‘Every Single AI Researcher Making $10-100 Million is a Dota 2 Player’
Forget Ivy League degrees or internships at Google—the new secret to cracking the top AI jobs these days? Dota 2. If you are not playing, you are not going to make it. The notoriously challenging and endlessly complex Multiplayer Online Battle Arena (MOBA) isn’t just a video game anymore; it has become a full-blown talent filter for the most elite AI researchers in the world. “What’s crazy about all of these top AI researchers making $10-100 million is that literally every single one of them is a Dota 2 player,” wrote a user in a viral post on X. “If you played Dota 2, there is a good chance that you were in a lobby with either them or me.” It might sound like a joke, but it’s not. Today’s top AI researchers—the ones earning million-dollar salaries—have likely spent over 5,000 hours getting flamed by strangers in a dimly lit room. Just ask Greg Brockman, Ilya Sutskever, or Jakub Pachocki, who are key figures at OpenAI and the masterminds behind OpenAI Five, the bot that crushed human pros at Dota 2. In the 2018 tournament, Five failed to defeat professional human gamers. Despite having the training and experience of over 180 years, the AI was unable to achieve the feat. However, that’s another story altogether. Even Sam Altman, while not a player himself, backed the project that made Dota 2 the proving ground for reinforcement learning, even though it did not win. These guys didn’t just study Dota 2; they lived it. Even Elon Musk is a dedicated player, once claiming he ranked among the 50 top players of all time. How he manages that while running five companies at the same time remains a mystery, and a topic of speculation across X’s feed. Dota 2 is All You Need “There is a 100% correlation between the most cracked people I know and whether they played Dota 2 or not,” Upamanyu Acharya wrote on X. “And it’s unique to this game; doesn’t apply to anything else.” So why this game? Why not chess, Go, or League of Legends? Because Dota 2 is, as one user put it, “a multi-decade AI talent filter disguised as digital pain”. A single Dota 2 match spans 80,000 ticks—agents (or players) must plan and adapt hundreds of steps ahead. That’s a goldmine for researchers building long-horizon planning models for real-world applications, such as robotics or autonomous driving. Notably, OpenAI acquired the company Global Illumination, which was meant for making agents based on games using reinforcement learning. Dota 2’s ‘fog of war’ mimics real-world uncertainty, making it a playground for inference algorithms. With ~1,000 valid actions every quarter second, it forces researchers to build models that work in environments messier than any board game. Five heroes per team play cooperatively while outmanoeuvring the opposition. It’s the norm in distributed AI systems and swarm robotics. Dota also demands split-second decision-making every 80 milliseconds, training algorithms to react under pressure. Valve’s open Bot API means you can run thousands of games in parallel, generating hundreds of years’ worth of data per day for pennies. That’s how OpenAI Five was trained—spinning up massive reinforcement learning experiments in the cloud while playing one of the most punishing games ever created. More Than a Game, It’s a Culture “Holy shit. The highest-earning guy I know is a Dota 2 player as well. F***,” wrote Mario Hachemer, echoing a sentiment that’s no longer anecdotal but approaching statistical fact. Moreover, there’s the factor of cultural overlap. Engineers like systems. Dota 2 is a system that is mechanical, unforgiving, but also beautifully complex. Its steep learning curve, data-rich replays, and obsession with optimisation mirror the mindset of top researchers. “Every cracked person I know was either addicted to RuneScape or Dota 2. No exceptions,” another post stated. Even hiring managers are catching on. “I played Dota 2 way too much,” confessed one X user. “I also think if I ever hire again, I will test people by playing some matches in ranked together with them. Nothing shows better how you react in stressful situations.” If that sounds like a joke, it isn’t. Dota 2 teaches patience, precision, teamwork, adaptability, and how to manage rage, which are exactly the traits AI researchers need. Dota 2 wasn’t just OpenAI’s testbed. Before ChatGPT took over the world, OpenAI spent years just trying to get bots to survive on the Dota map. And in doing so, they built a team of researchers who weren’t just skilled, they were hardened by thousands of hours of digital warfare. That’s why Dota 2 keeps showing up in resumes, in X threads, and increasingly, in salaries with a lot of zeros. So if you’re wondering what separates a $200,000 AI engineer from a $10 million one? Check their Steam profile, not GitHub.
If you’re wondering what separates a $200,000 AI engineer from a $10 million one, check their Steam profile, not GitHub.
If you’re wondering what separates a $200,000 AI engineer from a $10 million one, check their Steam profile, not GitHub.
[]
["Go", "ChatGPT", "OpenAI", "AI", "ML", "Git", "RAG", "Aim", "GitHub", "R"]
["AI", "ML", "ChatGPT", "OpenAI", "Aim", "RAG", "R", "Go", "Git", "GitHub"]
Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.