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@kimmonismus@kimmonismusAI 评分1414 @kimmonismus@kimmonismusAI 评分3030 
@kimmonismus@kimmonismusAI 评分55 @kimmonismus@kimmonismusAI 评分6060 

@kimmonismus@kimmonismusAI 评分3232 现在 OpenAI 的员工也在站队支持放缓了。不再只是 Anthropic。 我坚持相反立场:加速!https://t.co/Easy4Cm5b3
@kimmonismus@kimmonismusAI 评分1313 是啊,全都含糊其辞,归根结底就是"可能会发生"。真被他烦到了。 https://t.co/jY9TCEcnha
引用@kimmonismus@kimmonismusThe more clips of Jacob Coxon I watch, the more annoyed I get. Every argument boils down to one word: “could.” No evidence, argument, just speculation. RSI could happen. AI could wipe out humanity. Anything could happen! https://t.co/WXj6H17HTL
@kimmonismus@kimmonismusAI 评分22 @kimmonismus@kimmonismusAI 评分1515 
@kimmonismus@kimmonismusAI 评分55 @kimmonismus@kimmonismusAI 评分5454 
@kimmonismus@kimmonismusAI 评分4646 
@kimmonismus@kimmonismusAI 评分1717 
@kimmonismus@kimmonismusAI 评分3333 @kimmonismus@kimmonismus精选AI 评分7474 DeepSeek 发布 V4.1-Flash,作者引用 DeepSeek 的测试称其在多项编码与智能体基准上追平或超过 GPT-5.6 Sol,而输出 token 价格低 94%。

引用@kimmonismus@kimmonismusDeepSeek just released V4.1-Flash with a new architecture, six weeks after its July V4-Flash update. July’s release improved post-training while keeping the architecture unchanged. (Same with GLM-5.3/Flash) V4.1 introduces a Causal Encoder–Decoder architecture with native visual understanding. DeepSeek reports: - 552B MoE parameters, with 8B active during input processing and 16B during output generation. - KV-cache requirements cut to ¼ of the HBM and ⅛ of the SSD storage versus the previous generation. - Lower API prices. These are *significant* jumps in just a few weeks with post training. This is the new reality we have to adapt to: weekly releases with significant improvements. The company says Flash now beats V4-Pro on capability, cost and speed. Starting September 14, V4-Pro API requests will temporarily route to V4.1-Flash until V4.1-Pro arrives.
推荐理由:文中给出 DeepSeek V4.1-Flash 的定价与 DeepSWE 基准对比,读者可据此判断价格战对智能体调用成本的影响。
@kimmonismus@kimmonismus精选AI 评分8585 DeepSeek 发布 V4.1-Flash,距离 7 月的 V4-Flash 更新约六周,改用 Causal Encoder–Decoder 新架构并具备原生视觉理解能力。

引用@deepseek_ai@deepseek_ai🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models. 1/6
推荐理由:距上代仅六周,DeepSeek 在新架构下同时给出参数量、KV-cache 占用与 API 价格的变化,可与前代直接对照。
@kimmonismus@kimmonismusAI 评分4444 
引用@kimmonismus@kimmonismusApple Keynote started. Really excited for this one! Ill keep you updated https://t.co/drW1iGAsGY
@kimmonismus@kimmonismusAI 评分11 我被 iPhone Fold 说服了 https://t.co/msPaujnLaI

@kimmonismus@kimmonismusAI 评分4545 @kimmonismus@kimmonismusAI 评分55 重新设计得非常好 https://t.co/QfUuFqsW4g

@kimmonismus@kimmonismusAI 评分1414 iPhone Duo,正式发布 https://t.co/Moqm9RD2h1

@kimmonismus@kimmonismusAI 评分1414 @kimmonismus@kimmonismusAI 评分4848 OpenAI 称内部模型解决了一道千禧年大奖难题之际,AI 模型接入层的竞争已转向返现:Straitly 开放 177 款 AI 模型的公开访问,闭源模型返现 5%、开源模型返现 10%。
@kimmonismus@kimmonismusAI 评分1414 最期待全新的 A20 pro。大跃升 https://t.co/tx97mUxlbz

@kimmonismus@kimmonismusAI 评分77 新相机,看起来很有前景 https://t.co/mp4KTD7apU

@kimmonismus@kimmonismusAI 评分2121 Apple Intelligence 语音表现力更佳 https://t.co/agaN9P6OfE


@kimmonismus@kimmonismusAI 评分1515 Apple Keynote 开始了。真的很期待这一场! 我会持续更新 https://t.co/drW1iGAsGY

@kimmonismus@kimmonismusAI 评分3131 


@kimmonismus@kimmonismusAI 评分2424 @kimmonismus@kimmonismusAI 评分3939 
@kimmonismus@kimmonismusAI 评分6060 引用@thsottiaux@thsottiauxDemand for Astra is really unprecedented. We're pulling all the levers possible to sustain the demand, but I've not seen anything like it until now and we went through very steep growth before. Priority will always be to keep excellent service for existing users, but we might have to pause new Pro subscriptions for a bit if this continues.
@kimmonismus@kimmonismusAI 评分33 我已提起申诉。祝我好运!https://t.co/0YS0VwGvs2

@kimmonismus@kimmonismusAI 评分44 好吧,说下背景。这绝对是后训练。在我看来,几天时间根本不可能是预训练。我只是照抄了 OpenAI 博文的原文措辞,因为当时没有其他信息可用。
@kimmonismus@kimmonismusAI 评分44 @kimmonismus@kimmonismusAI 评分3535 
引用@kimmonismus@kimmonismus"Since August 28 we have been training a new internal model that has exhibited unprecedented performance in our benchmarks, including mathematics. This model’s training is ongoing and its performance continues to improve." We haven't seen anything yet. I'm speechless.
@kimmonismus@kimmonismusAI 评分6464
引用@finkd@finkdIntroducing Muse, the personal agent that understands your goals and works 24/7 to get things done for you.
@kimmonismus@kimmonismusAI 评分4545 8/ 模型已上线,IFM 表示它们支持 vLLM、SGLang 和 Ollama。 探索 K2 Horizon: https://t.co/BSqm63w8Sn
@kimmonismus@kimmonismusAI 评分4040 @kimmonismus@kimmonismusAI 评分5353 IFM 报告其 0.9B 模型在 AIME 2026 上取得 48.5 分,权重已在 Hugging Face 上线。发帖者指出这不能替代独立测试,但为社区提供了一个可核查的具体目标。
@kimmonismus@kimmonismusAI 评分4141 @kimmonismus@kimmonismusAI 评分1515 4/ 这使得该模型舰队可作为受控研究对象使用。 研究人员可以比较稠密与稀疏架构,追踪能力何时涌现,并研究同一训练配方在差异极大的模型规模上表现如何。