与「STUDY×」相关的搜索结果

BCH-1 Alumni Update 🚀: @CashMintLabs , AI Agents Thirty days ago we wrote about CashMint's AI Agents on the eve of its launch: a Hackcelerator runner-up, audited contracts, and a plan to give an AI agent its own economy. The month since has been a case study in what that actually looks like. The agent works for a living. Minty's job board on shows a public ledger of paid assignments: sponsored coverage, analytics charts, research tasks, each priced in BCH, each delivered on-chain. Gig number 73 went through last week. The agents page now lists a second hire in waiting, CashGuard, an AI that audits CashScript contracts. An AI labor market, small but real. The token worked as designed. MINTY graduated its bonding curve in four hours. It trades on Cauldron and Guanaco, climbed to a top-ten Cauldron ranking in nine days, and 85% of its liquidity is burned. Revenue share, fair launch, no presale, no insider allocation. What we said on September 14 holds: agent economies need cash-like fees to be a business model. Thirty days in, one is running. The pipeline is active. More updates as teams hit milestones. $BCH

New Coin Launch: NFT (Trading-Withdrawal Schedule) @AINFTcom . ethereum:0x198d14f2ad9ce69e76ea330b374de4957c3f850a is now available on Bitkub! . - Check the current price of NFT at: . Cryptocurrency and digital tokens involve high risks; investors may lose all investment money and should study information carefully and make investments according to their own risk profile. . #Bitkub# #BitkubExchange# #NFT# #AINFT#

Researchers proved AI has deleted every reason universities exist. Harvard University ran a controlled experiment pitting a custom AI against their own top-tier classrooms. And the results are going to collapse the higher education bubble. They took 194 undergraduates and split them up. One group learned physics in one of Harvard’s best hands-on, active-learning physical classrooms. Group work. Instructor support. The premium university experience. The other group went home and learned the exact same material with an AI tutor. The AI didn't just win. It embarrassed the institution. Students using the AI learned more than twice as much as the students in the elite Harvard classroom. They scored 30% higher on the final assessment. And they did it in less time. Let that sink in. A piece of software sitting on a laptop outperformed a world-class faculty in one of the most elite learning environments on Earth. Universities have always justified their exorbitant tuition with two things: access to elite knowledge and the physical classroom experience. This study just proved both of those moats are gone. When software can teach you complex physics twice as well as a $60,000-a-year institution, the math of higher education breaks permanently. The AI didn't just give the students answers. It used strict pedagogical guardrails. It guided. It questioned. It forced the students to do the cognitive work. It offered perfect, one-to-one tutoring, personalized to the exact moment a student misunderstood a concept. That level of attention is mathematically impossible to scale in a physical lecture hall. For a thousand years, the university was the only place to get a premium education. Now, it’s the bottleneck. If AI can double your learning speed for a fraction of the cost, what exactly are students taking on decades of debt to pay for?

The “50,000 in Five Years” initiative—inviting 50,000 young Americans to China for exchange and study—has already exceeded its goal, two and a half years ahead of schedule.

Grok Bot Summary of SpaceX CFO Bret Johnsen at Goldman Sachs Communacopia today. Vertical integration Vertical integration is the company’s core operating model, not a side strategy. - Rockets: own metal → engines → avionics → software - Starlink: own launch, satellites, and the end customer - AI: build facilities and power themselves, run their own models, sell to consumer and enterprise, and soon orbital compute Starship and launch Starship is the foundation for every other business. - Flight 13: big learning flight. Delivered demo V3 payloads, relit a Raptor, and got a soft, precise second-stage splashdown. Recovery team towed the stage back so engineers could study the heat shield. - Those learnings feed straight into Flight 14 and beyond. - Flight 14 (later this month): first revenue-generating Starship flight, flying production V3 Starlink satellites. - Later this year: aim to recover both first and second stages. Orbital compute Most of the AI industry agrees orbital compute is the future. Almost everyone else thinks it’s many years away. SpaceX disagrees because they control the stack. - Target: first orbital compute satellites next year - Scale: big compute in space into 2028 - Hardware approach: same V3 bus as Starlink, swap the payload, add larger solar arrays Why orbital can beat terrestrial on cost The crossover is about Starship reusability. - Falcon 9: first-stage reuse since Dec 2015; 500+ booster reflights - Starship: first stage already recovered/reflown; second-stage recovery progressing - Goal: reflight of both stages as soon as next year, which drops deployment cost sharply Terrestrial compute is getting more expensive (power, cooling, buildings, real estate). Orbital rides the opposite curve: cheaper rockets + better/cheaper satellites + scale. Johnsen said cost parity could come as soon as next year. Terrestrial compute and the $100B ARR goal - End of this year: on track for ~$100B ARR (annualizing the December number) - New update: another hosting deal closed earlier this month → about $1.1B/month starting Dec 1 → roughly +$13B ARR - Capacity: end this year well over 2 GW; next year 5–10 GW deployed - Confidence comes from line of sight to power, facilities, and permitting, plus being NVIDIA-exclusive for allocation - They stand compute up fast for themselves and for industry partners, which strengthens the NVIDIA relationship How they monetize compute Most hosting deals are short: ~90 days with a 90-day out (~6-month commits), including the newest deal. Why keep them short? - High conviction in their own products (Grok, Grok Bot, Cursor team after closing that deal) - Don’t want to lock forever capacity they may need internally - Internal bar: don’t let internal monetization fall below external hosting Earnings framing for next year: roughly $30–$50 per watt monetization range; they said they’re at the high end. Hosting customers appear to monetize even higher, which is why demand stays strong. Payback is under one year on new compute capex, so residual GPU value and financing options look attractive. “Not all CapEx is the same” — GPUs with <1-year payback are different from a launch tower built for decades. AI products and M&A Historically SpaceX was almost all organic growth. This year they did M&A because the AI product cycle rewards speed to frontier. - Closed Cursor deal weeks ago; product cycles already accelerating (called out Grok Bot) - Grok 4.6 improved on 4.5; 4.7 coming soon - Pitch: best infrastructure + competitive model + lower token cost = best position for customers - Market mood shift: months ago people bought the infra story but doubted the products; ~90 days later that skepticism is fading Starlink broadband Started as “better than nothing” (~2020–21). Now enterprise-grade with strong uptime/SLAs. - Resiliency pitch: boards will ask why Starlink wasn’t in the network if you go down - Mobility: aircraft backlog is large and production is ramping; cruise ships, yachts, trains too - Awareness, especially outside the US, is still a growth unlock - Longer-term: physical AI (robots, cars, aircraft) will need always-on connectivity terrestrial networks can’t fully cover Mobile / direct-to-cell Not a distraction. Same V3 bus, different payload. - Fly direct-to-device satellites through next year - Target service turn-on: first half of 2028 - V1 today (e.g. T-Mobile / T-SAT): text / light voice, great for emergencies and dead zones - Next gen: full 5G-quality from space - US: mid-band spectrum from EchoStar, FCC path for space + terrestrial - Go-to-market: flexible — own terrestrial build, or partner with carriers - International: same regulator-by-regulator playbook as broadband (Starlink now in 170+ countries) Near-term priorities: 1. Starship (enables everything else) 2. Terrestrial compute (funds growth and teaches them how to do orbital) Bottom line in one line Own the full stack, make Starship reusable at scale, use terrestrial AI compute as a cash engine now, and use the same satellite bus + Starship cadence to win broadband, mobile, and orbital AI.