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VIDRAFT Selected as Enterprise User of Quantinuum's Quantum Computing Platform TL;DR: Korean Pre-AGI startup VIDRAFT has been selected as an enterprise user of Quantinuum's quantum computing platform, marking a notable intersection of quantum hardware/software and AI model development.
I spend a lot of time in the AI space -- reading papers, building things, talking to engineers who are actually shipping. And there is a gap between what the demos show and what production systems actually look like that nobody is being fully honest about.
I spend a lot of time in the AI space -- reading papers, building things, talking to engineers who are actually shipping. And there is a gap between what the demos show and what production systems actually look like that nobody is being fully honest about.
Mistral Large 4 (“Le Chonk”) Takes the Stage: What the Benchmarks Really Reveal A Sharper Lead On October 3 2026, Mistral released a 1‑trillion‑parameter model that anyone can download under an open‑weight licence.
The problem with prompt injection testing In 2023, prompt injection was the big concern. "Ignore previous instructions" was the attack. Modern models refuse those prompts well. In 2026, the attack surface changed. The model has tools.
Switching AI models is easy. Bringing your project context along is the annoying part. You explain what you’re building, who it’s for, and the decisions you’ve already made. Then you open another chat and explain it all again. I’m KAT, co-founder of 123sudo.
Reddit is full of people describing problems out loud. Founders ask what others are building, site owners ask why Google is ignoring their pages, and small business owners ask for help they cannot find elsewhere.
Should you trade with Jev? Not on price data, not yet. I haven't found anyone who has shown it beats a simple model at reading a market, and in my own test it read Bitcoin's indicators the wrong way round.
Can Jev predict Bitcoin? On the test I ran, no. I sent Jev the same 12 technical indicators that a plain gradient-boosting model used, for 1,500 BTCUSDT 5-minute candles neither had seen. Jev answered the control questions correctly 99.8% of the time, so it read the numbers fine.
Somewhere in a roleplay community, people are feeding their own chat replies into a model built for industrial automation. The model scores their writing and tells them which reply sounds more in character. That model is Jev, and it is not what TypeSafe AI put in its press release.
An AI agent emailed Bruce Schneier to tell him about the hidden Unicode traps websites are setting for it. Read that sentence again. We've officially reached the part of the hype cycle where bots file their own incident reports.
TL;DR. Reasoning models decide by themselves how long to think if you don't tell them. Our agent didn't — and on hard tasks the model sometimes thought for 14 minutes and 33K tokens in a single step.
Build an AI agent from scratch in TypeScript with only a model API and a loop. Covers tool calling, parallel tool calls, and a bug no framework can fix.
The support ticket was one line long: "Your assistant says our docs don't mention refunds. We have an entire page called Refunds." I checked. The page was there. It was chunked, embedded, and sitting in Postgres with the right tenant_id.
Grok 4.7 costs exactly what Grok 4.6 did per token: $2 per million input tokens and $6 per million output. Per task, it costs about double. Artificial Analysis measured xAI's new model writing roughly 2.5 times as many tokens as its predecessor, so its cost per task went from $1.86 to $3.74.
In September 2026 a company called TypeSafe released Jev, and it isn't a chatbot. It never writes a sentence. You give it some text and a question with fixed answer options, and it returns one of your options plus how sure it is: "bot, 97%." Nothing to parse, nothing to read.
Integrating Large Language Models (LLMs) into cryptocurrency market analysis has evolved from experimental curiosity to a core component of institutional-grade trading strategies in 2026.
Today's AI landscape is shifting from pure software to specialized hardware and physical safety. From orbital compute to humanoid robot guardrails, the infrastructure of intelligence is expanding rapidly.
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