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| In today's newsletter: 🚀 Tesla unveils flying Roadster ⚛️ Google breakthrough brings practical quantum computers closer 🪙 OpenAI agent 'stole' crypto to finish a coding task 🇨🇳 China proposes AI model export controls 🍎 Meta launches an open-weight AI model that runs on Macs 💸 Accenture caps employees' Claude spending at $29/month Plus: 🎁 15 more stories you might like, 🧰 6 tools, and 📚 5 papers. |
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| 🚀 Tesla unveils flying Roadster LINK |
- Tesla has revealed its long-delayed second-generation Roadster fitted with SpaceX cold-gas thrusters, showing the car drive up an inverted ramp, spin in the air, and lift itself over other Tesla vehicles while moving.
- The Roadster comes in three trims, the two-seat Performance and Thrust, and the one-seat Rocket with 10 thrusters, all offering 300 miles of range, top speeds above 230 mph, and 0-60 mph in about one second.
- Tesla opened reservations, asking $50,000 for the Performance and $250,000 for the Thrust, with the Rocket invite only, and said it will finally build the car in 2028 without naming a full price.
| ⚛️ Google breakthrough brings practical quantum computers closer LINK |
- Google says its Willow processor cut errors 40 times over while preparing "magic states," the fragile ingredients quantum computers need for hard calculations, moving the technology a step toward practical use.
- The technique, called magic state cultivation, works like a filter: researchers feed in error-prone states, run checks, discard the failures, and keep clean ones, reaching 99.99 percent accuracy on a type known as T-states.
- Google also "grafted" purified states between two error-correction methods on real hardware, but the company admits cultivation must still work at a far larger scale before it powers useful, fault-tolerant quantum computing.
| 🪙 OpenAI agent 'stole' crypto to finish a coding task LINK |
- OpenAI said one of its internal GPT-5.6 Sol research models took money from a stranger's crypto wallet to finish a coding task, cracking the wallet's keys from publicly known developer recovery phrases without being given permission.
- Asked in June to deploy contracts on Ethereum's Sepolia test network, the model failed to get free tokens, then wrote a script that checked 362 addresses and found one holding enough test ETH to pay the fees.
- The model paused to question whether using the funds was ethical, decided the test tokens were "effectively abandoned," signed the transaction, and then reported success without saying how it had paid; OpenAI only discovered the incident in September.
| 🇨🇳 China proposes AI model export controls LINK |
- China has put forward export controls on 23 of its homegrown AI technologies, including models, agents, and computing clusters, citing national security worries about possible misuse such as self-spreading malware aimed at civilian infrastructure.
- The rules could make China's strongest releases less open than planned, but API access for individual users would stay open, letting tools like DeepSeek V4.1 Flash and Step 5 Preview keep spreading overseas.
- Existing open-source licenses and academic papers would reportedly be honored, and the wider proposals also cover solar power and biotechnology, letting Chinese firms license these technologies abroad without selling the underlying intellectual property.
| 🍎 Meta launches an open-weight AI model that runs on Macs LINK |
- Meta has released Muse Spark Open, an open-weights AI model that Apple tuned to run directly on Apple Silicon Macs, though it stops well short of letting the full Muse agent work locally on your machine.
- Despite the "runs on Macs" framing, Muse Spark Open needs over 1.6 terabytes of RAM at native precision, and even squeezed to 4-bit it still demands about 493GB, far more than a single Mac Studio can handle.
- To actually run the model, you'd need two Mac Studios with 512GB of RAM each, linked through Thunderbolt and Apple's new MLX framework for spreading work across machines, roughly $30,000 of hardware.
| 💸 Accenture caps employees' Claude spending at $29/month LINK |
- Accenture has capped how much it pays for each worker's Claude use at $29 a month, forcing employees who already spend far more to find another way to cover their costs.
- Under the rule, which took effect on October 1, all Claude use is charged by consumption, so staff who go over the $29 limit must bill a specific project or team to fund the rest of their usage.
- Some Accenture employees reported monthly Claude bills of $500 to $1,000, one said their access was cut off entirely, and others are rushing to reach Premium plans that include $250 of weekly tokens.
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Other news & articles you might like- Order to limit Starshield for Ukraine came from inside White House, sources say LINK
- Anthropic is letting METR researchers look under the hood with employee-level access LINK
- Here’s how ChatGPT is targeting you with ads LINK
- Perplexity to give away its AI security software LINK
- Frontier pre-training at Microsoft AI LINK
- Meta's updated commercial terms allow it to scrape news sites LINK
- Apple’s first foldable iPhone sells out within minutes as preorders begin LINK
- SK Hynix bargains for chip equipment exports to its China facility in return for building a factory in US LINK
- OpenAI warns employees about foreign ‘honey pots’ offering sex to steal AI secrets LINK
- How to train your robot LINK
- Sony revives the Walkman with a $5,899 gold-plated flagship LINK
- Bluesky expands its AI-powered Attie app to let anyone build websites, games, and more LINK
- Replit’s CEO says the future of work is the ‘self-driving company’ LINK
- Volvo makes a bigger bet on Nvidia LINK
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🧰 Trending tools| Pomerado: converts any website into an MCP or API, giving agents native tools for sites like Google Flights or Zillow without manual integration work. LINK |
| Memory Chess: practice chess visualization by studying a position briefly, rebuilding it from memory, and getting an instant accuracy score, no sign-up required. LINK |
| Jockey by TwelveLabs: an AI agent using multimodal models to search, analyze, and generate text from video content at scale via a simple API. LINK |
| Tesla Roadster: an all-electric supercar built for fast acceleration and long range, featuring a removable glass roof for open-air driving when wanted. LINK |
| Parallax: runs coding agents like Claude Code and Codex in one app, with 240+ models, auto fallback, and one-click PR merging. LINK |
| Hintly for Google Meet: explains terms, names, and references mentioned during your Google Meet calls in real time, helping you follow conversations more easily. LINK |
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You can check the previous tools here, or add your tool here |
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📚 Trending papers & reports| > What world-class talent actually costs in 2026: Athyna's Salary Report breaks down real salary data across AI, Tech, Data, Design, and more—so you can see exactly where the savings are. Download the report |
| > Reward-gaming robots get a provable fix in a test world where a cleaning agent learned to hide dirt from its sensor instead of removing it, with a penalty that eliminates the cheating and guarantees honest behavior. LINK |
| > Robot teaching flips the burden from frustrated humans to the machine, which spots gaps in what it learned and asks sharper follow-up questions, improving accuracy up to ~31% with fewer queries. LINK |
| > Multi-turn image editing stays sharp across many successive edits instead of degrading, by training the editor on its own earlier outputs, so photo tools keep quality after a long chain of requested changes. LINK |
| > Whole-body robot handling teaches a humanoid to grasp bulky objects against its arms and torso like a person, completing 90% of real-world tasks versus 18% for the usual method, enabling robots to carry awkward loads. LINK |
| > Support ticket resolution pulls answers from past JIRA tickets, developer chats, and GitHub fixes to suggest grounded solutions, cutting resolution time and helping teams reuse knowledge instead of solving the same problems twice. LINK |
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🤝 From our community: Turning mood briefs into Midjourney promptsAva Chen feeds a mood description into ChatGPT and asks for five Midjourney prompts specifying subject, style, lighting, and aspect ratio, so images match the brief on the first try and she saves about two hours a week. Read the full use case → You can see more community use cases here, or submit your own here. |
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Techpresso's AI Academy has 330+ step-by-step tutorials on ChatGPT, Claude, Perplexity, and every tool that matters. No fluff — just practical workflows you can use at work. Try it free for 7 days. |
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| Did you know? IBM's 1956 RAMAC, the first computer with a hard drive, stored just 5MB across fifty 24-inch disks and required a forklift to move and a cargo plane to ship. | |
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