Anthropic's Head of Growth: "70% of what I spend my time on is what we internally refer to as 'success disasters.' Where things have gone so well that other things are breaking.
Anthropic's Head of Growth: "70% of what I spend my time on is what we internally refer to as 'success disasters.' Where things have gone so well that other things are breaking. It's funny, because all the charts are green and fully up and to the right, but it can be quite tough
So maybe OpenAI *really* figured out superintelligence. In a way, Anthropic did, right? nitter.net/kimmonismus/status/204… Chubby♨️ (@kimmonismus) Looks like OpenAI reached Superintelligence. OpenAI: "Now, we’re beginning a transition toward superintelligence: AI systems capable of outperforming the smartest humans even when they are assisted by AI." OpenAI just published a 13-page policy blueprint for the "Intelligence Age"- proposing a Public Wealth Fund, 32-hour workweek pilots, portable benefits, a formal "Right to AI," and tax reforms to offset shrinking payroll revenue as automation scales. The document frames superintelligence not as a distant scenario *but an active transition requiring New Deal-level ambition*: new safety nets, containment playbooks for dangerous models, and international coordination modeled on aviation safety institutions. Here are OpenAI's suggestions (tl;dr): Open Economy: -Give workers a formal voice in AI deployment decisions -Microgrants and "startup-in-a-box" for AI-native entrepreneurs -Treat AI access as basic infrastructure (like electricity) -Shift tax base from payroll toward capital gains and corporate income -Public Wealth Fund — every citizen gets a stake in AI growth -Fast-track energy grid expansion via public-private partnerships -32-hour workweek pilots, better benefits from productivity gains -Auto-scaling safety nets triggered by displacement metrics -Portable benefits untied from employers -Invest in care economy as a transition path for displaced workers -Distributed AI-enabled labs to accelerate scientific discovery Resilient Society: -Safety tools for cyber, bio, and large-scale risks -AI trust stack — provenance, verification, audit logs -Competitive auditing market for frontier models -Containment playbooks for dangerous released models -Frontier AI companies adopt Public Benefit Corporation structures -Codified rules and auditing for government AI use -Democratic public input on AI alignment standards -Mandatory incident and near-miss reporting -International AI safety network for joint evaluations and crisis coordination Notably, OpenAI calls for stricter controls only on a narrow set of frontier models while keeping the broader ecosystem open, a clear attempt to position regulation as targeted, not industry-wide. They're backing it with up to $100K in fellowships and $1M in API credits for policy research, plus a new DC workshop opening in May. — https://nitter.net/kimmonismus/status/2041130939175284910#m
Compute Wars chart updated with the latest Anthropic/Google deal – it gets Anthropic much closer to the publicly known OpenAI capacity 2027 onwards – previously there was a big gap with OpenAI being significantly ahead, now OpenAI is only slightly ahead.
Appreciate the feedback. Since we introduced Claude Code at Anthropic, engineering velocity has increased hundreds of %, and the rate at which it is increasing is itself accelerating. The velocity is very much not performative — we're actively trying to figure out how to
Databricks co-founder and CEO @alighodsi joined CNBC anchor @dee_bosa on stage at HumanX today to talk about the race toward super intelligence, where enterprises should be focused instead, and what AI needs to be reliable at scale. "There is a lot of talk about super
We've partnered with Amazon Web Services, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks. Together we'll use Mythos Preview to help find and fix flaws in the systems on which the world depends. [Translated from EN to English]
I stole this framework, and it has genuinely been one of the most helpful hiring and onboarding guides my team uses. Being AI-first means nothing without solving real business problems. It's not enough to just use AI. I know plenty of folks using AI dozens of times a day, 7 days a week, who are still working at a Level 2. Even worse, they have no idea they're stuck as a surface user. You have to use AI for faster experimentation. To shorten the iteration cycle. To improve the actual outcome. Without those three, you're just wasting tokens. Most people I interview are at a 3 (solution-oriented, but not action-oriented). I want everyone to start at a 4 (action-oriented with a sense of technical, user, and business tradeoffs). And when they earn trust, we move up to a level 5 (full ownership of the problem, solution, and continued management of the work). Using AI doesn't replace your critical thinking. It means the work you can pull off now wasn't on the table a year ago, and your job is getting bigger. Save this for your next new hire. Source: this was a framework first introduced to me by Alex (@businessbarista) who was introduced to it by Steph (@stephsmithio). I added the AI parts.
About that 16,000-word piece on Sam Altman in The New Yorker
First of all, they spent a year and a half, and kudos to them. I love to see reporters spending time talking to people. The sum total of this 16,000-word essay from Ronan Farrow and Andrew Marantz, which is… pic.twitter.com/IYIE9hzBQL
About that 16,000-word piece on Sam Altman in The New Yorker First of all, they spent a year and a half, and kudos to them. I love to see reporters spending time talking to people. The sum total of this 16,000-word essay from Ronan Farrow and Andrew Marantz, which is
