科技推文精选 - 2026年6月6日

2026年6月6日科技每日简报

Today's top tech conversations are led by @matteocollina, whose post about 'RT @AnthropicAI: Our internal ...' garnered the highest engagement. Key themes trending across the top stories include improvement, models, research, claude, https. The community is actively discussing recent developments in AI, engineering practices, and startup strategies.

1. matteocollina (Group Score: 383.7 | Individual: 56.6)

Cluster: 12 tweets | Engagement: 8124 (Avg: 473) | Type: Tech

RT @AnthropicAI: Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.

It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx

See 11 related tweets

@cryptopunk7213: we’re almost at the point of no return.

anthropic has almost built an ai that autonomously self imp...

@WesRoth: Anthropic published new internal data suggesting Claude is accelerating AI development and may be cr...
@levie: Good thought provoking post from Anthropic. I think this paragraph points to the key element of the ...
@TheStalwart: Interesting chart, but the bar could go up 100x, and theoretically not be evidence that we’re closer...
@KirkDBorne: 17 Claude features most people will never find on their own.

From post by @AnatoliKopadze …\n\nQT @...

2. MarioNawfal (Group Score: 360.1 | Individual: 34.7)

Cluster: 17 tweets | Engagement: 431 (Avg: 457) | Type: Tech

🇺🇸 Google just signed a deal worth $920 million per month with SpaceX (yes, almost a BILLION a month) for AI computing.

The deal will offer access to computing resources, including ~110,000 NVIDIA GPUs, CPUs, memory, as part of a deal that will give access to SpaceX's family of data centers.

Source: @WatcherGuru\n\nQT @MarioNawfal: Morgan Stanley is projecting SpaceX hits $3.4 trillion in annual revenue by 2040

The rockets and Starlink built the company. Under these projections, they become the infrastructure for a global AI platform that happens to operate in orbit.

Source: Reuters https://t.co/8R8T35ULXf

See 16 related tweets

@SawyerMerritt: Anthropic and Google are now paying @SpaceX a combined $2.17 billon per month for compute capacity. ...
@cryptopunk7213: elon's on a generational run right now, google just agreed to pay spaceX ~$1 billion per MONTH for 3...
@edzitron: Also this is the firmest proof that data center capacity is just not getting built. If it were, give...
@TechCrunch: Google will pay SpaceX $920M per month for compute https://t.co/h585beoA9e...
@XFreeze: SpaceX’s compute business is already becoming massive

Anthropic: $1.25B per month Google:$ 920M per...

3. unusual_whales (Group Score: 279.3 | Individual: 42.7)

Cluster: 16 tweets | Engagement: 16016 (Avg: 1862) | Type: Tech

BREAKING: Anthropic has urged for a global pause in AI development as artificial-intelligence models are nearing capability to improve without human intervention, per WSJ

See 15 related tweets

@wallstengine: WSJ reported yesterday that Anthropic is urging top AI labs to consider slowing or temporarily pausi...
@BullTheoryio: THIS IS VERY CONCERNING.

Anthropic just called for a global pause in AI development, warning that A...

@mark_k: GFY Anthropic. https://t.co/54nOKRbq0a\n\nQT @Osint613: Anthropic is calling for a global pause on d...
@business: Anthropic has called for the creation of a mechanism to pause the development of AI https://t.co/u5I...
@JordanSchachtel: Anthropic wants to become one with the system, and their repeated doomsday proclamations are their p...

4. eliebakouch (Group Score: 178.7 | Individual: 40.9)

Cluster: 6 tweets | Engagement: 277 (Avg: 123) | Type: Tech

NVIDIA 💚🦋 Prime Intellect https://t.co/uRpaeqYkEo\n\nQT @PrimeIntellect: We're excited to join the NVIDIA Nemotron Coalition 💚

Frontier open models matter for the whole ecosystem.

We're bringing the RL infrastructure and environments we've built over the last year to help scale agentic capabilities.

https://t.co/bhrogG7lWH https://t.co/5obi6gmYs1

See 5 related tweets

@samsja19: 🫡🫡🫡\n\nQT @PrimeIntellect: We're excited to join the NVIDIA Nemotron Coalition 💚

Frontier open mode...

@WesRoth: NVIDIA released Nemotron 3 Ultra, a 550B MoE open frontier model built for long-running AI agents. I...
@m_sirovatka: RT @PrimeIntellect: We're excited to join the NVIDIA Nemotron Coalition 💚

Frontier open models matt...

@NVIDIAAP: Introducing NVIDIA Nemotron 3 Ultra.

A frontier smart open model built for long-running agents that...

@WesRoth: Nous Research joined NVIDIA’s Nemotron Coalition, a group of AI labs working together to advance ope...

5. Scobleizer (Group Score: 149.7 | Individual: 30.0)

Cluster: 6 tweets | Engagement: 40 (Avg: 254) | Type: Tech

I remember Techcrunch's founder @arrington once say something like "I hate lists, especially ones I'm not on the top of."

I doubt I'll be on the top of this one. I know quite a few people spending $1,000+ a day in AI token generation.

My budget is way smaller. :-)\n\nQT @alexisaftalion: Are you really tokenmaxxing?

We shipped your AI wrapped

Everyone's bragging about their token usage having 45 agents running at once

now it's time to prove it.

A command that turns how you really use AI into stats, a score, and a ranking.

Run “npx standout” in your terminal and find out who's really standing out.

See 5 related tweets

@godofprompt: 78/100. Top 12%.

Didn’t think I used AI that much… ok maybe I do.

Drop your score below, I want to...

@omarsar0: Neat little tool!

Ran my AI Wrapped, expecting to be humbled. Top 1%. Nice!

I use coding agent all...

@AskYoshik: I'm genuinely addicted to Claude Opus 4.8.

Half the time it doesn't feel like using an AI model. It...

@alex_prompter: 66/100. Top 37%.

Apparently I’m AI-maxxing, but not tokenmaxxing hard enough yet.

Comment your % b...

@ycombinator: RT @alexisaftalion: Are you really tokenmaxxing?

We shipped your AI wrapped

Everyone's bragging ab...

6. kimmonismus (Group Score: 144.6 | Individual: 31.8)

Cluster: 5 tweets | Engagement: 425 (Avg: 280) | Type: Tech

Holy cow. Mythos really is next level\n\nQT @testingcatalog: MYTHOS 🔥: Another early preview of recently spotted "Oceanus" checkpoint output.

"Oceanus" is rumored to be a version of the upcoming Mythos model, which is planned for public release within "weeks", according to Anthropic.

"Oceanus" prompt 👀 https://t.co/MVew8mQX7z

See 4 related tweets

@VaibhavSisinty: This is literally insane. 🤯

Anthropic is reportedly preparing to release a model codenamed, "Oceanu...

@WesRoth: According to early reports, Oceanus was briefly made available to some red teamers, but access may h...
@WesRoth: A new early preview of an Anthropic model checkpoint called Oceanus is circulating, adding more spec...
@theobearman: RT @synthwavedd: 🚨 SCOOP: Anthropic is gearing up for the public launch of a new version of Mythos, ...

7. rabois (Group Score: 120.2 | Individual: 32.6)

Cluster: 4 tweets | Engagement: 99 (Avg: 181) | Type: Tech

This.\n\nQT @eglyman: As I wrote this, I saw X go into meltdown over tokens.

You've seen the headlines: “Uber blows yearly AI budget in just one quarter.” “Meta employee burns 281 billion tokens in April.”

But, the problem isn't spending. Spending works. Since 2023, the top quartile of our AI spenders doubled their revenue. The bottom quartile? Flat.

It's blind spending. We don’t know which spend worked.

A sales team has qualified leads. A support team has resolved conversations. These are units you can measure against. All a token tells you is the meter ran, not whether the work was worth it or not.

Finance says, “half the budget,” engineering says, “double it” and you don’t know who’s right because there is no shared language of value. There’s no attribution, and no attribution means no allocation.

For example, right now, all work, no matter the size or shape, defaults to frontier models. But meeting summaries and calendar updates don’t require GPT-5.5 Pro.

In isolation this seems trivial, but re-route just 10% of a $10M AI bill from frontier to GPT-4 level intelligence you’ve saved nearly one million dollars. This sounds like a made-up stat — it’s not. It truly is that much cheaper.

This is the future of finance: not blindly rubber-stamping or rejecting AI spend, but allocating it with the same rigor companies apply to headcount.

See 3 related tweets

@edzitron: not , but,\n\nQT @eglyman: As I wrote this, I saw X go into meltdown over tokens.

You've seen the h...

@tryramp: RT @eglyman: As I wrote this, I saw X go into meltdown over tokens.

You've seen the headlines: “Ube...

@rohanpaul_ai: RT @rohanpaul_ai: Sam Altman admits AI budgets are turning into a “huge issue,” with customers burni...

8. MTSlive (Group Score: 119.9 | Individual: 37.4)

Cluster: 4 tweets | Engagement: 71 (Avg: 112) | Type: Tech

SITUATION ANALYSIS: Anthropic on Recursive Self-Improvement

A month after co-founder @jackclarkSF's blog post on recursive self-improvement, Anthropic has released their own report, based partially on internal data, arguing that AI systems that can fully autonomously design and develop their own successors are not very far away. If true, the implications for AI research narrowly and society more broadly are enormous.

They make a few different arguments:

First, if you just look at public data you see clear trends of consistent and rapid improvement. The famous METR time-horizons graph doubles every four months, and on research and engineering benchmarks like SWE-bench and CORE-bench, models have gone from near-zero to close to 100% in a year or two.
Claude writes 80% of new code at Anthropic now, and the code contributed per engineer per quarter has increased by 8x compared to the pre-2025 baseline. While quantity of code is not the same as quality, this is still a major speedup.
Code written by Claude works most of the time, and is rapidly getting better. Claude Mythos Preview was a major improvement in Claude’s ability to do open-ended problems.
Claude is getting better at open-ended research tasks. In one experiment, Anthropic examined Claude Code transcripts of real research tasks where a researcher had made a mistake. They gave the transcripts before the mistake to Claude models and asked them where to go next. Mythos was able to choose a better action than the one chosen by the human researcher 64% of the time.

AI models are still clearly subhuman at research taste (deciding which problems to pursue in the first place), but Anthropic points out that this capability can improve just like others once seen as inaccessible to AIs, like explaining why a joke is funny, and even if it “only” automates most of AI research and engineering, humans can focus on the remaining fraction of tasks to become much more productive.

Putting all this together, Anthropic argues that continued AI acceleration is highly likely, and full recursive self-improvement is strikingly plausible. (Co-founder Jack Clark goes even farther, arguing that fully autonomous AI R&D with no human in the loop is >60% likely by the end of 2028, just two and a half years away).

So what should we do about it? Anthropic recommends building global institutions with the power to coordinate the labs to pause or slow down AI research for a period of time until societal institutions and alignment research have caught up. They even say outright: “If it were possible to effectively slow the development of this technology to give ourselves more time to deal with its immense implications, we think that would likely be a good thing.” Demis Hassabis, CEO of Google DeepMind, is on record saying something similar.

There are two big trends of 2026 coming to a head here. One is the incredibly rapid improvement of frontier models, which in just a year have gone from slightly helpful with software engineering to able to complete hours-long tasks fully autonomously, solve open math problems, and show early signs of recursive self-improvement. If these signs continue, models will improve much faster. This would have absolutely monumental implications for practically every aspect of society. I’m optimistic that the world will be radically better, but there’s no doubt that the world will be radically different.

The other trend is the slow but steady awakening of people and institutions to the importance of AGI. Today you see anti-datacenter protests in town halls and voluntary government model evals, tomorrow you might see the full bipartisan force of Congress, or the UN, come together to globally pause AI as firmly as they paused nuclear power. If models improve too fast, we risk misalignment, loss of control, and other catastrophic scenarios. But if institutions have time to react, they may very well enact sweeping restrictions on the technology that prevent us from curing cancer, bringing abundance to everyone in the world, and conquering the stars. We are walking across a tightrope, and over the coming years we’ll have to balance very delicately.

Via @theojaffee\n\nQT @AnthropicAI: Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.

It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx

See 3 related tweets

@rohanpaul_ai: Anthropic just called for a global way to slow frontier AI because its own models may be approaching...
@minchoi: RT @minchoi: AI is starting to build AI.

Anthropic just published one of the clearest signals yet. ...

@alex_prompter: RT @alex_prompter: Read the actual Anthropic piece. It's wilder than the hype precisely because it's...

9. SakanaAILabs (Group Score: 115.1 | Individual: 49.3)

Cluster: 3 tweets | Engagement: 491 (Avg: 124) | Type: Tech

Building AI that Builds AI: Introducing the Sakana AI RSI Lab 🚀

https://t.co/AskX3J5oEJ

Today, we are announcing the Sakana AI Recursive Self-Improvement (RSI) Lab: a dedicated research group in Tokyo tasked with redesigning the AI development process itself using AI.

While the industry increasingly speculates about the theoretical potential of self-improving AI, we’ve spent the last two years actively laying the foundations to make it a reality:

▪ LLM²: AI models automating research to invent better preference optimization algorithms. ▪ Darwin Gödel Machine: Agents autonomously rewriting their own codebase to double software-engineering performance. ▪ ShinkaEvolve: Hyper-sample-efficient program evolution that builds novel loss functions for MoE models. ▪ ALE-Agent: Reinforcement agents outperforming hundreds of human experts via self-learning. ▪ Digital Red Queen: Open-ended adversarial coevolution laying the groundwork for RSI in cybersecurity. ▪ The AI Scientist: Towards end-to-end automation of AI research, recently published in Nature.

Now, we are unifying these breakthroughs. The Sakana AI RSI Lab is officially tasked with building open-ended, adaptive architectures that collectively self-improve.

Human intelligence did not emerge from limitless resources; it was forged through the open-ended, compounding process of evolution operating under strict constraints. We are applying this exact principle to AI.

We believe recursive self-improvement is achievable on modest, sample-efficient compute. It shouldn’t be a winner-take-all asset locked inside hyperscale clusters, but a democratized public good.

We’re scaling our team to execute this mission. We are looking for frontier scientists and engineers who are entirely unsatisfied with the brute-force status quo. If you are ready to break away from standard benchmarking and build the self-improving future in Japan, come build with us.

See 2 related tweets

@hardmaru: Today, we are officially launching the Sakana AI RSI Lab in Tokyo to build open-ended, adaptive AI s...
@SakanaAILabs: RT @hardmaru: Today, we are officially launching the Sakana AI RSI Lab in Tokyo to build open-ended,...

10. StockSavvyShay (Group Score: 114.3 | Individual: 26.0)

Cluster: 6 tweets | Engagement: 1112 (Avg: 665) | Type: Tech

$META is reportedly considering selling tens of billions of dollars in new shares to fund its AI buildout following$ GOOGL massive equity raise. https://t.co/xnfi4YQDwt

See 5 related tweets

@StockSavvyShay: $META is down nearly 7% after reportedly considering a stock offering worth tens of billions to fund...
@Techmeme: Sources: Meta is exploring a stock offering to raise tens of billions of dollars to fund AI capital ...
@zerohedge: Ringing The Bell: Meta Plunges On Report It May Sell "Tens Of Billions" In New Stock https://t.co/k6...
@Cointelegraph: 🚨 UPDATE: Meta shares fell more than 5% after reports the company is considering raising tens of bil...
@CNBC: Meta's stock sinks on report company could raise tens of billions of dollars to fund AI push https:/...

11. Techmeme (Group Score: 105.9 | Individual: 24.7)

Cluster: 5 tweets | Engagement: 13 (Avg: 11) | Type: Tech

OpenAI confirms it will follow President Trump's EO that asks AI companies to allow the US government to assess their models' capabilities before release (@michaelconsidi6 / CNBC)

(Visit Techmeme dot com for the link and full context!)

See 4 related tweets

@CNBC: OpenAI says it will comply with Trump's order requiring AI model reviews before release https://t.co...
@CNBC: Trump administration, OpenAI discussing possible government stake in the AI startup https://t.co/cEL...
@Cointelegraph: 🇺🇸 JUST IN: OpenAI and the Trump administration are reportedly discussing a potential U.S. governmen...
@FirstSquawk: OPENAI SAYS IT WILL COMPLY WITH TRUMP’S ORDER REQUIRING AI MODEL REVIEWS BEFORE RELEASE – CNBC...

12. chiefofautism (Group Score: 102.2 | Individual: 46.3)

Cluster: 3 tweets | Engagement: 7098 (Avg: 118) | Type: Tech

RT @trajektoriePL: Now we know why Peter Thiel packed his bags for Argentina.

Milei just submitted his AI legislative framework to Congress, where he proposes:

zero regulation on AI development,
a brand-new "non-human corporation" category for AI/robot-operated entities with limited liability -a low-tax regime with flexible governance rules.

The Dutch East India Company gave the world the limited liability company in 1602. Milei wants Argentina to do the same for autonomous AI agents in 2026.

See 2 related tweets

@ohryansbelt: Just after Peter Thiel announced he is fleeing the US to relocate to Argentina, Milei is pitching th...
@AISafetyMemes: Javier Milei plans to make Argentina a haven of unregulated "non-human corporations" run by AIs and ...

13. adrgrondin (Group Score: 96.0 | Individual: 28.2)

Cluster: 4 tweets | Engagement: 45 (Avg: 112) | Type: Tech

New @googlegemma Gemma 4 QAT model with a format optimized for mobile.

Only 1GB of footprint for E2B!

Doing my best to bring it to @LocallyAIApp soon.\n\nQT @osanseviero: Introducing Gemma 4 QAT 🤏

Quantization aware training to reduce models' precision while preserving quality
Introducing a new mobile quantization format that reduces memory footprint of E2B to 1GB
Q4 for all your favorite libraries ✨ https://t.co/pAL9WY9p4O

See 3 related tweets

@rseroter: RT @osanseviero: Introducing Gemma 4 QAT 🤏
Quantization aware training to reduce models' precisio...
@TeksEdge: 🚀 Great News Local AI got Faster! Google just dropped Gemma 4 QAT checkpoints! Grab new models from ...
@TeksEdge: Gemma 4 QAT's are now on LMStudio. Time to refresh models. Post speedups. I'm doing it now.\n\nQT @...

14. HedgieMarkets (Group Score: 94.4 | Individual: 39.1)

Cluster: 3 tweets | Engagement: 884 (Avg: 471) | Type: Tech

🦔SpaceX priced its IPO at $135 a share today.$ 75 billion raise, $1.75 trillion valuation, largest IPO in history. Goldman Sachs, the lead underwriter, projects SpaceX AI revenue will go from$ 3.2 billion to $322 billion by 2030. Morningstar says the company is worth$ 780 billion, less than half that. Fidelity dropped the buy-in from $500,000 to$ 2,000 and SpaceX reserved 30% for retail. S&P just confirmed it won't fast-track mega-cap IPOs into the index.

My Take SpaceX is a real company with a real business. Starlink prints revenue, the launch division has no serious US competitor, and the engineering is world class. None of that is in question. What's in question is whether a $1.75 trillion valuation built on a 100x AI revenue projection from the same bank collecting fees on the deal reflects reality or a sales target.

Goldman needs this IPO to be massive because Goldman gets paid when it's massive. So they wrote a forecast where xAI and X, neither of which has proven sustainable economics, somehow produce $322 billion in AI revenue by 2030. Morningstar looked at the same company and came up with half the valuation. Meanwhile Fidelity dropped the minimum to$ 2,000 and SpaceX carved out 30% for retail, which starts to look a lot like exit liquidity when you consider that the S&P 500 won't fast-track the stock into the index and the institutional demand backstop everyone assumed was coming isn't there. Anthropic just filed its S-1, OpenAI is next, and every AI valuation in the pipeline leans on the same kind of projections Goldman used here. If this one doesn't hold, it pulls the floor out from under all of them.

Hedgie🤗

See 2 related tweets

@shiri_shh: This could be the biggest IPO ever… and make Elon the first TRILLIONAIRE in history.

SpaceX is gear...

@wallstengine: From a $27M startup in 2002 to a reported$ 1.75 Trillion pre-IPO valuation in 2026.

The SpaceX valu...

15. WesRoth (Group Score: 90.6 | Individual: 33.2)

Cluster: 3 tweets | Engagement: 18 (Avg: 20) | Type: Tech

Agent Arena Current top models:

#1 OpenAI GPT-5.5 High #2 Claude Opus 4.7 Thinking #3 GLM-5.1 #4 Gemini 3.1 Pro #5 Kimi K2.6

Models are ranked using five signals: task success, steerability, error recovery, user praise vs. complaints, and tool hallucination. https://t.co/AdMJgY224p\n\nQT @arena: Introducing Agent Arena: real-world agentic evals at scale.

How do you evaluate agents doing actual work? We measure millions of live sessions where real users accomplish real tasks.

On Arena, models now get web search, filesystem, and terminal tools to complete complex workflows: writing code, creating slide deck, researching the web, building apps, and analyzing documents.

Every session produces rich signals. Users iterate with the agent turn-by-turn: approving, editing, correcting, praise or expressing frustration. The environment gives feedback too: shell errors, tool failures, recovery attempts, and more.

Our leaderboard measures each model's agentic performance using causal inference across five signals: task success, steerability, error recovery, user praise vs. complaint, and tool hallucination.

This leaderboard snapshot is built from 300K+ tasks, 2M+ tool calls, and 40M lines of code by agents.

Top labs in Agent Arena:

#1 @OpenAI: GPT-5.5 (High)
#2 @AnthropicAI: Claude-Opus-4.7 (Thinking)
#3 @Zai_org: GLM-5.1
#4 @GoogleDeepMind: Gemini-3.1-Pro
#5 @Kimi_Moonshot: Kimi-K2.6

More analysis in the thread, with the full technical blog below.

See 2 related tweets

@WesRoth: https://t.co/VaTlx3ZBkW introduced Agent Mode, a new way to test and compare agentic AI models direc...
@arena: RT @arena: Introducing Agent Arena: real-world agentic evals at scale.

How do you evaluate agents d...

16. rohanpaul_ai (Group Score: 89.9 | Individual: 31.5)

Cluster: 3 tweets | Engagement: 27 (Avg: 64) | Type: Tech

Anthropic’s new chemistry report has a genuinely wild result.

Claude Opus 4.7 is now competitive with dedicated NMR software, and the bigger story is that it can work the problem backwards, i.e. infer the molecule from the spectrum.”

NMR software is the chemist’s expert tool for turning molecular structures into predicted lab spectra.

So Opus 4.7 is no longer just “helping chemists read data” — it can work backward from NMR data and propose the molecule’s structure, a task the report says existing mainstream tools generally leave to human chemists.

Note, that Opus 4.7, a general-purpose model with no chemistry-specific fine-tuning.

Claude Opus 4.7 made the smallest hydrogen prediction errors and nearly matched MestReNova on carbon, meaning it can predict NMR signals about as well as specialist chemistry tools.

So AI now handle one of chemistry’s hidden bottlenecks: translating between a molecule, its spectral shadow, and the structure a chemist actually needs to trust.\n\nQT @AnthropicAI: New Anthropic Science Blog: Making Claude a chemist.

To manipulate a molecule, chemists first need to understand its structure. Their main tool is NMR spectroscopy.

We found Opus 4.7 matches—and on some tasks beats—dedicated NMR software. Read more: https://t.co/1jUvz7wdhV

See 2 related tweets

@MaziyarPanahi: Frontier models keep proving they can do hard science. Yesterday I ran OpenMed Agent on GPT-5.5; her...
@AnthropicAI: New Anthropic Science Blog: Making Claude a chemist.

To manipulate a molecule, chemists first need ...

17. PandaTalk8 (Group Score: 87.0 | Individual: 24.6)

Cluster: 5 tweets | Engagement: 1 (Avg: 102) | Type: Tech

期待 Kimi Code 新版本。

在汤泉搞封闭开发这个想法挺好，累了就去泡个澡释放一下。\n\nQT @real_kai42: 过去一个月是疯狂的一个月

大概一个月前，我下定决心重构 kimi-code，开始设计新的架构。我大概抱着电脑和便携屏在汤泉卷了两整天，花了几千刀的 token 去做架构分析、设计和验证，最终得到了一份我认为最优的架构方案。我觉得在 vibe 时代，架构变得更加重要了，一份好的架构能够在可控的范围内，让 Agent 肆意 coding，而不会打破东西

架构确定后，就开始冲刺实现。（过程中吵和推翻了无数次）
迅速组建了一个强大的 team，感恩兄弟们无条件的信任🙇‍♂️
迅速 onboarding 整个 team，🙇‍♂️ 再次感恩兄弟们
封闭开发了一段时间（🤣年轻的时候，觉得是糟粕，真到时候，发现是人类工程效率奇迹。你无法想象随时可以拉着全部人在白板前吵架的架构迭代速度）
虽然代码都是 vibe 的，但依旧逃不过 “代码质量正比于人类的注意力密度”。所以 agent 并不会替代所有程序员，只会让顶级的程序员生产力翻 20 倍，并淘汰其他程序员，且，集体主义 >>> 个人英雄主义。
一步一个坑的解决过程中遇到的问题。每一天都是最绝望的一天😭
开源后就病倒了，皮质醇分泌过度，影响免疫力
这一个月学的东西够我消化半年的
一周干了一整箱红牛，还得是生物燃料
🫥 也在 x 上消失了一个月

本来想写一些文章去总结过程中一些 insights 和 idea，但我本来就不擅长写长文，外加人脑自我保护让我迅速忘记了整个过程中的痛苦，并模糊了时间观念（冷知识，kimi-code 重构版开源其实才过了一周多，但在我的感性认知中，像是已经过了一个月）

等 kimi-code 陆续迭代到稳定，再去总结过程中的 lessons learned

See 4 related tweets

@GitHub_Daily: 让 AI Agent 自动化操作浏览器或抓数据，经常被各种反爬机制拦截，遇到验证码、人机验证直接卡死。

最近 BrowserAct 团队开源了一个 Skill，专为 AI Agent 设计的浏览器自...

@GitHub_Daily: 最近看到一个开源项目 Flipbook Canvas，挺有意思，能把每张 AI 生成的图变成一棵可以无限点击探索的知识树。

长按图片任意位置，系统会自动识别你点的内容，联网搜索相关资料，然后生成一张...

@xicilion: 这个数量级不对。正常高强度的话，一天 500 行就很多了，不可能有放空。同等强度， AI 辅助，一天 3000-5000 行很正常。真正的差异还在于一天 500 行不可能持续几天，因为很快就会进入...
@GitHub_Daily: 微信读书用久后，积累不少笔记和划线，想导出整理一下，发现没有提供很方便的方式。

有位开发者，便开源一个工具 readNeo，给微信读书做了一个独立的数据面板。

接入官方的 Skill API，直观...

18. secureainow (Group Score: 84.5 | Individual: 42.5)

Cluster: 4 tweets | Engagement: 730 (Avg: 40) | Type: Tech

RT @MittRomney: Our highest and most urgent national priority should be AI safeguards. The risks of AI weapons, pathogens, mass unemployment, surveillance, and even extinction must not continue to be largely ignored.

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@peterwildeford: 👀 https://t.co/KAXEU06EkJ\n\nQT @MittRomney: Our highest and most urgent national priority should be...
@Miles_Brundage: Whoa\n\nQT @MittRomney: Our highest and most urgent national priority should be AI safeguards. The r...
@firstadopter: Come on man\n\nQT @MittRomney: Our highest and most urgent national priority should be AI safeguards...

19. steipete (Group Score: 83.7 | Individual: 28.0)

Cluster: 4 tweets | Engagement: 1228 (Avg: 273) | Type: Tech

RT @OpenAIDevs: More of the iOS app loop, now inside Codex.

The Build iOS Apps plugin lets Codex view and test your iOS app in the in-app browser, open SwiftUI previews, and hot reload edits without leaving Codex. https://t.co/SksapiJFjY

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@Dimillian: Ice Cubes will forever be alive at this point\n\nQT @OpenAIDevs: More of the iOS app loop, now insid...
@WesRoth: OpenAI added more of the iOS app development loop directly inside Codex through the Build iOS Apps p...
@Dimillian: RT @PaulSolt: Codex is an iOS APP Development powerhouse.

... Close Xcode and get to work with you...

20. Reuters (Group Score: 83.2 | Individual: 20.8)

Cluster: 5 tweets | Engagement: 139 (Avg: 98) | Type: Tech

Nvidia CEO says robotics is South Korea's next big sector, points to 'some suprises' https://t.co/89drbfvRIS https://t.co/89drbfvRIS

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@Reuters: Nvidia CEO Jensen Huang said that he sees robotics as the next major sector in South Korea https://t...
@FirstSquawk: NVIDIA CEO Jensen Huang sees significant opportunities to deploy robotics technology in Korean indus...
@FirstSquawk: Robotics is poised to be Korea’s next key industry, according to NVIDIA CEO Jensen Huang...
@ReutersBiz: Nvidia CEO Jensen Huang said that he sees robotics as the next major sector in South Korea. More her...