“Google DeepMind CEO suggests China's AI models are only a few months behind the US, showing the rapid global convergence.”

“Think of it as separating remembering from reasoning.”

“This research investigates a new approach to how Large Language Models (LLMs) process information, potentially moving beyond pure calculation.”

“DeepSeek’s new Engram module targets exactly this gap by adding a conditional memory axis that works alongside MoE rather than replacing it.”

“The author finds the initial Qwen release to be the best, and suggests that later iterations saw reduced performance.”

“Anyone read the mhc paper?”

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“Measuring the impact of Qwen, DeepSeek, Llama, GPT-OSS, Nemotron, and all of the new entrants to the ecosystem.”

“DeepSeek mHC reimagines some of the established assumtions about AI scale.”

“Which of these state-of-the-art models writes the best code?”

“The new method mHC, Manifold Constrained Hyper Connections, keeps the richer topology of hyper connections but locks the mixing behavior on […]”

“DeepSeek recently released a paper, elaborating on a more efficient method of artificial intelligence development. The paper was co-authored by founder Liang Wenfeng.”

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“DeepSeek solved the instability by constraining the learnable matrices to be "Double Stochastic" (all elements ≧ 0, rows/cols sum to 1). Mathematically, this forces the operation to act as a weighted average (convex combination). It guarantees that signals are never amplified beyond control, regardless of network depth.”

“DeepSeek solved the instability by constraining the learnable matrices to be "Double Stochastic" (all elements ≧ 0, rows/cols sum to 1).”

“DeepSeek broke the scaling thesis. Anthropic won coding. China dominated open source.”

“DeepSeek-V3 has the best performance in all three categories... All three LLMs exhibited notably weak performance in Geometry.”

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“Manus's ability to perform tasks using a web browser without human supervision.”

“Agents are susceptible to prompt injection in 25% of tasks on average (13% for GPT-5 to 43% for DeepSeek-R1).”

“The article highlights the emergence of new AI-related terms in 2025.”

“XiaomiMiMo/MiMo-V2-Flash has 310B param and top benches. Seems to compete well with KimiK2Thinking, GLM4.7, MinimaxM2.1, Deepseek3.2”

“"acceptance becoming increasingly lottery-like."”

“MiniMaxAI/MiniMax-M2.1 seems to be the best value model now”

“The open-weights reasoning model DeepSeek R1 achieves state-of-the-art performance (50.6%), surpassing proprietary giants like Claude 3.7 Sonnet (47.7%) and GPT-4o (33.7%), it still exhibits a significant accuracy drop when moving from general benchmarks (BIRD) to CricBench.”

“LFM2-2.6B-Exp is an experimental checkpoint built on LFM2-2.6B using pure reinforcement learning.”

“DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models”

“DeepSeek-V3 and Llama 3 have emerged, and their amazing performance is attracting attention. However, in order to operate these models at a practical speed, a technique called quantization, which reduces the amount of data, is essential.”

“the AI hype train is showing no signs of slowing.”

“AI companies developing large models - OpenAI, Anthropic, Meta, Google, DeepSeek, etc. - must outline safety plans and transparency rules for reporting”

“The article presents a DeepSeek-powered AI system.”

“In 2025, Reinforcement Learning from Verifiable Rewards (RLVR) emerged as the de facto new major stage to add to this mix. By training LLMs against automatically verifiable rewards across a number of environments (e.g. think math/code puzzles), the LLMs spontaneously develop strategies that look like "reasoning" to humans - they learn to break down problem solving into intermediate calculations and they learn a number of problem solving strategies for going back and forth to figure things out (see DeepSeek R1 paper for examples).”

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“The article analyzes the effects of prompt language and cultural prompting.”

“Deepseek 3.2 New AI Model is Faster, Cheaper and Smarter”

“DeepSeek Releases New Reasoning Models, Mistral closes in on Big AI rivals with new open-weight frontier and small models”

“Based on the title, the article is likely about the DeepSeek-V3.2 LLM.”

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“Definitely a week about models releases.”

“The article's core focus is on enhancing the AI model's ability to verify the correctness of its own mathematical reasoning.”

“The research focuses on training LLMs with reasoning traces from either GPT-OSS or DeepSeek R1.”

““I credited my OpenAI API account with credits, and then it turns out I have to go through some verification process to actually use the API, which involves disclosing personal data to some third-party vendor, which I am not prepared to do. So I asked for a refund and am told that that refunds are against their policy.””

“The article mentions running DeepSeek-OCR on an Nvidia Spark and using Claude Code.”

“LLM inference that gets faster as you use it. Our runtime-learning accelerator adapts continuously to your workload, delivering 500 TPS on DeepSeek-V3.1, a 4x speedup over baseline performance without manual tuning.”

“Access DeepSeek-V3.1 on Together AI: MIT-licensed hybrid model with thinking/non-thinking modes, 66% SWE-bench Verified, serverless deployment, 99.9% SLA.”

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“From DeepSeek-V3 to Kimi K2: A Look At Modern LLM Architecture Design”

“Together AI inference is now among the world’s fastest, most capable platforms for running open-source reasoning models like DeepSeek-R1 at scale, thanks to our new inference engine designed for NVIDIA HGX B200.”

“The author found some AI-generated frontend designs surprisingly good and created a ranking game to evaluate them. They were impressed with DeepSeek and Grok and noted variance in OpenAI's performance across categories.”

“The site attempts to solve that. You just describe what you want to do, pick the input files and an LLM (currently DeepSeek) generates the FFmpeg command. You can then run it directly in your browser or use the command elsewhere.”