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Yes, the green flame is caused by burning copper from depleting fuel in the regenerative cooling circuit and going oxygen-rich (closer to stoichiometric temperature) in the main combustion chamber. Slight underperformance of engines on this flight is the reason. The booster is meant to land with tiny residuals, so the solution is to improve engine performance and performance consistency (underway with Raptor V3.2), as well as adjust flight software to do MECO1 about one second earlier to ensure enough propellant for boostback and landing (tiny change). These early ships and boosters are already outdated by improved designs in production or on the test stand, so this booster loss does not change our timeline to reach high volume, fully reusable Starship flights.

Four months after we launched Manus, I was invited to a dinner with President Macron. I ended up seated directly across from Jensen Huang. He was half an hour late, and Macron asked him to give a toast. Jensen picked up his wine glass and turned it into a fully improvised speech — in front of a table of European politicians and founders. It was electric. The charisma of a top founder, on full display. I typed the whole thing into my Notes that night. Still one of the sharpest takes I’ve heard on software, AI and Europe. What a pity. What a loss.

This slide from the Anthropic IPO roadshow was a big factor in my decision to leave. It’s an insane plot and I’m surprised they made it public. It shows the compute efficiency of pretraining over time. The y-axis is a **log scale**: they are seeing continued superexponential algorithmic progress. Mythos was not a one-time deviation, but a point on a superexponential. They could already retrain Mythos with a fraction of the compute originally needed. It doesn’t strictly imply a software-only intelligence explosion- they have been spending more on R+D. But algorithmic improvements do not require ridiculous creative genius and are on the verge of being automated. You do the math.

YOUR AI ASSISTANT CAN NOW FIND ANYONE'S EMAIL AND PHONE NUMBER wiza plugged 800M+ contacts into grok, claude, chatgpt and any mcp client the best b2b contact data for sales and marketing - now one prompt away you type who you need, it comes back with names, work emails and phone numbers here's how to put wiza mcp into a real workflow: > find new leads "find vps of sales at us software companies with 51-200 employees" your icp turns into a list of real people > map the account "get company info for [company], then find its sales leaders" you know the whole buying committee before the first call > enrich before you reach out "find the work email and phone number for [name] at [company]" no more jumping between linkedin and 5 tabs > source candidates "find senior backend engineers in seattle with available work emails" a recruiting pipeline without a sourcing agency > build a marketing list "save these prospects as conference follow-up and find their work emails" wiza saves the list and finds the emails in the background > chain it search companies, find the decision makers, enrich them, save the list one conversation instead of an afternoon of manual research setup: 1. add to your ai assistant 2. sign in with your wiza account 3. ask for what you need building your own tools? the same data is in the wiza api start here ↓

GCSA Insight: Critical Security Vulnerability Discovered in a Leading Robotics Manufacturer’s Product, with System-Level Privilege Compromise Verified on Physical Hardware As artificial intelligence and embodied AI technologies continue to advance, robots are evolving from conventional automated machines into intelligent systems capable of perception, decision-making, and autonomous operation. At the same time, cybersecurity risks are extending beyond software and data into the physical world. The security of robotic systems is no longer solely a matter of protecting data and devices; it can also directly affect operational safety, physical environments, and user safety. Recently, the security research team of the Global Cybersecurity Alliance (GCSA) discovered and verified a critical security vulnerability in a product developed by a leading robotics manufacturer. Through in-depth analysis and multiple rounds of testing on physical hardware, the team successfully breached the device’s system security boundaries and obtained the highest level of operating system privileges in a real-world device environment, demonstrating the vulnerability’s actual impact under specific testing conditions. This research encompassed the entire process, from identifying the security flaw and assessing its risks to validating its impact on physical hardware. The findings also highlight significant challenges facing the underlying security mechanisms of embodied AI systems. The research findings and supporting evidence have been formally submitted to the manufacturer. On November 13, 2026, the manufacturer responded by email, preliminarily confirming the existence of the vulnerability and stating that it had initiated internal remediation efforts and an assessment of the scope of affected products. It is important to emphasize that confirmation of a vulnerability does not mean the associated security risks have been eliminated. GCSA will continue to monitor the manufacturer’s assessment of the affected scope, remediation plans, and subsequent security validation, and will update its research findings as new information becomes available. For intelligent systems capable of physical interaction and movement, timely, effective, and verifiable security remediation is particularly important. In accordance with responsible vulnerability disclosure principles, GCSA is currently withholding sensitive information, including the manufacturer’s identity, specific product details, the vulnerability’s underlying mechanisms, and exploitation methods. GCSA is currently seeking guidance from relevant authorities and regulatory bodies regarding the associated security risks. Taking into account the manufacturer’s remediation progress and a comprehensive assessment of potential security implications, GCSA will carefully determine the appropriate arrangements for further disclosure. Subject to appropriate conditions and upon obtaining the consent of the relevant authorities and regulatory bodies, GCSA will publicly release a detailed security insight report, providing the industry with ongoing updates on the research findings and associated risk assessments. The findings of this research are based on specific testing environments and the evidence obtained to date. They do not imply that other product models or similar robotic systems are affected by the same security issue. This security research and validation on physical hardware represent one of GCSA’s initiatives in the field of embodied AI security. GCSA will continue to advance security research, coordinated vulnerability disclosure, and industry collaboration to promote stronger security response mechanisms across the artificial intelligence sector, enhance product security, and strengthen industry trust. 🔗 Read the full report: · Stay Connected with GCSA Follow GCSA's official social media channels for the latest news, product launches, research developments, and ecosystem updates. GCSA Official Telegram Channel: GCSA Official WeChat Account: #GCSAInsight# #GCSACybersecurity# #GCSASecVibe#

Everyone believes CUDA is NVIDIA's moat, the reason we've maintained our dominance in the AI era. I've never believed that. NVIDIA has only one true moat: its people. And the most important of them is Jensen Huang. I've worked on CUDA compilers, libraries, and DSLs for eight years, from Volta to Rubin. I think I've earned the right to share my perspective on what NVIDIA's moat really is. I hope you'll bear with me. 1. What is CUDA? Many people think CUDA is just a programming language and its compiler, and that NVIDIA's moat comes from the massive amount of software written in CUDA, making it impossible for developers to leave NVIDIA GPUs. This is completely wrong. It's an incredibly naive understanding of CUDA. To me, CUDA is everything NVIDIA does. CUDA isn't just a language, software, or hardware architecture. It's a product defined by a unique customer experience. When you find GPU programming too difficult, CUDA gives you an easier way. When your GPU code isn't fast enough, NVIDIA engineers respond and help you solve it. When a handful of GPUs can no longer push your technology forward, NVIDIA has already scaled its computing platform from desktops to massive data centers. When you need more data centers than anyone else can supply, NVIDIA has already secured wafer and HBM capacity years in advance to meet your demand. That experience is CUDA. It's made possible by the relentless, day-to-day work of everyone at NVIDIA. And the person who brings all these people together, who gives them a shared vision and purpose, is Jensen Huang. 2. What made CUDA possible? Patience. Perseverance. An unwavering commitment to a vision. Around 2006, NVIDIA bet that the future would demand far more computing power, and began transforming GPUs from graphics processors into a platform for general-purpose computing. Initially, it was a commercial disaster. The added costs hurt margins, the market wasn't ready, and the strategy faced enormous skepticism and pressure, including questions from the board. But Jensen persisted. For roughly a decade, NVIDIA kept investing in CUDA, building its hardware, software, and developer ecosystem long before the commercial payoff became clear. Eventually, deep learning arrived. And NVIDIA was ready. Today, this sounds like an inspiring story. But for those who lived through it, it meant a decade of perseverance, doubt, and being misunderstood. Looking back at the history of technology, how many people could have done the same? This is what I've always loved most about NVIDIA. And now, Jensen has been pushed out. This won't kill NVIDIA. The company can still create tremendous commercial value. But it has killed NVIDIA's soul. And how far can a body go without its soul? If this is how Jensen Huang is treated today, how will those of us who built CUDA be treated tomorrow? I love NVIDIA deeply, but I have to say it: NVIDIA is dead.

🚨 BREAKING: LONDON TRIED TO FLEX, ELON MUSK JUST DROPPED A TOTAL DIGITAL BLACKOUT! UK Prime Minister: "Elon Musk, adjust your platform algorithms and hand over satellite telemetry logs to our regulators immediately, or we will revoke your commercial spectrum licenses and seize all Starlink UK ground stations!" Elon Musk: "You confused parliamentary decrees with orbital mechanics. In space, satellite constellations don't bow to bureaucracy. Try revoking our licenses—your ministers can issue all the press releases they want, but your regional maritime routes can't function without high-speed telemetry." UK Prime Minister: "We will freeze SpaceX financial accounts in London and restrict your aerospace access!" Elon Musk: "Freeze whatever accounts you like! The moment your order goes live, SpaceX software shifts subsea data routing keys away from North Sea terminals. Good luck guiding transatlantic cargo fleets through maritime storms on dark screens!" If this exchange is real, the clash between government power and Elon Musk's technology empire just reached another level. Do you firmly support Elon Musk on this? YES or NO? IF Yes, Give me a THUMBS-UP👍!!

Jacek from DEGEN shares his perspective on how rapidly AI is changing software development and what that could mean for the future. “Jacek has seen the progress firsthand. Work that once required hiring separate developers to build an iOS app could now be handled by a single engineer using modern AI tools. The pace of improvement over the last 18 months has been remarkable.” “He believes AI could eventually become far more capable than humans across almost every type of work. Looking ahead, he sees two possible paths: humans adapting to a world led by advanced AI or integrating more closely with it. Either way, he believes this transformation is coming much sooner than many expect.”