Jason Adams @ealdent

GPT-5.6-Sol-Ultra built a Doom-like game in SQL: the game is running in the terminal on the left, while the SQL powering the game in the terminal on the right. How it works: DOOMQL is a game engine implemented in 2,000+ lines of SQL. Every frame, SQL raycasts the scene, calculates every RGB pixel, and encodes those pixels as coloured terminal characters. The same SQL then handles controls, movement, collision, enemy AI and combat, while Python connects SQLite to the keyboard, clock and terminal.

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Jason Adams @ealdent

2 months ago

@cwilliamsonwa @Polymarket all just marketing including when Mythos made the claim

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Jason Adams @ealdent

2 months ago

@LinkofSunshine How renowned are you if you get hired as an intern?

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Jason Adams @ealdent

2 months ago

@peakcooper I got this in the GLM 5.2 web chat interface, so you would expect the full system prompt to be in play.

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Jediwolf @Jediwolf

3 months ago

What happens when you post a real Monet and say it’s AI? The coolest art social experiment I’ve seen in a while. Thank you @SHL0MS

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Alexander Whedon @alex_whedon

4 months ago

Introducing SubQ - a major breakthrough in LLM intelligence. It is the first model built on a fully sub-quadratic sparse-attention architecture (SSA), And the first frontier model with a 12 million token context window which is: - 52x faster than FlashAttention at 1MM tokens - Less than 5% the cost of Opus Transformer-based LLMs waste compute by processing every possible relationship between words (standard attention). Only a small fraction actually matter. @subquadratic finds and focuses only on the ones that do. That's nearly 1,000x less compute and a new way for LLMs to scale.

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Jason Adams @ealdent

8 months ago

@Oliviacoder1 agent

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GREG ISENBERG @gregisenberg

11 months ago

OpenAI JUST released how people are using chatgpt each bar in this chart is a billion-dollar wedge if you build the right verticalized, trust-rich AI startup: 1/ tutoring + teaching (10.2%) - people want on-demand teachers more than almost anything else. a personal ai tutor that explains things your way, remembers your progress, and nudges you daily. 2/ how-to advice (8.5%) - this is consumer SaaS for micro-niches: “how to fix my resume,” “how to meal prep,” “how to set up my Shopify store.” every “how-to” is a wedge into a vertical AI agent. 3/ personal writing + editing (18% combined) - 8% of traffic is people asking AI to write emails, 10.6% is editing or critiquing text. this is demand for AI copilots inside every workflow tool: sales, legal, HR, PR. 4/ health, fitness, beauty, self-care (5.7%) - validated consumer wedge. people already trust AI with their bodies. AI trainers, AI nutritionists, AI skin coaches — with a human layer for accountability. note: btw if you like seeing ideas/trends like this, you'll like @ideabrowser (free/paid plans) 5/ purchasable products (2.1%)- tiny % but huge monetization. people literally asking AI what to buy. the Amazon affiliate model gets reborn here. whoever builds the “AI-powered shopping layer” owns the new SEO. 6/ translation (4.5%)still unsolved. what people want isn’t raw translation, it’s contextual translation: tone, culture, slang. AI that doesn’t just translate but localizes your intent. 7/ computer programming (4.2%) - we know this, but it’s worth underlining: devs want copilots. the non-obvious play is vertical code copilots... Shopify dev copilot, Unreal Engine copilot, etc. TLDR; every bar is a behavior that people are already paying for elsewhere. translate those behaviors into vertical ai agents and startups. the data doesn't lie.

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Jason Adams @ealdent

11 months ago

@Krishnasagrawal ML

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Krishna Agrawal @Krishnasagrawal

11 months ago

"Introduction to Machine Learning Systems" - FREE from MIT Press - Authored by Harvard Professor - 2048 Pages To Get It Simply: 1. Retweet & Reply "ML" 2. Follow so that I will DM you.