The Singularity Report

🏗️ AI-native jobs, AI infrastructure, autonomous systems

Every week I summarize the most interesting things happening in AI, in 5 minutes or less. Follow @tjhoyos on X/Twitter and subscribe to get this in your inbox every week!

Three big things

1. The AI-native workforce is forming

   1. Large private equity firms (and I think this is true generally) are aggressively hiring people who can help their portfolio companies deploy AI and become more efficient. As I said to someone earlier today, this feels like one of those “new jobs” AI will allegedly create as it reshapes the economy. I don’t think this role is perfectly defined yet, but it probably rhymes with “forward deployed engineer” or something along those lines.

   2. Relatedly, OpenAI is launching the OpenAI Deployment Company to help organizations implement AI in their real business workflows. They’re pairing models with embedded engineering teams, consultants, and system integrators. Plus, they just bought a company, Tomoro, which has 150 forward deployed engineers and deployment specialists.

2. AI and public markets

   1. Shocking stats: basically all positive S&P 500 performance over the last year has been driven by two categories heavily exposed to AI with semiconductors (+68%) and energy (+18%), while healthcare (-22%), consumer staples (-30%), software (-40%) and other categories have gotten killed; also, the capex from hyperscalers (projected to be $680B in 2026) is translating directly to free cash flow for AI infrastructure companies (projected to be $525B in 2026).

   2. More evidence AI infrastructure stocks are surging: “Almost every single semi stock has gone up 2x in the last month. More enterprise value created in non-Nvidia publics in the last month than all big labs this year.”

   3. AI inference company Cerebras is going public this week and apparently there is crazy demand as it is 20-30x oversubscribed. Curious to see how it trades. And just wait for OpenAI and Anthropic to go public later this year.

   4. Anthropic committed to spending $200B on Google Cloud and chips over the next few years, driving up Google’s stock price so it’s now the most valuable company in the world with a market cap of ~$5T.

3. The big deal

   1. We’re seeing another odd industry pairing with Anthropic agreeing to rent inference compute from SpaceX/xAI. Here’s my best understanding of why: Anthropic underestimated its compute needs and it’s had to throttle power users with rate limits, whereas OpenAI has not and now has momentum with developers. This is a competitive move from Anthropic to counter OpenAI, and it helps xAI offset some of their massive infrastructure spending by generating meaningful revenue from excess inference capacity. Anthropic will have access to the Colossus 1 data center as SpaceX/xAI prepares to train the next version of Grok on Colossus 2.

The rest

• A new type of insurance product is emerging: coverage for businesses that offers protection when their AIs mess up (e.g., hallucinations, copyright violations, data leaks).

• Thought-provoking: “There’s a teleology of humanness that almost is designed to produce AGI. We’re fulfilling almost some kind of Calvinist, religious project…This is the culmination of human intelligence and ingenuity. I just don’t see any way around that…There’s something beautiful about it. It fits. There’s some harmony in the idea that humans are designed to do this... to produce an intelligence greater than itself.”

• Some people are converging on the idea that AI increases demand for technical talent and jobs (as opposed to reducing it), pointing to Jevons paradox, i.e., in certain categories, the less something costs the more demand there is for it.

• New US labor data came in substantially stronger than expected: job creation is accelerating while unemployment held steady at 4.3%.

• Interesting piece from A16Z’s David George titled The “AI Job Apocalypse” Is a Complete Fantasy. He frames AI disruption as a labor-market transition problem similar to other historical technology waves.

• Demand for electricians is surging: “Young data center electricians in Texas are earning $240,000–$280,000/year with zero college debt.”

• Anthropic researcher Jack Clark believes we’ll get fully automated AI research (and recursive self-improvement) by the end of 2028.

• Confirming as much, Anthropic CEO Dario Amodei spoke about how they dramatically underestimated demand for their products and services, planning for 10x growth when they actually got 80x.

• Marc Andreessen shared the custom instructions he uses to improve the answers he gets from ChatGPT, Claude, etc.

• Shopify launched a ChatGPT app and a Claude connector to help ecommerce store owners manage their stores from those products.

• The White House is considering a new mandate requiring AI companies to allow the government to review AI models before they are released. Politicians are increasingly focused on AI safety and how it might collide with public policy.

• The US and China are discussing ways to prevent AI competition from escalating into a broader geopolitical or security crisis.

• OpenAI released its next-generation voice mode via API. I haven’t tested but apparently it’s much better with better intelligence, multimodality, turn handling, etc.

• Sam Altman on why this is important: “people are really starting to use voice to interact with AI, especially when they have a lot of context to dump.”

• ChatGPT is building out its ads infrastructure with the same tools you get from Meta and Google: conversion API, tracking pixel, self-serve.

• Claire Vo laid out the playbook for how to lean into AI, especially if you get laid off: “I found myself suddenly laid off from a company that cited AI as a cause, this is what I’d do: [1] download codex and Claude/code; [2] say: ‘this was my job and how I spent my day, how can you help me automate it w skills’; [3] push a dozen of those skills to GitHub; [4] open up Claude design and make a portfolio site, with an ‘agent’ per skill explaining how you built it, what tools it interacts with; [5] give to lovable or v0 or whatever to publish; [6] post that site and link to GitHub on LinkedIn; [7] search “ai for <job>” and try all the new startups, form an opinion, message their founders; [8] try something scary like openclaw, form an opinion; [9] take a course in tactical AI in your field; [10] build, share, build. The gap in AI adoption is getting bigger. Start reskilling now while it’s early. The time is now.”

• NVIDIA’s Jensen Huang explains why we are not bullish (and ambitious) enough: “If you could just see all of the things that I see every day, you would be so fired up, so excited about the future and realize that whatever ambition that you had in the past, the one thing that you have to say to yourself is whatever level of ambition you have, it’s just not high enough.”

• There is a new SWE-Bench eval that assesses models’ technical capabilities, and current frontier models get 0%. Over the last couple years I’ve come to realize that moving the goalposts on evals is a feature not a bug.

• I’m skeptical but intrigued in an apparent new algorithmic breakthrough: SubQ uses a sparse-attention LLM design that increases context windows and speed while lowering costs, i.e., it’s 52x faster than FlashAttention at 1M tokens while also 95%+ cheaper than Opus.

• Interesting development in AI industry pricing and competition: OpenAI’s frontier model GPT-5.5 is ~4-5x cheaper than Anthropic’s frontier model Mythos thanks to lower per token prices and higher token efficiency.

• Vori is building an AI-native operating system for supermarkets.

• OpenAI announced a new protocol and partnership with several industry players (AMD, Broadcom, Intel, Microsoft, NVIDIA) that makes it easier to network data centers together. This will be increasingly important as we build more of them and as people continue to push back on gigantic data centers in their towns, cities, and neighborhoods.

• Ethos raised $22M from A16Z to help connect people to paid professional opportunities like consulting calls, research, AI training, fractional work, and eventually full-time jobs.

• Anthropic CEO Dario Amodei described a robotics demo that feels like a real inflection point. He compared it to when coding agents started to display human-level competence.

• Thanks to Mythos, Firefox fixed more security bugs in one month than the last 15 months combined.

• Incredibly cool way to visualize how LLMs think differently than humans: “Neural networks might speak English, but they think in shapes.”

• Somewhat relatedly, Anthropic introduced Natural Language Autoencoders, a new interpretability method that is helpful for understanding how models think (without them knowing we’re watching).

• Fascinating post on Chinese AI labs written after in-person visits. The main takeaway is that export controls are working leading to compute constraints which create the conditions for innovative approaches. The market structure is more fragmented than in the US, and the data and infrastructure sub-industries are way less mature.

• Shopify is forcing their employees to use AI in public Slack channels to help disseminate knowledge internally and bring people up the AI learning curve more quickly. Great read.

• Different framing from Dario Amodei and David Sacks, but they converge on the same underlying idea: AI is either AGI-level capability or the foundation of an unprecedented concentration of economic power, i.e., monopolies. On the one hand, Google is still one of the most dominant businesses in history at ~$422B revenue over the last twelve months, growing ~22% YoY. On the other hand, Anthropic continues to grow exponentially at a terrifyingly fast rate. In May they hit a $45B run-rate, up from $30B in April, $19B in March, and $9B in February.

• Claude Mythos Preview is exceptionally strong on the METR benchmark, which measures how long a model can perform autonomously without human intervention. I’m extremely interested to see GPT-5.5’s performance here as I don’t think they’ve released it yet.

• Airbnb CEO Brian Chesky with an interesting take on interfaces in the age of AI and why chat isn’t a panacea: “I do not think a chatbot is the right interface for travel or e-commerce…I think the future is not apps. The future is agents, but I don’t think they’re going to be text-forward. I think they’re going to be really rich user interfaces…Imagine using iMessage to do everything, when in fact every other app has a unique interface…With e-commerce, you want a very rich user interface. It would be agentic. You can have a conversation with it, but the point is that it has to be more visual.”

• OpenAI employees were reportedly given the chance to cash out up to $30M each in secondary sales.

Every week I summarize the most interesting things happening in AI, in 5 minutes or less. Follow @tjhoyos on X/Twitter and subscribe to get this in your inbox every week!