News
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
Tesla teases greater Grok FSD integration and ‘Banish’ feature ‘in about 3 months’
Tesla is going to let you guide Full Self-Driving with Grok in 3 months, CEO Elon Musk confirmed on X.
The response from Musk, which revealed Tesla plans to allow drivers to effectively control the car and its navigation more explicitly using Grok, puts the feature for about September.
A Tesla owner said that Full Self-Driving is great, but owners should be able to “converse with Grok like we can with an Uber driver.” She then used examples like, “Grok, turn right here,” and “Drop us off right here, we’ll walk due to traffic,” and finally,” Drop at entrance first, then park far away.”
Coincidentally, the final piece of dialogue would also mean features like Banish are potentially on the way soon.
This functionality will be there in about 3 months or so
— Elon Musk (@elonmusk) June 18, 2026
Banish is also referred to as “Reverse Summon,” and would enable the car to self-park while dropping occupants off at their destination.
This would be a great way to improve the overall experience while supervising FSD. Navigation is already a major painpoint that many owners complain about. Manual overrides when a maneuver is requested or canceled (like using the turn signal stalk to override a navigation route), do not always work.
The feature could be especially useful in street parking scenarios in a city, where spots are sometimes tough to come by. Many of us who grab dinner in a more populated area will park a street or two over from wherever we’re going, because sometimes you know that’s the best you will get. If a driver using FSD could say, “Hey Grok, turn right here on Queen St. and park in that open spot on the right,” it could save a lot of confusion FSD might have on its own.
Musk teased that a similar feature was “coming” back in February:
Tesla Full Self-Driving set to get an awesome new feature, Elon Musk says
It is certainly surprising that Tesla is doing it at this point. The company’s more recent moves have been more evident of taking control and inputs away from humans and putting them in the AI’s hands more frequently. The biggest example of this was taking away Max Speed in AI4 cars, giving us Speed Profiles, and not having any input on the fastest speed the car will travel.
Of course, giving navigation preferences to Grok is availble already in Teslas, but not at the drop of a hat. Instead, you can suggest a certain route at the beginning of your drive.
Here’s an example of that from December:
🚨🏈 I am taking my parents and Fiancee to the @Ravens game next weekend and asked @Grok to help me route my @Tesla through a specific neighborhood to reach the correct Lot we will park in.
This is a great example of the new @grok nav integration with the Tesla Holiday Update: pic.twitter.com/rPp4I7q8Yv
— TESLARATI (@Teslarati) December 13, 2025
Finally, the original post that Musk responded to mentioned a parking preference after dropping off the occupants, which describes the Banish feature that Tesla has teased for years.
We’re not sure if Musk was responding more to the ability to guide the car with Grok, or whether he also was including Banish in the three-month prediction timeframe.
News
Tesla Cybercab has one important piece that AI4 cars might need for FSD
A close-up image of a Cybercab engineering vehicle in Peabody, Massachusetts, reveals a compact triangular side repeater camera housing equipped with an integrated washer mechanism.
This seemingly small hardware addition could prove to be one of the most critical components for achieving reliable, unsupervised Full Self-Driving (FSD) — not just for the dedicated Robotaxi but potentially for existing AI4-equipped vehicles as well.
The washer system’s importance cannot be overstated in Tesla’s vision-only autonomy approach. Cameras are the sole sensory input for the neural networks powering FSD, constantly interpreting the environment for safe navigation. In real-world conditions, however, lenses quickly accumulate rain, snow, mud, dust, or road spray.
Many of us Tesla owners, especially those who deal with any sort of winter weather at all, know the all-too-common alert that pops up when cameras are obstructed:
Even brief obstructions can drop perception confidence, trigger safety disengagements, or force the vehicle to pull over, although these are relatively rare. Instead, most of the time, the camera will need a wipe from the owner next time they stop the car.
But unlike human drivers who can manually clear their view, a Robotaxi operating 24/7 without a steering wheel or mirrors must maintain pristine vision autonomously. The Cybercab’s side repeater washer delivers targeted cleaning bursts precisely where needed for merging, lane changes, and blind-spot monitoring — functions that demand uninterrupted visibility from the external cameras:
And this is how the side camera and washer look like on a Cybercab. This is from an Engineering vehicle in Peabody MA. pic.twitter.com/Re8VknpmLM
— Tobias Goebel (Unsupervised) (@tpgoebel) June 17, 2026
This hardware directly tackles a known pain point in current FSD deployments. Owners frequently report camera-related alerts during inclement weather, which is understandable, but needs to be solved for a true autonomous experience.
For a production Robotaxi fleet aiming for high utilization and minimal downtime, robust washer systems represent a foundational reliability upgrade; essentially, they’re a must-have. Early sightings suggest the design may extend to rear cameras as well, creating a comprehensive cleaning architecture that keeps the entire vision suite operational in harsh environments.
Without it, even the most advanced neural nets struggle when their “eyes” are compromised.
What Does This Mean for AI4 Cars?
This Cybercab detail raises timely questions for AI4 cars already on the road. While Hardware 4 delivers superior compute and camera resolution compared to earlier versions, production models typically lack dedicated side and rear washers. Tesla has included them on Model Y robotaxis that it is using in the fleet:
Tesla Robotaxi has a highly-requested hardware feature not available on typical Model Ys
As Tesla refines unsupervised FSD for broader release, the gap in environmental resilience becomes evident. Software improvements can help mitigate issues, but they cannot fully replace physical cleaning in heavy rain or muddy conditions. Analysts and owners increasingly speculate that AI4 vehicles may eventually require similar washer retrofits — or a future AI4.5 variant — to match the Cybercab’s all-weather readiness and support the same level of autonomy.
As testing progresses, the Cybercab’s washer mechanism highlights Tesla’s pragmatic focus on real-world robustness. It may well become the hardware piece that determines how quickly and reliably FSD scales from prototypes to everyday vehicles.
Elon Musk
Elon Musk just upped his Tesla stake further fueling SpaceX merger conversation
Elon Musk just collected a $116 billion Tesla payday and the timing is eye-opening
Elon Musk quietly collected one of the largest single-transaction paydays in corporate history on Monday. A Form 4 filed with the SEC on June 17, 2026 disclosed that Musk exercised 303,960,630 Tesla stock options from his 2018 compensation package, with the transaction dated June 16. No shares were sold on the open market.
The numbers are straightforward but striking. Musk exercised the options at a split-adjusted strike price of $23.34, with Tesla closing at $404.66 that day, putting the spread at $381.32 per share and generating roughly $115.9 billion in paper gains in a single transaction. To cover the exercise cost, Tesla withheld 17,531,857 shares through a net share settlement, meaning Musk paid nothing out of pocket.
For perspective, in 2018, Elon Musk’s award was originally approved by Tesla shareholders on March 21, 2018, and structured entirely around performance milestones that many analysts at the time called unreachable. Every tranche eventually vested. The original grant covered 20,264,042 shares at $350.02, which after Tesla’s 5-for-1 split in 2020 and 3-for-1 split in 2022 adjusted to 303,960,630 shares at $23.34. A Delaware court rescinded the award in January 2024, ruling the board was conflicted. As Teslarati reported, Tesla shareholders voted to ratify the package anyway in June 2024 by a wide margin. The Delaware Supreme Court reversed the decision in December 2025, finding full cancellation too extreme, and Tesla’s board signed an Implementation Agreement on April 21, 2026 to formally deliver the shares.
The Tesla and SpaceX merger everyone is talking about is quietly building
The timing and structure of the Form 4 filing carries more weight than a routine stock option exercise typically would. Musk exercised his 2018 Tesla award on June 16, a week into SpaceX completing its IPO and trading publicly, and giving SpaceX a public market valuation and share currency for the first time in the company’s history. A stock-for-stock merger between two companies requires the acquiring entity to have tradeable shares it can offer to the target’s shareholders, and SpaceX now has exactly that. At the same time, Musk just increased his direct Tesla voting power to approximately 20%, giving him greater influence over any shareholder vote that a merger would require. The restricted shares he received cannot be sold until 2033, which removes any near-term incentive to cash out and instead positions this stake as long-term structural collateral in a deal. Additionally, Musk’s two companies are already deeply intertwined through shared semiconductor fabrication at their joint TERAFAB facility in Austin, cross-company supply chain transactions, and Tesla’s $2 billion investment in xAI prior to the SpaceX-xAI merger.
Wedbush analyst Dan Ives has publicly placed the odds of a Tesla and SpaceX combination at 80% to 90% by early 2027. The Implementation Agreement that made Monday’s exercise possible was signed on April 21, 2026, roughly two months before the SpaceX IPO closed. That sequencing, building Musk’s Tesla ownership to its highest point ever immediately before SpaceX gains the public currency needed to acquire it, is either an extraordinary coincidence or a carefully staged foundation for the largest corporate merger in history.