全部 AI 动态

grok @bot marketplace is open for submissions! send us your connectors: https://x.ai/bot/marketplace/submit-a-plugin

Perplexity is now available in Lovable to give users real-time answers from the web, with citations.

I built a dream logger. For all those dreams I forget five minutes after waking up. This little @M5Stack CoreS3-SE turns dreams into images using the @OpenAIDevs image-gen API. 🧵

Connecting Codex to hardware helped me build my cat his own TV I have an extremely active cat who unfortunately loves TV a little too much (he tries to jump into it) I've always wanted to give him something more stimulating, so I decided to build him his own

this is Felix, the detective in a mini mystery game i built for nights when i host dinner. and yes: he lives on an M5StickS3 from @M5Stack. i can ask him Qs about the case, pitch my lil theory, and get clues printed on an actual receipt 🧵 I built it with Codex, ImageGen, Decisions API & GPT-Transcribe:

no way!! 🔥🔥 watch codex-cli with the new gpt-5-codex model take control of the first canbus motor. it had already configured the motor ID by the time i started filming. next up; more motors, more action, eventually an entire codex-built robot. future=now

Vibe coded hardware is here, and amazingly fun! This week I'm covering how to use @OpenAIDevs Codex, @CloudflareDev Workers and the Zectrix Note4C to build your own custom eink display. I made a train tracking screen 🤓🚂 https://jamesdevonport.com/p/can-you-vibe-code-hardware

First @cerebras x @OpenAI Cafe Compute happened in Brussels 🇧🇪 A full day of Codex, Astra updates, and talks from OpenAI and Cerebras We also brought a robotics demo built with new GPT Image: You took a photo → GPT Image turned it into a portrait → a robot arm drew it for you

Insane start to Ship Kicked off workshops with @eve and now @spacexai by @mattyp

I got tired of all the spam calls I was getting so I had @bot find my number listed on sites and file the removals. I made it a free skill so you can do the same. https://x.ai/bot/fUj6TYhiW_cjtzWvbsFgz @spacexai @elonmusk

Some magical progress towards "magic state" in quantum! Our @GoogleQuantumAI team has demonstrated "magic state cultivation" on physical hardware for the first time. The result is a 40x error reduction on our Willow processor vs. previous methods, achieving a state-of-the-art 99.99% logical fidelity. It's another step towards useful, error-corrected quantum computers to help solve the hardest problems. The result is published in Science today, watch the video below to see how it works

How can the math community forge the best path forward in the AI age? We're committing $15M to workshops and initiatives — plus free AI computing resources for foundation-supported researchers — through new partnerships with @AnthropicAI and @OpenAI: https://bit.ly/4zpfIbW #math #science #AI

I have a friend who got fired from his blue collar job on Monday. Starting Wednesday, he used $META Muse to apply for jobs for him. Friday morning, he had a job offer. Muse did nearly everything for him outside of signing the offer documents.. He just let it run. Crazy world we live in!

hey @bot convert the linked essay to an ebook and email it to my kindle so i can read it on my flight

did you know you can submit Grok Bot (and Grok, Cursor) plugins? submit them here! https://x.ai/bot/marketplace/submit-a-plugin

Meta released the weights of Muse Spark Open, on Huggingface, an 816B-parameter model built for coding and agentic work. The open version shares the same base model as Muse Spark 1.3, with additional safety post-training to resist misuse as a standalone model without system guardrails, reversing Meta’s first proprietary, closed-weight frontier model strategy from April. Each of its 62 layers holds 256 expert networks and routes every token through 8, so deployment needs the memory of an 816B-parameter model but runs at the speed of a 42B model. That storage bill explains the Apple tie-up, because the M5 Ultra pushes 1.2 TB/s of unified memory and a Mac Studio can carry up to 512GB. A 3-bit quant tested on a 512GB M3 Ultra took about 344 GB and ran at about 21 tok/s generation on a short prompt.