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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.
Tesla Full Self-Driving v14.3.3 driver monitoring was reportedly scaled back in recent releases, but a new version that was released in the early hours of June 3 aimed to do a better job of keeping those in control of their cars honest, according to release notes.
The release notes for FSD v14.3.3, via Software Version 2026.14.6.7 added:
“Improved driver monitoring system sensitivity with better eye gaze tracking, eye wear handling, and higher accuracy in variable lighting conditions.”
However, Tesla said this was already enabled in the first rollout of FSD v14.3.3 in late May. We tested it anyway, especially as the Standard Speed Profile seemed less-than-worried about what you were doing during operation.
I decided to try out the Hurry and Mad Max Speed Profiles for this test, and it gave me results that I would have expected. Tesla has evidently ramped up driver monitoring based on the Speed Profile you are using to travel.
The more aggressive the Speed Profile, the more on the hook you will be for taking your attention away from the road. Our testing showed that Mad Max was less likely to allow you to do normal things like change music or adjust navigation without getting an on-screen warning or nag from the driver monitoring system.
Hurry Mode Results
On Hurry, the driver monitoring system on FSD v14.3.3, via Software Version 2026.14.6.7, was more restrictive than Standard but less restrictive than Mad Max. I found that I could scroll through music options for a considerable amount of time, more than 30 seconds:
Roughly :31 between first touching the center screen and getting the first nag
— TESLARATI (@Teslarati) June 3, 2026
Standard gave me about 80 seconds of phone scrolling with absolutely no nags or warnings in a previous test. It is worth noting that this was a previous branch of v14.3.3, but Standard is such a goodie-two-shoes on the road that it is my impression it would not change much.
Here’s an 80-second phone nag test on Tesla FSD v14.3.3.
No alerts, no nagging, no annoyance. https://t.co/1dxvTOw5Cn pic.twitter.com/vYViFpjfoK
— TESLARATI (@Teslarati) May 29, 2026
Mad Max Results
I spent the majority of the drive on Mad Max to see how it truly reacted to the driver having their attention elsewhere. While I did do a short phone test, I am aiming to steer away from those and use the center screen. I think it is a valid criticism that the phone test is dangerous and, not to mention, illegal in Pennsylvania. Changing the navigation and music is a more reasonable, more responsible, and safer test.
With Mad Max being the fastest and most aggressive Speed Profile, I anticipated this being the quickest mode to give me an alert that I needed to look at the road. That was the case with music:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nags on Mad Max https://t.co/qZALU2OujY pic.twitter.com/XddOJ0D47x
— TESLARATI (@Teslarati) June 3, 2026
As well as adjusting Navigation, when I received two nags:
🎥 Testing Tesla FSD v14.3.3 (via 2026.14.6.7) nag while adjusting navigation
Two nags here https://t.co/qZALU2OujY pic.twitter.com/xa3dtaDG1L
— TESLARATI (@Teslarati) June 3, 2026
These nags were more than reasonable, and I think it’s probably good that Tesla is ramping up the driver monitoring. I do believe that it should be relatively strict across all of the Speed Profiles, especially with phone use. When using the center screen, the nag intervals should be based on the speed profile you are utilizing at the time.
These driver monitoring adjustments are a great thing to have while FSD is still under its “Supervised” moniker, but I expect Tesla to continue pushing the limits on what it will allow, especially considering CEO Elon Musk has hinted that phone use is capable with the more recent versions.
You can watch the full drive on YouTube below:
Tesla has responded to the skeptics of its Robotaxi program by launching a massive expansion of the unsupervised program in its initial rollout city of Austin.
The company’s geofence, the enabled area of operation for rides, now covers the entire Austin Metropolitan area, an incredible move just days after media headlines attempted to discredit the ride-hailing service.
Those who have access to the Tesla Robotaxi app on their smartphones can now request a ride in any portion of the Austin Metro area. The company confirmed this on the social media platform X:
Unsupervised Robotaxi now in the entire Austin Metro area https://t.co/eXNBdarvVS
— Tesla Robotaxi (@robotaxi) June 3, 2026
This is Tesla’s fifth expansion of the geofence, with the others occurring in July, early August, late August, and late October 2025. It has remained at that size since October 26, but Tesla has now more than doubled that size.
It is now covering the entire area, including suburbs like Pflugerville and Manor, as well as I-35 highways, Gigafactory Texas, and the Austin-Bergstrom Airport.
The move comes just days after various media outlets highlighted the small fleet size of Tesla’s Robotaxi fleet in Austin, something that is a reasonable criticism but an understandable move on the company’s part to prioritize safety.
Tesla has expanded its Robotaxi geofence many times, but its fleet has remained at a relatively conservative size as the company continues to push safety as its most crucial metric.
The latest expansion is a key indicator of Tesla’s comfort level to expand the ride-hailing service. The move shows Tesla is scaling unsupervised autonomy, as it demonstrates that the company’s Full Self-Driving system has reached sufficient reliability for a broader real-world deployment, which is something the company has worked on extensively.
It also shows Tesla is game for a competition with its rivals in the autonomous ride-hailing sector. Tesla has often matched or exceeded competitors like Waymo in coverage area, despite its smaller fleet. This step highlights Tesla’s iterative, data-driven progress toward a high-margin, app-based Robotaxi network.
It’s not the absolute largest area expansion ever, but achieving full unsupervised operations across a major metro is a key moment in the Robotaxi story. It shifts the program from limited pilot/testing toward a more mature commercial service, while gathering the miles needed for faster growth.
Tesla has improved Dashcam playback with an awesome new addition, as the company has launched a web-based version that is potentially easier to navigate and operate.
The tool is available at dashcam.tesla.com and will be enabled as your vehicle receives the 2026.20 Software Version. Clips that are captured by your Tesla will be available on the Online Dashcam Clip Viewer once the files on your car’s storage drive are encrypted.
Not a Tesla App first noticed the new feature, and states that once your Tesla updates to 2026.20, the car will automatically protect the clips with an encryption key that is uniquely tied to your owner account.
Tesla Launches New Web-Based Dashcam Viewer https://t.co/AlJKXYxujJ pic.twitter.com/4igicYpvkX
— Not a Tesla App (@NotATeslaApp) June 2, 2026
The web-based viewer should be easier to operate for most. All you will do is head over to dashcam.tesla.com and log in using your account credentials.
Ensure your vehicle is updated to 2026.20 in order for the web-based viewer tool to fetch your vehicle’s saved dashcam clips.
Currently, only a small percentage of owners are updated to this, so it may be a couple of weeks until a majority of owners in the fleet are able to access this feature.
Watching Dashcam clips on the Tesla smartphone app is quick and convenient, as they can also be easily downloaded and stored right on your smartphone.
However, the clips are sometimes tougher to navigate, and in order to get details like self-driving activation, speed, and turn signals, owners have to screen record the Tesla app and crop out the rest of the screen.
It could also be a massive storage saver as you’ll be able to download the Dashcam clips from the online viewer and save them to your laptop, desktop, a flash drive, or even an external hard drive. This will keep all your clips in one place.
Tesla Full Self-Driving v14.3.3 driver monitoring: We tested it
Tesla responds to Robotaxi skeptics with a massive move in Austin
