تحويل الأحلام الأنيمي إلى واقع مع الشفرة
San Francisco
Joined May 2023
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Kai Yamamoto retweeted
Most AI tools want you locked into their ecosystem. Tencent's Octop takes a different approach.
It's an open-source, self-hosted AI workspace where you can bring your own models, tools, and coding agents like Claude Code and Codex.
What I find interesting is the focus on flexibility instead of another closed AI platform.
The real test will be how smoothly all these agents work together, but this is the kind of AI infrastructure I'd like to see more of.
Worth checking out: github.com/TencentCloud/Octo…
We open sourced Octop, a multi-user AI workspace for yourself, your family and your team.
Everyone gets their own login and can create multiple agents, each with its own workspace. Nothing you say or save shows up in another account. Almost everything can be swapped: models, storage, memory, plugins. Each agent comes with a browser, a terminal and a remote desktop.
You can hand off work to Claude Code, Codex, Cursor, OpenCode, CodeBuddy and other coding agents you already use. It also lives in your group chats on Telegram and Discord.
It runs on your own machine, and one command is all it takes: octop run.
The full picture is in the repo: github.com/TencentCloud/Octo….
Kai Yamamoto retweeted
In The Diamond Age, Neal Stephenson imagined a book that invents games and stories to teach a little girl what she needs, as she grows. I tried a small version of it. I gave Claude my brainstorm doc on alignment and asked it to make a game, something like Zelda, to teach people about AI alignment. Here's what came out 🪁
Short version: it's great at building the world, and still weak at understanding the player (details below)
Kai Yamamoto retweeted
This is kinda what we saw the whole of last year
Initially it was very important (and mentioned by respective Anthropic and OpenAI blogs) to give models good tools, with proper descriptions etc
Then giving them those tools started bottlenecking them, it was much better and simpler to give them a general way of interaction
Kai Yamamoto retweeted
It is becoming f*cking dangerous
A 19-year-old dropout from Lagos just ran 500 Claude Code agents at once
Caught them lying 245 times
And still handed a hedge fund 100 company profiles with zero errors in 6 minutes
He opens the live dashboard:
- 500 agents tearing through 100 companies at once
- 48,455 claims, each checked against the source in ~100 ms
- "$40M ARR" → made up → caught → rewritten
- 214 errors → 31 → 0 in three passes
- 1,830 backlinks dropped straight into Obsidian
The trick is the split
Opus does the work, a cheaper model decides if every claim is true
The loop doesn't stop until nothing false survives
The fund's own analysts spent 3 weeks on the same list
They missed 9 errors his swarm caught in the first pass
They paid him $40,000
And asked for 500 more companies by Friday
Kai Yamamoto retweeted
It's been a while since I talked about space.
Watch LEO satellites, not just space data centers.
But here's what most people overlook: This industry is fundamentally about LIGHT.
RF links to the ground. Laser links between satellites.
Once again, optics and semiconductors are at the heart of it all.
Kai Yamamoto retweeted
opencode breach hit 1.4% of its console users
attackers reached openai, anthropic and google api keys through a legacy system opencode was shutting down. the company calls it a large scale distillation attack and is working with all three labs
users on r/opencode say the keys were used before the notice came – $400 in anthropic charges, ~€200 on google and a project suspended for abuse
the open-source cli is not named in the breach. keys kept in local env vars never reached opencode's servers
We had a security breach last night related to a large scale distillation attack that impacted 1.4% of OpenCode Console users
We have notified them all this morning via email. If you did not get an email you were not impacted, it was a subset of users who had external providers linked
The incident is ongoing so we cannot share more details at this point but we are working with Anthropic, OpenAI, and Google to remediate
Kai Yamamoto retweeted
interesting proposal 👀
where will this leave europe?
完蛋了…..以后中国开源模型只能开源小参数的模型了….
商务部科技部就修订《中国禁止出口限制出口技术目录》征求意见，为期一个月，涉及人工智能（大模型、智能体、算力集群、信息处理等23项）生物医药、光伏3个领域。
1️⃣限制出口AI大模型：超过10^26计算量、或2T参数、或公开评估排名全球前10的大模型。
2️⃣限制出口智能体Agent：工具调用与系统操作技术，支持集成的第三方工具数量≥200个，工具选择准确率≥90%，且在需要调用3种及以上工具协同完成任务场景中，端到端任务平均成功率≥90%；自主规划与任务分解技术，可将自然语言指令自动拆解≥20步可执行子任务链，子任务分解精度≥80%，且子任务平均成功率≥90%；标准博弈基准超过90%的人类的博弈决策技术；得分75%以上的AI辅助漏洞挖掘技术。
限制出口算力集群技术：片间互联技术、分布式训练容错技术、通信调度技术、异构集群高效推理与调度。
征求意见期间，出口相关技术需向商务部填报登记表。已通过开源、发表学术论文等方式进入公共领域的技术，不纳入管理范围。
（中国商务部）
目前看来@Kimi_Moonshot 的K4、@MiniMax_AI 的M3 Pro、@Zai_org 的GLM5以及@deepseek_ai 的下一代模型都没法开源了…..
而且相关架构、训练优化和推理加速技术也都不行了。
Readers added context they thought people might want to know
该帖称中国大模型今后“没法开源了”、只能开源小参数模型，与官方文件不符。公告明确支持人工智能开源创新生态，对已通过开源等方式进入公共领域的技术不纳入管理范围，并对开源情形适用自动许可等便利措施（仍在征求意见中）。
mofcom.gov.cn/zwgk/zcfb/art/…
mofcom.gov.cn/syxwfb/art/202…
Kai Yamamoto retweeted
Want to work at METR? A Generator resident was recently hired there! BlueDot? A generator resident was recently hired there! Guidelight? A Generator resi-
Over half of the first Generator cohort has been hired since it ended in August 😎
Maybe you should apply to Generator 2.0?
Kai Yamamoto retweeted
Cool demo, it would be instant still if not for the 300ms launch animation. Imagine the EUV technology that makes sand do this but then stupid animations steal like 18 jilliongazilliontrillion clock cycles. Semiconductor engineers should revolt.
Kai Yamamoto retweeted
$TSM
TSMC beat the top of its revenue guide by 2.0%, its widest beat in five quarters, while gross margin landed inside the range for the first time in five. 2nm went from 3% to 8% of wafer revenue. We rate it Buy, $510 target.
Kai Yamamoto retweeted
I don't think most people realize how complex and complicated agentic AI systems inside mid-sized and above companies are: by necessity, because there is SO MUCH context, but only so little AI contex windows.
Case study on Uber's 19 internal, custom, AI-related systems coming later today in @Pragmatic_Eng
So many of those "AI-related systems" are "systems pre-AI" that turned out to become extremely useful with AI. Like their PRD+ERD system that conveniently documents connections between the ~5,000ish internal systems inside the company!
Kai Yamamoto retweeted
With Gemini 4 Argon we are so back, on the one metric that really matters: length of our safety report!
The Argon safety report is Google's most thorough by far and IMO there's a lot of good content, I particularly like the loss of control, alignment & monitorability assessments
Kai Yamamoto retweeted
NVIDIA $NVDA and ChipAgents have reportedly launched an evaluation of AI-powered semiconductor design technology, according to The Information.
The initiative aims to automate complex chip design, verification and debugging tasks, potentially reducing development time and costs.
The new evaluation was not independently confirmed, but the companies’ existing collaboration is verified.
Kai Yamamoto retweeted
The next generation won't ask permission to use AI. They'll expect it to be part of how work gets done.
But history has a warning: the steam engine didn't transform productivity overnight.
AI adoption is accelerating. Organizational transformation still has to catch up.
AI won't enter big companies from the top down. It'll come bottom up from the kids.
That's how the Mac happened. Corporate offices ran on PCs and Unix boxes. @Apple made Macs available in colleges, they spread to high schools, and eventually students handed them to their parents. Adoption moved up the generations, not down the org chart.
AI is going to follow the same path. Nobody in high school today does homework without it. When they enter the workforce, they won't accept writing code or documents the old way.
In my experience executives are talking about AI because it's on the cover of the @WSJ, but very few are actually using it every day.
Kai Yamamoto retweeted
Not every AI task needs a large language model generating answers token by token.
ScaleDown AI’s new models handle classification, extraction, and summarization, claiming 200x faster processing and 467x lower costs in its tests.
🤝 Paid partnership
You already gave the LLM the answer. So why is it writing it out from scratch?
Introducing a new AI model architecture: Constrained Decoding Models (CDMs)
LLMs were built to write. Most production workloads just need an answer: fast, consistent, and affordable.
CDMs are purpose-built for 1 task each. They read your input once and skip the token-by-token generative loop that makes LLMs slow and expensive.
Not just a decision model, but a family of 3 CDMs live today:
• Classify: define your labels and get back a calibrated probability + reason for each. Used for routing, tagging, and intent detection.
• Extract: describe the entities in natural language and get back well-formed JSON with confidence scores + citations. Used for web scraping, document processing, and PII redaction.
• Summarize: pass in long text, images, or PDFs and get back a consistent summary under 1,000 tokens. Used for context compaction, metadata generation, and transcript digests.
Built for production:
• 1M tokens of multimodal (text + image) input, 31x larger than Jev
• 77.2% on DecisionBench vs Jev's 72%
• 200x faster, 467x cheaper than frontier LLM APIs
• $0.05/M input tokens. Output is free (yes, even for summarize)
Live on your favorite platforms today:
@OpenRouter @vercel_dev @LiteLLM @LangChain @TrustedRouter @itsArthurAI @useRouterPlus
Get 50M input tokens for free (for the first 50 hours) at link below 👀
