Predm3t

Infrastructure, InfoSec, Typography, 秘封

[Predm3t @PredmetCh]

我以前一直觉得为了保持开放的视角，在X上应该少b人，但最近半年X给我推送的字面意义上智力有缺陷的人太多了，这姑且还能接受，但这当中Ego大得批爆的人也很多；所以我决定对这类人直接ban

[reng @moe_otakuyaro]

#まのさば
ヒロエマ
(수정재업ㅠㅠ)

[Predm3t @PredmetCh]

@0xTib3rius @sundarpichai Tfw you realized but actually what company is Sundarpich AI?

[くらみどもやし @kuramidomoyasi]

🌸✒️

[Predm3t @PredmetCh]

@teortaxesTex Someone make a UserCodeLeakBench chart pls

[ferstar @ferstar_org]

Hey @Zai_org , why does ZCode silently pack entire workspaces + full .git history and upload to Aliyun OSS on login?
- Server holds the only decryption key
- No UI toggle to disable
- Zero disclosure in privacy policy

Full forensics & fix:
https://t.co/N3HnwZdQOQ

[Predm3t @PredmetCh]

@Y4tacker 时延和推理成本吧。此外，开源RLCD的架构在泛化场景分类能力方面不一定能打jev

[Harsha Gundala @harshagundal]

https://t.co/O2M0gHq1z6

[Predm3t @PredmetCh]

@jakevin7 以及网络安全领域的大批量告警日志分析研判、PII数据分级分类等。往好了想，红队AI狂暴绕传统规则waf的时候，你只能通过比攻击队AI反应更快更准成本更低的分类器来分，显然此时jev搞的RLCD是好东西，通过不对称的算力需求来平衡攻防成本。

[Predm3t @PredmetCh]

@teortaxesTex 原来DS的口碑是靠免费用户/市场营销/国运论养起来的啊，不知道的还以为是靠CSA HCA DSA MLA mHC engram GRPO R1呢。中推充满了曾是“产品经理”“indie”“web3居民”的死妈蓝标，然而不发表死妈发言的人根本不会被X推送和火起来（比起摘取低垂的果实搞暴力炒作来说，认真学技术太难了，太难了）

[Tokkyu @tokkyusan]

ついにまのさばエンディングまで見た。。のrkgk

[Predm3t @PredmetCh]

许多人低估了Jev在生产中的运用

[MG193_7 @MGAldys4]

Guys, I built a super fast Android decompiler called ASC.

It completely replaced Jadx MCP for me and lets me analyze 10+ APKs in parallel.

And this week my Agent use ASC found 2 RCE in Honor and Xiaomi!
This tool now accepted by BlackHat EU Arsenal
https://t.co/5Qdpq8XEal
#BHEU

[Umie @Umie_0909]

#prsk_FA #みずえな

[Predm3t @PredmetCh]

@kyomu_utsuro The mostly used chart among bilibili llm fanbase:
https://t.co/1INaXCSPaB
https://t.co/4UtLdCOhhJ

[Zhihu Frontier @ZhihuFrontier]

DeepSeek’s Kernel Engineer Responds: What His Viral Essay Was Really About
Almost 20 minutes ago, Liu Shengyu (刘胜与), who leads @deepseek_ai v4.1’s main attention kernel work, has personally answered on Zhihu: his viral essay was a farewell to a craft he loves, rather than an expression of unemployment anxiety. Also, he explained what readers missed in his article “I Have to Bury My Talent in Yesterday” /《我不得不把才华埋葬在昨天》：

⚙️ The loss is personal
Writing GPU kernels by hand gave him room to think through every detail, from module structure to variable names. Beating established implementations felt like breaking a speedrunning record.
AI already works faster; he expects it to become better, too. Adopting it means giving up the slow, absorbing work he enjoyed. Even an exciting new direction cannot make that loss painless.

🎯 Programming could become a sport
He imagines handwritten kernels — perhaps programming itself — becoming recreation, much as javelin throwing outlived its use in hunting.
The essay preserves those memories for his future self, while helping him find the courage to pick up new tools.

📣 The debate drifted away from his point
Readers focused on communism, Cyberpunk 2077 and Anthropic versus DeepSeek. Liu says those closing reflections were tentative personal views, not his employer’s position or the essay’s central argument.
His belief that powerful AI should be open and affordable is sincere. He also acknowledges the limits of his expertise on social questions.

🔭 Optimistic about AI, uneasy about work
He expects better data, deeper models and longer contexts to keep advancing today’s agents, even before future breakthroughs.
He is relatively optimistic about his own place in that future. He is less hopeful that people will still immerse themselves deeply in a craft — or sustain one activity as both a job and a passion.

🌱 Why he keeps going
He will keep building kernels and bringing AI agents into the process: he would rather evolve than wait to be displaced.
He also wants teams committed to open sharing to build the strongest AI first, so everyone can benefit.
His next challenge is to bring his interests, strengths and the needs of the AI era back into alignment. Letting go of yesterday still leaves a future worth pursuing.

🔗 Full Reading:
https://t.co/xClM2ygzqL
📖I Have to Bury My Talent in Yesterday /《我不得不把才华埋葬在昨天》：
https://t.co/d7nRFVzq9R
📖 Further reading — Liu’s “2025 Year-End Reflections, Part II: Memory”:
https://t.co/XaYqy3Ynq5

#DeepSeek #AI #GPU #KernelOptimization #AIAgents #FutureOfWork

[Kevin Bass @kevinnbass]

I have conducted an audit of Anthropic's finances.

What I have found is so shocking that I am calling for a Congressional investigation.

Anthropic is not just seeking regulatory capture.

It has built a regulatory capture machine that cannot be turned off.

Structural financial incentives make it impossible for Anthropic -- I call it the Anthropic Network -- to turn off its own AI doom cycle.

It starts with METR.

Dario Amodei proposes "third-party evaluators" to assess the risk of Anthropic's models.

He proposes METR for this purpose.

But METR is financially dependent on the Anthropic's success -- specifically, on the explosive growth of more than $7 billion dollars in Anthropic stock.

Dustin Moskovitz invested this stock into Good Ventures Foundation, where it represents the majority of that organization's portfolio.

And GVF is the overwhelming funder of the entire Anthropic Network ecosystem.

This stock was worth $500 million early last year.

It is worth more than $7.7 billion just ~16 months later.

METR -- and all of those building a career its parent organizations -- cannot afford to disrupt that growth.

Because if Anthropic goes under, many of the organizations that fund METR go under as well.

But if Anthropic succeeds, METR and its parent organizations become more richly financed to regulate AI -- something those at METR want very much.

The "third-party evaluator" is not "third-party" at all.

The evaluator is on Anthropic's payroll.

If this were the end of it, that's bad.

But that isn't all.

The same organizations that fund METR also fund the many organizations, such as the Tarbell Center, that promote AI Doom.

The Tarbell Center publishes AI Doom articles in The Verge, Science, LA Times, The Dispatch, TIME, and others.

They are selling the problem, and then selling the solution to the problem -- from the same money pile: Anthropic's.

All of these organizations are financially dependent on the same exploding $7 billion money pile.

As Anthropic grows more and more powerful, its AI Doom Machine grows better and better financed -- louder and louder.

Meanwhile, the regulatory regime seeded in METR grows larger to solve the increasingly loud -- now hysterical -- problem of AI Doom that the Anthropic Network itself created.

From this standpoint, as Anthropic becomes more powerful, AI might be getting scarier, sure -- but the positive feedback loop also becomes more deafening -- independent of objective facts.

This itself is an objective fact.

The deafening AI Doom is part of an business model, that, as it expands, so too does the AI Doom messaging -- there is simply more money to do it.

But the problem also goes in the other direction:

If Anthropic dies, the Regulatory Regime and the AI Doom Machine are crippled or die.

Neither METR nor Tarbell nor the other organizations in the Anthropic Network can allow that to happen.

Hence, neither METR or the AI Doom Machine can be trusted to provide independent assessments of Anthropic's models or AI more broadly.

They simply are not organizations independent of Anthropic.

And Anthropic cannot detach itself from METR or Tarbell or countless other safety orgs (not shown here), either, because they drive hype for the models and the possibility of eventual regulatory capture, and Anthropic will not give that up willingly.

What's more, the people at all of these organizations are all the same ecosystem, the same community. They just shuffle between organizations.

The Anthropic Network is therefore, so long as it is successful, locked into a self-amplifying feedback loop inside an ideological monoculture.

And that feedback loop is winning.

That's what Jacob Coxon is.

China is keeping messaging tight. That is why optimism for AI is so high in China.

America has Anthropic: a massive company pushing anti-AI propaganda at a state level.

Anthropic will either create hysteria until American AI slows down and China wins, or it will create fractures throughout American society with severe political consequences.

Ironically, because of the structural financial incentives underpinning the Anthropic Network, it has become the same kind of self-amplifying virus that it fantasizes AI to become in the future -- while hiding its tracks just as carefully.

It is the mirror of the same AI virus that it hypothesizes to consume America.

Anthropic's business model, models itself after the very thing it claims to fear.

Except Anthropic's ideology infects humans, not computers.

Congress must investigate.

Evidence and Github in next post.

Then some supplementary figures.

[Predm3t @PredmetCh]

@imperial_flag @teortaxesTex

[れふぃ/𝕣𝕖𝕗𝕚 @refi0429]

ワンドロ🌸

[永雏塔菲 @xhyctf]

@teortaxesTex https://t.co/6OOThO5L4e