A Real Transformer Robot? A Historical IPO, & More

TLDR;

Welcome back! This week, we have robots from the future, an historical IPO (with detailed technical coverage at the end of the newsletter), a star Lab’s first model release, OpenAI’s personal finance tool, and many other news items you must know.

Enjoy!

RESEARCH

A New Type of Generative Model?

Thinking Machines, one of the most highly valued AI Labs in the private markets and packed with star researchers and engineers from other top Labs, is finally showing its teeth.

And the results are very promising because they aren’t simply following the same playbook as other top Labs; they are actually pushing novel research (and quite publicly, too).

Their first major model release is an interaction model, trained to offer a strong balance between intelligence and interactivity. The trade-off here is obvious because interactivity goes against both scaling laws of intelligence:

The smarter you want a model to become, the larger it is (and thus slower to run)

The more thinking budget you give it, the slower its response will be, too.

The solution is an architecture that may sound familiar if you’re a regular reader of this newsletter because it draws strong similarities to how robotics AI is being approached, but also includes unique features.

It’s inspired by Daniel Kahneman’s System 1 and System 2 ways of thinking. Known as Thinking, Fast and Slow, it argues that our brains think at two speeds, one fast one slow:

one is intuition-based, fast, unconscious, like flinching when someone is about to hit you,

and the other is slow, conscious, and deliberate, like solving a maths test.

Following this principle, and as the thumbnail suggests, here we have an architecture with a fast model, known as the interaction model, which is the one in charge of interacting with the user, and the background model, which is in charge of the ‘slow thinking’ and also of making the necessary tool calls (like calling a search API to check something on the Internet).

This way, the model can still handle long-range, reasoning-heavy tasks that require time while still appearing snappy and “real-time.” The result is a system that breaks with the way AIs have historically interacted with us, on a turn-by-turn basis.

Instead, both you and the model interact continually across all time slots. Therefore, the AI can talk alongside you and across multiple modalities, such as audio, video, or text.

These allow this “model” to do stuff we hadn’t seen before, certainly not at these levels of interactivity:

It can handle real-time multimodal interaction: audio, video, text, screen input, and tool outputs in one continuous stream.

It can process interaction every 200 ms, so it understands pauses, interruptions, overlapping speech, timing, hesitation, and turn-taking.

It can speak while listening, allowing simultaneous conversation, live translation, corrections, and backchanneling.

It can watch what you are doing live, spot bugs, follow a screen, count reps, comment on a video feed, or react to visual changes.

It can coordinate with tools and background agents, meaning one part…

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