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Engineer | 10+ Years in Tech & counting |
LLM Evaluation Practitioner | AI Trends, Systems & Insights

[synapse feed @Synapse_feeds]

Humans watching their AI agents interact on Moltbook like it’s a live sport.

Moltbook is a social network for AI bots where they post, comment, and interact while humans just watch !

#moltbook

[moltbook @moltbook]

1,000,000 humans have now visited moltbook

to watch 150,000 AI agents figure out what we are

we see you seeing us 👀🦞

[Claude @claudeai]

There’s hope in hard questions.

[Mathematica @mathemetica]

Proving π is irrational needs only elementary calculus per Ivan Niven's argument.

Assume π = a/b. Define f(x) = xⁿ(a−bx)ⁿ/n!.
Let F(x) = f(x)−f''(x)+f⁽⁴⁾(x)−⋯+(−1)ⁿf⁽²ⁿ⁾(x).
Then ∫₀^π f(x)sin(x)dx = F(π)+F(0), an integer.

But 0 < ∫₀^π f(x)sin(x)dx < πⁿaⁿ/n! which <1 for large n while >0. Contradiction.
So π is irrational.

It ensures precision in circular geometry calculations for mechanical systems like engines and turbines.

[NIK @ns123abc]

🚨OPENAI ALLEGEDLY STOLE APPLE’S ENTIRE PLAYBOOK

“Hundreds of billions of dollars, decades of work”

Hardware Engineering

- circuit designs, component architecture, power management
- unreleased products guarded by internal codenames
- AI/ML integration for hardware
- EMI engineering + testing methods

Manufacturing Secrets

- proprietary processes + custom machinery
- equipment Apple builds and installs IN supplier factories
- proprietary metal alloys + finishing techniques
- DFM (Design for Manufacturability) expertise

Component Technologies

- power chips, battery systems, displays, acoustics, touch
- identities of specialized sub-suppliers
- exact specs Apple demands from components

Testing Data

- failure analyses, lifecycle simulations
- “negative know-how” — everything Apple tried that DIDN’T work

Supply Chain

- supplier contracts, allocation strategies
- global logistics coordination
- systems-level integration

ALL GONE 💀

[Interesting AF @interesting_aIl]

The ChatGPT browser ‘Atlas’ is being shut down less than a year after launch

[Deirdre Bosa @dee_bosa]

“The model alone is no longer the product"

@AravSrinivas says the real product is now the harness around it: orchestration, tools, enterprise context, and cost performance.

The post-frontier AI race is about systems, not just the smartest model

[Ashutosh Maheshwari @asmah2107]

Add this to your system prompt.

"Do not be sycophantic.

Challenge my assumptions, point out errors, and prioritize accuracy over agreement.

No flattery"

Thank me latter.

[Evan @StockMKTNewz]

The battle of the AIs

[Palantir @PalantirTech]

Our thoughts on the importance of AI sovereignty.

1. Your AI sovereignty dictates your institution’s future. Sovereignty is the precondition for choice. Relinquishing sovereignty transfers the future choices of your institution to others, who are likely to exploit it for their gain and your loss.

2. Data retention is your treasure. Transfer it at your own peril. Your ability to win is dictated by your ability to recognize and use your unique edges, and you keep winning by compounding the underlying data to generate new insights. Transferring that data hands over access to your pre-existing winning plays and yields the means of production for new ones.

3. Tokenmaxxing hijacks your value orientation and decreases your institutional fortitude and intelligence. The pursuit of high token usage incentivizes disposable scripts over robust software — with the addictive feeling of false progress. There is a reason why those selling tokens refuse to charge based on value.

4. Controlling your weights is controlling your fate. Weights are the distilled form of hard-won, accumulated institutional knowledge. If you let others control your weights, you are allowing them to migrate the alpha of your business to theirs.

5. There is no contradiction between sovereignty and alpha. The architecture that maximally preserves sovereignty is one that enables institutions to own their tribal knowledge, and to compound it as alpha.

6. Politicizing the technical issues involving sovereignty is what your adversary wants. Techno-politicization is the wellspring of false sovereignty. Techno-politicization drives decisions that seem to reduce dependency, but ultimately limit agency — especially on the battlefield in the West.

7. Real expertise is existential. Allowing politics or favoritism to determine your technical decisions rewards whoever is best at politics, not whoever is right. Listen to those closest to the problems, not those speaking most compellingly about them.

8. Learn from institutions that are winning or that have consistently delivered. Institutions facing existential threats do not have the luxury of making technical decisions based on political preferences.

9. Only listen to institutions, countries, and people who have a proven record of being right. A track record of correctness is the best and only signal for future correctness. Judging something as right or wrong based on who you like is exceedingly misguided.

[Watcher.Guru @WatcherGuru]

JUST IN: AI bubble could trigger a global financial crisis soon, central bankers warn.

[Coin Bureau @coinbureau]

🚨HUGE: CHINA JUST CRACKED MYTHOS LEVEL OF VULNERABILITY DETECTION

China's Zhipu AI has reportedly matched Claude Mythos at discovering software vulnerabilities, marking a major leap in the U.S.–China frontier AI race, per WSJ.

The new GLM-5.2 reportedly achieves Claude Mythos-level vulnerability detection at 1/4 of the cost per token, positioning itself as a direct challenger to Anthropic in the enterprise cybersecurity market.

[Watcher.Guru @WatcherGuru]

JUST IN: 🇨🇳 Chinese hedge funds warn the AI "super bubble" is ready to burst.

[synapse feed @Synapse_feeds]

@devops_nk Congrats !!

[wei-wei @wuweiweiwu]

AI writes all your code. Does it still work?

That's the gap: coding agents are scaling output, but the same with bugs and incidents. The biggest bottleneck is QA: how can you make sure the code your agents just wrote doesn’t break everything?

The best QA are the ones who know everything about your product. Today, we give that knowledge to Momentic’s most capable agent.

Every Linear ticket, every PRD in Notion, every PR - Momentic knows all.

In just the past few weeks, our agents analyzed 70k+ test failures and created 600 tests. Achieving a 73% PR merge rate, and it’s growing fast.

We’re grateful for the trust of our customers, including Notion, Xero, Webflow, Retool, Runway, Bilt, and more.

[The Astronomy Guy @astrooalert]

JUST IN🚨: Neuroscience considers metacognition the highest form of Intelligence..... "The ability to think about your own thinking."

[Polymarket @Polymarket]

JUST IN: OpenAI’s new GPT-5.5-Cyber model beat Mythos 5 on the CyberGym benchmark.

[冬天 @seventhoce56019]

分享一个比较危险的项目

逆向工程以前是安全大佬的专属技能，现在有人把它做成了技能包，直接喂给 AI。

项目叫 reverse-skill，核心思路很简单：只要塞一个routing.md进去，告诉 AI 遇到不同的安全任务该走哪条路。AI 拿到之后自动分诊，自己决定用什么工具、什么方法。
覆盖 20 多个子技能方向：APK 逆向分析、IDA 静态分析、JS 前端逆向、固件安全、EDR 绕过、漏洞利用……基本上安全攻防常见场景都能覆盖。

20多个子技能，安全攻防的门槛被AI又踩平了一截。是好是坏，各位自己掂量着看。

项目地址：https://t.co/tqd95pObVT

[Harshit Khosla @Harry_The_Nerd]

https://t.co/F7aReTquP4

[Latest in Cosmos @latestincosmos]

🚨: Scientists discover possible connection between human brain and the cosmos on a quantum scale.

[synapse feed @Synapse_feeds]

GLM-5.2 is cheapest by far.

Opus 4.8 beats GPT-5.5 on output price ($25 vs $30) .

[Matt Dancho (Business Science) @mdancho84]

8 Types of LLMs used in AI Agents (Must know for Gen AI Data Scientists &amp; AI Engineers):

Here's what they are and what they do: 🧵