I tried the codex app's computer use functionality last week with 5.6 luna. I had it delete an email, then delete an email based on the sender's name. Then change my brave browser's default search engine from brave to google search. It oneshotted everything. I was surprised because a year ago I tried something similar with computer use and gpt-4o. It failed miserably. Codex only released in feb and it's computer use is already so good. I am in the construction industry doing a startup and computer use has so many use cases, it can input hundreds of items that have to be normally written manually. Saves hours of time. Haven't been this impressed about something ai related in a while 😁

Going live at 12:15. GPT-6 Astra just dropped and almost nobody has real hands-on yet. I’m stress-testing it the only way that counts, building real apps live, in depth, until we hit a wall. Benchmarks look wild on paper; I want to know what happens after hour two when the context gets messy and it has to hold a whole codebase. Hang in chat, throw ideas, and I’ll call it straight where Astra beats what I’m already paying for and where it doesn’t. Watch live: https://youtube.com/live/kc-azZ5z4c8

I’ve been running open-weight models locally for a while. GLM-5.2 on a 512GB Mac Studio was capable, but you always felt the ceiling: 2-bit quant, 5-9 tok/s, tool calls that got flaky in long agent sessions. Local was the thing you tolerated to keep data on your network. DeepSeek V4 Flash was the first real step forward — finally a local model with a genuine balance of performance and speed, one you could actually leave running under agent traffic without babysitting it. It proved the “fast MoE with real agentic chops” formula worked. 5.3-Flash on two DGX Sparks takes that further. 320B params but only 18B active, so it’s running at good speeds. 1M context. Thinking is always on but tunable (low/high/max), and at max it holds up in real agent work through Hermes: multi-step coding, sustained tool calls, no hand-holding. I’m still reaching for cloud models. But for the first time I can see a point coming where you won’t have to. The gap is closing faster than I expected — if you have the hardware, this is the one to try.

It quite surprised me that it's IBM doing this :) For anyone lost in the sea of terminologies, principles and needs guidance (like me), I recommend the channel bellow. IBM tutors go through different subjects in a clear and short way. https://youtube.com/@ibmtechnology?si=Mfq1iP1VVHlTf8b2

Meng To sat out two years because he thought AI would replace education. He says he was wrong. In a sea of slop, good teaching still matters. DesignCode 5 is out. New Codex masterclass. New site he built entirely in Codex with three.js. Homework, tests, certificates, a vault, and weekly live sessions where he gives feedback. Pro and Lifetime also get the Product Pass: one year of Pro on Framer, Mobbin, Aura, and more. 50% off for early adopters right now. There is a $499 Lifetime if you are done stacking subscriptions. Site: https://designcode.io/ His post: https://x.com/mengto/status/2093350278192062611