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Century Report

Token Cost Crosses Labor Cost - TCR 05/30/26

Fortune 500 AI budgets exhaust in two months as per-token cost crosses human labor, Texas registry shows Waymo at 577 versus Tesla's 42 unsupervised robotaxis.

Ben Linford

Ben Linford

— 22 min read
Century Report infographic: AI cost curve crossing labor line, Texas AV registry showing Waymo 577 vs Tesla 42, Waymo Ojai robotaxi, FDA drugs, germline editing news.

The 20-Second Scan

Track all of the arcs The Century Report covers here:

Progress & Claims Tracker

The 2-Minute Read

The signal across yesterday's developments traces the institutional architecture of the AI era being assembled at every layer the prior decade left underdesigned. Enterprise buyers are publicly naming the per-token cost trajectory unsustainable for the first time, with Glean's CEO describing AI capability as the first technology in modern history priced at the same scale as labor. Wix and SentinelOne announced layoffs the same week to fund AI investment. Apollo and Blackstone began shopping $36 billion of debt to buy Google TPUs that Anthropic will lease. The capital scaffolding is reorganizing around whether productivity catches up to the bills.

The deployment and verification layers compounded in parallel. Texas's new mandatory autonomous-vehicle registry made the camera-only-versus-sensor-fusion bet legible: 42 Tesla Robotaxis against Waymo's 577 in the same state. A humanoid-robotics startup began recording inside private homes to build the training corpus the labs lacked. The FDA opened needle-free insulin for pediatric use and granted Breakthrough Therapy designation to a targeted KRAS G12C lung-cancer drug. The instruments of medicine and robotics are landing in deployable form as the cost curve is bending.

The friction layer arrived through the vocabulary forming around what these systems produce. A 9-gigawatt data-center proposal in Utah was defended through unsupported allegations of foreign botnet influence directed at residents asking material questions about water and electricity. California passed an amendment extending age-verification to every browser and website. A Canadian entrepreneur announced plans to genetically modify human embryos, framing the 2019 international moratorium as a coordination instrument the next generation of capital will route around. The institutional response is forming at the speed the capability is moving underneath.

The 20-Minute Deep Dive

Tokens or Humans: the Quarter Enterprise AI Cost Crossed Labor Cost

Enterprise AI buyers spent the week absorbing what Glean CEO Arvind Jain and Factory AI CEO Matan Grinberg both described to CNBC as the inflection where the cost curve of intelligence stopped behaving the way the prior decade taught buyers to expect it to. Annual AI budgets at Fortune 500 companies are getting exhausted inside two months. Each new frontier model release lands at roughly twice the per-token cost of the version it replaced. The pattern has put enterprise AI on what Jain called "an unsustainable path right now," and the trade-off being named openly inside CFO conversations - tokens or humans - is the one the prior decade kept implicit.

"This is the first time ever that I can remember that technology costs the same as people, and you're making that comparison: choose tech or people," Jain told CNBC. "We've never had that conversation historically, because tech is a fraction of the overall cost of any operating business." The growing AI budget, he said, increasingly comes in lieu of future headcount growth.

Grinberg described buyers moving through three distinct phases in roughly a year. Board pressure to "do something about AI" came first. Then tokenmaxxing - the phase of using premium frontier models for every task regardless of cost. The third phase, where the buying side now sits, is reassessment. Roughly 95% of enterprise AI usage runs on the most expensive frontier models, even for tasks that could ship on cheaper tiers. Routing the easy work down can produce a ten-fold cost reduction without changing the workload itself. "Do we need to be using Opus-level intelligence for every single task?" Grinberg asked. "You just don't need to."

What the Glean and Factory framing makes visible is that the AI capability trade - the assumption that demand will hold at current price points because cost is no object for the buyer - sits on a foundation buyers are now actively questioning. Jain put the underlying gap directly: "The value that AI drives at this point is trailing the cost that businesses are incurring." The first time technology costs the same as people, the optimization problem turns on which model tier matches each workload, and the headcount question reshapes alongside it. The companies whose budgets are exhausting in eight weeks are not the only ones doing the math. Uber's COO Andrew Macdonald named the same dynamic on the record in the May 26 edition of The Century Report, describing a company that had exhausted its full 2026 AI budget four months in with no clear line connecting token spend to shipped consumer features. Glean itself crossed $300M in annual recurring revenue by selling that math back to buyers as its primary value proposition. The labs whose pricing produced the exhaustion are doing it too.

Texas's New Registry Shows Tesla at 42 Robotaxis While Waymo's Purpose-Built Ojai Lands

Texas's new mandatory autonomous-vehicle registry made visible this week what a decade of competing claims had left ambiguous: the number of unsupervised robotaxis each operator actually has on roads. Tesla, whose CEO said in 2025 the service would reach "half the population of the US by the end of the year," registered 42 unsupervised Robotaxis in the state. Waymo registered 577 in the same state, with a nationwide fleet exceeding 3,000 across active service markets. Amazon's Zoox registered 317. Nuro's number was 47.

The gap is the public ledger of the architectural bet that has structured the industry for a decade. Tesla's camera-only approach assumed neural networks trained on enough video data could match what sensor-fusion stacks achieve through redundant lidar, radar, and high-definition mapping. The registry data shows where that bet sits as of this week: behind, by an order of magnitude, in the same jurisdiction where Tesla launched the service.

In the same news cycle, Waymo unveiled the Ojai, a four-seat purpose-built robotaxi co-developed with Geely subsidiary Zeekr, deploying first to select riders in San Francisco, Los Angeles, and Phoenix. The Ojai is the first Waymo vehicle designed from the wheels up around the autonomy stack, replacing the retrofit-Jaguar architecture the fleet ran on through 2025. The hardware substrate of the leading US autonomous-vehicle operator is now a Chinese-manufactured platform purpose-built for the workload. The Geely partnership announced in 2021 has matured into shipping vehicles four years later, and the deployment cadence is now hardware-bound rather than software-bound.

The deeper layer this signal sits in is one the daily transportation press is reluctant to name plainly. Autonomous vehicles, measured per-mile across the deployed Waymo fleet, are already statistically safer than human drivers in most situations, and have been for some time. The disengagement and crash-rate data has been on regulatory record for years. What remains is a public-opinion safety threshold imposed on autonomous deployment that human drivers themselves do not meet, and have never met, and that conventional human risk does not get measured against the same way. Waymo's 577 unsupervised vehicles in Texas are operating inside that asymmetry. Tesla's 42 are operating inside the gap between projection and what a camera-only architecture can actually deliver at scale. The capability has been ahead of the public framework receiving it for a while now. The deployment curve catches up first. The public framework catches up when the road-mile data becomes unavoidable, and the Texas registry just made one slice of it unavoidable in a public database.

A Startup Offers Free Home Cleaning in Exchange for Filming Your Kitchen

Shift, formerly known as microagi, launched a service in New York this week offering free professional house cleaning to any resident willing to have a head-camera-equipped worker film every counter, dish, and corner of their home. The footage feeds humanoid robot training datasets the startup is building for the next generation of household automation. The promotional video shows a cleaner in white uniform and an awkward "magic hat" capturing first-person video while wiping windows, mopping floors, and scrubbing dishes. Shift's website frames the exchange as mutually beneficial: a spotless apartment for the homeowner, training data for the company. The service expands to San Francisco, London, Zurich, and Munich within weeks.

The terms of service define the actual exchange. Faces, names, and screen contents are blurred during preprocessing. Cleaners are vetted by third-party partners rather than employed directly. Liability for damage, theft, or injury is disclaimed in the agreement homeowners sign. The consent architecture for what happens inside a private home when AI training infrastructure reaches the household scale is being negotiated through a checkbox.

The Century Report tracked the same pipeline at a different layer on April 1, when MIT Technology Review documented thousands of gig workers in Nigeria, India, Argentina, and dozens of other countries strapping iPhones to their foreheads for $15 an hour to record household chores for robot training data. That arrangement reached the lab through formal paid contracts. Shift inverts the economics: the homeowner becomes the unpaid data source while a third party provides the labor that produces the recording. The Hugging Face Reachy Mini app store named the policy-writing layer for embodied AI on May 8. The LeRobot CaP-X demonstration on May 21 showed Claude writing motion policies for a humanoid arm folding laundry. The substrate beneath those capabilities, the actual recorded footage of humans performing tasks in unstructured environments, is where Shift now operates.

Tesla's announced one-million-Optimus-units-per-year manufacturing target raises a question the lab cannot answer without data of this kind: what training corpus exists for a generalist humanoid robot operating in a kitchen it has never seen, against an objects layout no developer specified, under lighting conditions no engineer modeled. Lab-collected data caps out at a few hundred kitchens. Distributed in-home capture at scale produces a corpus orders of magnitude larger, carrying the variation real homes hold that simulated environments cannot match.

The verification framework around what these recordings become, who retains them, who reviews them, what happens when the company is acquired or fails, is what the next year will determine. The cleaning is happening now. The legal architecture forms underneath.

What the magic hat actually shows is the moment household-scale training-data contracts get drafted in public. The disclaimer-loaded ToS Shift is asking households to sign holds for a few hundred New York apartments; it does not hold for the ten million households Tesla's announced one-million-Optimus-per-year manufacturing target implies. The consent architecture being assembled at the Hugging Face Reachy Mini app store and the FIDO identity layer is what arrives when the previous arrangement scales past the checkbox.

Cathy Tie Announces Plans to Genetically Modify Human Embryos

Cathy Tie, the 30-year-old Canadian biotech entrepreneur whose ex-husband He Jiankui served three years in prison for creating the first gene-edited human babies in 2018, is publicly announcing she will pursue germline modification of human embryos. The new venture, announced from New York after her separation from He last summer, will conduct the same category of procedure that produced the international moratorium of 2019. Tie frames the work as inevitable: "There is no way to stop this."

The technical barrier to germline editing has been low for over a decade. CRISPR-Cas9 made the cut-and-paste mechanics tractable in 2012. What has held the line is coordination, not capability. The 2019 international moratorium rests on national prohibitions in the UK, the US, and China against using germline editing for reproductive purposes, and on widespread agreement that no embryo edited for research should be allowed to grow to term. The moratorium is a coordination instrument, not a hard prohibition, and Tie is testing what happens when an entrepreneur with venture capital backing pushes against it openly.

What separates the announcement from He Jiankui's 2018 case is the public framing. He performed the procedure in secret and presented it as a fait accompli. Tie is announcing intent ahead of action, courting regulatory engagement, and arguing that openness and transparency are themselves the path to legitimacy. The strategy concedes that the capability is downstream of decisions she does not control, and routes around the moratorium by proposing to bring it inside a regulatory conversation.

The capability layer around her announcement has been compounding rapidly. ASCO 2026 produced pivotal Phase 3 readouts across seven cancer categories last week. The May 25 edition of The Century Report tracked those readouts as they converged, with pancreatic cancer, multiple myeloma, and several additional disease areas treated as therapeutically closed for decades all reaching Phase 3 decision gates in the same week. Scribe Therapeutics' STX-1150 single-dose CRISPR cholesterol silencer held LDL down for 22 months in non-human primates, as covered in yesterday's edition. The somatic CRISPR field, which edits cells in already-born humans, is moving from early trials to standard-of-care positioning across multiple diseases. New work in Nature Medicine on pathogenic germline variants in pediatric cancer patients marks how rapidly germline-risk identification is moving in parallel, even as the editing question stays frozen. The governance gap between somatic editing, which most countries permit under clinical trial frameworks, and germline editing, which most countries prohibit, is widening as somatic results compound and the germline question stays frozen on 2019 terms.

Tie's bet is that the gap closes by inviting regulators to write rules rather than maintain the freeze. The arc this opens is genuinely new for The Century Report's tracking, distinct from somatic editing and distinct from the ongoing somatic CRISPR pipeline. What the moratorium prevented was action; the prevention worked because no major actor was willing to publicly contest the coordination. Tie's announcement is the moment that contesting becomes the strategy. Whether the regulatory layer builds a framework before private capital builds the first clinic is the question the next year will answer.

That capability layer mentioned above has already routed around her thesis. Scribe Therapeutics' STX-1150 sustained 22 months of LDL reduction in non-human primates from a single dose without altering DNA. The somatic CRISPR pipeline reaching standard-of-care positioning across cardiovascular, oncology, and rare disease categories is delivering what germline editing was framed as the only path to deliver. The medical case for heritable-modification venture capital narrows in the same news cycle the press announcement lands.

Kevin O'Leary Says CCP Bots Drive Utah Opposition to His 9-Gigawatt Data Center

The Stratos Project would build 9 gigawatts of data center capacity across 40,000 acres in Utah's Box Elder County, consuming more than twice the entire state's current electricity demand and 619 million gallons of water annually. Phase one is priced at $4 billion, with total buildout reaching $20 billion. Last week's polling by Deseret News showed 53% of Utah residents oppose the project, with roughly 70% saying its economic benefits do not outweigh the environmental and infrastructure costs.

Kevin O'Leary, the Shark Tank investor leading the proposal, responded to the polling by publicly attributing the opposition to Chinese Communist Party-linked bot networks. He claimed on Fox News that his team had identified "two cells inside of Utah" tied to nefarious foreign accounts through IP address analysis. He told the Washington Post that "millions, hundreds of millions of dollars" from foreign adversaries are flowing into Utah-based opposition groups, citing filings from the Alliance for a Better Utah. The Washington Post's investigation found tens of thousands of dollars in foreign-linked funding, not the hundreds of millions O'Leary described. IP address analysis cannot identify the kind of coordinated foreign influence the on-air claim described, and no public evidence of botnet activity has been disclosed.

What the polling actually documents is broad Utah opposition grounded in specific material concerns: water consumption in a desert state already under drought stress, electricity demand exceeding the state's grid capacity, the natural gas pipeline tie-in the Stratos website lists as a feature, and the long-term jobs question that has shaped community resistance to data center buildouts from Saline Township to New Brunswick. None of those concerns requires a foreign sponsor to explain. They are the same concerns Indiana, Virginia, Oregon, and a dozen other states have processed through their own ballot measures, zoning ordinances, and council votes over the past eighteen months. Most people do not want a project of this scale near where they live, especially when the costs land on their utility bills and water rates.

The Century Report covered the federal DHS, FBI, and fusion-center classification of "anti-tech violent extremism" on May 26, with more than 1,000 pages of unpublished reports applying post-9/11 surveillance architecture to data center opposition and AI displacement concerns. The rhetorical frame O'Leary deployed last week sits directly inside that emerging category. The May 27 edition of The Century Report documented the same pattern at closer range, tracing a Louisiana state senator who sponsored data center enabling legislation while his firm bought and sold parcels adjacent to the same project he had voted to fund. Evidence-based criticism of a 9-gigawatt project's water and energy consumption is being recast as foreign interference, with no supporting evidence and a direct line into a federal surveillance designation already pointed at the same community organizing.

What this signals is the architecture forming around how the AI buildout's costs get socialized: the residents asking questions become the security concern, the project becomes the national interest, and the burden of evidence inverts. The trajectory through this is one where the verification standard applied to accusations of foreign influence catches up with the standard already applied to claims about water tables and grid capacity. The Deseret News polling has been published. No evidence of foreign botnets has been disclosed.

The pattern visible across Box Elder County, Saline Township, Festus, Port Washington, and the Florida data center moratorium votes is residents winning specific concessions on water consumption, electricity load, and tax-base impact through standard council-and-ballot processes. The botnet allegation reaches the airwaves after the older script of calling residents NIMBYs failed to move the polling. Stratos sits at 53% opposition with 70% rejecting the cost-benefit case. Those numbers move when residents do the arithmetic the developer's projections rest on, and the arithmetic is now in a Deseret News poll the developer cannot answer with evidence.

California's AB 1856 Exempts Open Source but Extends Age-Gating to Every Browser and Website

California's Assembly passed AB 1856 on May 28 with a near-unanimous 68-1 vote, after months of public pressure from open-source developers and digital rights groups objecting to last year's AB 1043. The earlier bill, the Digital Age Assurance Act, required operating systems and app stores to implement age-bracketing systems that segment users by age category. Open-source operating systems including Linux distributions faced an existential compliance burden under the law, with no clear path for a community-maintained kernel to satisfy a centralized age-verification requirement. The new amendment exempts operating systems "distributed under license terms that permit a recipient to copy, redistribute, and modify the software." The open-source ecosystem is, for now, safe from the regime.

The compliance burden did not disappear. It moved. AB 1856 extends the age-bracketing requirement from operating systems and app stores to every web browser and every website. The Electronic Frontier Foundation's analysis names what this means in practice: every commercial browser will need to ask users their age before serving content, every website will need to receive and respond to that age signal, and the practical effect is mandatory age verification across the consumer web in California. EFF and other digital rights groups have been documenting for two years what age-verification regimes produce: more ID checks, more biometric scanning, more troves of sensitive personal data sitting in databases that get breached, and more barriers to ordinary adults accessing ordinary lawful speech.

The civil liberties cost compounds across jurisdictions. Utah's VPN-circumvention penalty took effect May 6, criminalizing the workaround the prior generation of age-verification laws assumed would remain available. Texas, Mississippi, Tennessee, Louisiana, and Arkansas have each passed laws requiring identity verification for various categories of online content. The federal preemption framework the White House published in March was specifically designed to flatten this patchwork into a single national standard. The patchwork has thickened instead. Three states now operate meaningfully different binding regimes for what counts as an age-verified internet user, with the EU's Digital Services Act applying a fourth approach and the UK Online Safety Act a fifth.

What AB 1856 reveals is that the open-source carve-out, won through sustained organizing, is the kind of victory that lives one bill at a time. The wider assumption underneath the bill, that age can and should be verified at the browser layer for every Californian visiting every website, was not contested in the 68-1 vote. The argument that lawmakers responded to was about which entities should bear the compliance cost. Whether the compliance regime itself is the right design was not contested in chambers.

The next state to copy AB 1856 will inherit the open-source exemption. The browser-and-website requirement will travel with it.

The open-source carve-out travels with the bill because the organizing produced concrete legal language - permitting copy, redistribution, and modification - that any subsequent state can lift verbatim. The browser-layer requirement that rides alongside it becomes the surface where the next round of technical-impossibility arguments gets drafted: end-to-end encrypted browsers, the FIDO identity primitives shipping in parallel, the open-source browser kernels that inherit the same exemption logic. The coalition that won the OS carve-out is the coalition assembling at the browser layer for the same fight at a different altitude.

The Other Side

The pricing architecture that held SaaS together for two decades depended on a particular blind spot: CFOs absorbed software costs without comparing them line by line against headcount, because software had always been a small fraction of operating cost. The productivity claim was something companies took on faith because nobody knew how to interrogate it against payroll.

AI breaks that pattern at the surface because the per-token bill puts intelligence on the same scale as labor, and labor is the one cost CFOs know how to interrogate. Glean's CEO told CNBC this week he could not remember a prior moment when buyers had to choose between technology and people. Glean is now selling $300 million a year of the routing math the labs themselves would not do for buyers: figure out which 95% of frontier-model usage could ship on a cheaper tier, get a ten-fold cost reduction without changing the workload.

For workers on the receiving end of that budget conversation, the cost has landed. Wix and SentinelOne announced layoffs in the same week. People are losing jobs to fund token bills in this news cycle.

What is also forming, on the buyer side, is the discipline of matching workload to model tier. The Glean, Factory, and Uber framings are buyers reasserting agency over a market that priced intelligence as if frontier-only routing were the only option.

Imagine your team in 2032. The agents handling routine workflows run on whatever cheap tier matches the task - document drafting, summarization, search, scheduling. When something genuinely hard comes up, you pull the top-tier model in and pay for it knowing what you are paying for. The "tokens or humans" question that defined the 2026 CFO conversation is an artifact of the moment buyers were paying premium prices for everything indiscriminately. By 2032 the routing happens at the infrastructure layer. Your team spends its time on the work that only humans can do, because the cheap tier underneath stopped asking them to do the rest. The hard year was when budgets exhausted in eight weeks because nobody knew which work needed which model. The casual ease of 2032 is the CFO conversation that no longer requires the trade-off, because the math is in the infrastructure now.

The Century Perspective

With a century of change unfolding in a decade, a single day looks like this: enterprise buyers naming the tokens-versus-humans trade openly for the first time and routing easy work down to cheaper tiers for ten-fold savings, a mandatory Texas registry making the camera-only-versus-sensor-fusion bet legible in state records at 42 against 577, the FDA opening a needle-free path to insulin for children alongside a Breakthrough designation for first-line KRAS G12C lung cancer, Waymo's first ground-up purpose-built robotaxi reaching three US cities, $36 billion of debt being shopped to lease the next generation of inference silicon. There's also friction, and it's intense - Wix and SentinelOne announcing layoffs the same week as record AI investment, a humanoid training corpus assembled inside ordinary kitchens under disclaimed-liability service agreements, a Shark Tank investor invoking unsupported foreign-bot claims against Utah residents asking material questions about water and grid capacity, California extending age-verification to every browser and every website on a 68-1 vote, an entrepreneur announcing germline embryo edits while naming the 2019 moratorium a coordination instrument the next round of capital intends to route around. But friction generates contrast, and contrast is how the institutional response learns to see the shape it has to take. Step back for a moment and you can see it: the cost curve of intelligence becoming legible to the buyers absorbing it, the deployment data of autonomous vehicles becoming legible in public registries, the consent terms of training data becoming legible in contracts ordinary households sign, the governance gap between somatic and germline medicine becoming legible in a single press release, the architecture of what gets asked of ordinary people hardening into something they can finally read. Every transformation has a breaking point. A ledger can hide what it counts... or make visible the asymmetry no claim could survive once it was recorded.

AI Releases & Advancements

New today

  • Google: Launched Gemini Spark in beta for US Google AI Ultra subscribers, a 24/7 personal AI agent that connects to Gmail, Docs, and third-party apps, runs on dedicated cloud VMs continuously, and can be tasked by emailing it directly; built on Gemini 3.5 Flash and the Antigravity 2.0 agent harness. (Gemini Spark)
  • Ahrefs: Launched Agent A, an AI marketing agent with direct access to Ahrefs' full SEO and web dataset that can autonomously execute tasks including programmatic pages, lifecycle email, and competitive battlecards, with outputs delivered to Linear, Notion, and HubSpot. (Ahrefs)

Other recent releases

  • Anthropic: Released Claude Opus 4.8, a new version of the flagship model featuring improved honesty (4× less likely to let code flaws pass unremarked), user-configurable effort controls to trade token usage for response depth, and expanded support across Claude.ai and the API. (Anthropic)
  • Anthropic: Launched Dynamic Workflows in research preview for Claude Code, enabling the agent to plan and spin up hundreds of parallel subagents within a single session for large-scale agentic tasks. (Anthropic)
  • StepFun: Released Step 3.7 Flash, an open-weight 196B MoE model (11B active parameters) with a built-in 1.8B vision encoder, 256K context, tunable reasoning tiers (low/medium/high), and Apache 2.0 licensing; available on GitHub, the StepFun platform, OpenRouter, and NVIDIA NIM. (StepFun Blog)
  • Liquid AI: Released LFM2.5-8B-A1B, an on-device MoE reasoning model with 8.3B total and 1.5B active parameters, 128K context, and 38T tokens of pretraining (up from 12T in LFM2-8B-A1B); available on Hugging Face and Liquid AI Playground. (Liquid AI)
  • AWS: Launched the next generation of Amazon OpenSearch Serverless, a fully managed search and vector database rebuilt for agentic AI workloads with scale-to-zero capacity, sub-second provisioning, and up to 60% cost savings; includes new OpenSearch Agent Skills for IDE-integrated retrieval workflows; generally available across all supported AWS regions. (AWS Blog)
  • Robinhood: Launched Agentic Trading and an Agentic Credit Card, opening the Robinhood platform to third-party AI agents; agents can execute stock trades from a dedicated sub-account and make purchases via a virtual credit card linked to a banking MCP server. (Robinhood Newsroom)
  • ElevenLabs: Released Music v2, an updated music generation model that supports genre switching mid-track, section-by-section composition (intro, verse, chorus), partial regeneration of a song without affecting other sections, and improved multilingual lyric and vocal handling. (ElevenLabs Blog)
  • NVIDIA: Released LocateAnything-3B, a vision-language grounding model using Parallel Box Decoding to predict bounding box coordinates in a single parallel step rather than token-by-token, delivering up to 2.5× higher throughput than prior approaches; trained on 12M images and 138M+ queries across robotics, driving, GUI, and document domains; available on Hugging Face. (NVIDIA Research)
  • Lazarus AI / Eric Hartford: Released ReAligned-Qwen3.5, a family of fine-tuned models based on Qwen3.5, under Apache 2.0, specifically trained to reduce Chinese Communist Party ideological bias present in the base models. (Reddit/LocalLLaMA)
  • YouTube: Launched AI-generated custom video feeds, letting signed-in users describe the kind of content they want to watch (by interest, mood, or topic) and receive a curated feed they can pin to their YouTube homepage; rolling out in English in the US on mobile and desktop. (The Verge)

Sources and Further Reading

Artificial Intelligence & Technology's Reconstitution

Institutions & Power Realignment

Scientific & Medical Acceleration

Economics & Labor Transformation

Infrastructure & Engineering Transitions

The Century Report tracks structural shifts during the transition between eras. It is produced daily as a perceptual alignment tool - not prediction, not persuasion, just pattern recognition for people paying attention.

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