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Elon Musk’s Neuralink brain-machine interface is turning sci-fi into reality
Besides giving the world the option to switch to Tesla emissions-free electric cars and hopes of sending humans to Mars and beyond, Elon Musk also dreams of giving humans symbiosis with artificial intelligence through an implantable brain-machine interface created by Neuralink, a company he founded in 2016.
Neuralink is working on improving the basic structures of high-density Utah Array, a tiny chip that has become the industry benchmark for recording large populations of neurons. Dr. Richard Norman from the University of Utah invented the chip in 1997, which acts as an ultra-thin, flexible, and biocompatible polymer that connects the human brain to a tiny chip. During an event last year, Neurallink explained that the implant can be placed behind the ear and can interpret brain signals. Musk’s neural tech company has also invented a robot that can sew the implant to the brain with better precision than any human surgeon.
Wait until you see the next version vs what was presented last year. It’s *awesome*.
— Elon Musk (@elonmusk) February 3, 2020
So far, the brain-machine interface by Neuralink has reportedly helped a primate communicate with a computer interface. There are plans to install a prototype this year into a human. According to Musk, they are still on track to do this.
“It will ultimately be used to make up for entire lost sections of the brain due to stroke/accident/congenital. Don’t want to get too excited, but the potential is truly transformational for restoring brain & motor functions. There is no other way to do it imo,” Musk also wrote on Twitter.
The possibilities for Neuralink’s implant are endless. The symbiosis between humans and AI will be a long shot but Neuralink’s implantable device can pave the way for medical advancements that can help people with chronic neurological problems. Possible medical uses for Neuralink’s device in the future include controlling devices, restoring sensation, and synthetic speech.
CONTROLLING DEVICES
The brain is a complex network of nerves that uses impulses to sense the outside world and to control the human body. Neuralink will use these signals and amplify them so a patient can use them to be more functional. For example, someone with paralyzed upper extremity due to a stroke can have a brain-machine interface on the center of the brain that controls movements of the arm and hands which will help patients feed, dress, and generally function on their own.
Likewise, for someone who has an amputated limb, the Neuralink brain-machine interface will be able to communicate with a robotic arm to help someone use an artificial hand to write or use a computer. It can also be perfect for someone who needs to control a robotic leg to prop one up to stand without the help of anyone.
With a smart home setup, a paralyzed person who cannot clearly or is unable to speak and move can simply command a computer to dim the lights, turn on the air conditioner, or call someone if they need urgent attention.
While it might be a very long shot, these brain-machine interfaces interacting with other future technologies can also serve as bridges to parts of the body that are medically “disconnected”. For example, a patient with spinal cord injury has severed connections between the brain and parts of their body corresponding to the level their spinal cord was injured. The Neuralink implant can play pseudo stem cells that will provide the artificial connection so one can better function. Same for someone with multiple sclerosis whose nerves basically lose the sheath that makes them transmit electrical signals optimally.
“RESTORE” SENSATION
Just like how Neuralink can be exploited to help the brain control movement of a robotic arm, it is highly possible to tap into the sensory cortex of the brain. Sensation allows better manipulation of one’s environment and should be very helpful even when using robotic arms. One can tap the signals of the brain, send it to the brain-machine implant and to the robotic hand, for example, and back. If one grabs a glass of water, it can easily control the movement through space because the patient knows its shape, weight, texture, temperature, among other factors.
The Neuralink team also aims to use the brain-machine interface to “give back” one’s vision by tapping into the visual center of the brain.
SYNTHETIC SPEECH
With its ability to tap into specific signals of the brain, Neuralink also has the potential to create synthetic speech for people who are paralyzed or those with neurological conditions that do not allow them to speak.
These are just some of the things we can see Neuralink will be used for in the future. While all these seem to be fantastical, according to Neuralink, what they’re doing is not pulled from thin air but based on decades of neurological foundation.
Ultimately, with the dream of human-AI symbiosis, as more technologies develop, the use for Neuralink’s brain-machine implant will evolve. Elon Musk mentioned before that perhaps one day, it will be used for telepathic communication between humans or perhaps even drive a Tesla. Or perhaps, in the future, one can upgrade one’s knowledge and download terabytes of information with a blink of an eye through Starlink.
SpaceX confirmed today that it has officially signed its third massive compute deal, providing compute at its Colossus data center in Southaven, Tennessee.
Reflection AI will gain immediate access to NVIDIA GB300 chips at SpaceX’s Colossus 2 data center. In return, Reflection will pay SpaceX $150 million per month starting on July 1, with total payments reaching approximately $6.3 billion if the contract runs through its duration, which is until 2029. Either party can terminate the agreement with 90 days’ notice after the initial three-month period.
CNBC first reported the deal.
🚨 SpaceXAI has agreed to a new compute deal with Reflection AI.
Reflection gets access to NIVIDIA GB300s, and will pay $150M per month to SpaceXAI for the compute. pic.twitter.com/bNPare8U5u
— TESLARATI (@Teslarati) June 22, 2026
This latest partnership highlights SpaceX’s strategy of commercializing its massive Colossus supercomputing infrastructure, originally developed to power Elon Musk’s Grok AI models. The company has rapidly expanded its customer base in the AI sector following its February 2026 merger with xAI, a transaction that valued the combined entity at $1.25 trillion.
SpaceX has previously signed significant compute deals with other major players.
It granted Anthropic exclusive access to the full capacity of its Colossus 1 data center, which exceeds 300 megawatts and includes over 220,000 NVIDIA GPUs. Details from SpaceX’s IPO filings indicate Anthropic will pay $1.25 billion per month through May 2029, potentially generating around $45 billion over the term of the deal.
Additionally, Google agreed to pay SpaceX $920 million per month for compute capacity from October 2026 through June 2029. This 32-month period will provide Google access to roughly 110,000 NVIDIA GPUs, along with supporting processors and memory. Capacity ramps up through September at a reduced fee, with termination options after the first year.
SpaceXA also established arrangements for computing power with Cursor, an AI coding startup. SpaceX acquired them in a $60 billion all-stock deal.
These arrangements position SpaceX’s collective position as an AI infrastructure powerhouse with high-margin revenue potential. The Google deal alone could generate nearly $29.5 billion over its term, while the Reflection contract adds another $6.3 billion.
Combined with the Anthropic arrangement, SpaceX stands to realize tens of billions in revenue from compute leasing in the coming years, which diversifies beyond SpaceX’s traditional rocket launches and Starlink operation.
The deals underscore growing demand for advanced AI training and inference capacity amid chip shortages and surging model development needs. Reflection, valued at $25 billion and focused on “American open intelligence” with government and national security ties, cited recent restrictions on closed models as validation for open-source approaches.
For SpaceX, the partnerships transform capital-intensive data centers into flexible revenue sources while supporting its broader AI ambitions after the company has gone public.
It is safe to say SpaceX won’t be going for electric rockets anytime soon.
In a characteristically blunt reply on X, SpaceX frontman Elon Musk stated, “Unfortunately, electric rockets are impossible,” following reports that MSCI had assigned SpaceX its lowest possible ESG rating of CCC.
The assessment, issued just this past week, coinciding closely with SpaceX’s public market debut, placed the company on par with nations like Russia in sustainability scoring and cited significant risks in environmental, social, and governance areas.
MSCI flagged SpaceX’s exposure to rocket emissions and other operational impacts, alongside governance concerns such as concentrated control by Musk and limited shareholder protections. Musk’s terse comment directly addressed the environmental pillar, underscoring a core physical constraint that ESG frameworks often overlook when evaluating high-thrust industries.
Unfortunately, electric rockets are impossible
— Elon Musk (@elonmusk) June 21, 2026
Electric propulsion systems do exist and are widely used in space. Ion thrusters and Hall-effect thrusters accelerate ionized propellant, typically xenon or krypton, using electric fields, achieving very high specific impulse, often exceeding 3,000 seconds compared to roughly 300–450 seconds for chemical rockets.
This efficiency makes them ideal for satellite station-keeping, orbit raising, and deep-space missions where low thrust over long durations is sufficient. SpaceX’s own Starlink satellites employ electric propulsion for these purposes.
However, launching from Earth’s surface demands something entirely different: enormous thrust delivered rapidly to overcome gravity and atmospheric drag. A typical orbital-class booster must generate thrust far exceeding its weight, often in the millions of Newtons within seconds.
Chemical rockets achieve this through exothermic combustion of dense propellants, producing high-mass-flow, high-velocity exhaust. Electric systems, by contrast, expel very small amounts of mass at extremely high speeds. Generating equivalent thrust would require impractical onboard power levels, massive energy storage or generation systems, and prohibitive added mass, rendering the approach infeasible with current or near-term technology.
Musk has previously expressed a similar sentiment, noting a desire for electric orbital rockets while acknowledging the inescapable requirements of Newton’s third law and energy delivery. The distinction is clear: electric propulsion excels once a vehicle is already in space; it cannot replace the high-thrust chemical phase required to reach orbit from the ground.
The episode illustrates broader critiques of ESG ratings. Proponents argue they incentivize better risk management and long-term sustainability. Detractors, including Musk—who has previously called ESG a “scam”—contend that such metrics can penalize essential activities when no practical alternative exists, potentially discouraging innovation in sectors like space access.
Elon Musk dubs the S&P 500 ESG as “outrageous scam” after Tesla gets booted from index
SpaceX has sought to mitigate launch-related impacts through reusability: Falcon 9 boosters have flown more than 30 times in some cases, dramatically lowering the manufacturing and emissions burden per kilogram delivered to orbit. Starship’s design further emphasizes rapid reusability and methane propellant, which can theoretically be produced via sustainable pathways.
Ultimately, Musk’s remark serves as a reminder that certain engineering realities persist regardless of scoring systems. As humanity expands its presence in space for communications, science, and exploration, balancing genuine environmental progress with technological necessity remains a central challenge.
ESG frameworks may evolve, but the fundamental limits of electric launch propulsion are unlikely to change soon.
Tesla just trademarked ‘MEGAPOD’ with the United States Patent and Trademark Office (USPTO), its latest move in what seems to be a hint that the company is incredibly focused on its AI efforts and storage needs as compute increases.
The application carries serial number 99893717 and lists the applicant as Tesla, Inc., located at 1 Tesla Road, Austin, Texas 78725.
The filing remains in ‘live pending’ status, and it is a new application waiting for assignment to an examining attorney. It has not yet been published or registered.
Tesla just trademarked MEGAPOD
Summary:
“Modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence processing, computer networking hardware, electrical power distribution units, and… pic.twitter.com/3l85DsKadl— Robin (@xdNiBoR) June 19, 2026
According to the official goods and services description in the application, Tesla describes ‘MEGAPOD’ as:
“Modular data center hardware systems for artificial intelligence computing, comprised of computer servers, computer hardware for artificial intelligence processing, computer networking hardware, electrical power distribution units, and cooling systems, sold as a unit; self-contained modular computing hardware systems for artificial intelligence workloads; integrated computer hardware platforms for artificial intelligence computing, namely, enclosures containing computer hardware, power distribution hardware, and cooling hardware, sold as a unit; downloadable software for monitoring, managing, optimizing, and regulating modular artificial intelligence computing hardware systems.”
This description specifies complete, self-contained modular units that integrate servers and specialized AI processing hardware with networking components, power distribution, and cooling systems. It also includes associated downloadable software for oversight and optimization of these systems. The language emphasizes hardware sold “as a unit” and enclosures that combine the necessary elements for AI computing workloads.
Tesla has an established history of developing and commercializing modular hardware systems. Its Megapack product line, for example, consists of utility-scale battery energy storage systems designed as containerized units for grid applications. The MEGAPOD filing follows a similar pattern of protecting a name for modular, integrated hardware platforms, this time focused on artificial intelligence computing infrastructure.
This could be an early move, especially as Tesla did not have trademark rights to the word ‘Cybercab,’ the name of its self-driving, ride-hailing-focused vehicle.
Trademark applications of this type allow companies to secure priority rights to a name for defined categories of goods and services. The USPTO examines applications for compliance with legal requirements, including distinctiveness and absence of conflicts with prior marks. If the application proceeds successfully through examination, publication, and any opposition period, it could result in a federal trademark registration providing nationwide protection. This is what Tesla’s obvious intention is with ‘MEGAPOD.’
Public reports and analysis suggest MEGAPOD could represent modular, container-style AI computing pods designed for easy deployment. These would bundle servers, AI accelerators, power systems, and cooling into self-contained units suitable for distributed AI workloads. This approach aligns with Tesla’s announced AI compute strategy.
In March 2026, Elon Musk outlined plans for “Digital Optimus” (also referred to as Macrohard), a joint Tesla-xAI project for AI agents capable of handling complex digital tasks. The plans include running these agents on Tesla’s AI4 hardware in parked vehicles as well as dedicated compute units installed at Supercharger stations, which collectively offer substantial unused electrical capacity.
What is Digital Optimus? The new Tesla and xAI project explained
A modular hardware platform like the one described in the ‘MEGAPOD’ filing would support scalable, rapid deployment of such distributed compute resources. It could complement Tesla’s other AI infrastructure efforts, including the Dojo supercomputer used for training models and the development of AI systems for autonomous driving and robotics, by enabling edge or regional AI inference without reliance on traditional centralized data centers.
SpaceX confirms third massive compute deal at Colossus data center
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