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OpenAI reveals self-play information after successful Dota 2 test

Source: OpenAI

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OpenAI is revealing more information about its bot system after its win streak in the game Dota 2 last Friday, and it’s another step forward in the world of artificial intelligence.

The graph below was released this morning by OpenAI, which depicts the rate at which the bot improved in playing Dota 2.

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(Source: OpenAI)

“Our Dota 2 result shows that self-play can catapult the performance of machine learning systems from far below human level to superhuman, given sufficient compute,” OpenAI wrote in a post. “In the span of a month, our system went from barely matching a high-ranked player to beating the top pros and has continued to improve since then. Supervised deep learning systems can only be as good as their training datasets, but in self-play systems, the available data improves automatically as the agent gets better.”

OpenAI’s Dota 2 project started in March of this year, starting the bot off with simple tasks.

For background, Dota 2 is a free multiplayer battlefield game on Steam, a gaming streaming site. The game prides itself on not imposing limits on its players.

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The bot went on an impressive winning streak starting on August 7, beating a notable Dota 2 player named Blitz. That same day, the bot beat two more high-ranking players. The following day, the bot beat Arteezy, another respected player in the game. All four of the players the bot defeated said that fellow player SumaiL could defeat the bot.

SumaiL did not fare as well as his comrades thought he would.

Finally, the bot took on Dota 2’s former world champion, Dendi. The bot beat Dendi 2-0.

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As for how the bot learned to play the came, OpenAI had the following explanation, “The bot learned the game from scratch by self-play, and does not use imitation learning or tree search. This is a step towards building AI systems which accomplish well-defined goals in messy, complicated situations involving real humans.”

Some of the skills that the bot picked up were the ability to predict where players will move, to improvise in response to new situations, and how to influence the other players.

In between battles, OpenAI workers combined some “coaching” with self-play, which helped the bot continuously improve.

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OpenAI is a non-profit AI research company, founded by Tesla CEO Elon Musk, that researches safe artificial intelligence.

The Musk company has previously trained bots to successfully compete a task after watching it on virtual reality just once, and developed bots that created their own language.

Musk’s involvement in AI should come as no surprise as he has reiterated time and time again how important, and potentially dangerous, AI can be.

“I have exposure to the most cutting edge AI and I think people should be really concerned about it,” Musk has previously said. “I keep sounding the alarm bell, but until people see robots going down the street killing people, they don’t know how to react because it seems so theorial.”

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Aside from OpenAI, Musk is also the CEO of Neuralink, a brain-computer interface company.

The developments of the bot in these varied complex scenarios is a fairly large step forward in discovering the power of artificial intelligence. With limited input form the OpenAI engineers, the bot went from a decent player to being essentially unstoppable. This holds a promising future for further AI developments, if they can be contained.

Interim East Coast Editor for Teslarati, contributor for NextMobility. Share tips at mdolzer@teslarati.com

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Tesla owners surpass 8 billion miles driven on FSD Supervised

Tesla shared the milestone as adoption of the system accelerates across several markets.

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Credit: Tesla

Tesla owners have now driven more than 8 billion miles using Full Self-Driving Supervised, as per a new update from the electric vehicle maker’s official X account. 

Tesla shared the milestone as adoption of the system accelerates across several markets.

“Tesla owners have now driven >8 billion miles on FSD Supervised,” the company wrote in its post on X. Tesla also included a graphic showing FSD Supervised’s miles driven before a collision, which far exceeds that of the United States average. 

The growth curve of FSD Supervised’s cumulative miles over the past five years has been notable. As noted in data shared by Tesla watcher Sawyer Merritt, annual FSD (Supervised) miles have increased from roughly 6 million in 2021 to 80 million in 2022, 670 million in 2023, 2.25 billion in 2024, and 4.25 billion in 2025. In just the first 50 days of 2026, Tesla owners logged another 1 billion miles.

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At the current pace, the fleet is trending towards hitting about 10 billion FSD Supervised miles this year. The increase has been driven by Tesla’s growing vehicle fleet, periodic free trials, and expanding Robotaxi operations, among others.

Tesla also recently updated the safety data for FSD Supervised on its website, covering North America across all road types over the latest 12-month period.

As per Tesla’s figures, vehicles operating with FSD Supervised engaged recorded one major collision every 5,300,676 miles. In comparison, Teslas driven manually with Active Safety systems recorded one major collision every 2,175,763 miles, while Teslas driven manually without Active Safety recorded one major collision every 855,132 miles. The U.S. average during the same period was one major collision every 660,164 miles.

During the measured period, Tesla reported 830 total major collisions with FSD (Supervised) engaged, compared to 16,131 collisions for Teslas driven manually with Active Safety and 250 collisions for Teslas driven manually without Active Safety. Total miles logged exceeded 4.39 billion miles for FSD (Supervised) during the same timeframe.

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The Boring Company’s Music City Loop gains unanimous approval

After eight months of negotiations, MNAA board members voted unanimously on Feb. 18 to move forward with the project.

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(Credit: The Boring Company)

The Metro Nashville Airport Authority (MNAA) has approved a 40-year agreement with Elon Musk’s The Boring Company to build the Music City Loop, a tunnel system linking Nashville International Airport to downtown. 

After eight months of negotiations, MNAA board members voted unanimously on Feb. 18 to move forward with the project. Under the terms, The Boring Company will pay the airport authority an annual $300,000 licensing fee for the use of roughly 933,000 square feet of airport property, with a 3% annual increase.

Over 40 years, that totals to approximately $34 million, with two optional five-year extensions that could extend the term to 50 years, as per a report from The Tennesean.

The Boring Company celebrated the Music City Loop’s approval in a post on its official X account. “The Metropolitan Nashville Airport Authority has unanimously (7-0) approved a Music City Loop connection/station. Thanks so much to @Fly_Nashville for the great partnership,” the tunneling startup wrote in its post. 

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Once operational, the Music City Loop is expected to generate a $5 fee per airport pickup and drop-off, similar to rideshare charges. Airport officials estimate more than $300 million in operational revenue over the agreement’s duration, though this projection is deemed conservative.

“This is a significant benefit to the airport authority because we’re receiving a new way for our passengers to arrive downtown at zero capital investment from us. We don’t have to fund the operations and maintenance of that. TBC, The Boring Co., will do that for us,” MNAA President and CEO Doug Kreulen said. 

The project has drawn both backing and criticism. Business leaders cited economic benefits and improved mobility between downtown and the airport. “Hospitality isn’t just an amenity. It’s an economic engine,” Strategic Hospitality’s Max Goldberg said.

Opponents, including state lawmakers, raised questions about environmental impacts, worker safety, and long-term risks. Sen. Heidi Campbell said, “Safety depends on rules applied evenly without exception… You’re not just evaluating a tunnel. You’re evaluating a risk, structural risk, legal risk, reputational risk and financial risk.”

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Tesla announces crazy new Full Self-Driving milestone

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

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Credit: Tesla

Tesla has announced a crazy new Full Self-Driving milestone, as it has officially confirmed drivers have surpassed over 8 billion miles traveled using the Full Self-Driving (Supervised) suite for semi-autonomous travel.

The FSD (Supervised) suite is one of the most robust on the market, and is among the safest from a data perspective available to the public.

On Wednesday, Tesla confirmed in a post on X that it has officially surpassed the 8 billion-mile mark, just a few months after reaching 7 billion cumulative miles, which was announced on December 27, 2025.

The number of miles traveled has contextual significance for two reasons: one being the milestone itself, and another being Tesla’s continuing progress toward 10 billion miles of training data to achieve what CEO Elon Musk says will be the threshold needed to achieve unsupervised self-driving.

The milestone itself is significant, especially considering Tesla has continued to gain valuable data from every mile traveled. However, the pace at which it is gathering these miles is getting faster.

Secondly, in January, Musk said the company would need “roughly 10 billion miles of training data” to achieve safe and unsupervised self-driving. “Reality has a super long tail of complexity,” Musk said.

Training data primarily means the fleet’s accumulated real-world miles that Tesla uses to train and improve its end-to-end AI models. This data captures the “long tail” — extremely rare, complex, or unpredictable situations that simulations alone cannot fully replicate at scale.

This is not the same as the total miles driven on Full Self-Driving, which is the 8 billion miles milestone that is being celebrated here.

The FSD-supervised miles contribute heavily to the training data, but the 10 billion figure is an estimate of the cumulative real-world exposure needed overall to push the system to human-level reliability.

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