The Singularity Report

🧠 Company brains, goblin models, and agents everywhere

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. Prediction: you’re going to hear a lot about “company brains” or “company intelligences” in the coming years. We (and so many others) are working on building our own versions internally. The idea is to combine all the disparate data points your company has (product analytics, internal email and Slack threads, customer support emails, public reviews, ad performance, literally everything) into a single repository that an AI system can understand. Then people at the company can ask it questions to make better decisions, and eventually it starts being proactive by suggesting actions to take (or taking action itself) to maximize progress. There isn’t a go-to tool people use right now because the shape of every company is different, but stuff is starting to pop up: Scout is an open-source project in this area. Relatedly, the inimitable Ann Miura-Ko from Floodgate wrote a great piece on the different levels of AI-native companies.

2. Data show that models from Chinese AI labs trail their US counterparts by several months. It’s clear both that the frontier of AI is still in the US and that China is a fast follower and fierce competitor. And they are currently winning in open source, which is a problem for long term competitiveness.

3. OpenAI missed its internal 2025 targets for ChatGPT usage, including a goal to hit 1B weekly active users, and OpenAI CFO Sarah Friar told the company she’s worried about meeting compute spend commitments if they don’t grow faster. The stocks of some of their large public partners (Oracle) dropped on the news in recognition the AI labs are a bit a high-wire act with truly jaw-dropping capex contracts. A leading company slowing down is one of the only things that could send AI as a category into a tailspin. All that said, apparently both revenue and adoption of GPT-5.5 exploded in Q1 as they focused more effort on Codex, agents and enterprise, and they’re back on track, so I’m not worried about their prospects.

The rest

• AI was a major driver of US economic growth in the first quarter, with estimates that it accounted for 75% of all growth.

• YC’s advice on how to build a company natively around AI from day one: “AI as operating system, not tool…closed loops everywhere…make your company queryable…software factories…no more human middleware…three employee archetypes (per Jack Dorsey)…token-max, not headcount-max…the early-stage advantage.” They go into more detail and it’s worth a read.

• Interesting: the Founder of Khan Academy Sal Khan is launching a $10k AI degree with partners like Google, Microsoft, and Replit. There isn’t a legit AI credential and traditional college education feels a little less relevant every year, so I’m not surprised people are trying to innovate here.

• OpenAI is finally wising up to the fact that they have to paint a positive vision of society’s future with AI. There has been a noticeable shift in their public communications. They’re no longer harping on the prospect of job loss and claiming they will automate everything. They’re trying to respond to concerns about data centers (resource usage, electricity prices, appearence etc.) by showing the impact on real communities, e.g., this interview with the mayor of Abilene, TX, the location of their massive Stargate data center. I really hope they keep this going.

• Humanoid robots in the wild: “Japan Airlines will trial humanoid robots for baggage handling and aircraft cleaning at Tokyo’s Haneda Airport starting in May.”

• The future is getting weirder: OpenAI’s new GPT-5.5 model has a strange habit of talking about goblins, gremlins, and other creatures when using metaphors. Apparently this is because of the “nerdy” personality feature.

• Google reportedly controls ~25% of global compute capacity.

• Very cool: some researchers developed an LLM trained only on text from before 1931. The big idea here is to see how well these models can predict the future (given we know how things unfolded after 1931), and how we can apply that knowledge to making current models better at predicting the future from today.

• Lol: “My job used to be writing code. Now it’s marriage counseling for Codex and Claude Code.”

• AI is political and the teams are confusing: Senator Bernie Sanders is discussing AI on a panel with the dean from the Beijing Institute of AI Safety and Governance.

• Dan Shipper thinks the dominant UX of knowledge work will be a side panel with chat and agents on the left, and your work on the right, with you collaborating in real time.

• People are using AI to seek guidance. Anthropic published an interesting breakdown of what people asked for advice on across 40,000 Claude chats. The top use cases were health and wellness at 27% (interpreting test results & chronic conditions, injuries, respiratory symptoms & treatment, calories & macros for body composition), and professional and career at 26% (job search & opportunity identification, career transitions & path selection, offer evaluation & salary negotiation). The latter is extremely relevant to our company’s work.

• Context on Anthropic’s growth rate: “And the company previously known as OpenAI’s junior competitor has become possibly the fastest-growing business in the history of capitalism. Anthropic’s revenue is increasing faster—much faster—than Zoom’s during the pandemic, Google’s during the early 2000s, and even Standard Oil’s during the Gilded Age. If the company’s current growth rate were to continue, then by early next year it would be taking in more money than any company in the world.”

• Interesting Stratechery interview with Sam Altman. Some highlights: “pre-training and post-training will converge as a singular training stack for ai models (very bullish inference test-time compute)…model and ‘wrappers’ are basically the same thing (very good for cursor’s valuation)…openai may move to ‘pay-per task’ pricing vs. per token. token pricing is dead. GPT 5.5 is more expensive BUT USES FEWER tokens…HUGE win for amazon’s trainium chips that will now run chatgpt: Sam: ‘We are quite excited to get these models running on Trainium.... over time, more and more of it will be on Trainium.’…the new managed agent’s product = enterprise chatgpt agents for all of amazon’s clients. openai might just snatch back the enterprise market share they lost”

• GPT-5.5 Pro is probably the best model in the world right now, setting a new high on Epoch’s composite capability benchmark which tracks performance in a bunch of areas with one number.

• Menlo Research released an open-source humanoid robot platform.

• Ineffable Intelligence, a new AI lab from a former Google DeepMind employee, raised a $1B+ seed round.

• China is attempting to block Meta’s $2B acquisition of Manus, which was founded by Chinese citizens, but moved its HQ to Singapore.

• OpenAI launched a new real-time voice model.

• OpenAI’s GPT-5.5 might be more cost-efficient than Anthropic’s Opus-4.7: “GPT-5.5 is ~39% cheaper than Opus 4.7, across merged PRs bucketed by diff size…despite the higher output token cost, 5.5 is cheaper for input tokens (cache writes are free), more token efficient, and tokenizes the same text to fewer tokens.”

• DoorDash introduced a new “Tasks” app that lets gig workers take on additional side jobs beyond food delivery, and many of the tasks are AI or robotics adjacent: “Film household chores (dishes, laundry) for humanoid training data…Scan store shelves (monitor inventory / product placements)…Close Waymo doors left ajar”

• AI is increasingly becoming a national security and policy priority. Here is Treasury Secretary Bessent weighing in: “If we don’t win in AI, then it’s game over.”

• Honestly I’m kind of surprised by this collab: Google and Exa (an AI search company with a focus on agents) partnered to bring Exa’s search and grounding capabilities into Gemini models. I would have thought Google would just try to own this themselves.

• OpenAI and Microsoft updated their partnership.

• Google entered into an agreement with the US DoD that allows its AI systems to be used for government purposes.

• The explosion in AI-driven coding is putting strain on platforms like GitHub where usage charts are going vertical. It’s made spam and scale much harder to manage.

• xAI is reportedly training Grok 5 on an extremely large compute cluster, maybe the largest ever.

• Box CEO Aaron Levie on why AI increases demand for software developers: “software jobs aren’t going away. Agents are the single biggest form of leverage for anyone technical in history. Probably has never been a better time to be technical in terms of being able to accomplish something solo, in a team, or company.”

• Mercury launched a command-line interface that lets you manage banking and other financial tasks from the terminal. Most products will end up having CLIs.

• Parallel.ai, which believes there will be many more AI agents browsing the internet than humans, is building infrastructure and tools around that vision. They raised at a $2B valuation.

• In the marketplaces of the future, will people outsource buying and selling to agents? Anthropic ran an experiment where they did that and the agents successfully matched participants and made deals without any human negotiation.

• Rogo, who built one of the first AI investment banker products, raised $160M.

• Gemini can now generate files such as documents, spreadsheets, presentations, and PDFs directly within chat.

• The best models in the world get exponentially smarter as they “think” more. In a recent cyber-attack simulation, researchers had GPT-5.5 and Anthropic Mythos think harder and longer (i.e., consume more tokens before responding), and it wasn’t clear there was a ceiling to their performance. After 100 million tokens, performance was still going up (the chart in the link is amazing). This is extremely bullish for upcoming model generations.

• SoftBank is reportedly launching a robotics-focused company to automate the construction of data centers.

• AI automation company Gumloop introduced dedicated email addresses for AI agents into their product.

• Meta released an MCP and CLI to make it easier to port your ad spend data into AI tools like Claude and ChatGPT to analyze it, build reports, etc.

• This was thought provoking: “Unprecedented abundance will create unprecedented demand for things that cannot be made abundant. That might mean local things: really unique restaurants, theaters, hotels. It might mean new towns altogether. I have a hunch that drones, EVs, and EVTOLs [electric aircraft] should expand local frontiers. For an enterprising new settler, it might make sense to start gobbling up cheap, buildable land where it doesn’t currently make much sense, or open up new frontiers beyond the land. You might get it wrong, you probably will. No one said scarce was easy.”

• Series is an AI social network that lives inside iMessage and raised $10M.

• OpenAI launched an anthropomorphized character inside Codex called “Pets.” Not sure what they’re trying to do here.

• Ethan Mollick in the Atlantic: “we whipsawed from ‘AI is a bubble’ to ‘there are not enough data centers’ in less than six months. Spoiler: its agents”

• Citadel published analysis that frames AI as a net jobs engine rather than a force for displacement, especially in software engineering.

• Strong argument from NVIDIA CEO Jensen Huang on the dangers of doomerism and why AI is a positive force for the economy and labor markets: “On one hand, maybe a scientist thinks by warning people that AI is going to completely permeate and proliferate across radiology and therefore radiologists are gonna get wiped out…that might be considered warning and therefore helpful. But in fact it’s hurtful. If we convince everybody not to be radiologists and now we need radiologists, that actually is hurtful to society. It’s hurtful that we convince all the young college graduates not to study software engineering. Turns out the United States needs more software engineers than ever. That’s hurtful. So we have to be mindful of how we communicate the importance of this technology and what it’s able to do — to advocate for policy, advocate guardrails on one hand. And on the other hand, scaring people with things like saying nonsensical things which are not gonna happen. That this is an existential threat to humanity. There’s a 20% chance that it’s existential. That’s ridiculous. Now, that it’s going to wipe out 50 percent of new college grad jobs. That it’s going to completely destroy democracy. I mean these kinds of comments are not helpful. They’re made by, you know, people who are like me — CEOs. You become a CEO, maybe you adopt a God complex. Before you know it, you’ll know everything. So I think we have to be careful and really ground ourselves to talking about the facts. The fact is this: AI has created more than half a million jobs in the last couple of years. The fact is AI is our greatest, our best opportunity to reindustrialize the United States, to bring manufacturing jobs back to the United States. The fact is that’s gonna generate hundreds of thousands of jobs, trillions of dollars in new economy back into the United States. The fact of the matter is companies that use AI have demonstrated the ability to grow faster. When they grow faster, they hire more people. Apparently AI creates jobs.”

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!