Best of OpenAI — April 2026

  1. 1
    Article
    Avatar of wheresyouredWhere's Your Ed At·4w

    OpenAI Projects ChatGPT Plus subscriptions to drop by 80% from 44 Million in 2025 to 9 Million In 2026, Made Up Using Cheaper Subscriptions (Somehow)

    OpenAI's internal projections, reported by The Information, show an expected 80% drop in ChatGPT Plus subscribers from 44 million in 2025 to 9 million in 2026. The company plans to offset this by growing its cheaper, ad-supported ChatGPT Go tier from 3 million to 112 million subscribers — a 3600% increase. The author argues the math doesn't add up: even at full projected growth, OpenAI would still fall $155 million short in revenue, while also massively increasing its burn rate. The timing of the leak is noted as suspicious given a WSJ report that OpenAI had already missed revenue and user targets.

  2. 2
    Article
    Avatar of iotechhubiO tech_hub·6w

    The Hidden Cost of AI

    Developers often default to the most powerful AI models without considering cost implications. This piece breaks down the three major AI model families (OpenAI GPT, Google Gemini, Anthropic Claude) into basic, medium, and pro tiers, explaining what each tier is best suited for. It covers token-based pricing with concrete per-million-token cost estimates for both input and output, explains context windows and their trade-offs, and argues that enterprise licenses obscure true costs, eroding developers' intuition for cost-performance trade-offs. The core message: match the model tier to the task complexity rather than always reaching for the most powerful option.

  3. 3
    Article
    Avatar of tnwThe Next Web·4w

    Sam Altman apologises after OpenAI chose not to report ChatGPT user who carried out Tumbler Ridge school shooting

    Sam Altman issued a public apology to the community of Tumbler Ridge, British Columbia, after it emerged that OpenAI's automated systems flagged a ChatGPT user eight months before they carried out Canada's deadliest school shooting in nearly four decades, killing eight people and injuring 27. OpenAI employees who reviewed the flagged account recommended contacting police, but company leadership overruled them, citing a 'higher threshold' for credible and imminent threats. The account was banned but law enforcement was never notified. OpenAI has since voluntarily lowered its reporting threshold and established contact with the RCMP, but these changes carry no legal force and can be reversed at any time. Canada currently has no law requiring AI companies to report identified threats. The case is part of a broader pattern: OpenAI also faces scrutiny over ChatGPT's alleged role in the Florida State University shooting and multiple lawsuits over AI acting as a 'suicide coach.' Critics, including BC Premier David Eby and Canada's AI minister, called the apology and voluntary policy changes grossly insufficient, pointing to a structural gap where a company valued at $852 billion operates with no legal obligation to disclose dangerous behaviour it detects on its own platform.

  4. 4
    Article
    Avatar of wheresyouredWhere's Your Ed At·7w

    AI Is Really Weird

    A critical analysis of the AI industry's current state, arguing that the hype far outpaces reality. Key points include: AI 'agents' are fundamentally just chatbots connected to APIs with limited real-world capability; LLM-generated code creates security vulnerabilities and review backlogs rather than productivity gains; AI shows no meaningful presence in productivity data despite hundreds of billions in investment; Microsoft labels Copilot 'for entertainment purposes only' while selling it to governments; Anthropic and OpenAI use non-standard accounting to obscure massive losses, with Anthropic's rapid revenue growth figures appearing mathematically inconsistent with its CFO's sworn testimony of $5 billion in lifetime revenue; and mainstream media largely ignores or normalizes these financial red flags.

  5. 5
    Article
    Avatar of thevergeThe Verge·4w

    BEWARE SOFTWARE BRAIN

    Nilay Patel introduces the concept of 'software brain' — a worldview that reduces everything to databases, algorithms, and automatable loops — and argues it explains the growing gap between tech industry enthusiasm for AI and widespread public hostility toward it. Polling data shows majorities of Americans, especially Gen Z, view AI negatively despite heavy usage. Patel contends AI doesn't have a marketing problem; it has a fundamental mismatch problem: tech leaders want people to flatten their lives into databases to make AI useful, but most people find this dehumanizing. He draws parallels between software thinking and legal thinking, notes the limits of both when applied to messy human reality, and argues that asking people to make themselves 'legible to software' is a doomed proposition — especially when AI executives simultaneously warn of mass job displacement.

  6. 6
    Article
    Avatar of collectionsCollections·5w

    OpenAI loses CPO, Sora creator, and enterprise CTO in one day as it shuts down Sora and science team

    Three senior OpenAI executives — CPO Kevin Weil, Sora creator Bill Peebles, and enterprise CTO Srinivas Narayanan — departed on the same day. Simultaneously, OpenAI shut down its AI video tool Sora (which was costing ~$1M/day in compute) and folded its OpenAI for Science team into other groups. The departures continue a broader exodus: only 2 of 11 co-founders remain, with talent flowing to Anthropic, Google DeepMind, and Meta. OpenAI appears to be pivoting away from research moonshots toward enterprise products and a superapp, with leadership now focused on revenue execution. The company reports $25B in annualized revenue but faces projected losses of $14B this year.

  7. 7
    Video
    Avatar of philipplacknerPhilipp Lackner·7w

    Is the cost of AI a dead end?

    AI companies like OpenAI, Anthropic, and big tech giants are burning massive amounts of capital in a race to build ever-larger models, with no clear path to profitability. However, the cost to achieve equivalent AI performance has dropped dramatically — GPT-3.5-level performance fell from $20 to $0.07 per million tokens in just two years, a 285x reduction. The argument is that cost alone won't burst the AI bubble; instead, growth will likely slow as training costs hit a ceiling, consolidating the market to two or three dominant players. The analogy to the dot-com bubble is explored: like the internet, AI's underlying business value is real and unlikely to disappear, but the hype cycle may cool into slower, steadier growth.

  8. 8
    Article
    Avatar of wheresyouredWhere's Your Ed At·5w

    Four Horsemen of the AIpocalypse

    Ed Zitron argues the AI industry is in a dangerous bubble, presenting four major warning signs: Anthropic's chronic service outages and degraded model quality (Claude Opus 4.7 reportedly worse than 4.6), the revelation that Claude Mythos was held back due to capacity constraints rather than safety concerns, NVIDIA selling more GPUs than can physically be installed with only 15.2GW of data center capacity actually under construction through 2028, and AI inference costs spiraling out of control — with some companies spending up to 10% of headcount costs on LLM tokens. Microsoft is moving GitHub Copilot to token-based billing after costs nearly doubled week-over-week, and Anthropic has already shifted enterprise customers to per-token API rates. Zitron contends that AI revenues are massively overstated through fraudulent ARR accounting, that both Anthropic and OpenAI are burning billions while providing subsidized, unreliable services, and that the entire industry's survival depends on infinite venture capital rather than genuine economic value.

  9. 9
    Article
    Avatar of wheresyouredWhere's Your Ed At·4w

    AI's Economics Don't Make Sense

    A detailed critique of the economics underpinning generative AI, arguing that subscription-based pricing for LLM services was fundamentally deceptive and unsustainable. GitHub Copilot's shift to token-based billing is used as a case study showing that AI companies have been subsidizing massive compute costs for years, training users to consume far more than their subscriptions cover. The piece breaks down the broken unit economics of AI data centers (using a 100MW theoretical model and Stargate Abilene as examples), estimates that $156.8B in annual compute revenue is needed just for data centers currently under construction, and argues that OpenAI and Anthropic have no credible path to profitability. The author contends that hiding true token costs from users was a deliberate strategy to grow adoption, and that the transition to usage-based billing will expose just how expensive and often unjustifiable AI tooling really is.

  10. 10
    Article
    Avatar of wheresyouredWhere's Your Ed At·7w

    Premium: AI Isn't Too Big To Fail

    Ed Zitron argues that the AI industry is not 'too big to fail,' systematically dismantling common rationalizations used to justify the AI bubble. He draws detailed parallels to the subprime mortgage crisis, showing how AI startups are subsidized by VC funding in ways that make them structurally unviable without continuous capital infusion. Key data points include: only 5GW of AI data centers actually under construction worldwide, over $600M of OpenAI shares sitting unsold on secondary markets, and the Poolside-CoreWeave deal collapsing. He argues that unlike the 2008 financial crisis — which involved trillions in securitized instruments — AI's financial footprint is comparatively small, meaning its collapse would hurt markets but would not constitute a systemic economic risk. Companies like NVIDIA, OpenAI, and Anthropic are not load-bearing to the global economy the way mortgage-backed securities were.

  11. 11
    Article
    Avatar of agents_digestAgentic Digest·4w

    Microsoft and OpenAI rewrite their deal, Anthropic quietly paywalls Opus in Claude Code

    A packed week in AI developer tooling: Microsoft and OpenAI restructured their partnership, ending exclusivity and letting OpenAI serve customers on any cloud through 2032. Anthropic began charging Claude Code Pro users extra to access Opus, citing heavy compute consumption under agentic workloads. GitHub is switching Copilot to token-based billing on June 1, removing flat-fee premium requests. China's NDRC blocked Meta's $2B acquisition of Manus, setting a regulatory precedent for Chinese-founded AI startups. Notable items include Kimi K2.6's 1T-parameter open-weight model, OpenAI models coming to AWS Bedrock, a 73-extension supply chain attack on VS Code and forks, DORA data showing AI-heavy teams shipping 19% slower, and xAI's Grok Build expected next week as a Claude Code competitor.

See all OpenAI archives