Duke of AI
Duke's Tech Knowledge Database Living Handbook · v13 · Compiled 15 September 2026

Big Tech Industry, Legal & Business

Core Principles

  • Legal action between major AI/tech players is increasingly a proxy fight over the next hardware platform, not simply a dispute over a specific document or piece of code.
  • Movement of senior technical/design talent between major tech companies is a leading indicator worth tracking.
  • Proposals that blend government and private AI-company ownership or stakes are treated as commercially and politically significant enough to generate independent commentary about conflict-of-interest risk.
  • Government regulatory action against a specific frontier model can arrive and reverse within weeks, and third-party commentary on the same event can vary significantly in framing (DK-5 vs. DK-6). By v10 this pattern has broadened well beyond a single Anthropic episode — see the new General Operating Principle on pre-launch government review.
  • Speculative product-roadmap coverage is a recurring content genre running in parallel to confirmed announcements, held to the same "reported, not verified" discipline as AI-model rumors elsewhere in this Handbook (DK-20).
  • China's rapid AI progress despite U.S. chip export controls is prompting explicit strategic concern from U.S. policy officials, with commentators framing China's open-source AI strategy as a deliberate move to expand global technological influence (DK-40, DK-43).
  • NEW (v10) — Major frontier labs are racing each other to public markets on a compressed timeline, and each filing changes the valuation comp the next one has to price against: Anthropic filed confidentially for an IPO less than a week after its $65B Series H pushed its valuation to $965B (DK-63); OpenAI filed confidentially just over a week later despite reportedly missing internal growth/revenue benchmarks (DK-66's predecessor context, DK-58's precedent). SpaceX, in the same window, priced the largest stock offering ever — see Space, Robotics & Emerging Hardware — underlining that 2026's AI-adjacent IPO wave spans compute infrastructure as much as model labs.
  • NEW (v10) — Custom AI silicon has become table stakes for every major lab, not just a hardware-company initiative: OpenAI (Jalapeño, with Broadcom), Anthropic (a newly reported in-house chip team, alongside explored Samsung partnership talks), and Google (an internally-reported "Frozen v2" chip) are all now pursuing purpose-built inference silicon in parallel, each citing cost/efficiency rather than a single headline capability jump — reinforcing this Handbook's existing framing that cost and speed improvements are now as newsworthy as capability jumps.
  • NEW (v10) — The traffic/citation relationship between AI answer engines and the publishers whose content trains and grounds them is emerging as its own contested economic story, distinct from copyright litigation: platforms with real negotiating leverage (Reddit, cited as the single most-referenced source in AI answers by some measures) are reportedly reconsidering data-licensing deals as they come up for renewal, against a backdrop of steep reported traffic declines at several publishers whose content still feeds AI Overviews.
  • NEW (v11) — The circular-investment loop this Handbook has noted in passing (DK-76) now has a fully articulated bear case attached to it, and it deserves recording as a named position rather than left implicit. Ed Zitron argues that roughly 70% of AI revenue across the major cloud providers comes from OpenAI and Anthropic — two companies he describes as unable to exist without money from those same providers — and that the sector's capital expenditure cannot be justified by the revenue it produces. EVERY FIGURE IN THIS ARGUMENT IS HIS CLAIM ON A PODCAST AND IS UNVERIFIED HERE (DK-86). The part that does not depend on his arithmetic: unlike railways or fibre, he argues AI GPUs have no post-bubble second use, so the usual consolation that a burst bubble leaves useful infrastructure behind would not apply.
  • NEW (v11) — As the cost of building software collapses, the defensible asset moves from the product to what surrounds it. Two independent-of-each-other observations point the same way: a bespoke internal tool can now be built in a week that would previously have taken months, and the same collapse means any such tool is replicable by everyone else just as fast. The proposed answer — that a tool bundled with training, community, events and a personal reputation is defensible where the tool alone is not — is a business hypothesis this Handbook can test over time, not an established finding (DK-84).
  • NEW (v12) — The clearest adoption finding this Handbook holds, and it inverts the jobs story: the gap is not between people and machines, it is between firms. OpenAI's own research puts the distance between frontier firms (top 10% of usage by output tokens per active user) and typical firms at 8.3x by the end of June, up from 2.6x in January and about 2x for all of 2025 (DK-100). Frontier firms now use seventeen times as many tokens as eighteen months ago; average firms about twice as many.
  • NEW (v12) — What separates those firms is cheap and unglamorous. At typical firms 9% of weekly active users use plugins and 3% use skills; at frontier firms it is 21% and 19%; at OpenAI itself 95% and 93% (DK-100). The differentiator is not spend or model choice but whether anyone has set up reusable instructions and connections — which means even the frontier firms are early.
  • NEW (v12) — Sam Altman has publicly revised his own timeline and given the reason: "I thought when we got to GPT-4... that very quickly after that there was going to be much more disruption... I think I was wrong about a few things, but one in terms of the speed. The economy just has so much inertia" (DK-100). Recorded because this Handbook holds a large number of confident timelines, several of them his, and because institutional inertia is the same force that makes an archive of them worth keeping.
  • NEW (v13) — Work done inside a lab's product is not clearly insulated from that lab's own competing work. OpenAI's own wording on the Navier-Stokes dispute is the durable part: researchers and agents did not see the mathematicians' work, no specific user data was accessed, but "while unlikely, we cannot rule out that deidentified data derived from the usage of our products helped improve our models" (DK-109). That is the answer to the question every professional user now has, and it is not no.

Key Facts & Examples

  • Apple filed a lawsuit against OpenAI alleging improper acquisition of confidential hardware-related information, centered on former Apple employees who moved to OpenAI (DK-2). NEW (v10) — OpenAI publicly responded in a blog post titled "Apple is getting this wrong," calling the suit careless, aggressive, and oddly personal, and stating Apple never raised the allegations before suing (DK-79); the underlying allegations remain litigated, not established fact.
  • The dispute is connected by commentators to OpenAI's hardware partnership with Jony Ive, read as evidence OpenAI is building AI-native consumer hardware centered on voice interaction (DK-2). NEW (v10) — OpenAI and Jony Ive are reported to have debuted their first device, described as a $300 hockey-puck-sized AI smart speaker (DK-80) — treat as reported, not confirmed spec, pending fuller coverage.
  • Reports that OpenAI considered offering the U.S. government a 5% ownership stake — independent commentary raised conflict-of-interest concerns (DK-5). NEW (v10) — this was reported in more detail as a specific proposal (~$42.6B against an $852B valuation) that would also ask Anthropic, Google, Meta, and xAI to each contribute a similar 5% to a shared public wealth fund modeled loosely on the Alaska Permanent Fund; commentary explicitly links the timing to GPT-5.6's delayed release and the Fable 5/Mythos 5 export-control episode, reading the proposal as trading equity for political goodwill (DK-71).
  • A rumor-analysis source frames Anthropic's June–July Fable 5/Mythos 5 disruption as a structural AI-governance story (DK-6). NEW (v10) — the Commerce Department reportedly lifted the restrictions around 30 June 2026 (DK-70).
  • Commentary on Kimi K3's release frames it as evidence that Chinese labs engineered around U.S. chip export restrictions (DK-40, DK-43).
  • Apple reportedly pays another AI company roughly $1 billion per year for AI services (DK-42).
  • NEW (v10) — Anthropic filed confidentially for an IPO, lands less than a week after a $65B Series H valuing it near $965B, with revenue run-rate reportedly past $47B (up from $9B at end of 2025); Goldman Sachs projected 2026 US IPO proceeds could reach a record $160B, roughly quadrupling 2025, driven by AI listings (DK-63).
  • NEW (v10) — AMD is reported to be selling Anthropic tens of billions of dollars' worth of AI servers and investing up to $5 billion in the company; Anthropic plans to buy up to two gigawatts of AMD's Instinct MI450 chips from H1 2027. Nvidia has separately been reported to be discussing a $30 billion investment in OpenAI — described in the source as another turn of the industry's circular investment loop (DK-76).
  • NEW (v10) — Anthropic is reported to be hiring engineers with chip-design experience to build custom silicon and co-design hardware, on top of existing infrastructure deals with AWS, Google, Nvidia, and AMD and explored Samsung partnership talks; Google is separately reported to be internally designing a server chip ("Frozen v2") to run Gemini more efficiently, expected around 2028 and potentially 6–10× more efficient measured in tokens per unit of power (unconfirmed by Google) (DK-75, DK-80).
  • NEW (v10) — Samsung Electronics is rolling out ChatGPT Enterprise and Codex to staff in South Korea plus all Device eXperience employees globally — described by OpenAI as one of its largest enterprise deployments to date; Codex weekly actives reportedly exceed 5 million, with Korean weekly actives up nearly 800% since February (DK-68).
  • NEW (v10) — Netflix confirmed it paid $587 million for InterPositive, an AI filmmaking startup quietly founded by Ben Affleck in 2022 and run in stealth mode. Netflix says generative AI has been used on ~300 of its productions this year, mostly in post-production, and more than 10% of recent Hollywood job postings now list AI skills (DK-80).
  • NEW (v10) — Per a Wall Street Journal report, Reddit is weighing whether to end Google's access to its content for AI training when a 2024 deal (worth ~$60 million/year) comes up for renewal; Reddit's stock fell ~8% on the news. Reported traffic figures cited alongside this: between June 2025 and June 2026, Politico's Google traffic fell 23%, CNN's 25%, and Business Insider's 85%, while AI Overviews continued to answer queries using those same publishers' content. Reddit is described as now the single most-cited source in AI answers by some measures, ahead of Wikipedia and YouTube (DK-77).
  • NEW (v10) — The Trump administration is reported to be banning imports of new foreign-made humanoid robots, robot dogs, robot vacuums, and power inverters on national-security grounds, via an expanded FCC "advanced robotic devices" definition; the move largely targets China, which is described as holding over 85% of the humanoid and consumer robotics market (DK-78). See Space, Robotics & Emerging Hardware for the robotics-specific detail.
  • NEW (v10) — SpaceX priced the largest stock offering in history in June 2026, raising $75 billion at a $1.75 trillion valuation; see Space, Robotics & Emerging Hardware for the full compute/orbital-infrastructure thesis underlying that valuation (DK-66).
  • NEW (v11) — Zitron's specific claims, recorded as claims: Amazon sending $50bn to OpenAI and $5bn to Anthropic this year and Google $10bn to Anthropic; Microsoft FY2026 AI revenue of about $34.33bn (attributed to Bloomberg) of which $24.1bn came from OpenAI, against $115bn of capital expenditure and an intended $175bn next year; OpenAI losing $20.9bn last year; Semi Analysis finding a $200/month ChatGPT subscription can consume $14,000 of tokens and Anthropic's $8,000; Uber exhausting its annual token budget in three months; and Nvidia selling $215.9bn of GPUs in its last fiscal year. He also argues the "annualised run rate" figure labs quote is never defined and varies between uses (DK-86). None of this is verified here and none should be repeated as fact without checking.
  • NEW (v11) — The counter-case as put to him on the same programme, recorded because a one-sided entry would misrepresent the source: 88% of organisations use AI for at least one business function, and 95% of the host's own staff use a chatbot daily. Zitron's answer is that adoption under default-on pressure — Gemini in Google Docs, Copilot in Word — is not evidence of value, and that enterprises objected as soon as they were asked to pay actual cost; he quotes Sam Altman calling that "a huge issue" (DK-86). This is the weakest link in his case, since it substitutes an assertion about motive for evidence.
  • NEW (v11) — A first-hand cost datapoint on software build economics: Steven Bartlett's company replaced a commercial applicant tracking system it had been paying tens of thousands a year for by building its own in roughly a week, and reports the bespoke version is better than what it replaced. Daniel Priestley estimates the same build would previously have cost around £500,000 over 18 months — an estimate offered in conversation, not a costed figure. Priestley's related claim is that software companies once needing 20-30 developers and around 10,000 customers to break even can now be profitable at 500-1,000 customers in a narrow niche (DK-84).
  • NEW (v11) — On legal services specifically: Bartlett reports a case quoted at around £50,000 to begin with a law firm which he instead resolved using Claude on a $20/month subscription, which produced decision-tree options, the required documents and a negotiation script. Their conclusion is not that lawyers disappear but that the billable hour for regurgitating contracts does. Two figures given in the same conversation are unsourced and should not be repeated: that legacy legal tech and data firms lost roughly 20% of their value in 2026 with $280bn wiped off in a single week, and that Spotify's best developers have not written a line of code since December (DK-84).
  • NEW (v11) — An energy-arms-race framing is now explicit in the source material: that every major player will need its own Colossus-scale facility, and that the existing US grid cannot support that on a timescale of years rather than decades. The most checkable claim offered is a build-speed comparison — El Capitan, the supercomputer monitoring the US nuclear arsenal, took Hewlett-Packard around eight years, while phase one of Colossus was built in 122 days and doubled from 100,000 to 200,000 GPUs in a further 92 (DK-89, unverified). See the General Operating Principles for why two of that source's headline figures are excluded entirely.
  • NEW (v12) — The agentic crossover, traced in enterprise output tokens: essentially all ChatGPT before October 2025; 87% chat to 13% agentic in February; 73/27 in March; agentic passing half at 53% in late April; and 36/64 by June, where the data ends (DK-100). Output tokens are used as a proxy for volume of work done, not for how often someone sits down at the tool.
  • NEW (v12) — The shift is concrete inside a single profession. In legal work done through chat, 57% is writing and 20.5% knowledge retrieval, with system operation at 0.2%. In agentic legal work, writing falls to 16.2% and retrieval to 8.3%, while system operations rises to 17.7%, workflow automation to 7.7%, and coding — building applications, by people who are not software engineers — to 32.9% (DK-100).
  • NEW (v12) — CNBC tallied Nvidia's AI investments and commitments at $99bn, a figure the source claims exceeds the cumulative assets under management of every venture firm on earth (DK-93). Nvidia reported $42.3bn invested in private companies as of March (DK-100). The argument offered against calling this circular is that Nvidia owns no fabs, so its own growth is capped by suppliers it does not control, and investing outward is the only route it has to grow demand.
  • NEW (v12) — Taiwanese prosecutors charged nine people over smuggling Blackwell 300 systems to China, including a manager in Nvidia's distribution business and two people at Supermicro; of 130 servers ordered, 74 reached buyers in China and 56 were stopped (DK-100). Fewer than 10,000 chips — real, but as the source notes, nowhere near enough for a frontier training cluster.
  • NEW (v12) — On employment the same week's panel cited roughly 1 million US positions now classified as AI jobs, LinkedIn's estimate of 640,000 AI-specific jobs created between 2023 and 2025, about $500bn a year in additional infrastructure spending supporting electricians and HVAC technicians, and Principal Financial Group data across 100,000+ small-business clients showing 60%+ adding jobs because of AI against 1.4% losing them (DK-93). All are cited on air rather than independently verified, and the panel states its mission as keeping listeners optimistic.
  • NEW (v13) — The Navier-Stokes dispute, which should be carried as a live dispute rather than a result. OpenAI published a solution to one of the seven Millennium Prize problems, of which only one had been solved in 26 years, using an internal model described as significantly more capable than Astra (DK-104, DK-109, DK-103). NYU's Tristan Buckmaster published an account saying he and an Anthropic employee had worked on the problem for over a year using Codex, that he asked whether the model had been trained on their sessions and did not get an answer on training, that he was offered co-authorship conditional on removing his Anthropic collaborator, and quotes the reply to his threat to go public as "why would you ruin your career?" OpenAI's Sebastian Bubeck called the allegations false and inflammatory and published part of the message chain.
  • NEW (v13) — Two second-hand accounts of the same result are materially incompatible and both appear in this batch: one describes a swarm of 10,000 AIs over 88 hours costing around $15m (DK-111); another reports an internal OpenAI model over a week or two costing several million (DK-109). Neither is first-hand. Record the conflict; do not average them. The speed with which an unverified figure hardened across sources in one week is itself the finding.
  • NEW (v13) — Nvidia's acquisition of Hugging Face is confirmed, having been rumour the previous week (DK-101). The reading offered — interpretation, not company statement — is that it is a bet on open weights: as Meta, OpenAI and Google build their own silicon, Nvidia's growth case shifts towards enterprises and individuals running open models on their own hardware.
  • NEW (v13) — A class action has been filed on behalf of Claude Max subscribers alleging the $100 "5x" and $200 "20x" plans do not deliver five and twenty times a $20 plan's usage, because of how five-hour and weekly limits are calculated (DK-109). The lawyers' stated reason for taking it is the more interesting part: they were hearing from workers who felt they had to pay for a top-tier subscription to stay employable and did not believe they were getting what they paid for.
  • NEW (v13) — Funding and listings, September 2026: ElevenLabs hired a CFO from Adyen and is reported to be exploring an IPO, on track for $600m annualised revenue from $350m a year earlier, reportedly profitable with over half of revenue from large enterprise; Cognition raised $2bn at $48bn, up from $26bn in May, with revenue run rate reported going from $492m to almost $900m (DK-109).
  • NEW (v13) — SpaceX's shape has changed: it is now described as as much an AI business as a space business by revenue, following a $75bn IPO. Compute rental is called "a heck of a business" with no drop in demand, and is a new customer base for the company (DK-112).
  • NEW (v13) — Where the labs are moving as access stops being chargeable: downstream into deployment corps, forward-deployed engineers and service contracts, and into revenue-share arrangements where a company gets access to capability in exchange for a share of what it earns (DK-111). If accurate this is a different business from selling tokens and should be watched as such.

Source Articles: DK-2, DK-5, DK-6, DK-20, DK-40, DK-42, DK-43, DK-56, DK-58, DK-59, DK-63, DK-64, DK-65, DK-66, DK-67, DK-68, DK-70, DK-71, DK-75, DK-76, DK-77, DK-78, DK-79, DK-80, DK-84, DK-86, DK-89, DK-93, DK-100, DK-101, DK-103, DK-104, DK-109, DK-111, DK-112

Version 13, compiled 15 September 2026. 112 source entries (DK-2 – DK-113). Claims are recorded as their sources framed them; figures described as claimed or reported are not independently verified.