I remember being a child and after the lights turned out I would look around my bedroom and I would see shapes in the darkness and I would become afraid – afraid these shapes were creatures I did not understand that wanted to do me harm. And so I’d turn my light on. And when I turned the light on I would be relieved because the creatures turned out to be a pile of clothes on a chair, or a bookshelf, or a lampshade.
Now, in the year of 2025, we are the child from that story and the room is our planet. But when we turn the light on we find ourselves gazing upon true creatures, in the form of the powerful and somewhat unpredictable AI systems of today and those that are to come. And there are many people who desperately want to believe that these creatures are nothing but a pile of clothes on a chair, or a bookshelf, or a lampshade. And they want to get us to turn the light off and go back to sleep.
In fact, some people are even spending tremendous amounts of money to convince you of this – that’s not an artificial intelligence about to go into a hard takeoff, it’s just a tool that will be put to work in our economy. It’s just a machine, and machines are things we master.
But make no mistake: what we are dealing with is a real and mysterious creature, not a simple and predictable machine. — Read More
Recent Updates Page 17
The Claude Code SDK and the Birth of HaaS (Harness as a Service)
As tasks require more autonomous behavior from agents, the core primitive for working with AI is shifting from the LLM API (chat style endpoints) to the Harness API (customizable runtimes). I call this Harness as a Service (HaaS). Quickly build, customize, and share agents via a rich ecosystem of agent harnesses. Today we’ll cover how to customize harnesses to build usable agents quickly + the future of agent development in a world of open harnesses. — Read More
MIT report: 95% of generative AI pilots at companies are failing
The GenAI Divide: State of AI in Business 2025, a new report published by MIT’s NANDA initiative, reveals that while generative AI holds promise for enterprises, most initiatives to drive rapid revenue growth are falling flat.
Despite the rush to integrate powerful new models, about 5% of AI pilot programs achieve rapid revenue acceleration; the vast majority stall, delivering little to no measurable impact on P&L. The research—based on 150 interviews with leaders, a survey of 350 employees, and an analysis of 300 public AI deployments—paints a clear divide between success stories and stalled projects. — Read More
Is AI a bubble?
A month ago, I set out to answer a deceptively simple question: Is AI a bubble?
Since 2024, people have been asking me this as I’ve spoken at events around the world.
Even as Wall Street bankers largely see this as an investment boom, more people are asking the question in meeting rooms and conference halls in Europe and the US.
Some have made up their minds.
Gary Marcus called it a “peak bubble.” The Atlantic warns that there is a “possibility that we’re currently experiencing an AI bubble, in which investor excitement has gotten too far ahead of the technology’s near-term productivity benefits. If that bubble bursts, it could put the dot-com crash to shame – and the tech giants and their Silicon Valley backers won’t be the only ones who suffer.” The Economist said that “the potential cost has risen alarmingly high.”
The best way to understand a question like this is to create a framework, one that you can update as new evidence emerges. Putting this together has taken dozens of hours of data analysis, modeling and numerous conversations with investors and executives.
This essay is that framework: five gauges to weigh genAI against history’s bubbles. — Read More
Why America Builds AI Girlfriends and China Makes AI Boyfriends
On September 11, the U.S. Federal Trade Commission launched an inquiry into seven tech companies that make AI chatbot companion products, including Meta, OpenAI, and Character AI, over concerns that AI chatbots may prompt users, “especially children and teens,” to trust them and form unhealthy dependencies.
Four days later, China published its AI Safety Governance Framework 2.0, explicitly listing “addiction and dependence on anthropomorphized interaction (拟人化交互的沉迷依赖)” among its top ethical risks, even above concerns about AI loss of control. Interestingly, directly following the addiction risk is the risk of “challenging existing social order (挑战现行社会秩序),” including traditional “views on childbirth (生育观).”
What makes AI chatbot interaction so concerning? Why is the U.S. more worried about child interaction, whereas the Chinese government views AI companions as a threat to family-making and childbearing? The answer lies in how different societies build different types of AI companions, which then create distinct societal risks. Drawing from an original market scan of 110 global AI companion platforms and analysis of China’s domestic market, I explore here shows how similar AI technologies produce vastly different companion experiences—American AI girlfriends versus Chinese AI boyfriends—when shaped by cultural values, regulatory frameworks, and geopolitical tensions. — Read More
Hierarchical Reasoning Model
Reasoning, the process of devising and executing complex goal-oriented action sequences, remains a critical challenge in AI. Current large language models (LLMs) primarily employ Chain-of-Thought (CoT) techniques, which suffer from brittle task decomposition, extensive data requirements, and high latency. Inspired by the hierarchical and multi-timescale processing in the human brain, we propose the Hierarchical Reasoning Model (HRM), a novel recurrent architecture that attains significant computational depth while maintaining both training stability and efficiency. HRM executes sequential reasoning tasks in a single forward pass without explicit supervision of the intermediate process, through two interdependent recurrent modules: a high-level module responsible for slow, abstract planning, and a low-level module handling rapid, detailed computations. With only 27 million parameters, HRM achieves exceptional performance on complex reasoning tasks using only 1000 training samples. The model operates without pre-training or CoT data, yet achieves nearly perfect performance on challenging tasks including complex Sudoku puzzles and optimal path finding in large mazes. Furthermore, HRM outperforms much larger models with significantly longer context windows on the Abstraction and Reasoning Corpus (ARC), a key benchmark for measuring artificial general intelligence capabilities. These results underscore HRM’s potential as a transformative advancement toward universal computation and general-purpose reasoning systems. — Read More
Scientists just developed a new AI modeled on the human brain — it’s outperforming LLMs like ChatGPT at reasoning tasks
The hierarchical reasoning model (HRM) system is modeled on the way the human brain processes complex information, and it outperformed leading LLMs in a notoriously hard-to-beat benchmark.
Scientists have developed a new type of artificial intelligence (AI) model that can reason differently from most large language models (LLMs) like ChatGPT, resulting in much better performance in key benchmarks.
The new reasoning AI, called a hierarchical reasoning model (HRM), is inspired by the hierarchical and multi-timescale processing in the human brain — the way different brain regions integrate information over varying durations (from milliseconds to minutes). — Read More
After Hosting the AI Film Festival Screening
On the evening of Friday, September 26, I had the pleasure of hosting a film screening that showcased works created with artificial intelligence (AI). This was the event I had previously announced in my last posting.
The venue was Tōshunji Temple in Yamaguchi City, a Rinzai Zen temple with a history of around 500–600 years. At the same time, its grounds also host contemporary artworks, a horse, and a pottery studio — functioning almost like a community art center for the present day.
… It was in this city, at Tōshunji, that we hosted the international AI Film Festival organized by OMNI, based in Sydney, Australia. … One of the main goals was to raise literacy around AI. — Read More
Neuralink: We Have a Backlog of 10K Patients Who Want Our Brain Implant
Neuralink has a backlog of 10,000 individuals interested in having its N1 device drilled into their skulls, according to President and Co-Founder Dongjin (DJ) Seo. The company has implanted the N1 into 12 clinical trial patients so far; Seo expects the number to grow to 25 by year’s end.
People can sign up to participate in the company’s clinical trials online, but to qualify, they must have either limited or no ability to use their hands due to a cervical spinal cord injury or ALS. — Read More
A built-in ‘off switch’ to stop persistent pain
Nearly 50 million people in the U.S. live with chronic pain, an invisible and often stubborn condition that can last for decades.
Now, collaborative research led by neuroscientist J. Nicholas Betley finds that a critical hub in the brainstem, has a built-in “off switch” to stop persistent pain signals from reaching the rest of the brain.
Their findings could help clinicians better understand chronic pain. “If we can measure and eventually target these neurons, that opens up a whole new path for treatment,” says Betley. — Read More
Rick's Cafe AI 