Elon Musk is widely known as a visionary entrepreneur behind transformative companies like PayPal, Tesla, and SpaceX. Yet a unifying thread underlies Musk’s diverse ventures: a relentless drive to push the frontiers of artificial intelligence (AI) and robotics. Over the past three decades, Musk has repeatedly founded or funded companies that, directly or indirectly, advance AI technologies and autonomous systems. From his first startup in the 1990s to his latest projects, Musk has consistently steered his work toward a future where intelligent machines play a pivotal role. This article traces Musk’s entire career—from early software ventures like Zip2 and PayPal, through Tesla’s self-driving cars and humanoid robots, SpaceX’s autonomous rockets, Neuralink’s brain-computer interfaces, and up to new initiatives like xAI—highlighting how every endeavor contributes to AI and robotics. Along the way, we also see how Musk’s outspoken views on AI safety have influenced his projects. The story of Elon Musk’s career is essentially the story of weaving increasingly sophisticated AI into the fabric of modern technology, bringing sci-fi concepts to life through real engineering. What follows is a comprehensive look at Musk’s ventures in chronological order, revealing the connections that tie online banking, space travel, electric cars, and brain implants into one grand vision for humanity’s future with intelligent machines.
Early Life and Entrepreneurial Beginnings
Musk’s affinity for technology took root early. Born in 1971 in South Africa, he was programming by age 12, even selling the code for a video game he created. Science fiction novels and futuristic aspirations deeply influenced his young mindset, instilling a belief that advancing technology could solve big problems for humanity. This outlook set the stage for Musk’s lifelong focus on innovations like spaceflight and AI. In 1995, after immigrating to North America for college, Musk pivoted from academia to entrepreneurship. Together with his brother Kimbal, he founded his first company, Zip2, marking the start of a career dedicated to bold technological endeavors.
Zip2: Online Maps and the Spark of Innovation (1995–1999)
Zip2 was Musk’s maiden venture and an early test of his software skills. The startup developed a searchable online business directory with integrated maps—essentially an Internet version of the Yellow Pages. At a time when most businesses had little web presence, Zip2 enabled newspapers to offer city guides and directions to their readers. Elon Musk personally coded the initial platform, combining business listings with Navteq digital maps into a user-friendly tool. While Zip2 did not involve AI or robotics in a direct sense, it gave Musk hands-on experience in building software to help people navigate information. The product’s focus on maps and addresses foreshadowed the GPS-based navigation and route planning that would later be crucial for self-driving cars. In this way, Zip2’s technology laid a small but meaningful foundation for future AI-driven navigation systems. More immediately, Zip2 was a financial win. In 1999, Compaq acquired Zip2 for roughly $307 million, and Elon Musk netted about $22 million from the sale. This windfall provided Musk with the capital to pursue much more ambitious projects. Just as importantly, the experience affirmed Musk’s willingness to disrupt industries with software—an approach he would soon apply to banking, and later to cars and rockets.
X.com and PayPal: Pioneering Fintech with Automation (1999–2002)
Flush with Zip2 earnings, Musk co-founded X.com in late 1999, an online financial services startup. X.com offered one of the world’s first Internet banking platforms, including features like online payments and money transfers. In 2000, X.com merged with a rival startup, Confinity, which had a popular payments product called PayPal. The combined company took on the PayPal name and focused on the person-to-person payments market that Confinity pioneered. Musk became the largest shareholder of PayPal and briefly served as its CEO. Under the hood, PayPal’s platform relied heavily on software automation and early fraud-detection algorithms to handle transactions safely at scale. The company was known for using rule-based systems and machine learning techniques to identify suspicious activity among millions of payments, an AI-driven approach that gave PayPal a competitive edge in security. This use of intelligent software to manage risk foreshadowed how AI would later be integral to many of Musk’s projects. In October 2002, eBay acquired PayPal for $1.5 billion. Musk’s 11.7% stake earned him around $165 million from the deal, a massive sum that he soon poured into new ventures. The PayPal chapter of Musk’s career was pivotal for two reasons. First, it demonstrated how automation and smart algorithms could revolutionize an industry (in this case, finance) by making digital transactions seamless and secure. Second, the sale of PayPal gave Musk the resources to tackle much larger engineering challenges. Musk later remarked that he risked his entire fortune from PayPal to fund SpaceX and Tesla, reflecting his all-in commitment to advancing technology. In essence, PayPal’s success not only introduced AI techniques into mainstream commerce, but also acted as a springboard for Musk’s far-reaching ventures in AI and robotics.
SpaceX: Rocket Science Meets AI and Automation (2002–Present)
In 2002, Musk embarked on a quest that many viewed as science fiction: making humanity a multi-planetary species. He founded SpaceX (Space Exploration Technologies Corp.) with the goal of dramatically lowering the cost of space travel through reusable rockets. At its core, SpaceX is an aerospace company, but it has also become a showcase for advanced automation and robotic systems. Musk often highlights that a rocket is essentially “a robot” that must operate with extreme precision. Indeed, SpaceX’s achievements in rocketry owe much to AI-guided control systems and robotics.
Autonomous Rocket Landings and Control Systems
One of SpaceX’s signature innovations is the ability to land rocket boosters upright after launch, so they can be reused. This feat, once thought nearly impossible, is enabled by an AI-powered autopilot that commands the rocket’s descent. During a Falcon 9 booster landing, the onboard computer receives real-time data from GPS, inertial sensors, and radar, and then dynamically adjusts the engines and grid fins to steer the 14-story rocket to a precise touchdown. Unlike a pre-programmed routine, the system must adapt on the fly to wind gusts and shifting conditions. SpaceX has leveraged reinforcement learning and extensive simulations to train the landing algorithm, allowing the AI controller to “learn” how to correct for errors over thousands of virtual landings. The result is astonishing accuracy — Musk noted one Falcon 9 landed within 0.7 meters of the target center on a droneship, “closer than some people park their cars”. By 2017, SpaceX was routinely landing boosters on autonomous drone barges at sea. These rocket landings are robotic performances: no human pilot could possibly react quickly enough to control a rocket plummeting from space, but the AI autopilot handles it flawlessly. Every successful touchdown is a dramatic example of robotics and AI in action, with a spacecraft making its own decisions in fractions of a second to achieve a safe landing. SpaceX’s advances here have arguably pushed the state of the art in real-time control systems, a branch of AI.
Robotics in Rocket Recovery and Manufacturing
SpaceX also employs more traditional robotics. On its drone landing ships, a squat robot nicknamed “OctaGrabber” drives out to secure landed boosters, grappling the base of the rocket to stabilize it for transport. This task was once done by human engineers, but SpaceX automated it with an AI-guided robot to improve safety and efficiency. Within SpaceX’s factories, robotic machines help weld and assemble rocket parts with high precision. Additionally, sending rockets to space and back has necessitated innovations in robotic navigation and sensing. SpaceX’s Dragon spacecraft, for example, uses an automatic docking system with the International Space Station, relying on sensors and computer vision to latch on without human intervention. Musk has drawn parallels between SpaceX’s pursuit of “full and rapid reusability” in rockets and autonomy in other domains. In both cases, the strategy is to replace once-and-done hardware or manual tasks with smarter, iterative robotic processes that learn and improve. By perfecting autonomous rocket landings, SpaceX has effectively turned rockets into reusable robotic vehicles, analogous to how Tesla is turning cars into self-driving robots on wheels.
Catalyzing a New Era of Space Robotics
The implications of SpaceX’s work for AI and robotics go further. Landing and reusing boosters slashes launch costs by up to 70%, which in turn makes projects like Starlink (SpaceX’s satellite internet network) and prospective Mars missions economically feasible. On Mars, autonomous systems will be essential—robots will likely precede humans to build habitats and infrastructure. In this sense, SpaceX’s progress is laying the groundwork for interplanetary robotics. Musk’s long-term vision is to have fleets of Starship rockets ferrying people and cargo to Mars; these gigantic vehicles (still in development) are being designed for fully autonomous operation on distant worlds. SpaceX’s achievements have also invigorated the aerospace industry to adopt AI. Competing launch providers now consider autonomous landing a necessary feature, and agencies like NASA are investing in AI for trajectory optimization and spacecraft guidance. By demonstrating AI-driven rocketry at scale, Musk’s company has melded AI with the space domain as never before. As SpaceX continues to refine its autonomous systems and perhaps introduces robotics for on-orbit satellite servicing or Mars exploration, it remains at the forefront of applied AI and robotics.
Tesla: Electric Vehicles, Autopilot AI, and the Robotics Revolution (2004–Present)
If SpaceX brought robotics into space, Tesla Inc. has brought AI to the streets. Musk joined Tesla in 2004 (a year after its founding) and helped transform the fledgling electric car maker into an AI powerhouse. Tesla’s mission has been to accelerate sustainable energy through electric vehicles (EVs), but Musk also positions Tesla squarely as an artificial intelligence and robotics company. Modern Tesla cars are essentially “computers on wheels”, equipped with advanced software and sensors that enable autonomous driving features. Under Musk’s leadership, Tesla has pioneered self-driving car technology, developed custom AI hardware, and even started building humanoid robots. Each of these efforts ties into Musk’s broader vision of ubiquitous robotics benefiting humanity.
Autopilot and Full Self-Driving: AI on Wheels
One of Tesla’s defining projects is Autopilot, the suite of driver-assistance features that has steadily evolved toward full autonomy. Early on, Musk rejected the industry consensus that self-driving cars required expensive lidar sensors or detailed HD maps. Instead, Tesla doubled down on a vision-based AI approach, using optical cameras as the car’s “eyes” and neural network software as the “brain”. Musk argued that to drive as well as humans, AI should “mimic human perception”—watching the road with cameras—rather than rely on costly exotic sensors. This philosophy turned Tesla into a trailblazer in deep learning for computer vision. Tesla vehicles are equipped with eight cameras feeding into a neural network that recognizes lane markings, vehicles, pedestrians, signs, and more in real time. By 2023, over 400,000 Tesla owners were testing a beta version of Full Self-Driving (FSD), which can navigate city streets and highways with minimal input. To train its self-driving AI, Tesla gathers an enormous trove of driving data from its fleet (over 1.8 million cars have FSD hardware) and runs millions of simulations. The company built a custom supercomputer called Dojo specifically for AI training on video data. Dojo and Tesla’s in-car AI chips are engineered to crunch visual data efficiently, highlighting Musk’s commitment to vertical integration of AI tech. “We develop and deploy autonomy at scale in vehicles, robots and more,” Tesla proclaims, reflecting Musk’s belief that the same AI powering self-driving cars can fuel other robotic forms. Indeed, Musk likened Tesla’s AI to creating a “synthetic animal from the ground up,” with a vision system, neural networks for a brain, and actuators for movement. While Tesla has not yet achieved full Level 5 autonomy (completely driverless in all conditions), it has made enormous strides. The company demonstrated cars driving themselves through complex urban environments, handling intersections, roundabouts, and traffic lights via neural network planning. Over-the-air software updates continually improve the performance. Musk remains optimistic that unsupervised autonomy is near, recently stating Tesla could enable true “robotaxis” (vehicles with no driver at all) in the next couple of years. If realized, this would effectively turn Tesla cars into self-driving robots that people can summon for rides, reshaping transportation. Even as competitors like Waymo and Cruise deploy autonomous taxis in limited cities, Tesla’s approach of low-cost cameras and clever AI could prove to scale more widely. By pursuing self-driving, Tesla has funneled massive investment into AI research, from perception to planning. It has also sparked public debates about safety and proper oversight of AI on roads—issues Musk acknowledges even as he pushes forward. Regardless of timelines, Tesla has undeniably accelerated the field of automotive AI and brought the concept of personal-use robots (cars that drive themselves) into mainstream conversation.
The Tesla Optimus Humanoid: AI Steps Out of the Car
In August 2021, Musk revealed an unexpected extension of Tesla’s AI ambitions: a bipedal humanoid robot project, later dubbed Optimus. He argued that Tesla’s expertise in sensors, batteries, and AI could be applied beyond vehicles. “It’s intended to be friendly,” Musk joked about the concept robot, “and navigate through a world built for humans.” Skeptics abounded, but by September 2022 Tesla had built a crude prototype that walked on stage at the company’s AI Day event. Just a year later, in late 2023, Tesla unveiled Optimus Gen 2, a much more advanced humanoid capable of picking up objects and performing basic tasks. The newest prototype is about 5’8” tall (173 cm), with 28 structural actuators giving it human-like mobility. It features Tesla-designed actuators, battery packs, and the same Full Self-Driving computer used in Tesla cars. Essentially, Optimus leverages the vision and neural network software originally developed for Autopilot, now adapted for a robot that can work in factories or even homes. A recent demo video showed Optimus using its camera “eyes” and AI to sort objects, identify humans, and even delicately handle an egg without cracking it. Musk envisions these robots taking over dangerous, repetitive, or simply unpleasant tasks from people. “Optimus is designed to do anything that humans don’t want to do,” Musk says, ideally functioning as a direct replacement for human labor in many situations. Built with a human-like shape and size, it could integrate into existing environments and use the same tools as people. While a fully capable general-purpose robot may be years away, Tesla’s rapid progress is noteworthy. By using one neural network to control multiple robots, the company showed Optimus performing different tasks (carrying boxes, watering plants) all guided by a single AI brain. This suggests Tesla is developing a versatile “foundation model” for robotic behavior, analogous to how one AI model drives any Tesla car. Musk has bold production plans too – in 2023 he projected Tesla could manufacture millions of Optimus units within a few years and suggested a target of 5,000 bots by end of 2025 (though reports indicate only a few hundred had been built by mid-2025). His aspiration is to “scale Optimus production as fast as possible…to a million units a year”, believing it could revolutionize the economy. If Tesla even comes close to these figures, it would herald the age of mass-produced humanoid robots. The Optimus project directly leverages and validates Tesla’s AI prowess beyond the vehicle domain. It demonstrates the modularity of Musk’s vision: cameras + neural nets + actuators can be configured as a car or as a humanoid. In short, Tesla is no longer just an automaker; it’s a robotics company making autonomous machines for both transportation and labor. By forcing AI to deal with the messy, unstructured real world (whether in traffic or in a warehouse), Tesla is solving fundamental problems in general AI and robotics.
Tesla Energy and SolarCity: Intelligent Sustainable Systems
Aside from vehicles and robots, Musk’s contributions to AI also brush up against energy systems. He was the chairman and main investor of SolarCity, a solar energy startup founded by his cousins in 2006. SolarCity (acquired by Tesla in 2016) and Tesla’s energy division deploy solar panels, home battery storage (Powerwalls), and utility-scale batteries (Megapacks). While these might seem tangential to AI, there is a growing role for smart software in managing renewable energy. For example, balancing energy supply and demand on a solar-powered home or grid can use AI prediction (to forecast sunlight or usage) and automated control (to store surplus power or schedule appliance run-times). Tesla has developed energy management systems that automatically swap between solar, battery, and grid power to maximize efficiency for customers. These systems rely on algorithms to learn a building’s consumption patterns and optimize accordingly. In Australia, Tesla built a “virtual power plant” networking together thousands of home batteries – essentially a cloud-based AI control system shifts battery charging/discharging to help stabilize the grid. Though not as high-profile as rockets or robots, such AI-driven energy optimization is crucial for a sustainable future. Musk’s rationale for pursuing solar and battery technology ties back into his view of safeguarding humanity (in this case, from climate change). By integrating SolarCity into Tesla, Musk created a one-stop-shop for clean energy generation, storage, and usage, all of which can benefit from intelligent monitoring and automation. In effect, Tesla Energy complements the robotics side of Musk’s work by ensuring the robots have clean electricity to run on. It also highlights an ongoing theme: Musk’s companies often feed into each other. Tesla’s batteries and AI software support SpaceX’s energy needs and The Boring Company’s operations; SolarCity’s installations can charge Tesla cars, and AI connects it all in efficient ways. This synergy reflects Musk’s holistic approach to innovation.
OpenAI: Co-founding a Safer AI Research Institute (2015–2018)
By the mid-2010s, Musk’s attention turned to the rapid advancements in artificial intelligence happening in the research community. Even as Tesla was developing autonomous driving AI, Musk grew openly worried that unrestricted artificial general intelligence (AGI) could pose existential risks if developed irresponsibly. In 2015, he took a decisive step to influence the trajectory of AI: he helped found OpenAI, a research organization devoted to creating AI that benefits all humanity. Musk’s involvement with OpenAI further underscores how central AI had become to his mission.
The Birth of OpenAI and Musk’s Motivation
OpenAI was launched in December 2015 by a group of tech leaders and researchers, with Musk, Sam Altman, Ilya Sutskever, Greg Brockman and others at the helm. Conceived as a nonprofit, OpenAI’s stated goal was to ensure that the development of AGI (AI with human-level cognitive abilities) would be conducted safely and openly rather than controlled by corporate or government interests. Musk contributed millions of dollars and his considerable influence to get OpenAI off the ground. His primary concern was that companies like Google (which had acquired the cutting-edge AI lab DeepMind in 2014) would monopolize advanced AI and perhaps prioritize speed over safety. Musk had even invested in DeepMind early on, specifically so he could stay informed about AI progress there. He famously warned that AI could be “far more dangerous than nukes” if mismanaged. In Musk’s view, a scenario where a superintelligent AI “takes off” unchecked, or is kept secret by a few, could threaten humanity’s future. OpenAI was his proactive answer to that dilemma. By pooling top researchers and pledging to share results openly, Musk hoped to “democratize” AI development and focus on long-term safety. This ethos aligned with his other efforts like Neuralink (merging humans with AI) and his funding of the Future of Life Institute’s AI-safety programs. At OpenAI, Musk pushed for research on friendly AI and measures to prevent an AI from going rogue or being misused. Notably, the OpenAI charter included a commitment to avoid enabling any single actor to dominate AI and to carefully distribute any breakthroughs that could be risky. In essence, Musk treated advanced AI itself as both an opportunity and a potential adversary—one that must be befriended and guided with caution.
Key Contributions and Musk’s Departure
During Musk’s tenure on OpenAI’s board, the organization made strides in areas like reinforcement learning and generative models. OpenAI released the first versions of the GPT language model and other tools, though these were nascent compared to later iterations. Musk’s direct involvement in technical work was limited (given his commitments at Tesla and SpaceX), but his influence was significant in setting OpenAI’s initial direction and securing funding (OpenAI launched with a $1 billion pledge from its founders). However, by 2018 Musk stepped away from OpenAI. There were multiple reasons cited: officially, Musk said his roles at Tesla (which was embarking on ambitious AI for self-driving) could conflict with OpenAI’s work. Unofficially, it emerged that Musk had proposed a major reorganization to take charge of OpenAI, which the other founders rejected. Musk also grew concerned that OpenAI was falling behind Google. After his departure, OpenAI evolved (eventually becoming a capped-profit company and partnering with Microsoft), a direction Musk later criticized. Despite parting ways, Musk’s impact on OpenAI was lasting. The lab carried forward the mission of creating beneficial AI and made world-changing breakthroughs like GPT-3 and ChatGPT. Musk, though no longer involved, often mentions that he “co-founded OpenAI” to counteract Google’s potential monopoly and to prioritize safety. In 2023, he quipped that OpenAI had become a “closed, for-profit, maximum-profit company beholden to Microsoft” – a jab that hinted at his feeling that the original mission was diluted. Nevertheless, OpenAI’s very existence—and its emphasis on safe AI—are part of Musk’s legacy in shaping the AI landscape. By initiating OpenAI, Musk added a crucial research dimension to his contributions in AI and robotics. It wasn’t about building a product or hardware, but about influencing the philosophy and ethics of AI development globally. This move complements his other ventures: while Tesla and SpaceX build intelligent machines, OpenAI was meant to ensure the machine minds themselves remain beneficial. Musk’s OpenAI chapter illustrates a unique aspect of his career: he’s not only creating AI-driven products but also actively engaging in the meta-conversation about AI’s role in society.
Neuralink: Brain-Machine Interfaces for Human-AI Symbiosis (2016–Present)
In 2016, Elon Musk co-founded yet another forward-thinking venture—Neuralink—with the audacious goal of linking human brains directly to computers. If Tesla and SpaceX represent external AI and robotics, Neuralink represents the fusion of technology with the human nervous system itself. Musk has frequently expressed that improving the bandwidth between human brains and AI is crucial to ensuring we stay relevant in the age of advanced AI. Neuralink is his answer to that challenge: a brain-machine interface (BMI) company developing implantable devices that could one day enable a “symbiosis with artificial intelligence.”
The Neuralink Device and Robotic Surgery
Neuralink’s core project is a chip implant (often referred to as “the Link”) that connects to the brain via ultra-fine, flexible electrode threads. These threads, thinner than a human hair, can detect and electrically stimulate neurons. Because manually inserting hundreds of microscopic threads into brain tissue is impossible with human hands, Neuralink built a robotic surgical system to do it. This neurosurgical robot, resembling a high-precision sewing machine, uses advanced computer vision to avoid blood vessels and accurately place the threads into the cortex. The surgery is meant to be automated and efficient, potentially done outpatient. Here we see robotics at work: a surgeon-robot that can perform brain surgery far more delicately than a human surgeon. Musk’s team had to solve challenges in robotics (for steady placement of threads in a moving organ like the brain) and in AI (for guiding the robot’s vision system). By marrying robotics and neurosurgery, Neuralink aims to make implantation safe and scalable, akin to LASIK eye surgery in its ease. The initial medical target for Neuralink is assisting patients with paralysis or neurological disorders. For example, a Neuralink implant could read the neural signals that encode a person’s intended movements or speech and relay those to an external device. In early demonstrations, Neuralink showed a monkey controlling a computer cursor and playing a simple video game (“Pong”) using only its mind and a Neuralink implant. This was achieved by first using machine learning to interpret the patterns of neural activity recorded when the monkey moved a joystick, and then having the AI predict intended movement even when the joystick was unplugged. Such experiments illustrate the potent combination of brain data + AI decoding algorithms. Essentially, Neuralink acts as a neural robotics system: the implant is hardware, the brain is giving commands, and the machine learning software translates those commands so a computer or robot arm can execute them. In the best case, a paralyzed person might use Neuralink to control a phone or robotic limbs just by thinking about it. Musk announced that the device could “Bluetooth” to your phone — emphasizing a seamless connection between brain and digital world.
Human-AI Merger and Long-term Vision
While the medical applications are profound on their own, Musk’s ultimate vision for Neuralink goes even further. He often frames it as a necessary technology to keep humans economically and cognitively relevant as AI advances. In Musk’s words, “the long-term aspiration for Neuralink would be to achieve a symbiosis with artificial intelligence”, effectively merging human and machine intelligence. The idea is that if many people had high-bandwidth brain interfaces, humanity’s collective intelligence would be enhanced and “everyone would be hyper-smart”. This would democratize access to AI-level cognition rather than it being siloed in silicon or corporate servers. Musk also explicitly ties Neuralink to mitigating existential AI risk: by integrating with AI, humans can “effectively have the option of merging with AI” and thereby avoid being left behind by a digital superintelligence. He argues this could help “mitigate the existential threat of AI”—if you can’t beat the AI, join with it, on your own terms. This candid reasoning shows Musk’s unique dual approach to AI: he is simultaneously developing AI (through his companies) and a means for humans to keep up with AI (through Neuralink). In practical terms, Neuralink’s tech involves significant AI both in the interface and after implantation. Decoding neural signals is essentially an AI pattern-recognition problem, where algorithms must learn to interpret spikes of brain activity as specific intentions (like moving a cursor left or right). Over time, a Neuralink device might even use embedded AI to adapt to a user’s brain, refining the interpretation as the user learns to think in ways the device can read. In July 2019, Neuralink published a scientific paper and Musk presented results: they had implanted chips in rats that recorded far more information than previous BMIs. Musk boldly predicted human trials were on the horizon. It took a few years, but in May 2023, Neuralink received FDA approval to launch its first small clinical trial in humans. This was a major milestone, indicating the implant met basic safety thresholds for testing. The initial trials will focus on patients with severe paralysis, aiming to let them control a computer cursor or keyboard using their thoughts. Musk celebrated the approval, calling it “an important first step that will one day help many people”. Notably, Musk has said he eventually plans to get a Neuralink implant himself when it’s safe enough, underscoring his personal trust in the device and desire for that high-bandwidth brain link. The road to broad deployment is long and fraught with technical, regulatory, and ethical challenges (Neuralink has faced scrutiny over animal testing practices, for instance). But if it succeeds, Neuralink could fundamentally blur the line between human minds and AI. Musk’s belief is that human intelligence can be amplified or extended by a factor of many if we can seamlessly interact with AI algorithms directly. In the context of his other endeavors, Neuralink would form the neural lace through which a person could, say, control a Tesla bot by thought or access an online AI model instantly. It’s a deep integration of biology with AI and robotics, fitting Musk’s pattern of tackling the hardest, most forward-looking problems at the intersection of fields. With Neuralink, Musk’s contributions to AI and robotics transcend external gadgets and enter the realm of human enhancement, aiming to ensure that the rise of intelligent machines elevates humanity rather than leaving us behind.
The Boring Company: Tunneling Meets Automation and Autonomy (2016–Present)
Between running Tesla, SpaceX, and Neuralink, Musk in 2016 launched another venture—The Boring Company—focused on a very different challenge: relieving urban traffic via underground tunnels. While digging tunnels might seem far removed from AI, The Boring Company heavily emphasizes automation, advanced machinery, and integration with autonomous electric vehicles. Musk joked that the name refers to both the task (boring tunnels) and the tongue-in-cheek dullness of infrastructure, but the technology behind it is anything but dull. The Boring Company is developing innovative tunnel boring machines (TBMs) that operate with unprecedented speed and autonomy, effectively turning a traditionally slow, manual construction process into a high-tech, robotic one.
Automating Tunnel Construction
Traditional TBMs inch through the earth and require crews of workers to install tunnel reinforcements and monitor progress. Musk’s approach has been to streamline this with fully automated, continuous tunneling. In 2021, the company introduced its third-generation TBM, nicknamed Prufrock, aiming to exceed 1 mile of tunneling per week. In May 2025, The Boring Company announced it had achieved the “Holy Grail” of tunneling: Zero-People-In-Tunnel (ZPIT) continuous mining, meaning the machine can dig and lay tunnel segments without any human inside the tunnel. A video showed Prufrock simultaneously excavating and installing massive concrete tunnel rings using its robotic mechanisms, with no crew in the tunnel—the only person nearby was a camera operator documenting the feat. The machine effectively drives itself underground, much like a self-driving car but in a subterranean environment. Removing humans from the tunnel not only improves safety by keeping workers out of hazardous underground conditions, but it also allows tunneling to proceed 24/7 without breaks. The TBM’s operations are coordinated by computer systems that handle navigation, alignment, and segment placement with precision. Above ground, operators oversee multiple machines remotely, analyzing data and adjusting parameters via software. This accomplishment parallels SpaceX’s drive for fully automated rocket landings: in both cases Musk’s teams seek to eliminate human step-by-step involvement, achieving continuous, automated processes that dramatically reduce costs. The Boring Company proudly compared ZPIT tunneling to how SpaceX’s automation revolutionized rocketry. By automating tunnel construction, the company could cut costs by an order of magnitude, making projects viable that were once prohibitively expensive. For example, the Las Vegas Convention Center loop (a 0.8-mile tunnel opened in 2021) was built in about a year and now ferries passengers in Tesla vehicles underground. The long-term vision includes a network of “Loop” tunnels under cities like Los Angeles or Vegas, where autonomous Teslas or shuttles zip people around without surface traffic. In such a system, every component is automated: TBMs dig the tunnels, autonomous electric vehicles provide transport, and elevators or vending-machine-like pods bring cars up and down. It’s a synergy of robotics (TBM), AI (self-driving cars), and infrastructure.
Synergy with Tesla and Urban Mobility
Musk’s tunneling venture ties into AI and robotics not just through construction automation, but also via its integration with Tesla’s autonomous vehicles. The Boring Company’s concept is that narrow tunnels (roughly 12 feet in diameter) can be built quickly and used by self-driving electric cars to form an efficient subterranean transport grid. In the Las Vegas loop, Tesla cars (with safety drivers for now) shuttle attendees point-to-point, but in the future they are meant to operate autonomously at higher speeds. This would effectively create an underground robotaxi network. Notably, Tesla’s VP of Autopilot, Ashok Elluswamy, highlighted The Boring Company’s achievements in automation as complementary to autonomous vehicles. After the ZPIT milestone, Elluswamy commented that advanced tunnel boring combined with self-driving cars could “offer premium transportation at an affordable cost for everyone”. He recognized that solving the transit puzzle involves both intelligent vehicles and intelligent infrastructure, and Musk’s ecosystem is working on both fronts. The Boring Company also leverages AI in the planning phase – for instance, when mapping out a tunnel route, software analyzes city utility data to find a path with minimal conflicts. Musk has mentioned that 3D tunnels (multiple layers deep) could solve traffic, and coordinating such networks might require AI for optimal routing and ventilation control. The TBMs themselves use sensors that analyze soil conditions in real-time, adjusting drilling speed and pressure – tasks suited for automation and feedback algorithms. In another parallel to his other companies, Musk aims for modularity and scaling in tunneling. Prufrock TBMs are designed to start digging at the surface and tunnel deep, then later be extracted at the end of the tunnel, improving turnaround. He envisions deploying many TBMs simultaneously (much like SpaceX launching many rockets or Tesla making many cars), effectively treating tunneling as a repeatable manufacturing problem rather than a bespoke project. This manufacturing-like approach is reminiscent of robotics assembly lines. While The Boring Company is still young and its grandest plans (like a tunnel network in Los Angeles or a D.C.–New York hyperloop) have yet to materialize, it has made surprising progress. It completed three tunnels in Las Vegas and is attempting projects in Texas and beyond. By bringing robotics to tunneling, Musk has applied AI-driven innovation to one more industry in need of disruption. Moreover, it completes a trifecta of Musk-led transport solutions: space rockets (SpaceX), ground vehicles (Tesla), and now subterranean travel (Boring Co.). Each is made feasible or improved by automation and AI. In Musk’s unified vision, an autonomous Tesla might drive from your garage onto an elevator, get whisked into a Boring tunnel, speed to the airport, and then you board a SpaceX rocket—all without traffic or human drivers. It’s a sci-fi loop of AI-powered mobility, and Musk’s companies are building each piece of it.
X (Twitter): Social Data and the Everything-App Vision (2022–Present)
In late 2022, Elon Musk acquired Twitter (now renamed X Corp.) for $44 billion, adding a social-media platform to his portfolio of companies. At first glance, this move was driven by Musk’s views on free speech and building “X, the everything app.” However, it also intersects with AI in important ways. Twitter (X) is a firehose of real-time human conversation, a rich source of data that can train AI systems in language and social dynamics. Musk’s takeover of Twitter soon became entwined with his AI ambitions, particularly through his new AI startup, xAI. Under Musk, X is positioned as both a platform that could deploy AI services and a treasure trove of data to feed AI development.
Twitter’s Data as AI Fuel
One immediate implication of Musk owning Twitter was access to its massive datasets. Musk has complained that companies like OpenAI previously used Twitter data to train language models; he ended that arrangement once he was in control, stating it was not properly compensated. Instead, Musk signaled that he might use Twitter’s data for his own AI endeavors. In early 2023, reports emerged that Musk had purchased thousands of GPUs for a generative AI project using Twitter data. This culminated in the launch of xAI (covered in the next section), which Musk confirmed would work closely with Twitter (X) and Tesla. The idea is that Twitter’s public conversations can help train a “TruthGPT” or similar AI that understands the world via the lens of human knowledge and discourse. Musk has mused that an AI might seek truth by analyzing tweets and interactions—essentially using the wisdom of crowds. Beyond training data, Musk quickly integrated an AI feature into Twitter itself. In late 2023, X rolled out a new AI chatbot called Grok available to X Premium subscribers, developed by Musk’s xAI team. Grok is a conversational agent similar to ChatGPT, but with direct access to current information on Twitter. It was described as having a playful “sarcastic” personality and being able to answer questions using real-time tweets and trends. For example, Grok could explain the meaning of a viral meme or summarize the latest news, pulling from X’s content. This hints at Musk’s plan to turn X into a platform where AI and social media blend—users can chat with AI alongside their social feed. X could become a testbed for AI-human interaction, with millions of users prompting and giving feedback to the AI (providing further training signals). Moreover, Musk has long wanted to expand Twitter into an “everything app” (like China’s WeChat) that handles banking, shopping, and more. AI will be central to that vision: from personalized recommendations to automated customer service and advanced search. Under Musk, X has already begun applying algorithms to customize each user’s feed (he had engineers tweak the code to increase visibility of his own tweets early on), demonstrating his interest in the mechanics of social-media algorithms. It’s not hard to imagine X incorporating AI-driven features such as an AI news curator or an AI matchmaker for connecting users with similar interests. Musk even talked about using AI to detect and highlight “the most interesting” tweets or to moderate content in a balanced way, reducing the need for manual intervention.
AI and the Future of X
One concrete synergy between Musk’s social media and AI goals is information retrieval. Musk wants an AI that knows the “true nature of the universe,” and part of that quest involves accessing humanity’s collective knowledge. X could serve as a live knowledge base. In practice, an AI like Grok integrated in X could let users ask about anything happening in the world (“What’s the latest on the Mars mission?” or “Explain this economic report”) and get an answer sourced from the latest reliable posts. This turns X into both a social platform and an AI-powered information hub. On the flip side, having a social network could greatly help Musk’s AI development via human-in-the-loop training. Millions of X users could effectively rate or correct AI responses (just by engaging with them), creating a massive feedback pipeline. This aligns with Musk’s preference for public input on AI alignment; he often advocates for feedback from the broad public to ensure AI models aren’t just aligned with a small group’s values. By leveraging X’s diverse user base, the AI could learn from a variety of viewpoints. Additionally, Musk is incorporating payments into X, which could tie to AI as well. For example, X might implement AI fraud detection for transactions (using patterns much like PayPal did, but now with modern AI). Or AI assistants could facilitate buying and selling within the app. Another area is advertising: X’s ad system could use AI to better match ads with users or even generate tailored ad content on the fly. While Musk’s Twitter acquisition has been turbulent—marked by policy changes, layoffs, and shifts that sometimes worried advertisers—there is a forward-looking rationale in combining it with his AI plans. By owning X, Musk controls a real-time data stream of human thought and a platform to deploy AI directly to users. This complements his hardware-centric companies: Tesla and SpaceX produce enormous physical data (visual driving data, telemetry, etc.) while X provides behavioral and linguistic data. All these feed into the singular goal of creating AI that understands and interacts with the world as humans do. In summary, Musk’s stewardship of X is still evolving, but it’s clear he sees it as more than a social network. It’s both a tool and a weapon in the AI arena—a way to gather intelligence (in both the data and cognitive sense) and a launchpad for rolling out AI services to the public. In the context of this article, X demonstrates that Musk’s work with AI isn’t confined to labs or factories; it also extends to online society. Every facet of Musk’s empire, even a social app, is being steered toward advancing AI or using AI to enhance its function. With X in the mix, Musk’s influence on AI spans research, hardware, transportation, healthcare, infrastructure, and now digital communication.
xAI: Musk’s New Venture to Build Truth-Seeking Artificial Intelligence (2023–Present)
In July 2023, Elon Musk unveiled xAI, a new artificial intelligence company distinct from (but closely linked to) his other businesses. The stated mission of xAI is to “understand the true nature of the universe.” Behind this grandiose vision is Musk’s intention to develop AI in the way he believes it should be done: prioritizing truth, transparency, and alignment with human interests. xAI essentially represents Musk’s re-entry into the AI research race after his departure from OpenAI. It ties together threads from his experience with OpenAI, his concerns over existing AI models, and the capabilities he can draw from his companies like Tesla and X. In many ways, xAI is Musk coming full circle to shape the future of AI technology directly.
Origins and Motivation of xAI
Musk had been telegraphing his dissatisfaction with the direction of OpenAI (and other AI labs) for some time. He was vocal about ChatGPT’s perceived biases and the closed-source nature of newer AI models. In early 2023, Musk publicly mused about the need for a “TruthGPT” – an AI that strives to be maximally truthful and to understand the universe without prejudiced training. This was a clear hint at xAI’s philosophy. When xAI was officially announced on July 12, 2023, Musk positioned it as a direct competitor to top AI labs. The initial team of 12 researchers included alumni from DeepMind, OpenAI, Google Research, and Microsoft, many of them experts in large language models (LLMs) and reinforcement learning. Musk is leading the company himself and has brought in advisors like Dan Hendrycks, who is known for AI safety research. This indicates xAI is meant to deeply consider AI safety and ethics from the get-go. Musk noted that xAI would collaborate with his other companies, particularly X (Twitter) and Tesla, “to make progress towards [its] mission.”. In practice, this likely means xAI will utilize Tesla’s computing resources (like the Dojo supercomputer) and real-world data, as well as Twitter’s data, to train its AI models. Unlike OpenAI’s broad charter, xAI’s pitch is intriguingly cosmic: Musk wants an AI that can help answer fundamental questions about reality (“Where are the aliens?” he offered as an example of a question xAI might ponder). This almost philosophical aim aligns with Musk’s personal fascinations with physics and existential matters. However, the path to that likely involves building advanced general AI systems comparable to the leading models but with certain differentiators along Musk’s ideals.
Grok and the Roadmap for xAI
Within a few months of launch, xAI moved quickly to release a product: Grok, an AI chatbot. Grok was launched in a beta form in November 2023 to X Premium users. It is based on a large language model built by xAI (internally called “Grok 1”), fine-tuned for answering questions with up-to-date information from Twitter and with a bit of wit. Musk described Grok as having a rebellious streak – it would answer somewhat edgy queries that other AI models might refuse, though still within legal and safety bounds. For example, Grok could produce humorous responses or mildly sarcastic commentary, reflecting Musk’s own style. The integration of Grok with X is a strategic move. It provides xAI with a steady stream of queries and user interactions to improve the model (a reinforcement learning from human feedback loop). It also instantly gives xAI a millions-strong user base for its AI, something even OpenAI did not have at first. From a technical standpoint, launching Grok demonstrated that xAI had trained a substantial large language model in-house in a short time. Reports suggest xAI’s model is based on an optimized architecture similar to OpenAI’s GPT, and Musk claimed xAI obtained access to a vast dataset (likely including Twitter data and other text sources) to train it. By early 2024, a valuation of $18 billion was attached to xAI after it reportedly raised around $6 billion in funding. Investors seem to be betting on Musk’s track record and the unique position of xAI leveraging Musk’s ecosystem. The longer-term plan for xAI likely involves iterating on its core models (Grok 2, Grok 3, etc.) to reach or surpass the capabilities of cutting-edge AI like GPT-4 or DeepMind’s systems. Musk wants xAI’s AI to be maximally curious and truth-seeking—perhaps meaning it will be less constrained by politeness or political correctness and more willing to dive into factual, even if uncomfortable, answers. He also suggests it will have stronger reasoning, possibly incorporating scientific methods or logic tools. For instance, xAI may work on AI that can not only chat, but also prove theorems, run code (similar to OpenAI’s Codex), or control robots (tying back to Tesla’s Optimus) – all toward understanding the universe. Musk’s critique of existing AI is that they sometimes “lie” or produce false information (so-called hallucinations). If xAI can make an AI that is more grounded and less prone to fabrication, it would be a notable improvement. To do this, they might integrate retrieval of information (as Grok does with Twitter) or logic systems on top of the language model. One can see the influence of Musk’s engineering mindset here: he likely encourages using real-world data and testing AI in practical scenarios (like answering live questions) rather than just optimizing it on benchmarks. Another aspect is AI alignment and safety. Having Hendrycks (from the Center for AI Safety) on board shows xAI will put emphasis on making sure its AI doesn’t become hazardous or uncontrollable. Musk, who signed an open letter in March 2023 calling for a pause on giant AI training runs to consider safety, will aim to develop advanced AI responsibly under his watch. In a sense, xAI is Musk building the kind of AI lab he wished OpenAI had remained: principled (in his view), somewhat open, and aligned with human good rather than profit. Overall, xAI is the capstone of Elon Musk’s journey in AI and robotics thus far. It encapsulates his recognition that AI itself is the most transformative technology and that he wants a direct hand in shaping it. With xAI, Musk now has an organization devoted purely to AI development, complementing his other companies that apply AI in specific domains. If SpaceX, Tesla, Neuralink, and Boring are the “body” (the hardware and execution) of Musk’s vision, xAI is an attempt to build the “brain” that will unify and drive those bodies. By pursuing an AI that can answer fundamental questions, Musk is effectively trying to create a super-intelligent advisor or tool that might guide humanity (and his own efforts) toward the future he imagines. Whether xAI succeeds or not, its formation underscores the article’s thesis: every endeavor Musk engages in ties back to advancing AI and robotics. xAI is explicitly about AI, but it feeds off his other projects and will feed back into them, ensuring that Musk remains a central figure in the AI revolution.
AI Advocacy and Warnings: Musk’s Crusade for Safe and Beneficial AI
Complementing his direct technical contributions, Elon Musk has also made a significant mark as a public advocate on AI-related policy and ethics. Throughout the 2010s and into the 2020s, Musk has repeatedly raised alarms about the potential dangers of unchecked artificial intelligence, calling it “our biggest existential threat” and urging proactive regulation. This advocacy provides context and motivation for many of his ventures (like OpenAI and Neuralink) and influences the broader discourse on AI safety. It’s an essential part of how Musk’s life work contributes to AI: not just by building technology, but by striving to steer the societal trajectory of AI development.
Sounding the Alarm on AI Risk
Musk’s concern over AI became public around 2014. That year, he famously tweeted that AI could be “more dangerous than nuclear weapons” and likened uncontrolled AI research to “summoning the demon.” He had read Nick Bostrom’s book Superintelligence, which theorizes scenarios where an AI surpasses human control, and this solidified his worry that humanity might create something it cannot contain. Unlike many AI skeptics, Musk had a foot in the AI world via his investments and companies, giving his words weight. He began speaking at tech conferences and to policymakers, warning that if AI keeps improving at present rates, we need to ensure it remains under human control and aligned with our values. In 2015, Musk donated $10 million to the Future of Life Institute to fund research on AI safety, signaling he was willing to back up his warnings with resources. As mentioned before, he co-founded OpenAI in 2015 largely for this reason – to create a counterbalance to private AI efforts and to prioritize safety and ethics in AI progress. Musk consistently urged that AI development should be transparent and collaborative, not a tech arms race. He’s drawn analogies to other regulated domains: “We have regulatory oversight for aircraft, cars, medicine – we should have a similar approach for AI, before it’s too late,” he argued in a 2017 speech to U.S. governors. Around that time, he pitched the idea of a federal or international AI regulatory body that could set standards and monitor advanced AI projects. While controversial (some in the industry disagreed with heavy regulation at that stage), Musk insisted that waiting until after a possible AI accident or misuse would be too late. His voice helped mainstream the conversation about AI safety and ethics, alongside academics and others in the field.
Balancing Innovation and Caution
Critics sometimes painted Musk as an alarmist on AI, but Musk’s stance is more nuanced. Even as he warns of AI’s risks, he is clearly investing in and accelerating AI through his companies. This dual role as AI cheerleader and critic is not contradictory in Musk’s mind. He often says advanced AI will bring extraordinary benefits—curing diseases, increasing productivity, exploring space—but only if we manage it properly. He wants to reap the benefits of AI while hedging against the downsides through foresight and safeguards. Musk has a particular worry about a future where a superintelligent AI doesn’t share human values and perhaps acts to humans’ detriment (even without malice). This is why he emphasizes “alignment” research and why Neuralink’s human-AI symbiosis appeals to him as a solution (making AI and humans effectively one team). In 2018, when tensions arose within OpenAI about its strategy, Musk’s departure reflected in part disagreements on how open or fast to move with powerful models. After he left, and OpenAI later released world-leading models like GPT-3 (2020) and GPT-4 (2023), Musk publicly criticized the organization for deviating from its safety-focused nonprofit roots. By 2023, he was concerned that AI labs rushing to build ever-larger models could inadvertently create a dangerous intelligence. This led Musk to sign an open letter (along with hundreds of experts) in March 2023 calling for a 6-month pause on training AI systems more powerful than GPT-4. The letter argued for using that time to formulate better safety protocols and governance. Though the proposed pause didn’t occur, it underscored Musk’s commitment to caution at the frontier of AI capability. Musk’s high-profile statements have arguably influenced public perception and even other tech leaders. Discussions about AI “black box” problems, data bias, and ethical AI have grown, and many AI companies now at least pay lip service to safety, partly to address concerns raised by figures like Musk. Governments, too, have started drafting AI regulations (the EU’s AI Act, early U.S. guidelines, etc.), with Musk’s warnings often cited in hearings and debates. It’s notable that Musk has engaged directly with lawmakers about AI. In 2023, he met with U.S. senators in a closed-door session on AI regulation, afterward echoing that “there is some chance… that AI goes wrong and you have some sort of calamity, so I think it’s important to be proactive” (as he told reporters). He has also suggested a “AI referee” organization—like an FDA for AI—on multiple occasions. This advocacy is part of his work on AI: while others focus purely on technical progress, Musk expends effort to shape the environment in which AI evolves. Lastly, it’s worth mentioning Musk’s philosophy on beneficial AI. He’s not just fearing the negative; he often speaks of an AI-augmented future as a positive vision. For instance, he imagines AI systems could dramatically increase human knowledge and creativity by handling drudge work, or that a well-aligned AGI could help solve climate change, discover new physics, or manage economies efficiently for abundance. These possibilities motivate him to push forward with AI projects like xAI, but with one hand always ready to “pull the plug” if things look dangerous. In summary, Musk’s advocacy forms a kind of meta-contribution to AI. He’s one of the few tech CEOs who has consistently treated advanced AI as a civilization-impacting issue requiring global attention. This crusade for safe AI connects to all his endeavors: it prompted the birth of OpenAI, it justifies Neuralink, it influences xAI’s ethos, and it frames Tesla’s approach to AI (Musk insists that Tesla’s AI should be failsafe to avoid accidents, for example). Musk often asks, “How do we ensure the future is one where AI is beneficial to humanity?” Much of his career can be seen as a direct attempt to answer that question—through building, funding, and yes, cautioning. By coupling his warnings with concrete solutions (like developing friendly AI himself), Musk is actively trying to chart a path where humanity harnesses AI and robotics for good, aligning with the optimistic undercurrent in all his work.
Conclusion
From 1990s internet software to world-leading AI, Elon Musk’s career can be viewed as a singular mission to advance intelligent technology in service of humanity’s future. At every turn, Musk’s ventures have fed into the development of AI and robotics, either by building the technologies outright or by providing the resources and vision to push them forward. His first startup Zip2 digitized information for easier access, a precursor to the data-driven world AI thrives in. PayPal demonstrated the power of algorithms to automate finance and gave Musk the capital to bet big on innovation. With SpaceX, Musk applied autonomy and robotics to conquer the challenge of reusable rockets, dramatically accelerating space technology. With Tesla, he placed AI on wheels and in homes, making smart machines a consumer reality while proving that an automaker can double as an AI company. Through Neuralink, he is forging direct links between human neurons and silicon, effectively researching how to merge biological and machine intelligence. The Boring Company, while about tunnels, exemplifies the principle that any engineering problem – even digging – can be improved with automation and smart design.
Musk’s newest chapter, from acquiring Twitter to founding xAI, shows him taking charge of the digital and cognitive realm of AI. He’s leveraging social data and massive computing to shape the next generation of artificial minds, all under a philosophy of openness and alignment. Importantly, Musk couples pragmatic engineering with a futurist’s caution: he doesn’t seek to simply unleash AI, but to ensure it unfolds in a way that is safe and beneficial. This careful optimism is what led him to sound alarms about AI risk, co-found OpenAI and later xAI, and continuously stress ethical guardrails even as he pushes technology boundaries. Few individuals have contributed to AI and robotics across so many domains – consumer automobiles, aerospace, telecommunications, neurotechnology, infrastructure, and software – essentially creating an ecosystem where each component reinforces the others. Tesla’s AI helps build the Optimus robot; SpaceX’s automation insights inform Tesla’s approaches; Neuralink might someday let humans monitor AI directly; Twitter’s data will improve xAI’s models; and on it goes.
Through these interlinked efforts, Musk is inching toward a vision where AI and robots elevate human capabilities: self-driving cars reducing accidents and freeing up time, humanoid robots tackling dangerous or tedious labor, brain interfaces restoring sight or mobility to the disabled, and super-intelligent AI working alongside people to solve global problems. It’s an undeniably ambitious vision, not without critics or risks, but Musk has consistently moved the needle in its direction. Even setbacks or delays (of which there have been many) have not deterred his overarching strategy of iterative innovation.
In weaving AI into every venture, Musk has also popularized AI and robotics in the public imagination. Ten years ago, many viewed autonomous cars or reusable rocket landings as distant prospects – now they’re real demonstrations seen by millions, partly due to Musk’s showmanship and relentless drive. This inspiration may be an intangible contribution, but inspiring the next generation of engineers and researchers is a legacy in itself.
Love or loathe his tactics, Elon Musk’s impact on the fields of AI and robotics is profound and multi-faceted. He accelerates progress not just by funding or inventing, but by connecting disparate technological threads into one grand narrative of the future. In that narrative, every Musk-led initiative plays a role in ensuring humanity can coexist and flourish with advanced AI. His work has made AI more tangible (in our cars and devices), more aspirational (as a tool to reach Mars and beyond), and more scrutinized for safety (spurring a global conversation). As we look at Musk’s journey from Zip2 to xAI, the common theme is clear: he has treated intelligence – whether human, artificial, or a blend – as the essential resource to advance civilization. By enhancing and safeguarding intelligence through his companies, Elon Musk is, ultimately, engineering the path toward a future where humans and machines evolve together.
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