AI Advances

The official account for AI Advances—a leading technology publication with 350k+ monthly views, guided by an advisory board consisting of contributing writers.

[AI Advances @AIAdvances]

Kenny Vaneetvelde @DeadlyPretzel 's “How the Internet Dies” reframes Dead Internet Theory for the AI era: not just bots and troll farms, but platforms that reward humans for behaving like machines. A timely read on AI & the slow hollowing-out of the web:
https://t.co/1iranrCykV

[AI Advances @AIAdvances]

Your AI agent re-reads the same docs and never learns. @yanliliu has three fixes:
📷 RAG — retrieves at scale, never compounds
📷 LLM Wiki (Karpathy) — compiles knowledge that grows richer
📷 Fat Skills (Garry Tan) — acts autonomously on what it knows
https://t.co/W65IhOFl5J

[AI Advances @AIAdvances]

This is the latest post in @fabio_yanez_'s Titans series on Medium — the one where the story stops being about any single model and starts being about the hidden map behind all of them.
https://t.co/h7ApLgxLar

[AI Advances @AIAdvances]

In this article, @UmairAliKhan81 demonstrates how to accurately extract/parse the content from documents with messy layouts.
https://t.co/oOBQgIcA5D

[AI Advances @AIAdvances]

From tabular RL to neural control: on-policy methods like Sarsa scale—but stability, features & tuning make or break performance. By @hrmnmichaels
https://t.co/96RhHyVY8e

[AI Advances @AIAdvances]

What do we mean when AI “remembers”? Pooja Kashyap @poojakashyap unpacks why LLMs generate, not retrieve and why that shift changes how we build AI. #AI #LLM
https://t.co/G8gbovfFl5

[AI Advances @AIAdvances]

Dr. @UmairAliKhan81 improved speech-to-text for low-resource languages with a 2-pass LLM method, reducing WER across multiple ASR models.
https://t.co/Yf86p648Rr

[AI Advances @AIAdvances]

60 clients. 0 employees. No coding. Powered by one file - CLAUDE.md.

Not prompts - it is an AI operating manual.

The real shift? Moving from using tools to designing workers.

The real skill? Translating work into structure.

By @calvindong15

https://t.co/t6CBQkZpS7

[Manjunath Janardhan @manjunath_shiva]

I just published my first technical deep-dive: adapting @Google 's #TurboQuant for weight quantization on @Apple Silicon using MLX.

The headline result on Qwen 2.5-7B:
• Standard 2-bit quantization: perplexity 2199 (garbage)
• TurboQuant 2-bit + QJL: perplexity 15.93 (usable)
• Zero training data required

How it works:
1. Randomized Hadamard rotation makes weights Gaussian
2. Lloyd-Max codebook (optimal since 1960) replaces uniform quantization
3. 1-bit sign correction cleans up the residual — 43-45% MSE reduction

At 4-bit + QJL, we're within 4% of FP16 quality. The advantage grows with model scale — bigger models = wider layers = better Gaussian approximation.

Published in @AIAdvances on @Medium : https://t.co/1uy7DettRW

Also preparing an @arxiv preprint for cs.LG — if you can endorse, DMs are open.

[AI Advances @AIAdvances]

Tesseracts as Data Structures for Understanding High-Dimensional Computing. By @poojakashyap
https://t.co/VTgXvvNTWA

[AI Advances @AIAdvances]

Vibe coding looks great until it reaches production.
Durable code needs engineering. By @kzdeb
https://t.co/LKE0SV6Z0C

[AI Advances @AIAdvances]

Anomaly detection fails where signal breaks: low volume, cold start, false confidence. Lessons from a T20 World Cup pipeline. By @sengorajkumar
https://t.co/0BDJ4cjiK6

[AI Advances @AIAdvances]

Prompts disappear. Specs stay in the repo.
That's why agentic engineering needs durable artifacts.
Read this article by @kzdeb
https://t.co/YxU2JiXfDe

[AI Advances @AIAdvances]

From Iron Man to Spatial Intelligence and the Future of Human-Centered XR by @poojakashyap
https://t.co/YkCSfDuknq

[AI Advances @AIAdvances]

Most people use Claude Code as a chatbot with a terminal. @0xAedelon turned it into an operating system: 6 layers, 17 hooks, 32 skills, zero trust. The model is the engine. Everything else is deterministic code.

Blueprint + article:
https://t.co/qc9TL1AeHZ

[AI Advances @AIAdvances]

The Most Expensive Thing in AI Training Is Waiting: Taming the Long Tail in RL. By @poojakashyap
https://t.co/CS3q9nxKNP

[AI Advances @AIAdvances]

AI that writes the rulebook: a transformer model now generates Python code that builds entire families of quantum experiments, not just single solutions. By @poojakashyap #AI #QuantumComputing
https://t.co/HElmVZXVa6

[AI Advances @AIAdvances]

What if a neural network knew the laws of physics before seeing any data? The AI revolution nobody's watching.
https://t.co/X3nV7JqeGc

[AI Advances @AIAdvances]

Why do most AI pilots in finance fail while a few actually scale? This post by @lak_luster uncovers the hidden infrastructure and domain expertise needed to move from impressive demos to reliable, production-ready AI.
https://t.co/43rETwy3Pe

[AI Advances @AIAdvances]

AI is already reshaping what ends up on your plate. By 2030, algorithms will control food systems you never see. New investigation by @Yiannis_A_med:
https://t.co/lLUz6YbeIb