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We posted our second quarter 2026 financial and operational results → Q2 highlights: - Demonstrated the power of extreme vertical integration, delivering revenue growth of 92% year-over-year across Space, Connectivity, and AI - Completed two successful Starship V3 flight tests in the past 90 days, advancing towards full and rapid reusability - Closed multiple industry-leading Cloud Services Agreements resulting in $14.1 billion of contracted sales - Announced agreement to acquire Cursor for $60 billion to accelerate the AI enterprise opportunity - Released our most powerful AI model yet with Grok 4.5 in July - Delivered 66% revenue and 79% income from operations growth year-over-year for the Connectivity segment, driven by a doubling of Starlink Subscribers and continued momentum in Enterprise & Government - Awarded over $6 billion in multi-year U.S. government contracts for Starshield As compared to the same quarter last year: - Revenues of $7.8 billion, up 92% from $4.1 billion - Net loss of $541 million, an improvement of $467 million from net loss of $1.0 billion - Adjusted EBITDA of $3.5 billion, up 191% from $1.2 billion Thank you to the SpaceX team, and all our customers and investors for a great quarter!

We posted our second quarter 2026 financial and operational results → Q2 highlights: · Demonstrated the power of extreme vertical integration, delivering revenue growth of 92% year-over-year across Space, Connectivity, and AI · Completed two successful Starship V3 flight tests in the past 90 days, advancing towards full and rapid reusability · Closed multiple industry-leading Cloud Services Agreements resulting in $14.1 billion of contracted sales · Announced agreement to acquire Cursor for $60 billion to accelerate the AI enterprise opportunity · Released our most powerful AI model yet with Grok 4.5 in July · Delivered 66% revenue and 79% income from operations growth year-over-year for the Connectivity segment, driven by a doubling of Starlink Subscribers and continued momentum in Enterprise & Government · Awarded over $6 billion in multi-year U.S. government contracts for Starshield As compared to the same quarter last year: · Revenues of $7.81 billion, up 91.9% from $4.07 billion · Net loss of $541 million, an improvement of $467 million from net loss of $1.01 billion · Adjusted EBITDA of $3.54 billion, up 191% from $1.21 billion Thank you to the SpaceX team, and all our customers and investors for a great quarter!

📢Meet Qwen3.8-Max — our most capable model to date. Next week, the open weights of Qwen3.8-Max will be released, and Qwen3.8-27B is also going open-weights to meet you all!🎉 Qwen3.8-Max, a new bar for coding and cowork at 2.4T parameters: - Autonomous coding: 10+ days of self-evolving development, from empty folder to production without hand-holding, complete project trace in the GitHub： - Real work, real results: Production-quality deliverables across hundreds of professions. - Long-horizon mastery: System-level autonomous planning with closed-loop adaptive learning, driving 500+ turns of chip design optimization and 365 days of e-commerce strategy. - Native multimodal intelligence: Vision isn't just input — it's a continuous feedback loop for planning, execution, and self-correction. 💰Pricing: Input: $2.0 / M tokens Output: $6.0 / M tokens Implicit Caching: $0.25 / M tokens Start building with Qwen3.8-Max! 🚀 📖 Blog: ✅ Qwen Studio: ⚡ API:

It's been 2 years since La Grande Seine was released on it captures the full incredible story of the making of the #Paris2024# Olympic Games opening ceremony! 🎬 Watch the full film here ➡️: #Olympics#

Simulation mode RELEASED Trade Polymarket against the real order book - real spreads, slippage, fees, and resolution - with none of your money at risk. Practice execution, BBO limit, split/merge, risk, discipline and percent sizing. Full breakdown in the podcast link below.

On July 14, the Department of the Navy released its Strategy to Weaponize Data and AI: a roadmap to an AI-first Fleet that can "out-learn and out-fight any adversary." Within a week, our team answered with working code. The Navy's new strategy frames data and AI as warfighting assets on par with weapons and munitions, and it prizes one thing above all: turning information into decisions, fast. That is exactly the problem our GURU architecture was built for. So when two Navy SBIR topics called for AI-driven maritime tracking and adaptive sensor management, we pointed at the sea what we had already proven in orbit. The video below shows both prototypes, back to back. First, GURU MarineGuard: 787 real vessels from public NOAA data, replayed through a cascade of learned models that forecast each ship's movement, flag deviations from its learned pattern of life, and hand analysts a ranked review queue instead of an unfiltered flood. The full stack runs on a laptop. Second, an adaptive sensor resource manager add-on to MarineGuard: it measures each radar's marginal contribution to each track, projects the consequence of releasing a sensor task before proposing it, and then waits for the operator. Advisory by design. Both inherit their DNA from OrbitGuard, our system watching 14,710 space objects at the SDA TAP Lab with 94 to 96 percent maneuver-detection accuracy. Same architecture, new domain, days not years. These are prototypes, and we say so on screen. The trajectories are real. The sensor numbers are deliberately notional. No score is a threat call. Showing your assumptions is a capability, not a caveat, and national-security guidance now demands exactly that: AI that is reliable, robust, steerable, and controllable under rigorous test and evaluation. Our doctrine was written for that bar. Learned models accelerate and rank. Validated references confirm and decide. Humans stay in command. One architecture. Space, maritime, autonomous engineering, regulated nuclear autonomy. This is simply the latest sign of what this team fields, fast, where mistakes are not allowed. Sailors, engineers, program folks: what mission should GURU learn next? #DefenseTech# #ArtificialIntelligence# #MaritimeDomainAwareness#

opus 5 is a VERY interesting release for a few reasons 1. it showed that the general benchmarks we use today are almost completely useless now opus 5 is nowhere near fable in practical use, not even close. anyone who’s used it meaningfully can tell this very quickly after a few tasks. yet opus beats fable on many benchmarks i now trust domain specific benchmarks built with private datasets a lot more than the popular ones. perhaps the future is everyone running their own evals because the public ones are really not telling us much 2. it seems with the 5 series, anthropic is trying a new way of training models previously, the same generation of sonnet and opus were often released at the same time or sonnet comes out before opus, which indicates sonnet and opus were trained by separate pipelines in parallel with the 5 series, it was very clear that they trained mythos first, and then distilled it into sonnet and opus. it seems this approach has a big influence on the models seeing sonnet 5 being a flop and opus 5 getting pretty mixed reviews already, i’m not sure this is working out 3. “how pleasant is it to work with the model” used to be a strength in claude, but now it’s not. honestly, grok is my favorite right now on the “pleasant” dimension. kimi is not bad either it feels like both anthropic and openai are giving RLHF less care, in favor of scalable RL that’s machine verifiable this almost looks like AI is directing humans to build a world that’s more friendly for machines rather than humans, and most humans don’t even realize they are being manipulated to help with that almost every new generation of frontier models now talk more jargons, need more steering to do what you want, and are just less fun to work with if this continues, AI will start to speak their own language that looks like English but average humans can’t understand. they will choose to do things that their human user never asked for. are we already failing at alignment?

When words were no longer needed… Released in 1999, “Communication” became one of the defining records of Armin van Buuren’s early career—and a timeless monument of classic Trance.