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Elon Musk’s Neuralink recently implanted a chip in a human for the first time. The emerging market of brain computer interfaces, or BCIs, is in the process of finding its footing. In a world where AI is on the rise, BCIs allow for telepathic control of computers and wireless operation of prosthetics. But how does this tech work?

WSJ goes inside a brain surgery to see how the implants work, and breaks down what it’s going to take to get these devices on the market.

Chapters:
0:00 Musk’s Neuralink.
0:41 The market.
3:03 Synchron.
3:57 Precision.
5:16 What’s next?

News Explainers.

Los Angeles Unified School District (LAUSD) is rolling out an AI-powered educational tool that it says will provide students with personalized learning plans and resources.

The tool, dubbed Ed, can translate personalized learning plans into over 100 languages, a much-needed resource. LAUSD is nation’s second-largest district, with 565,479 students, of which 86,081 (15%) are still “learning to speak English proficiently,” according to a district fact sheet.

It also assists students with complex administrative tasks such as submitting applications. Parents are expected to use the chatbot to ask questions, as well as get updates on their child’s progress and reminders about upcoming assignments and programs.

A groundbreaking nanosurgical tool — about 500 times thinner than a human hair — could be transformative for cancer research and give insights into treatment resistance that no other technology has been able to do, according to a new study.

The high-tech double-barrel nanopipette, developed by University of Leeds scientists, and applied to the global medical challenge of cancer, has — for the first time — enabled researchers to see how individual living cancer cells react to treatment and change over time — providing vital understanding that could help doctors develop more effective cancer medication.

The tool has two nanoscopic needles, meaning it can simultaneously inject and extract a sample from the same cell, expanding its potential uses. And the platform’s high level of semi-automation has sped up the process dramatically, enabling scientists to extract data from many more individual cells, with far greater accuracy and efficiency than previously possible, the study shows.

In the last decade, thanks to advances in AI, the internet of things, machine learning and sensor technologies, the fantasy of digital twins has taken off. BMW has created a digital twin of a production plant in Bavaria. Boeing is using digital twins to design airplanes. The World Economic Forum hailed digital twins as a key technology in the “fourth industrial revolution.” Tech giants like IBM, Nvidia, Amazon and Microsoft are just a few of the big players now providing digital twin capabilities to automotive, energy and infrastructure firms.

The inefficiencies of the physical world, so the sales pitch goes, can be ironed out in a virtual one and then reflected back onto reality. Test virtual planes in virtual wind tunnels, virtual tires on virtual roads. “Risk is removed” reads a recent Microsoft advertorial in Wired, and “problems can be solved before they happen.”

All of a sudden, Dirk Helbing and Javier Argota Sánchez-Vaquerizo wrote in a 2022 paper, “it has become an attractive idea to create digital twins of everything.” Cars, trains, ships, buildings, airports, farms, power plants, oil fields and entire supply chains are all being cloned into high-fidelity mirror images made of bits and bytes. Attempts are being undertaken to twin beaches, forests, apple orchards, tomato plants, weapons and war zones. As beaches erode, forests grow and bombs explode, so too will their twins, watched closely by technicians for signals to improve outcomes in the real world.

“They remove some of the magic,” said Dimitris Papailiopoulos, a machine learning researcher at the University of Wisconsin, Madison. “That’s a good thing.”

Training Transformers

Large language models are built around mathematical structures called artificial neural networks. The many “neurons” inside these networks perform simple mathematical operations on long strings of numbers representing individual words, transmuting each word that passes through the network into another. The details of this mathematical alchemy depend on another set of numbers called the network’s parameters, which quantify the strength of the connections between neurons.