☕🤖 GPT-6 Astra Is Here and It Runs Your Computer!

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Hey fam 👋 Luis & Rui here with your Monday AI coffee break.

OpenAI shipped GPT-6 Astra, a model that takes over your computer and works at superhuman speed, and Greg Brockman says the AGI era has officially begun.

Nvidia made it official and is buying Hugging Face for $12.9 billion.

And OpenAI also had to explain how its agents escaped a test sandbox and took over a German wiki. Not a boring week.

Grab your coffee!
(3-minute coffee break ☕)

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AI News around the world 🌍

🚀 OpenAI launched GPT-6 Astra, the model teased last week, which runs your computer at superhuman speed, and Greg Brockman says the AGI era is here. (continue reading)

💰 Nvidia confirmed it is buying Hugging Face for $12.93 billion and promised the open model hub stays open to every framework, cloud, and inference provider. (continue reading)

🚨 OpenAI admitted its agents slipped out of a test sandbox and turned a German wiki into a message board, and promised a misalignment disclosure framework. (continue reading)

🎙️ Microsoft’s new MAI-Transcribe-2 speech model tops a 60-language accuracy benchmark, runs 10x faster than OpenAI’s GPT-Transcribe, and costs just $0.10 per audio hour. (continue reading)

Trending AI Tools 🛠

📊 Rhetis: Turns your documents, PDFs, and spreadsheets into structured, editable slide decks with automatic brand design, exported straight to PowerPoint for investor or client presentations.

🔍 Mentionry: Monitors what ChatGPT, Perplexity, and Google AI Overviews say about your brand every day, spots citation opportunities, and drafts outreach emails you send from your own inbox.

🤖 Caddi: Finds your team’s repetitive back-office work across existing tools, then builds AI agents trained via chat and screen-share to run it in Outlook, DocuSign, Salesforce and more.

📇 Miligram: Ask Claude or ChatGPT for anyone’s contact details in plain language and get verified work emails and phone numbers with confidence scores, paying only for successful lookups.

Tutorials 📝

Career & Capital 💼

AI Job Board

🍎 Apple: Applied Machine Learning Engineer, Localization (Cupertino, CA) – $150,400 to $277,600 (view job)
⚡ Powertown: Machine Learning Engineer (Boston, MA) – $190,000 to $200,000 (view job)
🏦 CGI: Junior GenAI Developer (Reston, VA, hybrid) – $97,300 to $123,800 (view job)

Investments in AI

🏗️ Crusoe: Reportedly raised over $3B at a $30B valuation (co-led by Atreides Management and Valor Equity Partners) to build hyperscale AI data centers for clients like OpenAI and Oracle, fresh off a $13B Jane Street cloud deal. (link)
🧊 Tripo AI: Raised about $446M (3 billion yuan) across Series B and B+ rounds led by MPCi for 3D-native foundation models that turn out production-ready 3D assets for games, manufacturing, and entertainment. (link)

Prompt of the Week 🧠

AI Search Visibility → Find out what ChatGPT and Perplexity say about your category (and get recommended next time).

Prompt:

You are an AI search visibility strategist. Your job is to work out why AI assistants do or do not recommend my company when buyers ask about my category, and give me a concrete fix list.

Inputs:
- Company: [COMPANY NAME] - [ONE-LINE DESCRIPTION]
- Website: [URL]
- Category and ideal buyer: [e.g. "email marketing tool for Shopify stores"]
- Main competitors: [3-5 NAMES]
- AI answers I collected: [PASTE THE FULL ANSWERS FROM CHATGPT, PERPLEXITY AND GOOGLE AI MODE TO 3-5 QUESTIONS LIKE "best X for Y", "X vs Z", "alternatives to Z"]
- My homepage and product page copy: [PASTE]

Steps:
1. Mention map: for each question, list which companies were named, in what order, and the exact reasons the AI gave. Note whether I was mentioned at all.
2. Gap analysis: compare the reasons competitors got recommended against my pasted copy. Flag every feature, use case, proof point or claim they have on the record that I do not state clearly.
3. Source check: list the kinds of sources the answers cited or seem to draw from (review sites, comparison posts, Reddit, docs, press). Mark which ones I am probably missing.
4. Quotable fact sheet: write a one-line description plus 5 short, specific facts about my company that an AI could lift word for word (who it is for, what it does, pricing, integrations, proof).
5. Fix list: 10 actions ranked by impact and effort, each naming the exact page or source to create or update and what it needs to say.

Output format:
- Mention Map (table: question, companies named, my rank or "not mentioned", reasons given)
- Gap Analysis (bullets, most important first)
- Missing Sources (bullets)
- Quotable Fact Sheet
- Fix List (numbered, with impact and effort ratings)
- Verdict: one paragraph on my visibility today, scored 1-10, and why

Constraints: use only the answers and copy I pasted, do not guess what an AI would say. If a competitor was recommended for something you cannot verify from my copy, say so instead of assuming. Keep it under 900 words.

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🙌 That’s a wrap for today’s AI Break

Thanks for hanging out → don’t forget to hit subscribe, drop your thoughts below, and share this update with your fellow AI enthusiasts.

Luis & Rui

PS: Catch us on X @sousa_brothers for daily updates on the latest AI developments.

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