Meta’s Brain2Qwerty v2 turns thoughts into text, and it doesn’t need brain implants


Artificial intelligence is getting surprisingly good at understanding humans. Now, Meta wants it to understand our brains too. The company has unveiled Brain2Qwerty v2, an upgraded AI system that can translate brain activity into full sentences, all without requiring brain implants or surgery. The goal isn’t mind reading for the masses. Instead, it’s to help people who have lost the ability to speak communicate again.

How a Brain-powered keyboard works

The easiest way to think about Brain2Qwerty v2 is as an incredibly advanced brain-powered keyboard. Volunteers wear a Magnetoencephalography (MEG) scanner, which measures tiny magnetic signals produced by the brain while they type. Instead of watching the keyboard, the AI watches those brain signals and predicts what the person intended to type.

The biggest leap over the original Brain2Qwerty is that it no longer tries to decode one letter at a time. Instead, it looks at characters, words, and entire sentences, using large language models to fill in the blanks, much like your smartphone predicts the next word while typing. Meta even describes the system as adding semantic understanding, allowing it to recover coherent sentences from extremely noisy brain signals.

Under the hood, the AI combines deep learning models such as Transformers and Convolutional Neural Networks with fine-tuned language models that act almost like a spellchecker for the brain. If the neural signal is incomplete or distorted, the language model uses context to infer what the user most likely intended to say. Meta also used AI agents to optimize the decoding pipeline itself, helping improve real-time performance.

As highlighted in the official research paper, the system was trained using around 22,000 typed sentences collected from nine volunteers, each of whom spent roughly 10 hours wearing an MEG scanner while typing. Brain2Qwerty v2 currently achieves an average 61% word accuracy, while the best participant reached 78% accuracy, with more than half of their decoded sentences containing one word error or less. Meta has also open-sourced both the training code and dataset so other researchers can build on the work.

The magic of skipping surgery

The funny thing is that the biggest breakthrough here isn’t the AI. It’s the fact that it works without opening someone’s skull. Most high-performance brain-computer interfaces today, including Elon Musk’s Neuralink, rely on surgically implanted electrodes to achieve high accuracy. Brain2Qwerty v2 takes a very different approach by using a completely external Magnetoencephalography (MEG) scanner to read brain activity, eliminating the risks associated with intracranial implants while still achieving surprisingly strong results.

Meta is still a long way from building a consumer product, and nobody should expect to type emails using their thoughts anytime soon. The MEG scanners used by Brain2Qwerty are massive, expensive machines that belong in research labs, not living rooms. But by combining advances in neuroscience with modern AI, Meta is showing that non-invasive brain-computer interfaces may not be as far away as they once seemed. And for people who have lost the ability to communicate, that could end up being far more meaningful than any chatbot or image generator.



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Bezos’s Prometheus raised $12B at a $41B valuation from JPMorgan, Goldman Sachs, and BlackRock. It builds AI for engineering physical products with 150 employees.

Prometheus, the AI startup co-led by Jeff Bezos, has raised $12 billion in a funding round that values the company at $41 billion. Investors include JPMorgan Chase, Goldman Sachs, BlackRock, DST Global, and Arch Venture Partners, alongside Bezos himself. Total funding now exceeds $18 billion.

The company is building what Bezos calls an “artificial general engineer,” AI tools designed to accelerate the process from design to manufacturing for physical products. Target industries include computing, aerospace, automotive, advanced manufacturing, and drug discovery. Prometheus currently has about 150 employees.

Bezos co-leads the company with Vik Bajaj, a Stanford medical school professor who previously co-founded Alphabet’s Verily health research lab. Bezos started as a founding investor in late 2024 but became so involved he took an operational role. “I became so impressed by what was happening and the potential that I decided I couldn’t sit on the sidelines and I needed to jump in with both feet,” he told CNBC.

This is Bezos’s first operational role in a technology company since stepping down as Amazon CEO in 2021. Prometheus launched in November 2025 with $6.2 billion in initial funding. The earlier reporting valued the round at $38 billion. The final close came in at $41 billion, a 7.9% markup from the figure reported in April.

The company’s pitch is “physical AI,” models trained on real-world experimental data, robotics interactions, and engineering workflows rather than just text and images. Where most AI companies focus on language or code, Prometheus is targeting the hard science of making things, from bridges to chips. The approach is designed to understand the laws of physics, not just patterns in data.

Prometheus has also sought to raise tens of billions more for a holding company that plans to acquire firms it sees as benefiting from the technologies the lab is developing. That would make it not just a startup but a conglomerate, one that develops the AI and then buys the companies that use it.

Bezos’s broader AI portfolio now spans robotics firms Physical Intelligence and Nvidia-backed Generalist AI, plus his continuing role as Amazon’s executive chair. With Prometheus, he is betting that AI’s biggest value is not in chatbots or code generation but in accelerating the engineering of physical objects, the domain where the physical AI race is attracting its largest cheques.



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