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Paralyzed individuals successfully use brain waves to operate tablet computers

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In a collaborative study presented by scientists primarily affiliated with Stanford and Brown Universities, participants suffering from significant paralysis were successfully able to use non-modified applications on an Android tablet using their brain waves. In previous studies, “point-and-click” computer functionality interpreted from these kinds of signals has been accomplished, but the applications available to participants was limited to software and devices that had been specialized and personalized for users’ specific needs. This study has demonstrated technology that overcomes this limitation and enables access to the full range of software available to non-disabled users. Participants enjoyed applications previously unavailable to them such as streaming music services and a piano keyboard player.

To accomplish the study’s objectives, scientists capitalized and combined existing technologies for their unique end. Brain waves from participants’ brain implants were sent to a commercially available recording system and then processed and decoded by an existing real-time interpreter software. The decoded data was then transmitted to a Bluetooth interface configured as a wireless mouse which was paired to an Android tablet. While the steps to accomplish the task at hand are many, the result somewhat resembles telepathy but largely resembles greater accessibility for the disabled.

A study participant searches for orchid care information using signals from her brain. | Credit: CC0 via PLOS One

Individuals suffering from various forms of paralysis generally have difficulty using communication technologies. Strokes, neurological injuries, and neurodegenerative diseases such as ALS (Amyotrophic Lateral Sclerosis) can all lead to limited physical functionality that impairs the use of communication devices. However, although physical mobility is affected by paralytic conditions, the brain often continues to send signals to muscles to trigger movement. Using this attempted signaling, scientists have been developing technology to bridge the disconnect between the brain’s signals and the intended outcomes.

Brain-computer interfaces (BCIs) record activity in the brain and interpret that data to generate an action. Using microelectrode arrays implanted into areas of the brain corresponding to desired functionality, neural signals are transmitted to the array’s plates or shanks that interpret their activity into usable data. All of the participants in this study had implants placed in the hand area of their brains’ dominant motor cortexes from which signals were recorded. Since computers inherently operate via digital signals, they stand as promising tools to facilitate communications originating from BCIs. In particular, algorithms developed using machine learning have been designed to interpret brain signals into computer mouse movement, a capability which can be expanded into software accessibility.

One of the study’s researchers, Krishna V. Shenoy, is a consultant for Neuralink Inc., Elon Musk’s brain-computer interface company. While BCIs in general have similar goals to Neuralink’s, the major difference is in purpose, namely in that Musk’s company aims to enhance human capabilities to better compete with artificial intelligence rather than restoring or improving lost abilities. Where BCIs interpret existing brain signals to reenable preexisting capabilities, Neuralink hopes to merge computing and brain power into a seemingly singular function via tiny, dust-sized particles rather than traditional implants.

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Watch the video below to see the participants’ tablet use during the study:

Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Elon Musk

Tesla Terafab set for launch: Inside the $20B AI chip factory that will reshape the auto industry

Tesla set to launch “Terafab Project: A vertically integrated chip fabrication effort combining logic processing, memory, and advanced packaging.

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Tesla is making one of the boldest bets in its history. On March 14, Elon Musk posted on X that the “Terafab Project launches in 7 days,” pointing to March 21, 2026 as the start date for what he has described as a vertically integrated chip fabrication effort combining logic processing, memory, and advanced packaging.

Tesla first confirmed Terafab on its January 28, 2026 earnings call, where Musk told investors the company needs to build a chip fabrication facility to avoid a supply constraint projected to materialize within three to four years. But the seeds were planted even earlier. At Tesla’s annual general meeting last year, Musk warned that even in the best-case scenario for chip production from their suppliers, it still wouldn’t be enough, and declared that building a “gigantic chip fab” simply had to be done.

While there has been no official announcement on where Tesla plans to break ground on the massive Terafab, all signs point to the North Campus of Giga Texas in Austin.

Months of speculation has surrounded Tesla’s North Campus expansion at Giga Texas, where drone footage captured by observer Joe Tegtmeyer revealed massive construction site preparation just north of the existing factory on a scale that rivals the original Giga Texas footprint itself.

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Samsung’s Tesla AI5/AI6 chip factory to start key equipment tests in March: report

The project is projected to produce 100–200 billion AI and memory chips annually, targeting 100,000 wafer starts per month, at an estimated cost of $20 billion. Tesla is targeting 2-nanometre process technology and anticipated to be the most advanced node currently in commercial production. Dubbed the Tesla AI5 chip, the chip will pack 40x–50x more compute performance and 9x more memory than AI4, and will be among the first products Terafab factory is set to produce. This highly optimized, and massively powerful inference chip is designed to make full self-driving (FSD) and Tesla’s Optimus robots faster, safer, and with full autonomy.

tesla-optimus-pilot-production-line

(Credit: Tesla)

This is where Terafab becomes a genuine game-changer. If Tesla successfully builds a 2nm chip fab at scale, it becomes one of only a handful of entities that’s capable of producing AI silicon in-house, with competitive implications that extend far beyond Tesla’s own vehicles, and potentially positioning Tesla as a chip supplier or licensor to other industries.

The next-gen Tesla AI chips will power advancements in Full Self-Driving software, the Cybercab Robotaxi program, and the Optimus humanoid robot line. Musk’s projections for Optimus require chip volumes that no existing external supplier can commit to on Tesla’s timeline.Competitors like Waymo and GM’s Cruise remain dependent on third-party silicon, leaving them exposed to the same supply chain vulnerabilities Tesla is now working to eliminate entirely.

The Terafab launch this week may not mean a factory opens its doors overnight, but it signals Tesla is serious about owning the entire AI stack, from software to silicon.

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What is Digital Optimus? The new Tesla and xAI project explained

At its core, Digital Optimus operates through a dual-process architecture inspired by human cognition.

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Credit: Grok

Tesla and xAI announced their groundbreaking joint project, Digital Optimus, also nicknamed “Macrohard” in a humorous jab at Microsoft, earlier this week.

This software-based AI agent is designed to automate complex office workflows by observing and replicating human interactions with computers. As the first major outcome of Tesla’s $2 billion investment in xAI, it represents a powerful fusion of hardware efficiency and advanced reasoning.

Tesla announces massive investment into xAI

At its core, Digital Optimus operates through a dual-process architecture inspired by human cognition.

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Tesla’s specialized AI acts as “System 1”—the fast, instinctive executor—processing the past five seconds of real-time computer screen video along with keyboard and mouse actions to perform immediate tasks.

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xAI’s Grok model serves as “System 2,” the strategic “master conductor” or navigator, providing high-level reasoning, world understanding, and directional oversight, much like an advanced turn-by-turn navigation system.

When combined, the two can create a powerful AI-based assistant that can complete everything from accounting work to HR tasks.

Will Tesla join the fold? Predicting a triple merger with SpaceX and xAI

The system runs primarily on Tesla’s low-cost AI4 inference chip, minimizing expensive Nvidia resources from xAI for competitive, real-time performance.

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Elon Musk described it as “the only real-time smart AI system” capable, in principle, of emulating the functions of entire companies, handling everything from accounting and HR to repetitive digital operations.

Timelines point to swift deployment. Announced just days ago, Musk expects Digital Optimus to be ready for user experience within about six months, targeting rollout around September 2026.

It will integrate into all AI4-equipped Tesla vehicles, enabling parked cars to handle office work during downtime. Millions of dedicated units are also planned for deployment at Supercharger stations, tapping into roughly 7 gigawatts of available power.

Digital Optimus directly supports Tesla’s broader autonomy strategy. It leverages the same end-to-end neural networks, computer vision, and real-time decision-making tech that power Full Self-Driving (FSD) software and the physical Optimus humanoid robot.

By repurposing idle vehicle compute and extending AI4 hardware beyond driving, the project scales Tesla’s autonomy ecosystem from roads to digital workspaces.

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As a virtual counterpart to physical Optimus, it divides labor: software agents manage screen-based tasks while humanoid robots tackle physical ones, accelerating Tesla’s vision of general-purpose AI for productivity, Robotaxi fleets, and beyond.

In essence, Digital Optimus bridges Tesla’s vehicle and robotics autonomy with enterprise-scale AI, promising massive efficiency gains. No other company currently matches its real-time capabilities on such accessible hardware.

It really could be one of the most crucial developments Tesla and xAI begin to integrate, as it could revolutionize how people work and travel.

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Tesla adds awesome new driving feature to Model Y

Tesla is rolling out a new “Comfort Braking” feature with Software Update 2026.8. The feature is exclusive to the new Model Y, and is currently unavailable for any other vehicle in the Tesla lineup.

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Credit: Tesla

Tesla is adding an awesome new driving feature to Model Y vehicles, effective on Juniper-updated models considered model year 2026 or newer.

Tesla is rolling out a new “Comfort Braking” feature with Software Update 2026.8. The feature is exclusive to the new Model Y, and is currently unavailable for any other vehicle in the Tesla lineup.

Tesla writes in the release notes for the feature:

“Your Tesla now provides a smoother feel as you come to a complete stop during routine braking.”

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Interestingly, we’re not too sure what catalyzed Tesla to try to improve braking smoothness, because it hasn’t seemed overly abrupt or rough from my perspective. Although the brake pedal in my Model Y is rarely used due to Regenerative Braking, it seems Tesla wanted to try to make the ride comfort even smoother for owners.

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There is always room for improvement, though, and it seems that there is a way to make braking smoother for passengers while the vehicle is coming to a stop.

This is far from the first time Tesla has attempted to improve its ride comfort through Over-the-Air updates, as it has rolled out updates to improve regenerative braking performance, handling while using Full Self-Driving, improvements to Steer-by-Wire to Cybertruck, and even recent releases that have combatted Active Road Noise.

Tesla set to activate long-awaited Cybertruck feature

Tesla holds a unique ability to change the functionality of its vehicles through software updates, which have come in handy for many things, including remedying certain recalls and shipping new features to the Full Self-Driving suite.

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Tesla seems to have the most seamless OTA processes, as many automakers have the ability to ship improvements through a simple software update.

We’re really excited to test the update, so when we get an opportunity to try out Comfort Braking when it makes it to our Model Y.

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