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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.”

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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.

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Tesla Full Self-Driving insurance program with heavy discount expands

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Lemonade has expanded its innovative Autonomous Car insurance program to Tennessee, giving Tesla owners in the state a substantial discount on Full Self-Driving (FSD) miles. Announced on August 3, the product offers 50 percent off every mile driven with FSD activated, positioning the digital insurer as a leader in pricing insurance around autonomous technology.

The program, marketed as Lemonade Autonomous Car insurance, uses a direct connection via Tesla’s Fleet API (with customer permission) to automatically distinguish FSD-engaged miles from manual driving. Policyholders pay a low base rate when the vehicle is stationary and a few cents per mile when moving, with the 50 percent reduction applied specifically to FSD miles.

Coverage includes standard protections such as liability, collision, comprehensive, roadside assistance, and Tesla-specific benefits like access to certified repair shops and emergency crash services. Eligible vehicles require Hardware 4, as well as recent firmware.

Lemonade first unveiled the product on January 21 of this year, describing it as a first-of-its-kind offering designed for self-driving cars, starting with Tesla FSD. It began rolling out in Arizona on January 26, followed by Oregon about a month later. Subsequent expansions brought it to Indiana in early June 2026 and Colorado later that month.

Tennessee marks the fifth state.

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Tesla Full Self-Driving gets outrageous insurance offer with insanely cheap rates

The discount rests on Lemonade’s strong belief in the safety of Tesla’s FSD system. The company cites Tesla’s data showing that FSD-driven miles are twice as safe as those driven manually, or associated with roughly a 50 percent crash reduction.

Lemonade Co-founder and President Shai Wininger has emphasized this distinction: “Traditional insurers treat a Tesla like any other car, and AI like any other driver. But a car that sees 360 degrees, never gets drowsy, and reacts in milliseconds can’t be compared to a human.”

He added that “Teslas driven with FSD are involved in far fewer accidents” and committed that as FSD software improves and becomes safer, Lemonade’s prices will drop further.

Tesla Full Self-Driving gets an offer to be insured for ‘almost free’

This approach leverages Lemonade’s existing pay-per-mile technology and AI-driven risk models, which analyze nuanced vehicle data including software version and sensor performance. The company expects the model to reward higher FSD usage with greater savings while supporting mixed households that include both Tesla and non-Tesla vehicles under one policy. Bundling with home, renters, or pet insurance can yield additional discounts.

As autonomous driving technology advances, Lemonade’s state-by-state expansion of usage-based pricing that directly reflects real-world safety data represents a notable shift in how insurers evaluate risk.

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Tesla owners in the five available states – Arizona, Oregon, Indiana, Colorado, and now Tennessee – can obtain quotes quickly through the Lemonade app or website, potentially lowering the overall cost of ownership for vehicles equipped with advanced driver-assistance systems. Further states are expected as regulatory approvals progress.

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Tesla quietly made the Cybertruck even stronger

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Credit: Tesla

Tesla has continued to flex the strength, rigidity, and robustness of its all-electric pickup, the Cybertruck. In fact, since 2019, Cybertruck’s ability to avoid dents, dings, and even gunfire has been one of the main selling points Tesla has used to attract buyers who are looking for a vehicle that can handle the most intense challenges.

But that does not mean Tesla is not still actively trying to make it even better.

In a new hardware update, Tesla has decided to change the material of the Cybertruck’s underbody panels from aluminum to carbon fiber, a move that aims to not only increase pricing efficiency but also improve strength.

RELATED:

Tesla Cybertruck is officially the safest pickup, IIHS says

Cybertruck Lead Engineer Wes Morrill confirmed the change was made to the Cybertruck recently after it was spotted by Coleton Guerin of Out of Spec. This particular trim level was a Cyberbeast, but it is being applied to all trims to keep supply chain efficiency high and have less variance across trim levels.

Morrill said that Tesla tested different materials for the underbody panel protection, and carbon fiber performed better than aluminum, which is what the company was using since its first deliveries in 2023.

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Additionally, there are some efficiency improvements because Tesla can better form the areas around the bolts to keep underbody airflow cleaner than previously.

Carbon fiber is traditionally lighter and more durable than aluminum, which is why it is such a popular material among luxury automakers, and EV makers will utilize some of the materials around battery packs to save weight.

This is the first instance of Tesla utilizing carbon fiber on the Cybertruck’s exterior to help with overall performance and strength. As previously mentioned, Tesla used aluminum to protect the underside of the body, but it is pretty typical for the company to continue making engineering changes that will improve the car in the future.

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Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident

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Credit: Teslarati

Tesla released Full Self-Driving version 14.3.7 yesterday, and after about 90 miles of testing today, it is evident there are some definite fixes from version 14.3.6, which I wrote about last week and called a regression.

Within the first 40 minutes of my drive on v14.3.7, it saved me from getting into an accident with an unaware Dodge Charger driver, and some of the things Tesla seemed to miss in v14.3.6 were definitely improved. All in all, the release so far has some really great performance, and I’m looking forward to testing it further.

For now, here’s everything I noticed with v14.3.7:

Overall Improvement

Just generally speaking from a ride perspective, this was a really great experience. A lot of the hesitancy I experienced on v14.3.6 was gone. There were no instances of brake-stabbing, wheel-jerking, or any uncertain or unconfident movements. It was void of anything that I felt made it timid with v14.3.6.

The one thing I do hope to see down the road is a smaller need to adjust Speed Profiles so often. Because Tesla calls FSD “Supervised,” I’m okay with needing to hit the scroll wheel a few times a drive.

However, I hope that things can be incrementally improved upon with speed. Sometimes it’s too fast; other times it’s too slow. It’s a difficult thing to hone in and refine, but I hope it eventually gets there.

I didn’t notice any significant left lane camping or any behaviors that were completely out of line. I am hopeful that this opinion does not change, but after driving a few days with this version and putting it in a variety of different situations, you are exposed to more behaviors, some of which are not necessarily what I’d prefer.

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The big things to notice, at least in my experience thus far, are that the major issues with previous versions — meaning the braking stabbing and wheel jerking — simply weren’t there. That’s enough to already consider this progress compared to .6.

Manual Signal Override is More Responsive

On .6, I had quite a few issues with FSD ignoring my manually input turn signals. If Tesla wants to call it “Supervised,” then the car should not ignore any input the driver gives. If I touch the accelerator on FSD, the car speeds up.

The car did a great job of obeying my turn signals when I wanted it to change lanes, which is welcome.

Parking Lot Performance

Before .6, I traditionally took over in nearly every parking lot my car entered, because I knew it would not park somewhere that I wanted, and usually, it was just a tad too timid in this setting.

The one bright spot of .6 was how well it handled parking lots. This continued with v14.3.7:

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I’m always really happy to see progress at all, but once parking preferences come to FSD, as long as this performance is still around, that could potentially be the biggest improvement I’ve seen in FSD in the year I’ve been using it personally on a daily basis.

Full Self-Driving Averts Disaster

A Dodge Charger changed into my lane without checking if I was there, running me off the road. FSD made the initial avoidance maneuver; I grabbed the wheel out of instinct, looked in my side mirror to ensure I had nobody following closely behind, hit the brake, and straightened the car back up to avoid a curb:

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There have been quite a few responses to this video stating that I should never have grabbed the wheel. To be honest, I really wish I had not done so, because I do believe FSD would have avoided any sort of collision with anything, including the car or the curb.

However, this was the first time I had ever been this close to being hit while using FSD. My natural reaction was to take over. I think if I had had something like this happen before, my reaction might have been different.

Hitting the brake avoided hitting the curb, while FSD swerved to avoid the car. My concern after the car was clear of my front end was the curb. All in all, I’m really happy with how things turned out, and I think anyone could be a critic of how I handled it. I only had a split second to really make a decision, and thankfully, any damage was avoided.

It is clear FSD managed to avoid the car coming down before I was able to. I truly credit FSD for avoiding the collision.

What Needs to Improve

Better Recognition of Potholes, Uneven Roads, Sharp Changes in Roadway/Bumps

On Friday, my Fianceè and I were in the car, and FSD was driving us. We crossed over a roadway that has a traffic light, and FSD was traveling at 40 MPH on Standard, 5 MPH over the speed limit. Everything was more than reasonable.

However, the road we were crossing at the light has a major bump both as you start and finish crossing it. Without a speed reduction, your car can go airborne. The Tesla did just this on Friday on v14.3.6; it was an uncomfortable bounce that pretty much confirmed I would not ever let FSD go over again unless we were sitting at that intersection when there is a red light.

I even tried scrolling down into Sloth quickly, but I ended up just taking over:

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A few people have said it remains related to the vision-based approach and its difficulty comprehending 3D. This is a huge issue because this can cause serious damage at certain speeds.

Navigation

Nothing new here. I still turn off “Online Routing” quite frequently to get the car to take logical routes from time to time.

Auto Wipers

Auto Wipers are just plain bad. I really hope Tesla just uses a rain sensor. I thought they had improved at one point, but I still get dry wipes, Speed 4 on a drizzle, and Speed 2 on a steady rain. In reality, these should be switched.

You can watch our full review of Tesla Full Self-Driving v14.3.7 below:

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