Paolo Schiattarella

[GitHub Projects Community @GithubProjects]

Litho generates C4 architecture documentation directly from source code using AI, keeping docs synced as your codebase evolves.

- Automatically produces context, container, component, and code-level diagrams
- Built in Rust for high-performance codebase analysis
- Generates professional Wiki-style documentation for any repository
- Available as a crate on https://t.co/MZZZd9J2EO

[MathType @MathType]

The Navier-Stokes Equations define the complex physics of fluid dynamics: by balancing acceleration against pressure, gravity, and friction, this framework models how liquids and gases move through space.

#Math #Mathematics #Physics #FluidDynamics #MathType #DidYouKnow #STEM

[Physics In History @PhysInHistory]

“I think I can safely say that nobody understands quantum mechanics.”

- Richard Feynman (1964 Cornell Lecture)

[elvis @omarsar0]

This is one of the most interesting papers on self-improving agents for this year.

(bookmark this one)

Most self-improving AI systems hit the same wall: the mechanism that generates improvements is fixed and can't improve itself.

This new work from Meta and collaborators breaks through this limitation.

They introduce Hyperagents, self-referential agents where the self-improvement process itself is editable.

The DGM-Hyperagent combines a task agent and a meta agent into a single modifiable program, enabling metacognitive self-modification.

It autonomously discovers innovations like persistent memory and performance tracking, and these meta-improvements transfer across domains and compound across runs.

Why does it matter?

- On paper review, DGM-H improved from 0.0 to 0.710 test accuracy.

- On robotics reward design, it went from 0.060 to 0.372.

- Transfer hyperagents achieved 0.630 on Olympiad-level math grading in a domain they were never trained on.

This is a step toward AI systems that don't just find better solutions but continuously improve how they search for improvements.

Paper: https://t.co/Q0f7zWhNMD

Learn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX

[Archaeo - Histories @archeohistories]

Cleopatra ascended the throne at the age of 17 and died at the age of 39. She spoke 9 languages. She knew the language of Ancient Egypt and had learned to read hieroglyphics, a unique case in her dynasty. Apart from this, she knew Greek and the languages ​​of the Parthians, Hebrews, Medes, Troglodytes, Syrians, Ethiopians and Arabs. With this knowledge, any book in the world was open to her. In addition to languages, she studied geography, history, astronomy, international diplomacy, mathematics, alchemy, medicine, zoology, economics, and other disciplines. She tried to access all the knowledge of her time.

Cleopatra spent a lot of time in a kind of ancient laboratory. She wrote some works related to herbs and cosmetics. Unfortunately, all her books were destroyed in the fire of the great Library of Alexandria in 391 AD. The famous physicist Galen studied her work, and was able to transcribe some of the recipes devised by Cleopatra. One of these remedies, which Galen also recommended to her patients, was a special cream that could help bald men regain their hair. Cleopatra's books also included beauty tips, but none of them have come down to us.

The queen of Egypt was also interested in herbal healing, and thanks to her knowledge of languages ​​she had access to numerous papyri that are lost today. Her influence on the sciences and medicine was well known in the early centuries of Christianity. She, without a doubt, is a unique figure in the history of humanity.

📷 © Elizabeth Taylor in Cleopatra (1963) by Joseph L. Mankiewicz/Universal History Archive/Universal Images Group via Getty Images

#archaeohistories

[Y Combinator @ycombinator]

.@envariant is building an AI interpretability SDK to enable foundation model builders to analyze, steer, and control their model's behaviors.

Congrats on the launch, Varun!

https://t.co/O25NZDJpow

[Lukasz Olejnik @lukOlejnik]

Anthropic published a blog post and playbook on how Claude Code handles COBOL. This isn’t about fixing old code or keeping it on a mainframe. The process has two stages: first, AI automates the analysis – mapping dependencies, documenting workflows, identifying risks. Work that used to take consultants months. Then it incrementally migrates the code to Java or Python, with the option to host it on any cloud provider. IBM stock dropped 13%. The reason is simple: IBM makes money because COBOL is hard. The company keeps clients on its mainframes, sells modernization through watsonx, but makes sure the end result still runs on its hardware. The CFO boasted about a 3-4x revenue multiplier from each mainframe client. Anthropic isn’t offering modernization – it’s offering an escape from the entire ecosystem. Accenture and Cognizant fell too. The whole legacy systems consulting sector got the signal that AI can replace “armies of consultants.”
Anthropic wrote that understanding the code used to cost more than rewriting it. IBM would prefer that sentence had never been said publicly. 95% of ATM transactions in the US run on COBOL. No bank CTO will make a migration decision based on a blog post – but every board member will read it.

[Julian Goldie SEO @JulianGoldieSEO]

Agent Zero might be the most underrated AI agent on the internet right now.

It’s free.

It runs locally.

It builds tools, writes code, spawns sub-agents, and actually finishes tasks.

It built better apps.

It handled multiple tasks at once.

It didn’t break mid-workflow.

If you’re serious about AI automation, you need to test this.

Link in the comments.

[Yuchen Jin @Yuchenj_UW]

The coding LLM war escalated after OpenAI acquired the creator of OpenClaw.

I noticed Anthropic and Google blocked OpenCode from using their Pro plan subscriptions, so I really can use Codex and open-source models there.

Only OpenAI seems generous here.

[Saurav @ravsau]

@Yuchenj_UW Feels like OpenAI is buying goodwill and pulling ecosystem gravity toward Codex. Smart long-term move.

And honestly understandable why other providers would restrict OpenClaw access.

[METR @METR_Evals]

We estimate that Claude Opus 4.6 has a 50%-time-horizon of around 14.5 hours (95% CI of 6 hrs to 98 hrs) on software tasks. While this is the highest point estimate we’ve reported, this measurement is extremely noisy because our current task suite is nearly saturated.

[TechCrunch @TechCrunch]

Peak XV raises $1.3B, doubles down on AI as global VC rivalry in India heats up https://t.co/zTGLZAMqqW

[Paolo Schiattarella @schpao]

@Its_BS @elonmusk Who are you?

[Qwen @Alibaba_Qwen]

🖼️ AI Slides Just Got a Brain Upgrade!
🎯Meet Qwen AI Slides — your personal presentation designer that actually thinks. Powered by Qwen3 Agent + Qwen-Image 2.0, it turns chaos into clarity, beautifully.
✅ Type a simple idea, throw in a wall of text, or upload a document — it just works
✅ Search Agent researches, organizes & builds the story structure for you
✅ Qwen-Image 2.0 directly generates each slide as a polished visual — text, layout, color scheme & graphics, all in one shotStop designing slides. Start designing impact. 💡✨
Try it now: https://t.co/R1P4UxCAD3

[Deedy @deedydas]

Anthropic is at $14B run rate revenue, the fastest growing software business of all time.

– Claude Code run rate is $2.5B in <1yr
– $0 -> $100M -> $1B -> $14B in 3yrs
– $100k+ customers 7x'd last year
– $1M+ customers 40x'd last year, 500+
– 4% of Github commits by CC

Insane.

[Ethan Mollick @emollick]

Had Claude Code build a little plugin that visualizes the work Claude Code is doing as agents working in an office, with agents doing work and passing information to each other. New subagents are hired, they acquire skills, and they turn in completed work. Fun start.

[🚨 AI News | TestingCatalog @testingcatalog]

Google is working on integrating Agentflow into Gemini for Business.

Agentflow is an automation builder in Google Workspace that allows you to build agentic pipelines, and it seems like they will become more integrated into Gemini Agent builder in the future.

Consolidation 👀

[Archaeo - Histories @archeohistories]

A modern reconstruction of a Saka (Scythian) warrior, featuring a pointed cap inspired by Reliefs from Pasargadae (Persepolis, 550 BC).

© The Archaeologist

#archaeohistories

[Dmitrii Kovanikov @ChShersh]

After 8 years of Haskell, 2 years of OCaml, 2.5 years of C++ and 45 minutes of Go, I present you the ultimate Design Pattern.

The Context Pattern

FP, OOP, Procedural and Declarative Programming combined to create The Last and Only design pattern you ever need.

A single record containing all your dependencies that you pass to every function explicitly.

No more inheritance.
No more classes and methods.
No more Dependency Injection.
No more singleton pattern.
No more private/public.
Mocks have never been easier.

This is the only pattern you need to structure EVERY SINGLE APP NO MATTER THE INDUSTRY (microservice, compiler, spaceship system).

[Bitcoin @Bitcoin]

Snatching a head of state and stuffing him in a potato bag is a very clever budget neutral way to increase a strategic #Bitcoin reserve.