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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.

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.

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

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.”

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.

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

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How SpaceX Is raising Raptor’s sea-level thrust while holding engine mass steady

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Credit: SpaceX

SpaceX’s Raptor engine family has steadily increased sea-level thrust while simultaneously reducing mass, turning iterative engineering gains into substantially higher performance for the Super Heavy booster. CEO Elon Musk shed more light on how powerful Raptor 4 will be, and it’s pretty crazy.

Raptor 1 delivered 185 metric tons of thrust at roughly 2,080 kilograms, while Raptor 2 raised that to 230 tons while cutting mass to about 1,630 kilograms. SpaceX data for Raptor 3 lists a target of 280 tons at 1,525 kilograms (with further reductions in associated vehicle hardware), while operational flight ratings have been cited near 250 tons.

This morning, Elon Musk stated that Raptor 4 is expected to reach 300 tons of sea-level thrust at roughly the same mass as Raptor 3. Across these versions, thrust has risen by more than 60 percent from the first engines while engine mass has fallen, producing a sharp improvement in thrust-to-weight ratio. This is a true testament to how great SpaceX engineering has been:

With 33 engines on SuperHeavy, the jump from earlier versions to a 300-ton Raptor 4 would produce roughly 9,900 metric tons of total liftoff thrust, nearly three times the Saturn V’s approximately 3,400 metric tons from its five F-1 engines.

This is not just a larger number on a data sheet, either, as sea-level thrust is the force available the moment the vehicle leaves the pad. This is when it is heaviest and still deep in Earth’s gravity well and dense atmosphere.

Higher levels of sea-level thrust directly improves the initial thrust-to-weight ratio of the full stack. A higher ratio produces faster acceleration off the pad, which shortens the time the rocket has to spend fighting gravity, and gravity losses during the first minute or two of the flight are a major drain on total available delta-v. Every second shaved off of that early climb preserves more propellant energy for reaching orbital velocity or for carrying extra payload.

Because Super Heavy’s engine count is constrained by vehicle diameter and packing density, increasing thrust per engine is the most straightforward way to raise total liftoff performance without redesigning the booster structure or design.

The same-mass target for Raptor 4 is equally important. Holding engine mass roughly constant while raising thrust improves the engine’s own thrust-to-weight ratio and reduces the structural and propellant mass fraction that must be carried solely to support the engines.

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Earlier Raptor iterations also simplified or eliminated extensive vehicle-side hardware such as heat shields. These gains compound: more force for less installed mass leaves additional capacity for propellant, payload, or operational margins such as engine-out capability.

For Starship’s architecture, the practical effects are large. Greater liftoff thrust supports heavier vehicles, larger propellant loads, and higher payloads to low Earth orbit, figures SpaceX has targeted in the 100-plus-ton reusable range. That capacity underpins orbital refueling, lunar missions, and eventual Mars cargo and crew flights.

Continued growth in sea-level thrust therefore tightens the gap between theoretical rocket performance and the high flight rates and reusability needed to make large-scale space transport practical.

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Tesla Assisted Driving expands to tenth EU country

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Tesla has expanded its Tesla Assisted Driving (TAD) suite to its tenth European country, as Latvia joined a growing list of European Union member states authorizing the company’s advanced driver assistance technology.

Tesla Europe announced this morning that the system is now approved in Latvia, with a software rollout to begin soon.

The approval and rollout follow recognition of a provisional European type approval originally granted by the Netherlands’ RDW authority on April 10.

Latvia’s Road Traffic Safety Directorate (CSDD) evaluated the Dutch documentation, coordinated with the other national authorities, and reviewed updates from Tesla. These included tightened limits on speed offsets, automatic resets of any manual speed adjustments after each trip, and stronger driver monitoring.

In Europe, the feature is marketed as Tesla Assisted Driving after a recent rule change that labeled the name “Full Self-Driving” as misleading.

Tesla starts showing how FSD will change lives in Europe

The system remains an SAE Level 2 driver assistance tool, not unsupervised autonomy. It can control speed, steering, braking, lane changes, and intersections while following a navigation route. Drivers need not keep their hands on the wheel at all times, yet they must continuously monitor the road and be prepared to intervene immediately.

The sequence of EU recognitions began with the Netherlands in April and continued through Lithuania, Estonia, Denmark, Belgium, Slovenia, Czechia, Croatia, and Slovakia. Most have relied on mutual recognition of the single Dutch provisional approval rather than independent national testing.

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These national clearances do not yet constitute bloc-wide authorization. An EU-wide decision requires a qualified majority in the Technical Committee on Motor Vehicles: at least 15 of 27 member states representing 65 percent of the EU population. Larger markets, like Germany, France, and Italy, remain under review, and a vote is expected this December.

However, for Latvian Tesla owners with compatible vehicles and software, the imminent rollout expands access to the supervised system while underscoring that attentive human oversight remains essential.

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Tesla expands Robotaxi geofence in Houston with an ode to SpaceX merger

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Tesla expanded its Robotaxi geofence in Houston, Texas, today, enlarging the service area and drawing a new rocket-shaped boundary across the city’s northwestern and central parts.

Although CEO Elon Musk said it was just a coincidence, the expansion seems to be an ode to SpaceX and its potential merger with Tesla.

The official Tesla Robotaxi account announced the change with the lines “Houston, we have liftoff” and “Bigger service area now live,” pairing them with a map overlay.

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The prior white geofence, roughly 25 square miles covering Jersey Village, Harvest Bend, and the Willowbrook corridor along U.S. 290 and State Highway 249, now sits inside a larger blue zone that stretches southeast toward Bellair and closer to central Houston.

Houston’s Robotaxi service launched on April 18, 2026, the same day as Dallas, as Tesla’s first unsupervised public expansion beyond Austin. From the start, the vehicles were Model Ys running without anyone in the front seats, booked through the dedicated Tesla Robotaxi app and open to the public inside the geofence.

Trackers measured the initial zone at about 25 square miles; by late September it had not grown substantially. Community and registry data indicated a modest local fleet of unsupervised Model Ys, while dozens to nearly 200 Cybercabs, the purpose-built, steering-wheel-free two-seaters, have been spotted staging and testing in Houston lots, though public Cybercab rides remain limited to Austin for now.

Across the broader Robotaxi program, Tesla began public Robotaxi rides in Austin in June 2025, as a small geofence and vehicles with safety monitors became available for a ride-hailing service. Later on, Tesla removed the monitors and steadily expanded the service area until it covered most of the Austin metro area.

Unsupervised Robotaxi services now run in six cities: Austin, Dallas, Houston, Miami, Orlando, and Tampa. Cumulative driverless miles reported by the company have reached several million. The Cybercab entered public service in Austin in early September 2026 and has scaled rapidly there. The company has also said that Dallas is next for Cybercab rides in November, with further cities and 24/7 hours targeted by year-end, plus fleet-operator sales of the vehicle.

Waymo also operates a fully driverless service in Houston, which has been open to the public since August of this year.

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The Houston expansion continues Tesla’s pattern of starting with tightly controlled validation zones before widening coverage as real-world data accumulates, while the rocket motif on the map underscores the company’s habit of injecting visual flair into its autonomy rollout.

Riders inside the new boundary can request unsupervised Model Y trips in the Robotaxi app; exact operating hours and further Cybercab availability remain subject to app updates and company statements.

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