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Elon Musk’s OpenAI to battle in Dota 2 World Championship video game tournament
OpenAI, a research lab co-founded by Elon Musk, has developed a new breed of AI agents that are capable of playing Dota 2, a complex strategy game, in 5-on-5 multiplayer matches. OpenAI’s new bots have so far been able to beat amateur and semi-professional teams. With this accomplished, the research lab is now looking to bring its bots to The International, a prolific Dota 2 tournament, this coming August.
The new bots go by the name of OpenAI Five, a reference to the number of neural networks working together in the team. To train the neural networks, the AI has been playing roughly 180 years worth of gameplay every day using reinforcement learning. This enables the AI to learn the intricacies of the game, considering that it is far more complicated than board games like Chess and Go. Dota 2, for example, involves hiding data from players, preventing the system from perceiving the entire playing field at a given time.
The hardware employed by the research lab to train OpenAI Five is impressive. The five neural networks train through a scaled-up version of Proximal Policy Optimization running on 256 GPUs and 128,000 CPU cores. The same setup was adopted in a much smaller scale last year when OpenAI rolled out an artificial intelligence system that proved capable of beating the best Dota 2 players in the world in 1-on-1 matches.
Currently, however, OpenAI Five can only play the game with several restrictions. For one, the AI system can only use five of the 115 heroes available in the game. Skills such as Invisibility, Summons, and the placement of wards are also disabled. The research lab, however, hopes that through time, the neural networks would be able to play the game without any restrictions at all.
As could be seen in a recent video shared by the research lab, OpenAI Five is actually being received well by the Dota 2 community. Professional Dota 2 player Blitz, for one, noted that the bots are adopting strategies that are incredibly effective. In a match against OpenAI Five, Blitz, together with four employees of the research lab, put up a fight before getting dominated by the articificial intelligence. In a statement after the game, Blitz sheepishly stated that the bots capitalized on every small error he made during the match.
“I think the team fight aspect of the bot(s) was excellent. It didn’t mess up. When it came to coordination, it was some of the best pure team fighting because it felt like I was getting hammered every single time I made a mistake. I feel like normal humans don’t do that,” the professional Dota 2 player said.
So what’s the secret behind OpenAI Five? In a statement to The Verge, OpenAI CTO Greg Brockman noted that unlike human players, the bots have “no ego” when they play the game. The teamwork aspect of the bots was also trained by allowing them to work individually at first, then encouraging them to work together.
“The bots are totally willing to sacrifice a lane or abandon a hero for the greater good. For fun, we had a human drop in to replace one of the bots. We hadn’t trained them to do anything special, but he said he just felt so well-supported. Anything he wanted, the bots got him,” Brockman said.
Ultimately, Brockman is encouraged by OpenAI Five’s development so far. The research, after all, is motivated by the idea that if AI systems can be trained to perform complex tasks such as learning a game as intricate as Dota 2, it could eventually be used to solve equally complex real-world challenges. Some examples of real-world applications could be designing and managing a city’s transport structure, or the logistics of a massive business.
“This an exciting milestone, and it’s really because it’s about transitioning to real-life applications. If you’ve got a simulation of a problem and you can run it large enough scale, there’s no barrier to what you can do with this,” he said.
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Tesla Robotaxi will be a 24/7 service: here’s when
Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.
The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.
Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.
Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.
By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.
Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.
Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.
If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.
That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.
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Tesla Full Self-Driving will now overtake manual driving to avoid disaster
Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.
Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.
The intervention is meant as a last-resort safety net, not a replacement for attentive driving.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.
After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.
The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.
Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.
The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.
If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.
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Tesla Cybercab launch catches NHTSA’s attention who wants to know more
Tesla launched the all-electric, steering wheel-less, and pedal-less Cybercab last night at a quiet and small event in downtown Austin, Texas.
The launch, which marked the beginning of unsupervised ride-hailing for Tesla’s Robotaxi platform with Cybercab, has already caught the attention of the National Highway Traffic Safety Administration (NHTSA) who has more questions.
NHTSA opened an Audit Query (AQ) into the Cybercab’s Federal Motor Vehicle Safety Standards (FMVSS) certification that Tesla gave the vehicle. Manufacturers self-certify vehicles much of the time to avoid excessive regulatory delays.

Tesla Cybercab interior, note the lack of steering wheel and pedals. (Credit: @niccruzpatane/X< /a>)
However, the agency needs more information; it said in a summary:
“On September 3, 2026, Tesla began commercial deployment with a small number of its Cybercab vehicles in Austin, Texas. Tesla notified the Agency that it certified those Cybercab vehicles as compliant with all applicable Federal Motor Vehicle Safety Standards (FMVSS). Tesla also notified the Agency that it plans to gradually expand commercial deployment of the Cybercab to include additional vehicles and locations.”
It also went on to state that the Cybercab lacks traditional automotive controls, which is a groundbreaking move. The process is entirely new to the NHTSA, which gives the agency some leverage to put Tesla’s launch under a microscope:
“The vehicles lack permanently attached, conventional manual controls, such as a brake pedal, gas pedal, steering wheel, and mirrors. NHTSA is opening this AQ to examine the process and technical data on which Tesla relied when certifying the Cybercab and related issues. Among other things, NHTSA will consider the extent to which Tesla’s certification depended on determinations that certain FMVSS are inapplicable to the Cybercab.”
Tesla has added 45 Cybercab units to its fleet of Robotaxi-enabled cars in Austin, according to public documents the company submitted to the State of Texas over the past week. Enabling this level of self-driving is something Tesla has worked toward for many years, and now that it is finally here, it seems more than reasonable that regulatory agencies will have some questions.
Many outlets might try to frame this as a negative, but it is truly an agency looking to gain more information about groundbreaking tech that Tesla has been developing for years.
In an effort to keep riders, pedestrians, and property safe, any and all data accumulated from these first days, weeks, and months of rides will likely be shared with the NHTSA to enable broader rollout strategies across the United States and more in the future.