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Musk’s OpenAI will train artificial intelligence through video game ‘Universe’

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Elon Musk’s OpenAI will introduce Universe, a virtual training ground aimed at teaching AI to play video games, use apps and even interact with websites. OpenAI, the artificial intelligence research company backed by the Tesla founder and billionaire entrepreneur, defines Universe in a blog post as “a software platform for measuring and training an AI’s general intelligence across the world’s supply of games, websites and other applications.”

Put simply, Universe will provide a gym that allows AI agents to go beyond their specialized knowledge of an individual environment to something approaching common sense. “Any task a human can complete with a computer.” Using a VNC (Virtual Network Computing) remote desktop, it allows the AI to control the game or app using a virtual keyboard and mouse, and to see its output by analyzing the pixels displayed on the screen. It’s essentially an interface to the company’s Gym toolkit for developing reinforcement algorithms, a type of machine learning system.

“Our goal is to develop a single AI agent that can flexibly apply its past experience on Universe environments to quickly master unfamiliar, difficult environments, which would be a major step towards general intelligence,” OpenAI says. As an example, it points to success of Google’s DeepMind AlphaGo initiative, which defeated the world champion human Go player earlier this year. While that success was impressive, when faced with a different challenge, the agent would have to go back to square one and learn the new environment through millions of trial and error steps.

OpenAI hopes to expand the Reward Learning (RL) lessons learned in one environment so that an AI agent can build upon past experience to succeed in unfamiliar environments.

OpenAI says in its blog post, “Systems with general problem solving ability — something akin to human common sense, allowing an agent to rapidly solve a new hard task — remain out of reach. One apparent challenge is that our agents don’t carry their experience along with them to new tasks. In a standard training regime, we initialize agents from scratch and let them twitch randomly through tens of millions of trials as they learn to repeat actions that happen to lead to rewarding outcomes. If we are to make progress towards generally intelligent agents, we must allow them to experience a wide repertoire of tasks so they can develop world knowledge and problem solving strategies that can be efficiently reused in a new task.”

Prior to Universe, the largest RL resource consisted of 55 Atari games — the Atari Learning Environment, says The Register. But Universe will begin with the largest library of games and resources ever assembled. “Out of the box, Universe comprises thousands of games (e.g. Flash games, slither.io, Starcraft), browser-based tasks (e.g. form filling), and applications (e.g. fold.it),” the OpenAI blog claims. Gaming companies that are cooperating with OpenAI include Flash, Microsoft – OpenAI announced a strategic partnership with the Redmond-based software giant – EA, Valve, Nvidia, Zachtronics, Wolfram, and others.

Universe is about more than gaming.  It’s main focus is on training AI agents to complete common online tasks with speed and accuracy. “Today, our agents are mostly learning to interact with common user interface elements like buttons, lists and sliders, but in the future they could complete complex tasks, such as looking up things they don’t know on the internet, managing your email or calendar, completing Khan Academy lessons, or working on Amazon Mechanical Turk and CrowdFlower tasks.”

The OpenAI blog post introducing Universe gives a long and detailed accounting of how Universe was created and what it hopes to accomplish. At the end, it provides a number of ways that companies and individuals can contribute to the process. It’s fascinating reading for anyone interested in what the future of computing is likely to be.

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There is also a darker side to artificial intelligence, which Elon Musk refers to as “summoning the Devil.” As The Register suggests, “While making software smarter may appeal to researchers, society as a whole appears to be increasingly unnerved by the prospect. Beyond the speculative fears about malevolent AI and more realistic concerns about the automation of military weaponry, companies and individuals already have trouble dealing with automated forms of interaction.”

One area of concern is that AI agents may one day be able to reactivate themselves after being shut down by human controllers. What was once the stuff of science fiction such as Minority Report and I, Robot could one day become all too real.

OpenAI Universe has been open-sourced on Github for those that may be interested in testing their own video game bot. We’ve included a video below showing OpenAI in action.

"I write about technology and the coming zero emissions revolution."

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Tesla Robotaxi gets a massive upgrade in Nevada

Nevada regulators just approved a massive expansion of Tesla’s robotaxi fleet across the entire county.

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Concept art of a Tesla Cybercab in Las Vegas Strip as rendered via Grok

Tesla’s robotaxi footprint in Nevada just grew by roughly 500 times in a single regulatory vote.

The Nevada Transportation Authority approved Tesla’s full Autonomous Vehicle Network Company permit on Thursday, clearing the way for the company to deploy up to 5,000 driverless vehicles across Clark County over the next 12 months. The decision came during a four hour general session meeting that Tesla investor Sawyer Merritt watched live and reported on X, noting the vote replaces the interim order that had limited Tesla to just 10 robotaxis on a narrow stretch of the Las Vegas Strip.

That earlier cap, covered here after it surfaced on August 13, came with restrictions that looked stricter than what Tesla runs in Austin: a 45 mph speed ceiling, no airport pickups, and a geofence confined to the Strip corridor. The new approval extends Tesla’s operating authority to all of Clark County, with room to request an even wider geofence across the state.

Tesla representatives at the meeting said they have no intention of putting 5,000 cars on the road right away. Commercial rides are expected to start within 30 days, pending vehicle inspections, insurance filings, and fare approval, the standard steps every robotaxi operator in Nevada has had to clear.

Tesla’s own Robotaxi account replied to the news with a short line, The golden future is upon us.

The timing lines up with Tesla’s broader robotaxi push this month. The company is preparing to open Cybercab rides to the public in Austin as soon as this month, and it opened a sweepstakes for riders to win a seat at the launch event. Tesla filed its original application for a 5,000 vehicle Nevada fleet back in June, a request regulators trimmed to 10 vehicles when they issued the interim order in July. Thursday’s vote effectively grants the number Tesla asked for from the start.

Zoox, the Amazon owned robotaxi operator, has run in Nevada since 2025 and was capped at 100 vehicles before Thursday’s decision. Tesla’s new ceiling puts it well ahead of that comparison on paper, though the company has said its actual fleet size will depend on how quickly FSD v15 rolls out, the software update executives have called the gateway to scaling unsupervised robotaxi operations nationwide.

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Tesla admits to slow Model Y Robotaxi integration, but for a good reason

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Credit: Tesla

Tesla welcomed JPMorgan analysts to one of its factories earlier this month, with the Wall Street firm highlighting its findings in a new note to investors. One of the more pertinent pieces of information is that Tesla admitted to slowly integrating Model Y vehicles into its Robotaxi fleet, but it has a good reason.

JPMorgan analysts recently toured Tesla’s Fremont Factory and met with the company’s investor relations team, emerging with a clearer picture of the automaker’s Robotaxi strategy. According to the bank’s note, Tesla is intentionally limiting the addition of Model Y vehicles to its existing Robotaxi fleet.

The firm’s analysts said:

“Tesla indicated it is intentionally holding back on adding Model Y units to the robotaxi fleet, expressing confidence in its ability to scale Cybercab in the near-term. On FSD V15, Tesla views this release as a step-change in performance, comparable to the leap from V13 to V14. The V15 upgrade encompasses seven core technologies, with ~40% of those currently being tested in the robotaxi fleet, where initial feedback has been encouraging.”

Far from signaling delays or doubts about autonomy, the move reflects strong management confidence in the near-term scalability of the purpose-built Cybercab.

Tesla has operated its Robotaxi service primarily with modified Model Ys since launching in Austin and expanding to other markets. Yet the company is now deliberately holding back further Model Y conversions. The rationale is straightforward: leadership believes the Cybercab, a two-seat, steering-wheel- and pedal-free vehicle optimized for high utilization, can ramp production and deployment more efficiently in the coming months.

This dedicated form factor promises better unit economics for the majority of rides, which typically involve one or two passengers, while freeing consumer Model Y inventory for retail sales.

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Supporting this pivot is Full Self-Driving (FSD) software version 15, which Tesla describes as a genuine step-change in performance, comparable to the leap from V13 to V14. The update incorporates seven core technologies; roughly 40 percent are already undergoing real-world testing in the current Robotaxi fleet, with early feedback described as encouraging.

Tesla is carefully managing software development to minimize regressions in core driving functions as new capabilities are added. Management positions V15 as the primary gateway to scaling unsupervised FSD. Importantly, the existing AI and Hardware 4 stack is already capable of running V15 and supporting unsupervised operation.

Cybercab itself is only the first vehicle on the platform. Tesla reiterated that additional form factors will follow, pointing to concepts such as the earlier “Robovan” demonstration as examples of how the architecture can evolve.

Tesla’s mysterious Robovan makes a sneak peek with Optimus in Terafab video

Parallel progress continues on the Optimus humanoid robot, which remains on track for start of production in the coming months, with commercial sales possible as early as the second half of 2027. Generation 3 details will be revealed closer to production to preserve competitive advantages, while Generation 4 scope will draw on real-world Gen 3 experience.

JPMorgan left the meeting with a deeper appreciation for Tesla’s manufacturing automation and maintained its $475 price target. The decision to slow Model Y Robotaxi integration is therefore not a setback but a calculated prioritization of a more efficient, purpose-built solution that management believes is ready to scale.

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Elon Musk gives a timeline for SpaceX’s first Starship catch attempt

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SpaceX Starship V3 from Starbase, Texas on April 14, 2026

SpaceX CEO Elon Musk announced today that the company will likely attempt to catch the Starship upper stage with its launch tower arms “in a few months.”

In a post on X, Musk wrote, “Looks like we will probably catch the ship with the tower in a few months. If there had been a tower out to sea where we practiced landing the ship, it would have been caught.” He added that the first reflight of a Starship vehicle is expected by the end of 2026 or early 2027, describing it as “a fork in the road of history for consciousness reaching the stars.”

Musk’s prediction comes amid ongoing progress toward full reusability of the Starship system, a two-stage rocket designed for rapid turnaround and dramatically lower launch costs. Catching the upper stage, known simply as “ship,” with the Mechazilla tower’s mechanical arms would mark a major milestone. It would allow both stages to return directly to the launch site for quick refurbishment and reuse, eliminating the need for ocean recovery.

Musk has previously signaled plans for a ship catch. In July, shortly after SpaceX’s wildly successful Starship 13 mission, he stated that the company would attempt to catch the ship with the tower on the next flight unless problems emerged in the mission data review. Earlier comments also outline conditions such as successful soft ocean landings before attempting a land recovery to minimize risk.

SpaceX has solved Starship’s biggest challenge, Elon Musk says

The latest update from Musk adjusts this timeline to a few months, reflecting the iterative nature of the test campaign.

SpaceX has already demonstrated the tower catch technique successfully with the Super Heavy booster on a couple of occasions. The first successful booster catch occurred during Flight 5 in October 2024, when the massive first stage returned to the Starbase pad in Texas and was plucked from the air by the tower arms.

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Additional catches followed on later flights, including Flight 7, proving the concept for the booster and building confidence in the system as a whole.

Achieving a similar catch for the upper stage would represent a significant step forward. The ship returns from much higher speeds and greater heat loads after orbital or near-orbital flight. Success would advance SpaceX’s goal of full and rapid reusability, potentially reducing the cost of access to orbit by a factor of 100 or more and supporting ambitions for frequent satellite deployments, lunar missions, and eventual Mars flights.

Musk has long emphasized that true reusability, refueling rather than discarding hardware, is essential for making humanity a multi-planetary species.

As SpaceX continues refining Starship through successive test flights, the coming months will test whether the ambitious catch timeline can be met. The combination of prior booster successes and improving ship landing precision suggests the company is steadily closing in on this historic capability.

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