finegrained MoE architecture, large context window, and multi-agent system applications.
QwQ-32B claims to match DeepSeek R1-671B
qwen-2.5-plus qwq-32b deepseek-r1 gpt-4.5 gpt-3 davinci alibaba openai deepseek-ai reinforcement-learning math code-execution instruction-following alignment reasoning model-release model-benchmarking scaling performance inference-costs aidan_mclau sama scaling01 juberti polynoamial reach_vb
Alibaba Qwen released their QwQ-32B model, a 32 billion parameter reasoning model using a novel two-stage reinforcement learning approach: first scaling RL for math and coding tasks with accuracy verifiers and code execution servers, then applying RL for general capabilities like instruction following and alignment. Meanwhile, OpenAI rolled out GPT-4.5 to Plus users, with mixed feedback on coding performance and noted inference cost improvements. The QwQ model aims to compete with larger MoE models like DeepSeek-R1. "GPT-4.5 is unusable for coding" was a notable user critique, while others praised its reasoning improvements due to scaling pretraining.
Google's Agent2Agent Protocol (A2A)
kimi-vl-a3b gpt-4o llama-4-scout llama-4-maverick llama-4-behemoth deepcoder-14b o3-mini o1 llama-3.1-nemotron-ultra-253b deepseek-r1 google google-deepmind moonshot-ai meta-ai-fair uc-berkeley openai nvidia hugging-face togethercompute deepseek agent-interoperability multimodality vision math reinforcement-learning coding model-training open-source model-benchmarking context-windows streaming push-notifications enterprise-authentication model-release reach_vb _akhaliq epochairesearch artificialanlys winglian danielhanchen yuchenj_uw jeremyphoward
Google Cloud Next announcements featured the launch of Google and DeepMind's full MCP support and a new Agent to Agent protocol designed for agent interoperability with multiple partners. The protocol includes components like the Agent Card, Task communication channels, Enterprise Auth and Observability, and Streaming and Push Notification support. On the model front, Moonshot AI released Kimi-VL-A3B, a multimodal model with 128K context and strong vision and math benchmark performance, outperforming gpt-4o. Meta AI introduced smaller versions of llama-4 family models: llama-4-scout and llama-4-maverick, with a larger Behemoth model still in training. DeepCoder 14B from UC Berkeley is an open-source coding model rivaling openai's o3-mini and o1 models, trained with reinforcement learning on 24K coding problems. Nvidia released llama-3.1-nemotron-ultra-253b on Hugging Face, noted for beating llama-4-behemoth and maverick and competing with deepseek-r1.
OpenAI adopts MCP
gemini-2.5-pro gemini-1.5-pro gemini-2.0-flash qwen-2.5-omni-7b deepseek-v3-0324 deepseek-r1 openai google-deepmind alibaba togethercompute model-benchmarking multimodality reasoning scaling-laws model-quantization synthetic-data model-performance context-windows speech-recognition translation audio-processing video-processing swyx
OpenAI announced support for MCP, a significant technical update. Google's Gemini 2.5 Pro leads benchmarks with top scores in MMLU-Pro (86%), GPQA Diamond (83%), and AIME 2024 (88%), featuring a 1 million token context window and multimodal inputs. Alibaba's Qwen 2.5 Omni 7B was released as a fully multimodal, interactive, open-source model with a novel "thinker-talker" architecture supporting voice and video chat. DeepSeek V3-0324 outperforms its predecessor on multiple benchmarks. Research on reasoning features in large language models using sparse autoencoders was highlighted, alongside a study on scaling laws of synthetic data showing performance plateaus near 300B tokens. Discussions also covered the fastest output speeds of Gemini models and concerns about over-reliance on benchmarks for intelligence measurement. Swyx will curate the Data Council AI Engineering Track in April.
not much happened today
gemini-2.0-flash-thinking command-a qwq-32b gemma-3-27b gemma-3 shieldgemma-2 llama-3-70b deepseek-r1 o1-mini deepseek-v3 google-deepmind cohere meta-ai-fair alibaba hugging-face model-updates model-performance benchmarking reinforcement-learning transformers normalization-layers image-generation vision memory-efficiency context-windows fine-tuning yann-lecun
Google DeepMind announced updates to Gemini 2.0, including an upgraded Flash Thinking model with stronger reasoning and native image generation capabilities. Cohere launched Command A, a 111B parameter dense model with a 256K context window and competitive pricing, available on Hugging Face. Meta AI proposed Dynamic Tanh (DyT) as a replacement for normalization layers in Transformers, supported by Yann LeCun. Alibaba released QwQ-32B, a 32.5B parameter model excelling in math and coding, fine-tuned with reinforcement learning and freely available under Apache 2.0 license. Google DeepMind also released Gemma 3 models ranging from 1B to 27B parameters with a 128K token context window and over 140 language support, plus ShieldGemma 2, an image safety checker. Benchmarking shows Gemma 3 27B has strong vision and memory efficiency but is outperformed by larger models like Llama 3.3 70B and DeepSeek V3 671B. The Hugging Face LLM leaderboard history was shared by @_lewtun.
not much happened today
deepseek-r1 gemma-3 gemma-3-27b openai nvidia deepseek hugging-face fp8 model-efficiency hardware-requirements quantization benchmarking model-deployment open-source sam-altman
DeepSeek R1 demonstrates significant efficiency using FP8 precision, outperforming Gemma 3 27B in benchmarks with a Chatbot Arena Elo Score of 1363 vs. 1338, requiring substantial hardware like 32 H100 GPUs and 2,560GB VRAM. OpenAI labels DeepSeek as "state-controlled" and calls for bans on "PRC-produced" models, sparking community backlash accusing OpenAI and Sam Altman of anti-competitive behavior. Discussions emphasize DeepSeek's openness and affordability compared to OpenAI, with users highlighting its local and Hugging Face deployment options. Meanwhile, Gemma 3 receives mixed community feedback on creativity and worldbuilding.
not much happened today
gpt-4.5 claude-3.7-sonnet deepseek-r1 smolagents-codeagent gpt-4o llama-3-8b tinyr1-32b-preview r1-searcher forgetting-transformer nanomoe openai deepseek hugging-face mixture-of-experts reinforcement-learning kv-cache-compression agentic-ai model-distillation attention-mechanisms model-compression minimax model-pretraining andrej-karpathy cwolferesearch aymericroucher teortaxestex jonathanross321 akhaliq
The AI news recap highlights several key developments: nanoMoE, a PyTorch implementation of a mid-sized Mixture-of-Experts (MoE) model inspired by Andrej Karpathy's nanoGPT, enables pretraining on commodity hardware within a week. An agentic leaderboard ranks LLMs powering smolagents CodeAgent, with GPT-4.5 leading, followed by Claude-3.7-Sonnet. Discussions around DeepSeek-R1 emphasize AI model commoditization, with DeepSeek dubbed the "OpenAI of China." Q-Filters offer a training-free method for KV cache compression in autoregressive models, achieving 32x compression with minimal perplexity loss. The PokéChamp minimax language agent, powered by GPT-4o and Llama-3-8b, demonstrates strong performance in Pokémon battles. Other notable models include TinyR1-32B-Preview with Branch-Merge Distillation, R1-Searcher incentivizing search capability via reinforcement learning, and the Forgetting Transformer using a Forget Gate in softmax attention. These advancements reflect ongoing innovation in model architectures, compression, reinforcement learning, and agentic AI.
Anthropic's $61.5B Series E
gpt-4.5 claude-3.7-sonnet deepseek-r1 anthropic openai deepseek lmsys perplexity-ai deutsche-telekom model-performance benchmarking style-control coding multi-turn funding partnerships workflow lmarena_ai teortaxestex casper_hansen_ omarsar0 aidan_mclau willdepue vikhyatk teknim1 reach_vb _aidan_clark_ cto_junior aravsrinivas
Anthropic raised a $3.5 billion Series E funding round at a $61.5 billion valuation, signaling strong financial backing for the Claude AI model. GPT-4.5 achieved #1 rank across all categories on the LMArena leaderboard, excelling in multi-turn conversations, coding, math, creative writing, and style control. DeepSeek R1 tied with GPT-4.5 for top performance on hard prompts with style control. Discussions highlighted comparisons between GPT-4.5 and Claude 3.7 Sonnet in coding and workflow applications. The importance of the LMSYS benchmark was emphasized, though some questioned the relevance of benchmarks versus user acquisition. Additionally, Perplexity AI partnered with Deutsche Telekom to integrate the Perplexity Assistant into a new AI phone.
lots of small launches
gpt-4o claude-3.7-sonnet claude-3.7 claude-3.5-sonnet deepseek-r1 deepseek-v3 grok-3 openai anthropic amazon cloudflare perplexity-ai deepseek-ai togethercompute elevenlabs elicitorg inceptionailabs mistral-ai voice model-releases cuda gpu-optimization inference open-source api model-performance token-efficiency context-windows cuda jit-compilation lmarena_ai alexalbert__ aravsrinivas reach_vb
GPT-4o Advanced Voice Preview is now available for free ChatGPT users with enhanced daily limits for Plus and Pro users. Claude 3.7 Sonnet has achieved the top rank in WebDev Arena with improved token efficiency. DeepSeek-R1 with 671B parameters benefits from the Together Inference platform optimizing NVIDIA Blackwell GPU usage, alongside the open-source DeepGEMM CUDA library delivering up to 2.7x speedups on Hopper GPUs. Perplexity launched a new Voice Mode and a Deep Research API. The upcoming Grok 3 API will support a 1M token context window. Several companies including Elicit, Amazon, Anthropic, Cloudflare, FLORA, Elevenlabs, and Inception Labs announced new funding rounds, product launches, and model releases.
not much happened today
claude-3.7-sonnet claude-3.7 deepseek-r1 o3-mini deepseek-v3 gemini-2.0-pro gpt-4o qwen2.5-coder-32b-instruct anthropic perplexity-ai amazon google-cloud deepseek_ai coding reasoning model-benchmarking agentic-workflows context-window model-performance open-source moe model-training communication-libraries fp8 nvlink rdma cli-tools skirano omarsar0 reach_vb artificialanlys terryyuezhuo _akhaliq _philschmid catherineols goodside danielhanchen
Claude 3.7 Sonnet demonstrates exceptional coding and reasoning capabilities, outperforming models like DeepSeek R1, O3-mini, and GPT-4o on benchmarks such as SciCode and LiveCodeBench. It is available on platforms including Perplexity Pro, Anthropic, Amazon Bedrock, and Google Cloud, with pricing at $3/$15 per million tokens. Key features include a 64k token thinking mode, 200k context window, and the CLI-based coding assistant Claude Code. Meanwhile, DeepSeek released DeepEP, an open-source communication library optimized for MoE model training and inference with support for NVLink, RDMA, and FP8. These updates highlight advancements in coding AI and efficient model training infrastructure.
AI Engineer Summit Day 1
grok-3 o3-mini deepseek-r1 qwen-2.5-vl openai anthropic xai togethercompute alibaba sakana-ai benchmarking model-performance cuda model-training open-source debugging inference-speed batch-size reinforcement-learning aidan_mclau giffmana nrehiew_ teortaxestex epochairesearch andrew_n_carr borismpower yuhu_ai_
The AIE Summit in NYC highlighted key talks including Grace Isford's Trends Keynote, Neo4j/Pfizer's presentation, and OpenAI's first definition of Agents. Speakers announced $930 million in funding. On AI Twitter, discussions focused on Grok-3 and o3-mini models, with debates on performance and benchmarking, including Grok-3's record compute scale of 4e26 to 5e26 FLOP. The o3-mini model uncovered a critical CUDA kernel bug in Sakana AI's code. DeepSeek-R1 was promoted as an open-source alternative with notable training batch sizes. Additionally, Alibaba announced the Qwen 2.5-VL model release.
not much happened today
grok-3 deepseek-r1 siglip-2 o3-mini-high r1-1776 llamba-1b llamba-3b llamba-8b llama-3 alphamaze audiobox-aesthetics xai nvidia google-deepmind anthropic openai bytedance ollama meta-ai-fair benchmarking model-releases performance reasoning multimodality semantic-understanding ocr multilinguality model-distillation recurrent-neural-networks visual-reasoning audio-processing scaling01 iscienceluvr philschmid arankomatsuzaki reach_vb mervenoyann wightmanr lmarena_ai ollama akhaliq
Grok-3, a new family of LLMs from xAI using 200,000 Nvidia H100 GPUs for advanced reasoning, outperforms models from Google, Anthropic, and OpenAI on math, science, and coding benchmarks. DeepSeek-R1 from ByteDance Research achieves top accuracy on the challenging SuperGPQA dataset. SigLIP 2 from GoogleDeepMind improves semantic understanding and OCR with flexible resolutions and multilingual capabilities, available on HuggingFace. OpenAI's o3-mini-high ranks #1 in coding and math prompts. Perplexity's R1 1776, a post-trained version of DeepSeek R1, is available on Ollama. The Llamba family distills Llama-3.x into efficient recurrent models with higher throughput. AlphaMaze combines DeepSeek R1 with GRPO for visual reasoning on ARC-AGI puzzles. Audiobox Aesthetics from Meta AI offers unified quality assessment for audio. The community notes that Grok 3's compute increase yields only modest performance gains.
X.ai Grok 3 and Mira Murati's Thinking Machines
grok-3 grok-3-mini gemini-2-pro gpt-4o o3-mini-high o1 deepseek-r1 anthropic openai thinking-machines benchmarking reasoning reinforcement-learning coding multimodality safety alignment research-publishing model-performance creative-ai mira-murati lmarena_ai karpathy omarsar0 ibab arankomatsuzaki iscienceluvr scaling01
Grok 3 has launched with mixed opinions but strong benchmark performance, notably outperforming models like Gemini 2 Pro and GPT-4o. The Grok-3 mini variant shows competitive and sometimes superior capabilities, especially in reasoning and coding, with reinforcement learning playing a key role. Mira Murati has publicly shared her post-OpenAI plan, founding the frontier lab Thinking Machines, focusing on collaborative, personalizable AI, multimodality, and empirical safety and alignment research, reminiscent of Anthropic's approach.
not much happened today
chatgpt-4o deepseek-r1 o3 o3-mini gemini-2-flash qwen-2.5 qwen-0.5b hugging-face openai perplexity-ai deepseek-ai gemini qwen metr_evals reasoning benchmarking model-performance prompt-engineering model-optimization model-deployment small-language-models mobile-ai ai-agents speed-optimization _akhaliq aravsrinivas lmarena_ai omarsar0 risingsayak
Smolagents library by Huggingface continues trending. ChatGPT-4o latest version
chatgpt-40-latest-20250129 released. DeepSeek R1 671B sets speed record at 198 t/s, fastest reasoning model, recommended with specific prompt settings. Perplexity Deep Research outperforms models like Gemini Thinking, o3-mini, and DeepSeek-R1 on Humanity's Last Exam benchmark with 21.1% score and 93.9% accuracy on SimpleQA. ChatGPT-4o ranks #1 on Arena leaderboard in multiple categories except math. OpenAI's o3 model powers Deep Research tool for ChatGPT Pro users. Gemini 2 Flash and Qwen 2.5 models support LLMGrading verifier. Qwen 2.5 models added to PocketPal app. MLX shows small LLMs like Qwen 0.5B generate tokens at high speed on M4 Max and iPhone 16 Pro. Gemini Flash 2.0 leads new AI agent leaderboard. DeepSeek R1 is most liked on Hugging Face with over 10 million downloads. Reasoning Models are Near-Superhuman Coders (OpenAI IOI, Nvidia Kernels)
o3 o1 o3-mini deepseek-r1 qwen-2.5 openthinker openai nvidia ollama elevenlabs sakana-ai apple reinforcement-learning gpu-kernel-optimization fine-tuning knowledge-distillation scaling-laws chain-of-thought-reasoning model-accessibility alex-wei karpathy abacaj awnihannun
o3 model achieved a gold medal at the 2024 IOI and ranks in the 99.8 percentile on Codeforces, outperforming most humans with reinforcement learning (RL) methods proving superior to inductive bias approaches. Nvidia's DeepSeek-R1 autonomously generates GPU kernels that surpass some expert-engineered kernels, showcasing simple yet effective AI-driven optimization. OpenAI updated o1 and o3-mini models to support file and image uploads in ChatGPT and released DeepResearch, a powerful research assistant based on the o3 model with RL for deep chain-of-thought reasoning. Ollama introduced OpenThinker models fine-tuned from Qwen2.5, outperforming some DeepSeek-R1 distillation models. ElevenLabs grew into a $3.3 billion company specializing in AI voice synthesis without open-sourcing their technology. Research highlights include Sakana AI Labs' TAID knowledge distillation method receiving a Spotlight at ICLR 2025, and Apple's work on scaling laws for mixture-of-experts (MoEs). The importance of open-source AI for scientific discovery was also emphasized.
not much happened today
gemini-2.0-flash-thinking-experimental-1-21 zonos openr1-math-220k huginn-3.5b deepseek-r1 o1 claude google zyphraai hugging-face anthropic deepseek openai vision multilingual-models text-to-speech voice-cloning math reasoning latent-reasoning chain-of-thought dataset-release fine-tuning model-training model-performance context-windows benchmarking jeremyphoward andrej-karpathy tom-goldstein reach_vb iscienceluvr
Google released Gemini 2.0 Flash Thinking Experimental 1-21, a vision-language reasoning model with a 1 million-token context window and improved accuracy on science, math, and multimedia benchmarks, surpassing DeepSeek-R1 but trailing OpenAI's o1. ZyphraAI launched Zonos, a multilingual Text-to-Speech model with instant voice cloning and controls for speaking rate, pitch, and emotions, running at ~2x real-time speed on RTX 4090. Hugging Face released OpenR1-Math-220k, a large-scale math reasoning dataset with 220K problems and 800K reasoning traces generated on 512 H100 GPUs. Tom Goldstein introduced Huginn-3.5B, an open-source latent reasoning model trained on 800B tokens that outperforms larger models on reasoning tasks like GSM8K. Discussions by Jeremy Howard and iScienceLuvr highlight advances in implicit latent reasoning and debate the future of human-readable reasoning traces. Anthropic launched the Anthropic Economic Index to analyze AI's economic impact using millions of Claude conversations.
not much happened today
deepseek-r1 alphageometry-2 claude deepseek openai google-deepmind anthropic langchain adyen open-source reasoning agentic-ai javascript model-release memes ai-development benchmarking akhaliq lmthang aymericroucher vikhyatk swyx
DeepSeek-R1 surpasses OpenAI in GitHub stars, marking a milestone in open-source AI with rapid growth in community interest. AlphaGeometry2 achieves gold-medalist level performance with an 84% solving rate on IMO geometry problems, showcasing significant advancements in AI reasoning. LangChain releases a tutorial for building AI agents in JavaScript, enhancing developer capabilities in agent deployment. Reflections on Anthropic's Claude model reveal early access and influence on AI development timelines. Lighthearted AI humor includes calls to ban second-order optimizers and challenges in web development longevity. The AI Engineer Summit 2025 workshops were announced, continuing community engagement and education.
Gemini 2.0 Flash GA, with new Flash Lite, 2.0 Pro, and Flash Thinking
gemini-2.0-flash gemini-2.0-flash-lite gemini-2.0-pro-experimental gemini-1.5-pro deepseek-r1 gpt-2 llama-3-1 google-deepmind hugging-face anthropic multimodality context-windows cost-efficiency pretraining fine-tuning reinforcement-learning transformer tokenization embeddings mixture-of-experts andrej-karpathy jayalammar maartengr andrewyng nearcyan
Google DeepMind officially launched Gemini 2.0 models including Flash, Flash-Lite, and Pro Experimental, with Gemini 2.0 Flash outperforming Gemini 1.5 Pro while being 12x cheaper and supporting multimodal input and a 1 million token context window. Andrej Karpathy released a 3h31m video deep dive into large language models, covering pretraining, fine-tuning, and reinforcement learning with examples like GPT-2 and Llama 3.1. A free course on Transformer architecture was introduced by Jay Alammar, Maarten Gr, and Andrew Ng, focusing on tokenizers, embeddings, and mixture-of-expert models. DeepSeek-R1 reached 1.2 million downloads on Hugging Face with a detailed 36-page technical report. Anthropic increased rewards to $10K and $20K for their jailbreak challenge, while BlueRaven extension was updated to hide Twitter metrics for unbiased engagement.
o3-mini launches, OpenAI on "wrong side of history"
o3-mini o1 gpt-4o mistral-small-3-24b deepseek-r1 openai mistral-ai deepseek togethercompute fireworksai_hq ai-gradio replicate reasoning safety cost-efficiency model-performance benchmarking api open-weight-models model-releases sam-altman
OpenAI released o3-mini, a new reasoning model available for free and paid users with a "high" reasoning effort option that outperforms the earlier o1 model on STEM tasks and safety benchmarks, costing 93% less per token. Sam Altman acknowledged a shift in open source strategy and credited DeepSeek R1 for influencing assumptions. MistralAI launched Mistral Small 3 (24B), an open-weight model with competitive performance and low API costs. DeepSeek R1 is supported by Text-generation-inference v3.1.0 and available via ai-gradio and replicate. The news highlights advancements in reasoning, cost-efficiency, and safety in AI models.
not much happened today
deepseek-r1 deepseek-v3 coder-v2 prover deepseek hugging-face dell openai instruction-tuning performance-benchmarks model-deployment training-costs hardware-scalability ai-safety risk-mitigation ethical-ai open-source gpu-utilization yann-lecun yoshua-bengio francois-chollet giffman
DeepSeek-R1 and DeepSeek-V3 models have made significant advancements, trained on an instruction-tuning dataset of 1.5M samples with 600,000 reasoning and 200,000 non-reasoning SFT data. The models demonstrate strong performance benchmarks and are deployed on-premise via collaborations with Dell and Hugging Face. Training costs are estimated around $5.5M to $6M, with efficient hardware utilization on 8xH100 servers. The International AI Safety Report highlights risks such as malicious use, malfunctions, and systemic risks including AI-driven cyberattacks. Industry leaders like Yann LeCun and Yoshua Bengio provide insights on market reactions, AI safety, and ethical considerations, with emphasis on AI's role in creativity and economic incentives.
not much happened today
deepseek-r1 qwen-2.5 qwen-2.5-max deepseek-v3 deepseek-janus-pro gpt-4 nvidia anthropic openai deepseek huawei vercel bespoke-labs model-merging multimodality reinforcement-learning chain-of-thought gpu-optimization compute-infrastructure compression crypto-api image-generation saranormous zizhpan victormustar omarsar0 markchen90 sakanaailabs reach_vb madiator dain_mclau francoisfleuret garygodchaux arankomatsuzaki id_aa_carmack lavanyasant virattt
Huawei chips are highlighted in a diverse AI news roundup covering NVIDIA's stock rebound, new open music foundation models like Local Suno, and competitive AI models such as Qwen 2.5 Max and Deepseek V3. The release of DeepSeek Janus Pro, a multimodal LLM with image generation capabilities, and advancements in reinforcement learning and chain-of-thought reasoning are noted. Discussions include GPU rebranding with NVIDIA's H6400 GPUs, data center innovations, and enterprise AI applications like crypto APIs in hedge funds. "Deepseek R1's capabilities" and "Qwen 2.5 models added to applications" are key highlights.
DeepSeek #1 on US App Store, Nvidia stock tanks -17%
deepseek-r1 deepseek-v3 qwen2.5-vl o1 deepseek openai nvidia langchain moe-architecture chain-of-thought fp8-precision multimodality vision agentic-ai inference-scaling gpu-optimization model-efficiency ai-chatbots memory-integration tool-use stock-market-reactions sama mervenoyann omarasar0 teortaxestex nptacek carpeetti finbarrtimbers cwolferesearch arthurrapier danhendrycks scaling01 janusflow
DeepSeek has made a significant cultural impact by hitting mainstream news unexpectedly in 2025. The DeepSeek-R1 model features a massive 671B parameter MoE architecture and demonstrates chain-of-thought (CoT) capabilities comparable to OpenAI's o1 at a lower cost. The DeepSeek V3 model trains a 236B parameter model 42% faster than its predecessor using fp8 precision. The Qwen2.5 multimodal models support images and videos with sizes ranging from 3B to 72B parameters, featuring strong vision and agentic capabilities. LangChain and LangGraph integration enable AI chatbots with memory and tool use, including applications like the DeFi Agent. Discussions highlight NVIDIA's role in hardware acceleration, with concerns about stock drops due to DeepSeek's efficiency and market fears. The compute demand is expected to rise despite efficiency gains, driven by inference scaling and MoE design improvements.
TinyZero: Reproduce DeepSeek R1-Zero for $30
deepseek-r1 qwen o1 claude-3-sonnet claude-3 prime ppo grpo llama-stack deepseek berkeley hugging-face meta-ai-fair openai deeplearningai reinforcement-learning fine-tuning chain-of-thought multi-modal-benchmark memory-management model-training open-source agentic-workflow-automation model-performance jiayi-pan saranormous reach_vb lmarena_ai nearcyan omarsar0 philschmid hardmaru awnihannun winglian
DeepSeek Mania continues to reshape the frontier model landscape with Jiayi Pan from Berkeley reproducing the OTHER result from the DeepSeek R1 paper, R1-Zero, in a cost-effective Qwen model fine-tune for two math tasks. A key finding is a lower bound to the distillation effect at 1.5B parameters, with RLCoT reasoning emerging as an intrinsic property. Various RL techniques like PPO, DeepSeek's GRPO, or PRIME show similar outcomes, and starting from an Instruct model speeds convergence. The Humanity’s Last Exam (HLE) Benchmark introduces a challenging multi-modal test with 3,000 expert-level questions across 100+ subjects, where models perform below 10%, with DeepSeek-R1 achieving 9.4%. DeepSeek-R1 excels in chain-of-thought reasoning, outperforming models like o1 while being 20x cheaper and MIT licensed. The WebDev Arena Leaderboard ranks DeepSeek-R1 #2 in technical domains and #1 under Style Control, closing in on Claude 3.5 Sonnet. OpenAI's Operator is deployed to 100% of Pro users in the US, enabling tasks like ordering meals and booking reservations, and functions as a research assistant for AI paper searches and summaries. Hugging Face announces a leadership change after significant growth, while Meta AI releases the first stable version of Llama Stack with streamlined upgrades and automated verification. DeepSeek-R1's open-source success is celebrated, and technical challenges like memory management on macOS 15+ are addressed with residency sets in MLX for stability.
OpenAI launches Operator, its first Agent
operator deepseek-r1 videollama-3 llama-4 o1 claude openai anthropic deepseek-ai google-deepmind perplexity-ai computer-using-agent reasoning multimodality performance-benchmarks open-source ai-safety benchmarking video-generation model-evaluation sam-altman swyx
OpenAI launched Operator, a premium computer-using agent for web tasks like booking and ordering, available now for Pro users in the US with an API promised. It features long horizon remote VMs up to 20 minutes and video export, showing state-of-the-art agent performance but not yet human-level. Anthropic had launched a similar agent 3 months earlier as an open source demo. DeepSeek AI unveiled DeepSeek R1, an open-source reasoning model excelling on the Humanity's Last Exam dataset, outperforming models like LLaMA 4 and OpenAI's o1. Google DeepMind open-sourced VideoLLaMA 3, a multimodal foundation model for image and video understanding. Perplexity AI released Perplexity Assistant for Android with reasoning and search capabilities. The Humanity's Last Exam dataset contains 3,000 questions testing AI reasoning, with current models scoring below 10% accuracy, indicating room for improvement. OpenAI's Computer-Using Agent (CUA) shows improved performance on OSWorld and WebArena benchmarks but still lags behind humans. Anthropic AI introduced Citations for safer AI responses. Sam Altman and Swyx commented on Operator's launch and capabilities.
Project Stargate: $500b datacenter (1.7% of US GDP) and Gemini 2 Flash Thinking 2
gemini-2.0-flash deepseek-r1 qwen-32b openai softbank oracle arm microsoft nvidia huggingface deepseek-ai long-context quantization code-interpretation model-distillation open-source agi-research model-performance memory-optimization noam-shazeer liang-wenfeng
Project Stargate, a US "AI Manhattan project" led by OpenAI and Softbank, supported by Oracle, Arm, Microsoft, and NVIDIA, was announced with a scale comparable to the original Manhattan project costing $35B inflation adjusted. Despite Microsoft's reduced role as exclusive compute partner, the project is serious but not immediately practical. Meanwhile, Noam Shazeer revealed a second major update to Gemini 2.0 Flash Thinking, enabling 1M token long context usable immediately. Additionally, AI Studio introduced a new code interpreter feature. On Reddit, DeepSeek R1, a distillation of Qwen 32B, was released for free on HuggingChat, sparking discussions on self-hosting, performance issues, and quantization techniques. DeepSeek's CEO Liang Wenfeng highlighted their focus on fundamental AGI research, efficient MLA architecture, and commitment to open-source development despite export restrictions, positioning DeepSeek as a potential alternative to closed-source AI trends.
DeepSeek R1: o1-level open weights model and a simple recipe for upgrading 1.5B models to Sonnet/4o level
deepseek-r1 deepseek-v3 qwen-2.5 llama-3.1 llama-3.3-70b deepseek ollama qwen llama reinforcement-learning fine-tuning model-distillation model-optimization reasoning reward-models multi-response-sampling model-training
DeepSeek released DeepSeek R1, a significant upgrade over DeepSeek V3 from just three weeks prior, featuring 8 models including full-size 671B MoE models and multiple distillations from Qwen 2.5 and Llama 3.1/3.3. The models are MIT licensed, allowing finetuning and distillation. Pricing is notably cheaper than o1 by 27x-50x. The training process used GRPO (reward for correctness and style outcomes) without relying on PRM, MCTS, or reward models, focusing on reasoning improvements through reinforcement learning. Distilled models can run on Ollama and show strong capabilities like writing Manim code. The release emphasizes advances in reinforcement-learning, fine-tuning, and model-distillation with a novel RL framework from DeepSeekMath.
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.
Qwen with Questions: 32B open weights reasoning model nears o1 in GPQA/AIME/Math500
deepseek-r1 qwq gpt-4o claude-3.5-sonnet qwen-2.5 llama-cpp deepseek sambanova hugging-face dair-ai model-releases benchmarking fine-tuning sequential-search inference model-deployment agentic-rag external-tools multi-modal-models justin-lin clementdelangue ggerganov vikparuchuri
DeepSeek r1 leads the race for "open o1" models but has yet to release weights, while Justin Lin released QwQ, a 32B open weight model that outperforms GPT-4o and Claude 3.5 Sonnet on benchmarks. QwQ appears to be a fine-tuned version of Qwen 2.5, emphasizing sequential search and reflection for complex problem-solving. SambaNova promotes its RDUs as superior to GPUs for inference tasks, highlighting the shift from training to inference in AI systems. On Twitter, Hugging Face announced CPU deployment for llama.cpp instances, Marker v1 was released as a faster and more accurate deployment tool, and Agentic RAG developments focus on integrating external tools and advanced LLM chains for improved response accuracy. The open-source AI community sees growing momentum with models like Flux gaining popularity, reflecting a shift towards multi-modal AI models including image, video, audio, and biology.
LMSys killed Model Versioning (gpt 4o 1120, gemini exp 1121)
gpt-4o-2024-11-20 gemini-exp-1121 deepseek-r1 openai google-deepmind anthropic deepseek mistral-ai model-release model-ranking open-source vision coding reasoning market-competition
AI News for 11/21/2024-11/22/2024 highlights the intense frontier lab race with OpenAI's gpt-4o-2024-11-20 and Google DeepMind's gemini-exp-1121 trading top spots on the Lmsys leaderboard. The trend of using date-based model identifiers instead of traditional versioning is noted across leading labs including Anthropic. DeepSeek R1 is gaining attention as a potent open-source alternative, especially in the context of the AI competition between China and the US. Gemini-Exp-1121 is praised for improvements in vision, coding, and reasoning, while MistralAI expands with a new Palo Alto office, signaling growth and hiring.