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Musk’s OpenAI will train artificial intelligence through video game ‘Universe’
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.
We're releasing Universe, a platform for measuring and training AI agents: https://t.co/bx7OjMDaJK
— OpenAI (@OpenAI) December 5, 2016
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.
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.
Elon Musk has acknowledged that early discussions with Taiwan Semiconductor Manufacturing Company (TSMC) could bring the company into his ambitious Terafab semiconductor project, signaling a possible partnership with the world’s leading contract chipmaker.
Musk confirmed that early talks are underway, but as of right now, they are “just discussions.” There is no confirmation of a deal nor dismissal of the possibility of one, leaving open the prospect of one of the largest advanced-chip collaborations under discussion in the U.S.
@wholemars Just discussions, but something may come of it
— Elon Musk (@elonmusk) October 3, 2026
The report that speculated on potential discussions between Terafab and TSMC comes from Tim Culpan, who outlined a few ways the collaboration could operate. One is TSMC using the project as an “anchor customer” for future facilities in Texas, potentially contributing process expertise, operational know-how, or capacity while Terafab provides capital, long-term purchase commitments, or both.
Tesla and SpaceX jointly developed the Terafab project, with Intel already participating on the tech side. Elon Musk announced the project in March, and it intends to produce more than one terawatt of AI compute capacity annually once fully built.
Company statements place the first phase at approximately $16.8 billion in cost, with later filings pointing to a total that could reach well into the tens of billions across multiple stages.
Intel joined the effort in April 2026 and is expected to supply its 14A manufacturing process for the full-scale plant.
Musk has said existing suppliers, including Samsung and TSMC, remain important for near-term needs; Tesla already has production arrangements with Samsung for AI5 and AI6 chips, but that future demand from Optimus robots, Cybercab vehicles, and planned space-based data centers will eventually exceed what the global industry can currently deliver.
Terafab is positioned as the long-term answer to that projected shortfall, and Tesla did something similar during COVID to avoid a chip shortage. This is just a much larger-scale solution.
If the partnership were to materialize, it would add TSMC’s industry-leading strategies to a project that already combines Tesla’s and SpaceX’s capital and offtake with Intel’s process technology. For now, the only public confirmation is Musk’s brief acknowledgement that conversations are occurring.
Tesla’s early strategy for charging units operating within its Robotaxi fleet reveals that the company surely has not lost any of that scrappy DNA that took it from an unlikely success story to the most valuable carmaker in the world.
An observer at a Tesla Supercharger in Austin spotted ten total Robotaxi vehicles arrive: one Cybercab and nine Model Y units. A Tesla employee was waiting at the lot and allowed each unit to park itself; every car that arrived had nobody in it.
Tesla wins FCC approval for wireless Cybercab charging system
The Tesla employee would walk around and plug each car in, adjusting the parking if needed:
So look at what I found. This is how Tesla charges unsupervised robotaxis at a public supercharger. Here is a driverless Cybercab showing up with no one in it. There are 9 other Model Ys that showed up too. A Tesla employee is walking around and plugging each of them in. She also moves the cars if they are not positioned well enough to charge. I love this process. One person charges multiple robotaxis at once
— Abhimanyu Yadav (@WorldlyReviewer) October 3, 2026
It’s a very interesting strategy, but extremely understandable at this early point in the Robotaxi program. It’s only been out for about 15 months, and Cybercab just entered the fleet in early September.
On top of that, Tesla is still working tirelessly on its wireless charging apparatus, and a new patent was just published regarding that product last week.
However, this is just another example of how Tesla still has plenty of that scrappy DNA leftover from the “production hell” days, when CEO Elon Musk slept on the floor of the factory, employees were working crazy hours, Tesla was building Sprung Structures to build cars in, and the company was tiptoeing on the brink of bankruptcy.
@Teslarati Sheer magnitude of the entire production system is hard to appreciate. Almost every element of production is >75% automated. Only wire harnesses & general assembly, which are <10% of production costs, are primarily manual.
— Elon Musk (@elonmusk) October 12, 2020
For now, Tesla is utilizing a simple system for recharging its ride-hailing vehicles, and that is a Tesla employee doing it manually until another solution presents itself. Sure, it’s not the most high-tech thing, and it certainly is not what people might have expected at this point in time, but it works, and it’s keeping the entire suite running.
Tesla is expanding its Robotaxi service hours by pushing the time back by one hour, keeping the ride-hailing service operational until 11 p.m., one hour later than previously.
CEO Elon Musk confirmed the change and offered a specific reason the expansion has been gradual: the system still needs to reliably avoid small pets that are difficult to see after dark, as they commonly blend into the color of the road, especially when they’re grey.
The latest adjustment restores only a fraction of the operating window the service once held. When paid Robotaxi rides began in Austin on June 22, 2025, vehicles ran from 6 a.m. to midnight.
In September 2025, Tesla lengthened the day to a 2 a.m. close, producing a 20-hour window that stayed in place for most of the following year. By early August of this year, the cutoff had already been pulled back; an August 26 update formalized hours of 6 a.m. to 10 p.m. across Austin and several other markets.
The October move to 11 p.m. therefore leaves the Austin day one hour shorter than the original launch schedule and three hours shorter than the 2025 peak.
Musk addressed the constraint directly after the announcement. “The main thing we’re trying to solve is making sure that we don’t run over pets when they’re hard to see at night,” he wrote. “Literally trying to avoid grey kittens on grey tarmac in the dark.”
Robotaxi operating hours moved from 10pm to 11pm.
The main thing we’re trying to solve is making sure that we don’t run over pets when they’re hard to see at night. Literally trying to avoid grey kittens on grey tarmac in the dark.
— Elon Musk (@elonmusk) October 3, 2026
The example points to a low-contrast perception problem in which a small animal can blend into the road surface under limited lighting.
Tesla’s vehicles rely on cameras and neural-network processing rather than lidar; Musk has previously argued that advanced vision software can extract useful information even in low light by analyzing photon counts, but the pet-detection case remains the stated limiter in later hours.
The modest schedule change arrives alongside faster growth in the purpose-built Cybercab fleet. Texas registration data tracked by observers showed the Austin Cybercab count rising sharply in recent weeks, reaching 169 vehicles after more than 100 were added in a short span.
Tesla has indicated that a broader shift toward 24-hour operation is tied to the upcoming FSD v15 software release expected this month on Robotaxi vehicles. Until that capability is validated for the edge cases Musk described, the company continues to add service time incrementally rather than jumping straight to overnight coverage.
The one-hour extension gives Austin riders a later option for evening trips while the underlying detection work continues.
Elon Musk teases TSMC as potential Terafab partner
Tesla reveals early Robotaxi charging strategy, showing scrappy DNA
