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@kimmonismus@kimmonismusAI 评分22 @kimmonismus@kimmonismusAI 评分4040 
@kimmonismus@kimmonismusAI 评分44 Clip teddit.net/r/singularity/s/d…
@kimmonismus@kimmonismusAI 评分2424 人们到底为什么还认为蓝领工作不会被自动化取代? 机器人可以连续工作 200 小时不停歇。 人类每周工作约 40 小时,还需要周末、睡眠、休息、病假和假期。 这彻底改变了经济账。 视频

@kimmonismus@kimmonismusAI 评分2222 引用can (@marmaduke091)@marmaduke091claude-opus-4.8 is on Google Vertex 👀
@kimmonismus@kimmonismusAI 评分5454 引用Homeland Security (@DHSgov)@DHSgovAn alien who is in the U.S. temporarily and wants a Green Card must return to their home country to apply. This policy allows our immigration system to function as the law intended instead of incentivizing loopholes. The era of abusing our nation’s immigration system is over.
@kimmonismus@kimmonismusAI 评分44 @kimmonismus@kimmonismusAI 评分3838 引用Pamphlets (@PamphletsY)@PamphletsY🚨🇨🇳 BREAKING — China Unveils Gaming GPU To Challenge NVIDIA Video
@kimmonismus@kimmonismusAI 评分00 @kimmonismus@kimmonismusAI 评分4646 Demis 表示,奇点如今可能只剩几年之遥,或由真正的 AGI 到来所启动。 "它如此具有变革性,将成为史上最重要的技术" 视频

@kimmonismus@kimmonismusAI 评分4141 Anthropic 的 Jack Clare 非常乐观: - 到 2028 年底,“AI 系统将能够设计自己的继任者” - 12 个月内,人类 + 机器人将取得诺贝尔奖级别的发现
引用prinz (@deredleritt3r)@deredleritt3rJack Clark: - AI will make a Nobel Prize-winning discovery within 12 months (working collaboratively with humans) - Bipedal robots will help with enterprise work ("tradespeople") in 2 years - AI systems will be able to design their own successors by year-end 2028 (i.e., RSI) - Companies run solely by AI will be generating millions of USD in revenue within 18 months - Clark's most conservative prediction is that vast swathes of the economy and society will go through profound changes, potentially including "a machine economy decoupling from the human economy, robots gaining brains, science progressing without humans, and scientific equipment that people hadn't conveived of but which worked".
@kimmonismus@kimmonismusAI 评分55 @kimmonismus@kimmonismus精选AI 评分8282 
推荐理由:彭博消息给出融资规模与 ARR 增长两组数字,读者可据此对照 Anthropic 与 OpenAI 的估值位置。
@kimmonismus@kimmonismus精选AI 评分7474 DeepSeek 正在推进一轮 102.9 亿美元的融资,消息来自彭博。报道称梁文锋仍专注于构建开源 AI 模型,而不是追求短期商业化。

推荐理由:融资规模与创始人仍坚持开源路线并置,提供了一个观察 DeepSeek 商业取向的窗口。
@kimmonismus@kimmonismus精选AI 评分7777 引用DeepSeek (@deepseek_ai)@deepseek_aiWe are making our discount permanent! 🎉 Enjoy building with DeepSeek-V4-Pro and bring your innovative ideas to life! 🚀
推荐理由:DeepSeek-V4-Pro 将 75% 折扣改为永久定价,读者可据此比较它与 v3.2 在算力与缓存开销上的差距。
@kimmonismus@kimmonismusAI 评分5555 引用Ben Cera (@Bencera)@BenceraPolsia just raised $30M at a $250M valuation. Approaching $10M annual run rate. One Founder + AI. Zero employees. Polsia runs companies autonomously. It also ran its own fundraising. I just showed up for signatures. Video
@kimmonismus@kimmonismusAI 评分3232 我只能重申我昨天说过的话:只要 AGI 没有统一的定义,讨论 AGI 何时实现就毫无意义。尤其是当每个人都有自己的定义时。
引用Polymarket (@Polymarket)@PolymarketNEW: Marc Andreessen declares AGI was achieved three months ago.
@kimmonismus@kimmonismusAI 评分3636 引用Howie Liu (@howietl)@howietlWe’re giving away $10,000,000 to founders building agent-first businesses. Autonomous, proactive agents will run tomorrow's companies. We're backing 500 founders building them. The Founding 500. hyperagent.com Video
@kimmonismus@kimmonismusAI 评分2525 
@kimmonismus@kimmonismusAI 评分5454 引用Hedgie (@HedgieMarkets)@HedgieMarkets🦔Microsoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable, even for a company with effectively infinite cloud resources. Uber's CTO sent an internal memo warning the company burned through its entire 2026 AI budget in just four months. American AI software prices have jumped 20% to 37%, and GitHub (owned by Microsoft) is dropping flat-rate plans for usage-based billing across its products. My Take The AI subsidy era is ending in real time. The same company that put $13 billion into OpenAI and built the Azure infrastructure powering most of Anthropic's compute just looked at the bill from a competitor's coding tool and decided it was not worth paying. That is not a productivity failure on Anthropic's end. Token-based pricing is forcing every enterprise customer to confront the actual cost of running these models at scale, and the number turns out to be far higher than the flat-rate experiments suggested. This ties directly to my Gemini Flash post yesterday. Anthropic, OpenAI, and Google all raised effective prices in the last six months. Enterprises that built workflows assuming AI costs would keep falling are now watching annual budgets evaporate in months. Two outcomes look likely from here. Either enterprises scale back AI usage to fit budgets, which slows the revenue ramp the labs need to justify their valuations ahead of IPOs, or the labs cut prices and absorb the losses, which makes the unit economics worse at exactly the wrong moment. Both paths land in the same place, the numbers stop working, and somebody has to take the writedown. Hedgie🤗
@kimmonismus@kimmonismusAI 评分3939 
@kimmonismus@kimmonismusAI 评分1313 引用Sam Altman (@sama)@samawhat problem do you most hope AI will solve in the future? maybe we can help!
@kimmonismus@kimmonismusAI 评分22
引用Vamsi Batchu (@vamsibatchuk)@vamsibatchukIt was so good to meet and hangout with you, my friend !!
@kimmonismus@kimmonismusAI 评分22 
@kimmonismus@kimmonismusAI 评分22 @kimmonismus@kimmonismus精选AI 评分6868 Karpathy 将参与组建一个新团队,专注于用 Claude 本身加速预训练研究。该团队的方向是递归自我改进。

推荐理由:Karpathy 参与的新团队把 Claude 用于加速预训练研究,指向递归自我改进这一方向。
@kimmonismus@kimmonismus精选AI 评分6565 
推荐理由:推文对比两家公司的营收口径与盈亏状况,读者可据此了解年度化营收为何会反转排名。
@kimmonismus@kimmonismusAI 评分11 @kimmonismus@kimmonismusAI 评分2020 不错的小更新。喜欢这些小更新。Cmd+cmd 截取打开的窗口 视频

@kimmonismus@kimmonismusAI 评分5858 @kimmonismus@kimmonismusAI 评分6363 @kimmonismus@kimmonismusAI 评分2626 4/ 我为这张 1950 年代漫画封面尝试了一种完全不同的风格。模型对空间关系和布局的理解足够好,能把角色和文字精确放在该在的位置。 这让单流程生成海报或漫画变得容易得多。

@kimmonismus@kimmonismusAI 评分2222 3/ 它也能很好地处理高密度信息渲染。我生成了这张认知信息图,来看看它如何处理复杂布局。 它保持了文字清晰、图标结构规整,而这正是开源模型常见的痛点。

@kimmonismus@kimmonismusAI 评分2323 2/ 我通过从达斯·维达的单色草图开始,测试了交错生成。它逐步构建机械纹理和光照,同时始终保持相同的视觉风格。 看着它在不丢失原始结构的情况下细化图像,相当令人印象深刻.. 视频

@kimmonismus@kimmonismusAI 评分3737 
@kimmonismus@kimmonismusAI 评分00 这不可能是真的吧?是真实的地铁广告,还是游击营销。 不管怎样:对当年发生的事情的描绘完全夸张了。
引用Spelling Mistakes Cost Lives (@darren_cullen)@darren_cullenOn the tube
@kimmonismus@kimmonismus精选AI 评分6969
引用Artificial Analysis (@ArtificialAnlys)@ArtificialAnlysCursor's new Composer 2.5 takes third on the Artificial Analysis Coding Agent Index and is ~10-60x lower cost than the higher-effort Opus 4.7 and GPT-5.5 variants above it. This release puts Composer among the leading coding agent models, something that wasn’t clear for past releases @cursor_ai has released Composer 2.5, the latest model in its Composer line. Composer 2.5 scored 62 on our Coding Agent Index, a 14 point gain over Composer 2 (48). This puts it in third place of our tested agents, behind only Claude Opus 4.7 (max) in Claude Code (66) and GPT-5.5 (xhigh reasoning) in Codex (65). These cost $4.10 and $4.82 per task respectively, ~10x the cost of Composer 2.5 Fast ($0.44) and ~60x the cost of Composer 2.5 standard ($0.07). Key results for Composer 2.5 in Cursor CLI: ➤ Cost-quality Pareto frontier: At $0.07 (standard) and $0.44 (Fast) per task, Composer 2.5 is cheaper than every other agent scoring above 60 on the Index. Medium-effort peers cost $1.24–$2.21 per task; higher-effort variants land 3-4 points above at $4.10–$4.82 ➤ Per-benchmark gains vs Composer 2: +35 points on SWE-Bench-Pro-Hard-AA (12% → 47%), +2 points on Terminal-Bench v2 (64% → 66%), and +3 points on SWE-Atlas-QnA (69% → 72%). At 47%, Composer 2.5's score on SWE-Bench-Pro-Hard-AA is comparable to Claude Opus 4.7 (max) in Claude Code ➤ Among the fastest coding agents: Composer 2.5 Fast runs at an average wall time of 6.7 minutes per task, the third-fastest agent on the Artificial Analysis Coding Agent Index, behind only Claude Opus 4.7 (medium) in Claude Code (5.8m) and GPT-5.5 (medium) in Cursor CLI (6.2m) ➤ Fast mode enables better responsiveness at 6x pricing: Fast runs 30% faster than standard Composer 2.5, but is ~6x the cost per task ($0.44 vs $0.07). Token pricing is 6x higher for Fast: $3.00/$15.00 vs $0.50/$2.50 per million input/output tokens Model details: ➤ Base model: Continued training on @Kimi_Moonshot's open weights Kimi K2.5 as with Composer 2, with Cursor reporting ~85% of total compute from its own additional training and reinforcement learning ➤ Pricing: $0.50/$2.50 per million input/output tokens for the standard variant; $3.00/$15.00 for the Fast variant (the default in Cursor) ➤ Available exclusively in Cursor: both Cursor IDE and Cursor CLI, an externally accessible API is not available Congratulations @cursor_ai and @mntruell on the impressive release!
推荐理由:推文用每任务成本对比 Composer 2.5 与两个更高分编码智能体,读者可据此权衡编码任务上的性能与花费。
@kimmonismus@kimmonismusAI 评分1515 @kimmonismus@kimmonismusAI 评分2626 
@kimmonismus@kimmonismusAI 评分2222 