What did Aaron Donald think of the late penalty that took the Rams interception off the board?
"Rough call ... can't do nothing now. Woulda, shoulda, coulda but it is what it is."
@CBSLosAngeles #
RamsHouse#
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🦔Someone is buying Japanese used books by the ton. Not novels or comics. Philosophy, history, medical law, Edo-period cultural texts. Multiple buyer accounts all ship to one logistics center in Okayama Prefecture that won't answer questions. Export records show over 50 tons, roughly 100,000 volumes, shipped to the US since last year. No buyer has been identified.
Separately, court documents confirmed Anthropic's "Project Panama" bought millions of books in the US, cut the spines off, scanned them, and shredded the originals. An internal memo said the goal was to "destructively scan all the books in the world." Similar operations have been reported across Europe.
My Take
Anthropic's US book operation came out in court filings earlier this year. Project Panama. Millions of books, cut the spines off, scanned, shredded. Their VP chose the codename so nobody outside the company would find out. That story broke and apparently the same operation just moved to Japan. Anonymous buyer accounts, a warehouse in Okayama that won't take questions, and 100,000 volumes of specialized academic texts that nobody buys to resell.
I don't know how you build a trillion-dollar industry on material you had to acquire in secret through middlemen because you knew the public would object. Authors spent years on those books and now they're fed through a scanner and thrown away so a chatbot can sound smarter. If the data was free to use, they wouldn't need codenames and anonymous warehouses. The lawsuits over who owns this material have barely begun and I think the copyright exposure across the whole AI industry is enormous. Anthropic's internal memo said the goal was every book in the world, which describes the foundation of the product.
Hedgie🤗
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🚨 OMG. President Trump has Xi CRACKING UP in how he presented the Biden autopen portrait
"TRUMP, and then TRUMP...and this is the autopen!"
*Xi begins laughing*
"It's BIDEN!"
This man is absolutely priceless 😭😭
Even the other members of the Chinese delegation are cracking up!
Aside from showing off the helipad, this might be the highlight of Trump's morning 🤣
Trump first put up this autopen portrait roughly 1 YEAR AGO on the "Presidential Walk Of Fame" and it's remained up ever since!
Welcome to the Trump White House 🔥
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Grok 4.7 works really well with Blender. I’ve been using them to create these rough Raptor engine 3D models, and the improvement in quality is huge.
They’re still early versions, but the details are already coming together beautifully.
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Rough back of the envelope math: if 40% of US physicians are OpenEvidence DAUs and there's ~22 workdays a month, 42m queries in August implies ~5 queries per workday day per physician (Google is ~4.2 searches per day and ChatGPT is ~2.5 queries per day).
This kind of pulse on real-time clinical uncertainty is remarkable. Imagine you could now categorize those queries: see for which flavors of clinical uncertainty existing knowledge / solutions are most scant (or don't exist at all) and then plug in that knowledge / those solutions, fund studies / initiatives to create that knowledge / those solutions, etc. You see how OpenEvidence's flywheel will start to spin a lot faster than the labs in terms of capabilities.
It's all about your product enumerating demand in some valuable subset of economic reality faster than competitors. In this case, OpenEvidence enumerates physician demand for information / capabilities that can help solve patient problems. They do this faster and with higher fidelity than anyone else. This is incredibly valuable.
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Stunning stat: "Anthropic’s investors are expecting the company to reach a valuation of $2tn when it goes public in the coming weeks. Add in SpaceX, which began trading at $2tn after its IPO in June, and OpenAI, which is considering raising money privately at $1.2tn ahead of a public listing next year, and these companies alone could be worth well north of $5tn. Now compare that with the entire history of IPOs from 1980 to 2025. The 3,365 tech companies that went public in that period were worth a combined $4.1tn when they started trading."
While I've written much about AI's transformative potential across sectors, I've always been dubious about how much value hyperscalers can seize enabling that transformation. As I dissect in my recent report on "The AI Trade" ( it's not about user acquisition. OpenAI claims to have over one billion active users across its services and two million businesses using its AI models. Anthropic has claimed to have more than 300,000 business customers. The question is not whether they can bring users to their services, but rather how much average revenue they can generate per customer relative to the price of building and maintaining their models. The cost of compute is inflating at the same time competition is depressing token pricing power. That's a precarious dynamic when so much hinges on the success of two companies.
To again quote the report:
"It’s hard to overstate how much hinges on these IPOs. As mentioned in the Executive Summary, OpenAI and Anthropic will account for 13% of AWS revenue and 27% of Google Cloud revenue this year. As for Microsoft, OpenAI alone accounts for roughly 70% of its AI-specific revenue ($24.1 billion out of an estimated $34 billion total for the fiscal year ending in June 2026). OpenAI has committed to tens of billions of spending on chips from the likes of Nvidia and Broadcom. Deepening circularity concerns, tech giant earnings growth has been increasingly driven by paper gains in the private-market valuations of Anthropic and OpenAI. In Q2, Amazon, Alphabet, Nvidia, Meta, and Microsoft reported $160 billion in cumulative “other income”, trouncing the $69 billion in “other income” reported in Q1. To quote the FT: “These one-off valuation boosts, derived in large part from enthusiasm around AI, risk distorting the financial picture at a time when investors are closely scrutinizing tech earnings.” If either Anthropic or OpenAI stumble in their IPOs, it’ll hit tech giants on multiple balance-sheet fronts and likely ripple through the US and global economy. A pin-prick popping of the AI bubble may not be our base case, but if a pin is out there, it’s likely the revenue versus spending trajectories of Anthropic and OpenAI."
FT link:
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What does long-term innovation look like?
In 2025, Huawei invested approximately US$27.5 billion in R&D, equal to 21.8% of annual revenue, or roughly $1 out of every $5 earned. The company also ranked 6th among the world's leading R&D investors.
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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.
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We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics.
The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra.
The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.
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