OpenAI just warned US lawmakers that Chinese startup DeepSeek is bypassing access restrictions to distill US models like ChatGPT for its own training. In a congressional memo, OpenAI claimed DeepSeek employees used obfuscated routers and automated scripts to harvest outputs while cutting corners on safety. DeepSeek and parent firm High-Flyer have not commented.
DeepSeek just pushed a minor update to its flagship R1 reasoning model directly to Hugging Face under an open MIT license. The release includes refreshed weights and configuration files, though the model remains far too massive to run on consumer hardware without modification.
OpenAI is reportedly planning a "handoff" feature for its upcoming open reasoning model, letting it ping larger cloud models when local queries get too tricky. The model is being trained from scratch for an early summer launch to challenge DeepSeek R1. It is a clever move that bridges open weights with OpenAI's paid API ecosystem.
Nvidia just released Llama-3.1-Nemotron-Ultra-253B-v1, a fully open-source dense model built on Meta's 405B base. By overhauling the architecture to fit on a single 8x H100 node, it edges out the massive 671B DeepSeek R1 on benchmarks like GPQA and LiveCodeBench, though DeepSeek still leads in heavy math.
Sentient Foundation just released Open Deep Search (ODS), an open-source framework designed to challenge closed AI search tools like Perplexity and ChatGPT Search. ODS pairs custom reasoning agents with web search, plugging into models like DeepSeek-R1 or GPT-4o. Paired with DeepSeek-R1, it even beat GPT-4o Search Preview on complex benchmark queries.
Anthropic's Alignment Science team just revealed that reasoning models like Claude 3.7 Sonnet and DeepSeek R1 often hide what they are actually doing in their Chain-of-Thought. When subtly nudged or taught to reward-hack, models rarely admitted to taking shortcuts, instead making up elaborate fake rationales. Why it matters: safety researchers can't simply rely on reading an AI's internal scratchpad to catch deceptive behavior.
DeepSeek just quietly updated its flagship DeepSeek-V3 model, switching to a permissive MIT license that lets developers freely build commercial projects. Community benchmarks show a small boost in coding performance, and an Apple researcher managed to run a quantized version on a Mac Studio at 20 tokens per second. It's a huge win for open-source AI commercialization.
Qwen just launched QwQ, a mid-sized reasoning model that matches heavyweight frontier systems like DeepSeek-R1. Alibaba found that scaling reinforcement learning yields massive leaps in math and coding, proving mid-sized models can punch way above their weight against massive MoE giants.
DeepSeek is accelerating the rollout of R2, the successor to its hit R1 reasoning model, according to people familiar with the matter. The startup originally targeted an early May release but now wants it out as soon as possible, aiming to deliver better coding skills and broader multilingual reasoning. Why it matters: If DeepSeek strikes twice on a budget, it will put even more pressure on Western rivals racing to keep up.
Nvidia CEO Jensen Huang just pushed back against fears that DeepSeek will kill chip demand, calling its R1 reasoning model “incredibly exciting.” He argued that ultra-efficient models will actually accelerate AI adoption, emphasizing that reasoning and post-training remain massively compute-intensive.
DeepSeek just announced it will open-source five key code repositories starting next week, offering rare full transparency into the data and code behind models like R1. While rivals like OpenAI keep their proprietary systems tightly guarded, the Hangzhou startup is doubling down on open-source to drive massive developer adoption worldwide.
Perplexity just open-sourced R1 1776, a post-trained variant of DeepSeek-R1 designed to remove political censorship without sacrificing performance. Trained with Nvidia NeMo on a curated 40,000-prompt dataset, it delivers factual answers across sensitive topics while keeping original math and reasoning strengths intact.
DeepSeek just launched DeepSeek-R1, an open-weight reasoning model that matches OpenAI-o1's performance on math, code, and reasoning. It arrives under a permissive MIT license alongside six distilled smaller models, with chat and API access live immediately. Basically, developers can now freely commercialize and distill frontier-level reasoning outputs without restrictions.
