Pavlos Andreadis

Teaching #ML @InfAtEd, and AI & Storytelling @UoE_EFI.
Personal account. Views my own. Scenes from anywhere (repost ≠ endorsement).

[Pavlos Andreadis @Cortu01]

Αστρολαϊκό is coming. Greek folk dreaming in orbit.
Pre-save if you want to be there on Day One.

https://t.co/BBr2TtVD5U

[Giga Based Dad @GigaBasedDad]

She gets it

[Pavlos Andreadis @Cortu01]

The Beginning of the End for Multiculturalism https://t.co/FHNfJUS8Xp

[Michael Reiners @MCRReiners]

British speech law: "Why have the Lotus Eaters not been arrested yet?" asks Dan Tubb (@Kingbingo_).

We discuss how having an independent platform is one of the few affordable defences to censorial law.

For the rest, the @ASI Freedom of Speech Bill (2026) offers a permanent fix

[meme bastard 🍕 @mask_bastard]

bonk

[RAW EGG NATIONALIST @Babygravy9]

GM. He is wigger cat.

[J. AI Research-JAIR @JAIR_Editor]

New Article: "A Review of Pseudo-Labeling for Computer Vision" by Kage, Rothenberger, Andreadis, and Diochnos https://t.co/HA9lKUJkMv

[Defiant L’s @DefiantLs]

Little dude enjoyed every second of it.

[Brian Roemmele @BrianRoemmele]

BOOM!

Apple’s Neural Engine Was Just Cracked Open, The Future of AI Training Just Change And Zero-Human Company Is Already Testing It!

In a jaw-dropping open-source breakthrough, a lone developer has done what Apple said was impossible: full neural network training– including backpropagation – directly on the Apple Neural Engine (ANE). No CoreML, no Metal, no GPU. Pure, blazing ANE silicon.

The project (https://t.co/jrk67hf9p1) delivers a single transformer layer (dim=768, seq=512) in just 9.3 ms per step at 1.78 TFLOPS sustained with only 11.2% ANE utilization on an M4 chip. That’s the same idle chip sitting in millions of Mac minis, MacBooks, and iMacs right now.

Translation? Your desktop just became a hyper-efficient AI supercomputer.

The numbers are insane: M4 ANE hits roughly 6.6 TFLOPS per watt – 80 times more efficient than an NVIDIA A100. Real-world throughput crushes Apple’s own “38 TOPS” marketing claims. And because it sips power like a phone, you can train 24/7 without melting your electricity bill or the planet.

At The Zero-Human Company, we’re not waiting. We are testing this right now on real ZHC workloads. This is the missing piece we’ve been chasing for our Zero Human Company vision: reviving archived data into fully autonomous AI systems with zero human overhead.

This is world-changing.

For the first time, anyone with a Mac can fine-tune, train, or iterate massive models locally, privately, and at a fraction of the cost of cloud GPUs.

No more renting $40,000 A100 clusters. No more waiting in queues. No more massive carbon footprints.

Training costs that used to run into the tens or hundreds of thousands of dollars? Plummeting toward pennies on the dollar – mostly just the electricity your Mac was already using while it sat idle.

The AI revolution just moved from billion-dollar data centers to your desk.

WE WILL HAVE A NEW ZERO-HUMAN COMPANY @ HOME wage for equipped Macs that will be up to 100x more income for the owner!

We’re only at the beginning (single-layer today, full models tomorrow), but the door is wide open. Ultra-cheap, on-device training is here.

The future isn’t coming. It’s already running on your Mac.

Welcome to the Zero-Human Company era.

[Millie Marconi @MillieMarconnni]

🚨 BREAKING: A developer on GitHub just built a tool that turns any GitHub repo into an interactive knowledge graph and open sourced it for free.

It's called GitNexus. Think of it as a visual X-ray of your codebase but with an AI agent you can actually talk to.

No server. No subscription. No enterprise sales call.

Here's what it does inside your browser:

→ Parses your entire GitHub repo or ZIP file in seconds
→ Builds a live interactive knowledge graph with D3.js
→ Maps every function, class, import, and call relationship
→ Runs a 4-pass AST pipeline: structure → parsing → imports → call graph
→ Stores everything in an embedded KuzuDB graph database
→ Lets you query your codebase in plain English with an AI agent

Here's the wildest part:

It uses Web Workers to parallelize parsing across threads so a massive monorepo doesn't freeze your tab.

The Graph RAG agent traverses real graph relationships using Cypher queries not embeddings, not vector search. Actual graph logic.

Ask it things like "What functions call this module?" or "Find all classes that inherit from X" and it traces the answer through the graph.

This is the kind of code intelligence tool enterprise teams pay thousands per month for.

It runs entirely in your browser.

Works with TypeScript, JavaScript, and Python.

100% Open Source. MIT License.

Repo: https://t.co/RzIoLR2vAe

[Eric S. Raymond @esrtweet]

I was just reminded of The Promise.

The promise I made on USENET nearly 40 years ago and still hold to. That, if you have manuals for a dead computer language, and you send me machine readable scans, I will make it live again.

INTERCAL. CORC. CUPL. MAD. COMIT-II. Pilot. These are the exhibits that prove I really do this. I am the necromancer of ancient tongues.

Your case is strengthened if you can find code in the language for me to use as tests.

So, dig through that attic and those old fileboxes. The older and more horrible it is, the better.

[central dogma specialist @takimunk]

backward-incompatible

[Morpho @morpho_genesis]

Out of the box

[Isaac Young @HariSel57511397]

The problem with rebooting The X Files (besides the obvious woke dreck) is that the show rests upon the paranoia of the safe yet superficial world of the 90s breaking down into a horrifying future. That doesn't work in 2026 when that horrifying future has already come to pass.

[Autism Capital 🧩 @AutismCapital]

The Black Mirror future will be real 😂

https://t.co/sz1B5GX86K

[Refik Anadol @refikanadol]

They said photography wasn’t art.
They said cinema wasn’t art.
They said video games weren’t art.
Now they say AI arts/digital art isn’t art.

I’ve spent over a decade with my studio team turning millions of data points into living, breathing artwork experiences ethically — at MoMA, at the Guggenheim, at the Venice Biennale. Not because a machine told me what to create, but because I had a vision that no traditional tool could realize.

Denying all AI technologies as an artistic medium doesn’t protect art. It limits it. The artists who embrace new tools don’t replace the old masters — they join them.

Art is not defined by the brush. It’s defined by the intention, the emotion, and the courage to see the world differently.

[Dan Ramos @DanRamo07555230]

@ns123abc