Preface: Co-written with Gemini.

Demis Hassabis was born in North London to a Greek-Chinese-Singaporean family. He described them as “quite bohemian”, I’m guessing that’s the British equivalent of “hipster” here. According to Demis, his dad did a lot of different things, including working as a singer-songwriter with aspirations of being like Bob Dylan, working as a teacher and running a toy shop with his mom. His mom, on the other hand, is Chinese Singaporean and moved to Britain in the early 1970s. She originally trained as a nurse for children with special needs. She later worked as a manager at the department store chain John Lewis, ran the family toy shop, and also worked as a teacher. Hassabis has noted that his parents were not interested in computers and did not particularly like them, which he believes forced him to be self-reliant in his technical pursuits. He credits his mother’s roots for his early exposure to technology, as the family spent summers in Singapore, where he encountered "futuristic" gadgets and Nintendo games that were not yet available in the UK. While Demis became a scientist, his siblings followed their parents' more artistic path: his sister is a composer and pianist, and his brother is a professional poker player who studied creative writing.

At age 13, Hassabis was the second-highest-rated player in the world in the Under-14 category. He was only 35 Elo points behind the top-ranked player, Judit Polgár, who is widely considered the greatest female chess player of all time. He reached an Elo rating of 2300 by age 13, which is the "Master" standard. For perspective, the average casual chess player typically has a rating between 400 and 800. Hassabis often credits chess as the reason he became obsessed with Artificial Intelligence. He has said that playing at such a high level forced him to look "under the hood" of his own mind. He would ask himself questions like: "Why did I make that mistake?" or "How am I visualizing these moves five steps ahead?" He’s so good at thinking, that he became curious about why he’s so good at it: what is it that I’m doing when I think? How does that make me better? Why am I different? Geniuses always realize their difference from the rest from a young age, contrary to popular belief though, while it is confusing to watch how a genius does his work from the outside, it is equally confusing being the genius himself and not knowing where this genius-ness is coming from. He knew he was good at thinking, exceptionally good, yet he didn’t know why he had this gift. What is this gift that he clearly has that other people don’t? In this documentary that premiered at the 2024 Tribeca Film Festival called The Thinking Game, Demis Hassabis describes the moment he decided to give up on chess. During one of his final competitions, he started to wonder what he could possibly do with all the brains and computing power in this room he’s competing in, being surrounded by all the best players in the world. Could they have solved cancer? Instead of wasting their brain power on this game called chess? A deep sense of meaninglessness swallowed him, he started to feel sick. And right there, on the spot, he decided to give up on chess. 

Most eight-year-olds have to beg their parents for a computer. Hassabis didn't have to. He used the prize money he won from a major chess tournament to buy his first machine—a ZX Spectrum 48K. That was 1984, when he was just eight years old. 1984 was the height of the home computing revolution in the UK. The ZX Spectrum (developed by Clive Sinclair) was the affordable, rubber-keyed machine that essentially taught an entire generation of British engineers how to code. Because he bought it himself, he didn't have to follow anyone else's rules. He spent his time typing in code from magazines and books, which is how he transitioned from playing chess to thinking about how a machine could be programmed to "think" like him. A few years later, he upgraded to a Commodore Amiga, which was significantly more powerful. It was on the Amiga that he wrote his first "real" AI program—a version of the board game Othello (Reversi) that could beat him. It's fascinating to think that the same brain that was winning chess prizes in 1984 to buy a 48KB computer would, exactly 40 years later in 2024, be awarded the Nobel Prize in Chemistry for using AI to map the "building blocks of life." 

When Demis Hassabis stepped back from professional chess at 13, he didn't stop being competitive; he simply shifted his focus to programming, simulation games, and early AI experiments. He taught himself Assembly language, which allowed him to write code that ran directly on the computer's processor, making his programs much faster and more efficient. He was part of a small group of teenagers in the late 1980s who "hacked around," making their own games and software tools. He bought the Computer Chess Handbook by David Levy to learn about search algorithms and evaluation functions. He used these concepts to write an AI program to play Othello (also known as Reversi). He famously tested the program on his younger brother, George; the program was successful enough to beat him, which Hassabis cites as a major "aha!" moment regarding the potential of AI.

Writing that Othello program on a Commodore Amiga was Demis’s first real "Frankenstein moment"—the first time he built something that could outthink a human. Since he couldn't just download an AI library like developers do today, he had to build the "brain" from scratch using the fundamental logic he had learned from chess. To make the computer "think," Demis used a classic AI concept called Minimax. In simple terms, Minimax is a decision-making algorithm used in two-player games (like Chess, Tic-Tac-Toe, or Othello) to find the optimal move. The name comes from its core goal: Minimizing the maximum possible loss. It assumes your opponent is just as smart as you and will always make the best move for themselves. Imagine a tree where the "trunk" is the current board position, and every "branch" is a possible move. You want to choose the move that leads to the highest score (the "Max"). Your opponent wants to choose the move that results in the lowest score for you (the "Min"). The algorithm works backwards from the future. It looks ahead several turns to the end of the game (or a certain depth). It assigns a score to those future boards (e.g., +10 for a win, -10 for a loss). It then "bubbles" those scores back up to the present. If a future branch leads to a guaranteed loss because your opponent is smart enough to take it, the algorithm "discards" that path and picks a safer one. If you are about to win on the next turn, the Minimax algorithm sees a +10 score on that branch. However, if it sees that by moving there, you leave an opening for your opponent to win first, it sees a -10 on that branch. It will choose the move that minimizes the chance of that -10 happening. The problem with Minimax is the "State Space Explosion." In Tic-Tac-Toe, there are only 255,168 possible games. A computer can calculate every single one in a fraction of a second. In Chess, there are more possible moves than there are atoms in the observable universe. Because of this, young Demis couldn't just use "pure" Minimax. He had to use Heuristics (shortcuts). Since the computer couldn't see to the end of the game, he wrote a "Scoring Function" to tell the computer: "Even if the game isn't over, having control of the center of the board is worth +5 points." This is exactly what DeepMind eventually disrupted. In the old days, Demis had to hard-code those "points" himself. With AlphaGo, the AI taught itself what a good position looked like through deep learning. 

He programmed the computer to look at the current board and "branch out" every possible move he could make, then every possible move the opponent could make in response. Even on that limited hardware, he tried to make the computer look 4 or 5 moves ahead. In a game like Othello, where the board can flip entirely in one turn, this required massive computational efficiency. A computer can see the moves, but it doesn't know which board position is "good" or "bad" unless you tell it. Demis wrote a mathematical Evaluation Function—a set of rules that gave points for certain positions (like owning the corners of the board, which is vital in Othello). He essentially translated his own strategic intuition into a scoring system. Demis famously used his younger brother, George, as the test subject. He sat George down in front of the Amiga and had him play against the code. When the program started beating George, Demis realized he had created a "digital version" of his own strategic mind. It was a profound moment of realizing that intelligence wasn't just a "human" thing—it was a process that could be coded. ☀️