Information became a resource when minds began storing it externally. Exchange organized it, while a curiosity for automating sequences and patterns led to unique playgrounds. In the ancient world, a player with access to chemicals used a catalyst. One acquainted with theatre actors used an inciting incident. One familiar with music could use a hydraulis, a programmable console for triggering an array of instruments. The simplest interface emerged in 6th-century India, one that would become epochal. It allowed anyone to play; an emperor, a hobbyist, or a kid in the Bronx could orchestrate and incite sequences in the silence of their bedroom…the players who elevated the resource of information until it defined an age.

The Information Age

In the 1700s, the excitement for new hardware given the power of man was revolutionizing industries. Machines given the coordination of our arms or the precision of our hands—like the Spinning Jenny —were small steps towards a new age. The leap towards a machine with the power of our mind was still far from practical. In 1770, an Austrian clerk named Wolfgang von Kempelen, undeterred by practicality, decided to create one. Much like the ancient chemists bettering metallurgists in creating gold, this prescient leap lacked integrity, but made up for it in influence. Kempelen's automaton would grant him a new status in the royal court, but retrospectively, like the ancient “chemists”, it's fair to refer to them as what we can now see their actual achievement was: an excellent illusion. This late 18th-century illusionist created a life-size mechanical humanoid dressed in Turkish garments. The mechanical Turk was built atop the game from 6th century India, designed for any kind of player, known as chess.

Artificial Artificial Intelligence

The chess-playing automaton—known as the Mechanical Turk—was beating esteemed figures no less notable than the currencies their portraits have since adorned. Optimists were enthralled, while skeptics were pushed to great lengths to subvert the greatest machine the world had seen. A young reporter ended up establishing a new literary genre altogether after(un)covering the story. The eminence grise behind(within) the automaton, which remained secret for long after Kempelen's time, was a man hiding within a compartment of the chess table. If not for a curious biographer half a century later, this man would have remained hidden in an unchecked compartment of history as well. During exhibitions, sections of the Turk were opened intermittently to reveal its faux autonomous clockwork. The hidden player used a variety of crawl spaces, levers, and magnets to operate the enchanting animatronics, all while being able to give the best chess player of the time (Philidor) “his most fatiguing game of chess ever”. There were practically no known records of this hidden player until the biographer found that he was Johann Baptist Allgaier of Vienna. An unassuming player held in high regard by the local chess cafes. The biographer found that Johann had been burdened with breathing problems after fighting in the Napoleonic wars, and in need of money later in life, was approached by an exhibitor hiring the brain for his chess machine. A lowly player, undocumented and forgotten to history, playing chess against one of the most polarizing, universally known megalomaniacs during the peak of his power. Just a few years before, these players faced each other in the Napoleonic War. This would be their second encounter, where one indirectly battles the other, conducting a methodically arranged fleet from out of sight.

Details vary (Napoleon requested it to be off record), but consistent accounts from a range of bystanders assemble the evening: Napoleon initially tries to cheat, as a keen assessment or perhaps just amusement, or both. After the Turk swiftly rejects the invalid moves, Napoleon persists in making the first move of the game. Of all the possible openings, he chooses one befitting of a boy born on an annexed island, with a desire to acquire power in meteoric fashion. The Scholar's Mate Opening is either the quickest way to leverage power against an opponent or the most impatient. It immediately threatens checkmate within the first few moves of a game—obvious, yet effective against negligent opponents. The combative mastermind's impulsive attacks and reliance on tactics would inevitably lose to strategy. The Turk(Johann Allegier) had a chance to checkmate Napoleon towards the end of the game, but instead took Napoleon's most powerful pieces, drawing out a swaggering finish as flamboyantly dominant as the emperor himself. Whether the strategist—the one crammed inside the table—overlooked the possible earlier checkmate or elongated the game purposefully, cannot be known for sure.

Wolfgang von Kempelen wasn't in attendance that evening, in fact, he died a few years before. He had resentfully disassembled his deceptive automaton, shelving it long before, as its unexpected celebrity status eclipsed his genuine automata. A “rude and churlish showman” (according to Beethoven) waited until Kempelen's death to resurrect the Turk, and re-exhibit it under his own name: “Maelzel's Chess Player”. This exhibitor has a paper trail of palimpsests (to this day, he is still credited for others' inventions, most notably the metronome). Maelzel added a few gimmicks to the Turk, including a crude speech device that announced when opponents were in “check!”. This further obscured Kempelen, whose other automata were the first to speak using anatomically accurate components. Kempelen may have despised the Turk, but its success gave him the creative freedom to compile his ideas and designs for over 20 years into a lesser-known book. A book that happened to leave an indelible mark on a particular family of linguists. The Bell family used a system called “Visual Speech”, devised by their father, to communicate with their deaf mother. The Bell children were taken to see reconstructions of Kempelen's automata and received a copy of his comprehensive book. Throughout their adolescence, they assembled the mechanical larynx, diaphragm, and other parts detailed and illustrated by Kempelen. The boys configured their first automaton to say “Mama”. Only one sibling, Alexander, survived into adulthood, marrying a deaf woman himself. Alexander refined these speech-producing contraptions with the advent of electricity, patenting his system in 1876, he called the telephone.

Automata

Before Kempelen's automata became his posthumous liaison to a family of practitioners, Maelzel's sensational marketing found other types of players. When exhibiting in England, a recent graduate struggling to find a purpose after attending Cambridge University sat across the updated Turk. Charles Babbage—like most 20-something-year-olds—was in search of where and what to aim themself and their new college degree towards. Soon after playing (losing twice) against the Turk, Babbage wouldn't just find an aim, but a trajectory toward becoming “The Father of the Computer”. Babbage set out to achieve what the Turk deceitfully claimed to have: the first machine that could possess our mind as well. In 1822, Babbage devised the plans for his “Difference Engine,” which was expanded upon for over a decade into the programmable “Analytical Engine”. These plans evolved into the machine you are currently reading this on. Babbage's assistant, a young unsung woman named Ada Lovelace, wrote the theoretical language this sort of machine would speak. Ada was the first computer programmer. Like Kempelen, both Babbage and Lovelace died before either of their engines' full potential could be realized. However, the integrity and detailed plausibility of the plans were enough to push the next players to move.

The next player was made in Spain but was largely overshadowed by household names in the West. Leonardo Torres Quevedo was a Spanish civil engineer who worked on railroads before becoming inspired by Babbage’s shortcomings a century before. He saw the advent of electricity as the missing piece of Babbage’s thinking machines. Quevedo began implementing switches—used for relaying early telephone calls—into specialized machines. He is the first person on record to use these electromechanical switches, not just to turn on remote power sources to extend telephone signals, but to activate operations within a calculating machine. These machines were among the first to prove Charles Babbage wasn’t necessarily quixotic; he was just born too early. Much of Quevedo’s work remains underappreciated compared to his contemporaries. Nikola Tesla and Leonardo Torres Quevedo respectively introduced the world to wireless control capabilities with a toy boat at the turn of the 20th century. Quevedo's wireless signals were far superior, creating the first-ever device capable of genuine remote control, aptly named Tele-kine, Greek for "movement(at)distance". A cable car system he designed to transport people across otherwise untraversable areas is also still in use today.

Quevedo’s controls and interconnected transportation systems were foundational, but not iconic enough to have his surname commemorated on automobiles a century later. In the 21st century, his same endeavors result in the richest person in the world. When Elon Musk's company Neuralink introduced the world to the most advanced remote control technology it has seen, they happened to demonstrate it using the same game initially computerized by Quevedo. In 1912, Quevedo built “El Ajedrecista” (Spanish for “The Chess Player”). El Ajedrecista was the first machine able to play an endgame of chess (and win every time). This was the first electromechanical game-playing machine, making Quevedo a worthy consideration as the father of the first computer game. This chess-playing automaton wasn't an illusionary hoax or theoretical plan, it was real, enough to intrigue established scientists. A professor from MIT who founded the field of “Cybernetics” (and now known as “The Father of Automation”) eventually came out to play against Quevedo's chess machine in 1951. Academia was following close behind, with many sensing paternal opportunities. A player named Claude Shannon gathered with a few colleagues in the summer of 1956 to coin an official term separate from the previously popularized “Automata” or “Cybernetics”. They came up with “Artificial Intelligence”.

Digital Paternity

While attending MIT, 22-year-old Claude Shannon wrote what is now considered the most significant master's degree thesis ever written. It devises the DNA for a digital world. The scientific community gradually recognized the insights as being on par with Einstein’s theory of relativity or the atom bomb. Claude later downplayed it as simply pairing two existing concepts that others didn't notice a connection between at the time. He spent much of his youth and professional life playing games like chess, “pursuing interests without much regard for final value or value to the world, spending lots of time on totally useless things.” This was his explanation for why he saw an old obscure concept with no practical use, and entertained it as the solution that early computer scientists couldn't formally answer.

When Man understood which materials the phenomena of lighting preferred (like we once did with fire) harnessing it meant switching it on or off. A switch that could direct electricity into reactive components that heat, illuminate, or spin. Connecting a few of these components could wash clothes, compress refrigerant, or a variety of other contraptions that turned on the Machine Age with a flip of a switch. The properties of electricity complemented aspects of physical procedures, but it made even more sense for mental ones. What happens when an electric switch isn't connected to heating, spinning, or illuminating…but to another switch? The Machine Age turns off as quickly as it turned on.

Earlier on, Quevedo had used switches to selectively automate Babbage's (theoretical) clunky gears. Scientists of this day were beginning to use more and more of these switches to replace calculations carried out by numbered cogs and dials. An electric switch with “Nighttime” written on it could rely on another switch labeled “Below 72°F” to turn on a heater, but if a switch labeled “Summer” is on, then “Below” switches to “Above”, which turns on a ceiling fan instead, but only when the “Nighttime” switch is off…With enough patience and trial and error, basic “computers” could be meticulously configured, but forget managing lengthier setups, let alone the potential of scalability. Claude sensed that a formal structure, a methodology, was necessary. He found it in the rigidity of algebraic formulas devised a century before, by a relatively unknown mathematician.

The formulas symbolized how a mind reasons, upon conditions being true or false: A room catches on fire…the door is blocked(True) AND Fire extinguisher empty (True) = Climb out window (True). Using a “1” to represent true and a “0” for false, this logical procedure is written symbolically as 1x1=1. If one of those previous conditions were instead false, such as 1x0, then a different procedure is taken. Some situations only need one true variable: Opponent moves chess piece OR you're put into check = Your turn to move. This type of “either OR” situation can be symbolized with addition: 1+0=1. There are also situations when a variable switches an answer entirely, as in “1+0=Your turn to move, but NOT if in checkmate”. These AND / OR / NOT combinations simply turn two inputs into one logical output. The refined output could then be combined with another…Placing a king ♔ and a rook ♖ onto any of El Ajedrecista’s 64 squares would combine the inputs into a single move by the machine. With each move, internal switches are combined, cornering your king—eliminating all its internal switches—until arriving at its final output: checkmate. Quevedo’s machine was undeniably executing logic, but he couldn’t explain it without using chess terminology. As much as Claude enjoyed symbolizing electric switches with chess pieces, he imagined a world where they could symbolize anything.

Parts & Paradigms

Claude Shannon formalized 1(true) or 0(false) to represent the state of a given electric switch, which killed two birds with one output. These binary digits (“bits” for short) could also be rearranged into coded patterns to represent any scripted information: Sentences, pixels in an image, music...Now that both man and machine had a respective native language, we could begin introducing ourselves. Coders came up with ways to translate between these two languages to make instructing machine during its infancy easier for both of us. Processing 64 switches at a time, 8 rows of 8 bits, became the standard. Any amount could have worked, but 8 x 8 could be argued as an amount not too small yet sufficient. Whatever the motivation was, a row of 8 bits either on or off was established to make up a “byte”. These were eventually stored by magnetizing them onto tape (like VHS), and then eventually burning them onto discs (like CDs and DVDs), and are now so ubiquitous that the world around us depends on them for almost every aspect of daily life. Whether it's a text from a friend, a video by a president, medical imaging, GPS signaling where to go, or a street light signaling when to stop…Claude’s achievement remains difficult to appreciate only because it's hard to imagine the world before it. A million bytes is a megabyte, a thousand megabytes is a gigabyte…Claude contemplated how many would be needed for every possible chess game (known as the “Shannon Number”), which ended up exceeding the amount of atoms in the observable universe. Computers began with large physical switches, later swapped for smaller vacuum tubes, then even smaller microscopic transistors, and even smaller nanoscopic semiconductors…and will keep getting smaller because Claude devised what can be applied to a “switch” of any scale: a philosophy. Unless we can make a “switch” smaller than an atom, then all the space in the universe taken up by matter (and more) would need to be filled with switches to compute every possible chess game.

While researchers and scholars were eagerly awaiting Claude Shannon's follow-up to what was considered the magnum opus of a digital age, Claude was busy building a chess automaton in isolation. The resulting Programming a Computer for Playing Chess published in 1950, was the first scientific paper of its kind. According to a colleague, “Claude was playing so much chess” while working for Bell Labs(named after the family of linguists) that supervisors expressed concern. He argued that a chess-playing computer might seem “perhaps of no practical importance”, but it begs a theoretical question that a solution for “acts as a wedge in attacking other problems of a similar nature and of greater significance”. Like Ada Lovelace, Claude also imagined a machine of greater significance being one "capable of orchestrating a melody." Claude credits the designs of El Ajedrecista as a source for his findings: Chess “involves general principles, something of the nature of judgment,[...] not being merely right or wrong, but having a continuous range of quality from the best down to the worst…perhaps a computer that designs good filters even though they were not always the best possible [could be satisfactory]”. Claude confronts the counter-intuitive nature of intelligence, adding, “there isn't a practical method to fully determine if a given chess position results in a win, draw, or loss, otherwise chess would be determined from the first move and lose most of its interest as a game. Our understanding of best and worst is from previous games won or lost”. Even if there is a method of perfection, it would be impossible for a man or a machine to compute, especially as new contributions redefine our criteria.

Bell Labs employees went on to create the first chess computer able to play at a “Master” level, just a few tiers below the most revered “Grandmaster” level of play. They called their artificial chess player "Belle". This project was led by later Bell employee Ken Thompson, whose own fascination with chess was amplified in middle school when he saw a teenager the same age as him on the cover of Look magazine. The player on the cover was a 14-year-old player named Bobby Fischer. Thompson decided to buy some books on chess theory and continue pursuing what eventually got him hired by the labs. Belle was unveiled in competition in 1972 but was largely overshadowed that same month by Bobby Fischer on the cover of Look Magazine, again. Although Alan Turing, whose codebreaking work helped end World War II, hand-wrote the first algorithm capable of playing a full game of chess, it wasn't until Claude Shannon was the first to publish the subject that it became formative to the most consequential practical laboratory in history.

/Home/User/Files/Ranks

Of all the renowned aspects of its design, it's usually the symbolic hierarchy of chess that permeates far-reaching zeitgeists. In the 1470s, after the first attempt at mass-produced information, the very next book printed in English was about the game's characters. Whether you see yourself as a pawn or a king, or not caring as every piece is put in the same box in the end, the symbolism carved into each piece is one of the more easily appreciated aspects. Computer code was similar to a pile of identical checkers pieces before Ken Thompson and Bell employees introduced hierarchical operating systems. Claude's protégés seemed to share this mutual affection: Operating interfaces using less code and more hierarchical objects. In a 1963 doctoral thesis supervised by Claude Shannon, Ivan Sutherland envisioned a new medium: Man interacts with objects, while Machine facilitates manipulating the ideas. While others in the 1960s were hoping a computer could be smaller than a truck, Claude's protégé and his student Alan Kay were imagining the unfathomable: Hand-held tablets, Head-mounted “virtual reality”, volumetric displays. Users arranging objects that interact characteristically was the key to these intuitive machine interfaces. While Alan Kay was designing prototypes with these principles at Xerox, a young visitor in their 20s, named Steve Jobs, had an impressionable tour. A few months later, this visitor shifted their focus towards developing what became the Mac. Alan Kay explained some of the design philosophies behind the prototypes with the first concept of a carry-anywhere computer, suggesting the ideal computer is one in the hands of a child:

“A child is a "verb" rather than a "noun".[...] An environment which allows many perspectives to be taken is very much in tune with the differentiating, abstracting and integrative activities of the child.[...] We do not feel that a [carry-anywhere device] is a necessary constituent for this process any more than is the book. It may, however, provide us with a better "book", one which is active (like the child)rather than passive.[...] Just as with the book, it brings a new set of horizons and a new set of problems. The book did, however, allow centuries of human knowledge to be encapsulated and transmitted to everybody; perhaps an active medium can also convey some of the excitement of thought and creation."

He postulated the socio-economic factors as well: “Just as easy xerography has enhanced publishing (rather than hurting it as some predicted), and as tapes have not damaged the LP record business but have provided a way to organize one's own music. Most people are not interested in acting as a source or bootlegger; rather, they like to permute and play with what they own.”

Kings, Castles, and Canons

Considering the arbitrary rules of most games, few feel as inevitable as the design of chess. A symmetrical plane of light and dark. Checkered squares delineate 8 x 8 subdivisions. Arrangeable objects interact characteristically atop the checkered squares. The board could be subdivided into any amount, but a row of 8 light or dark pieces was not too few, yet sufficient. Whatever the motivation was, 64 was established as the number of squares a player considers per operation. The pawn ♙ moves forward one square at a time, the King ♔ does the same except in any direction, while the Queen ♕ does that as far as it wants. The bishop ♗ travels diagonally, Rook ♖ orthogonally, and the seemingly arbitrary Knight ♘ , when explained as an “L-movement,” feels less so when considering it hops/skips over a square, with the choice of landing on either square directly perpendicular to that hop. Moving one of these characters can incite at least 1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000 different stories (at least according to Claude Shannon). A few other rules have been introduced since 600 AD, but this constitutes most of the game. We can revisit these past games for the same reason we can still listen to what pianists played hundreds of years ago: a universal notation. A record of the exact moves of a given chess game from start to finish. Chess notation uses algebraic symbols, in turn, entitled “Algebraic Notation”. On a chessboard, “e4” signifies the square where file “e” and rank “4” intersect. A player tabulates this data with a chess piece. The first few moves of Napoleon vs the Turk is compressed as: 1. e4 e5 2. Qf3 Nc6 3. Bc4 Nf6 4. Ne2 Bc5 5. a3 d6…When players revise and add to this with alternative sequences, it becomes a refined code, one for achieving checkmate. In chess books predating computer science books by hundreds of years, you'll find this algebraic code with directions explained in a “if this, then do this” format. This is the essence of an algorithm.

“On the fourteenth move white moves their queen horizontally 5 squares putting the opposing king into check” is instead written as 14.Qe8+. This allowed entire games to be transcribed onto a paper card in real time. Patterns and sequences from the best players from different local cafes, cultures, or periods could now be recognized, refuted, and analyzed as a whole. Universal data for reinforced learning. This was the key to unlocking the highest chess level humanly possible…and then higher. As the Machine Age materialized, many of the first machines considered the first “computers” were the ones that relied on tabular data on paper cards to compute data. Leonardo Torres Quevedo's El Ajedrecista would have likely used them, except there was no need, as it used a graphical user interface of objects for inputting and arranging data.

A man working in the US Census Bureau saw the potential in processing and handling data this way. In 1911, he established a company for machines that used these paper cards, called “Computing-Tabulating-Recording Company”, subsequently renamed to International Business Machines (IBM). While Bell Labs was leading pioneering research, it was IBM that began largely turning it into products. While these titans were nurturing Ai in its altricial infancy, dramatic minds were imagining Her potential. The illusionists, who always held the mirror up to ourselves, were in the golden age of a relatively new medium. One that enabled them to hold the mirror at a fantastical angle, letting us collectively see an imagined reflection. A young player from New York saved up enough money in chess winnings to kickstart their foray into this medium. This player, named Stanley Kubrick, eventually angled the mirror to an imagined space odyssey in the year 2001. Peculiarly, the odyssey starts long before, in a period rarely shown in cinema—the dawn of intelligence. The 1968 film 2001: A Space Odyssey begins with primitive humans wandering a desolate earthly landscape before willing their ideas into existence, or apparently vice versa. Then, a miraculous occurrence foreign to the organic formations initiates a new landscape: a tool. Kubrick cuts the 65mm film stock here and splices it seamlessly to 2001, an effect to a cause a few epochs before. A novel form of intelligence wielding a bone tool launches it into outer space, transporting us to a metal container wielded by an Ai super-computer named HAL. Whether HAL is juxtaposed as the novel tool or the novel form of intelligence depends on whether there was a distinction to begin with. Aboard the spaceship in what may have felt like a throwaway scene in 1968 for those expecting a ticket's worth of space wars, ended up as the most prescient.

The scene captures the reality of co-existing and co-piloting in the deep expanse of nothingness. Kubrick keeps the camera in the same spot without a single cut: Intelligent Dr. Frank Poole and artificially intelligent HAL take turns announcing chess moves on a shared graphical user interface. Depictions of sentient computers in science fiction usually relied on vicious humanoids sounding the alarm with robotic brute strength, but HAL lurked like carbon monoxide. When HAL breaks his silence, he speaks with calm indifference, an intonation much more honest than Siri or Alexa's artificial enthusiasm. There is no suspense during the chess game; HAL effortlessly defeats Dr. Poole. This was considered a bold sentiment at the time, but one that foresaw a very real chess match involving IBM soon after. Kubrick dismissed being referential to IBM, despite fortuitous allusions such as each letter in H.A.L. preceding I, B, and M in the alphabet. A private message written during production suggests Kubrick's vigilance: "Does IBM know that one of the main themes of the story is a psychotic computer? I don't want to get anyone in trouble, and I don't want them to feel they have been swindled. Please give the exact status of things with I.B.M. Best Regards, Stanley." IBM is credited as an advisor on the film, although only accepted under the condition of having no association with the equipment failure of HAL. This refers to the scenes following HAL playing chess with faultless functionality. Perhaps HAL's "equipment failures" weren't what IBM wanted to disassociate from, but instead a capable machine assessing terminating us as indifferently as it does checkmating us.

The film’s writer Arthur C. Clarke frequented Bell Labs during production. Internal memos show the Labs’ suggestions for the futuristic communications technology featured in the film, notably the “video-phone”. A cinematic trope near the end of the film offers a nod to the labs. Similarly to “Rosebud” in the 1941 film Citizen Kane, HAL’s final utterances reminisce about an earlier innocence. While being unplugged once and for all, HAL shuts down singing the song “Daisy Bell”. This was the first song ever sung by a computer during a Bell Labs demonstration in 1961, which Arthur C. Clarke attended.

Flanks in Opposition

Around the same time, efforts to establish general criteria to evaluate intelligence, of any kind, were becoming prevalent, especially between the US and the Soviet Union. Any and all demonstrations of intelligence became a foot race between the two nations. There proved to be no clearer display than a face-off where a king has to fall, and a handshake of defeat becomes a better photo op than a flag on a moon. The World Chess Championship Match between Bobby Fischer and Boris Spassky was headlined as “US vs USSR”. A chess game between apocalyptic arsenals may seem redundant, until considering there wasn't anything at the finish line in space either. Much like the initial lead in the space race, the USSR at this point was untouchable in chess. The Soviets were unbeaten for an uninterrupted 24 years, the same number of games(coincidentally) that Fischer would need to win the majority of in the match.

For many people, this was a first impression of the kinds of players who played this game. Early in the match, Fischer's infamous bouts of paranoia were immediately a factor, showing up late and resigning games before they started. Before the third game, now up 2-0, Spassky sympathetically obliged to meet the unusual demands made by Fischer about the lighting, cameras, chairs, and everything in between. During this chaos, everyone from President Nixon's closest advisors to Soviet facilitators was trying to keep the match on the rails. Fischer was finding solace in his bible, a worn-in red book cataloging every recorded chess game played by Spassky. The third game of the match was the first glimpse of Fischer's combustibility as horsepower. Looking at photographs of Fischer carrying his red book around, or any photograph of him for that matter, there's a pattern. Not just under the pieces he's usually looming over, but in the stillness that is captured, like that of a nuclear reactor. Not so much the internal power, but the walls burdened with containing it. Bobby Fischer beats Boris Spassky for his first time in game 3.

Spouses have yet to carry a book around of each other's every move, but competitors at the highest level remain exceptionally intimate collaborators. For Spassky, co-creating excellence on the board meant collaborating with Fischer's madness off of it. After his first loss, Spassky was having his own chair X-rayed and chess pieces inspected by his team. The 4th game was a draw, and now the world was tuning in to see if the 29-year-old phenom from the Bronx could surmount the Soviets in the 5th game of the tied match. On the 27th move of game 5, Fischer sacrifices a bishop to gain a positional lead. Spassky considered the caustic implications of this move before resigning, making it the shortest game of the entire match. Fischer won 4 more decisive games, maintaining a comfortable lead until the end. The match, politicized as another proxy battlefront between the world's leading hegemonies, catapulted the young Bobby Fischer into an icon as the first and only US-born chess champion. A reclusive game from the 6th century, effectively used as a drosophila for information science, was becoming equally as affective for mass media, just in time for the next chapters.

Technological breakthrough divides the constant of time. There was daily life before agriculture, and then after. Our chapter using stone tools, ended with metal tools. As technology accelerated, so did the potential for fewer people to understand it. Inventors initially grasp it, but those who tame it into the right presentation, become the authors of the ensuing chapters: lightbulbs(invented: 1870s), motion picture cameras (invented: 1880s), touchscreens (invented: 1960s), or the internet (invented: 1980s)...remained footnotes until the right demonstration. In the 1990s, IBM wanted to author the next chapter. However, demonstrating Artificial Intelligence wasn’t like Thomas Edison demonstrating candle-like light, produced artificially. Intelligence isn't as obvious, regardless if it's artificial or not. IBM began organizing an undeniable watershed moment: An IBM machine autonomously beating the best human chess player, Garry Kasparov. This rivalry began in 1989, when a computer named Deep Thought beat a human chess grandmaster for the first time, earning itself a chance to play against Kasparov.

Gary Kasparov had already beaten 32 of the best chess computers, simultaneously, but Deep Thought offered a new threshold. Deep Thought lost both times against Kasparov in 1989, but IBM saw the potential to invest in the prospective machine. After years of upgrades and extensive refinements, a match was set up in 1996 between Kasparov(the reigning undefeated chess champion for over a decade) and IBM's re-branded machine, “Deep Blue”. The machine shockingly beat Kasparov in their first game. Kasparov corrected his complacency and won the rest of the match without losing another game. Deep Blue had lost, but that first game was enough for IBM to initiate a blockbuster publicity campaign around a rematch. For over a year, the Deep Blue team at IBM “hired additional chess grandmasters to improve their endgame databases, evaluation accuracy, and methods to disguise the computer's strategies”. They announced the prize fund for the winner contained over a million dollars, which largely favored Kasparov in pre-match predictions. Kasparov’s in-match fortitude was known to be second to none; Kasparov had yet to lose a chess match in his professional career. In 1997, a small eight-by-eight checkered dance floor for intelligence gained the gravity of a colosseum: Man vs Machine, the seminal demonstration of artificial intelligence vs organic intelligence. With increased tensions, Ken Thompson was brought in to monitor the match as an unbiased third party. This was needed to appease the usual suspicions of a computer cheating by using a man. After the first game, Kasparov boastfully joined the reporters and television crews waiting outside for results. During a tense second game, Deep Blue and Kasparov were taking longer to make their moves. Towards the end, Deep Blue took over 15 minutes to make the (now infamous) 36th move. A move that made the best human player resign a few moves later and leave without addressing the press.

With mounting pressure, Kasparov opened the next games with unusual moves, intentionally playing in a way the machine wouldn't have sufficient data on. This led to hard-earned draws, keeping the match tied heading into the last game. Behind the scenes, there were talks of Deep Blue needing reboots. Kasparov felt that a player short-circuiting shouldn’t warrant in-match corrections, and began questioning the fairness of the ordeal. Going into the last game, Kasparov was overwhelmed, but unlike the usual intimacy of competitors at the highest level, this wasn’t a collaboration. There was no faithful book of each other's moves, at least not for Kasaparov. He was guessing what style of play the machine might conjure next, while Deep Blue was analyzing 200 million moves a second. In the last game, Deep Blue tactically sacrificed a piece early on—an unexpected style of playing for computers at the time. Kasaprov couldn't find a direction for the rest of the game, losing the shortest, most decisive game of the match. Twenty years after the world was introduced to the fictitious HAL, IBM's Artificial Intelligence was on a press tour after finally beating Man at his own game. But amongst the scientific community, IBM was dissociating its accomplishment from “Artificial Intelligence”, which had become a vague, almost disreputable field. DeepBlue possessed no autonomous “learning” apart from simply outputting what intelligent humans exhaustively input into it. In Academia, Deep Blue's greatest achievement was perhaps an etymological one; Deep Blue raised the defining bar of “Ai” until it disqualified itself underneath. Thereafter, a machine merely appearing intelligent within the confines of a narrow task wasn't “artificially intelligent”. At least not to the captain of the Cambridge University chess team, who was watching the televised match from England.

Alpha Beta Cuda Data

This chess player would have graduated from Cambridge the year prior, in 1996, but admissions suggested a gap year because he was too young when he was initially accepted. Demis Hassabis started playing chess when he was 4 years old after seeing his dad and uncle play. Within a year he was beating them and most others across England. By the time he was 8, he had enough in competition earnings to buy himself his first computer (a ZX Spectrum designed by Clive Sinclair), which kindled programming custom games. At 13, Demis was ranked the 2nd highest chess player in the world under 14 years old, only behind Judit Polgár: the daughter of a psychologist attempting to prove his theories on nurtured intelligence (all of his offspring became chess grandmasters, with Judit becoming the best female chess player of all time). Demis's aspiration towards professional chess shifted while looking up from the board during a particularly grueling tournament. He recalls looking up at the brilliant minds around him toiling over marginal wins, all looking down instead of at each other. After winning a programming competition to work for an esteemed video game company, he designed and programmed games until he was old enough for Cambridge.

During his gap year, one of the games he developed sold over 15 million copies, becoming one of the top-selling games of the era. The game involved arranging a theme park that would elicit behavior from Ai parkgoers: Loop rides would need to be placed far enough from snack booths, or else janitor stations would need to be nearby to clean up the vomit, which could gross out parkgoers enough for them to leave...Rather than a pre-packaged story, your design incited a new one every time, like a chess opening. Players and critics lauded this as an extraordinary use of Ai for the time. Demis reflected on the uniqueness of the medium, “You as the player aren't passively consuming the entertainment, you're actually actively involved as an agent”. Games were increasingly allowing in-game possibilities in no guaranteed linear order, so the burgeoning gaming industry built hardware to process in parallel. The company that created these parallel processing units became the highest valued company in the world in 2025. Natural language processing chatbots, like ChatGPT, parallel process the context of large texts by using these processors originally conceived for games in the ‘90s. While Demis was studying computer science in college, Deep Blue was studying human chess players, both of them graduating in 1997. Demis reflects, “I was more impressed with Kasparov's mind, that he could play chess to this level where he could compete on an equal footing with the brute of a machine. But of course, Kasparov can do everything else humans can do too. It was a huge achievement, but the truth of the matter was Deep Blue could only play chess. What we would regard as Intelligence was missing from that system. This idea of generality and also learning.”

In the four years after graduating, Demis entered an annual contest involving winning a variety of classic board and strategy games. He won every year, setting the record for the Mind Sports Olympiad. Demis began focusing on his idea of a generalized artificial intelligence that could (learn to) play a similar range of games as himself. Demis, along with two friends, co-founded a company to solve this kind of intelligence. After creating Ai models capable of self-learning how to play classic arcade games, their company, DeepMind, became Google’s largest European investment ever. Demis decided their next goal was to beat the best human Go player, a feat thought to be impossible at the time. The board game Go is older than chess, yet the best players still can't quite describe the gut feeling behind their best moves. Unlike beating the best chess player, beating the best Go player couldn't rely on as much human data, despite having more possibilities than the Shannon Number. DeepMind called their Ai model AlphaGo, which learned to play Go similarly to how organically intelligent players must. By playing. AlphaGo taught itself how to play through trial and error, reinforced with rewards and penalties. This approach would allow machines to “exceed human capabilities [regardless of limited data], and to operate in domains where human expertise is lacking.”

After defeating the best human Go player in a match, DeepMind expanded upon these principles with their Ai chess model AlphaZero. After playing against itself for just a few hours, AlphaZero was able to beat Stockfish, the best chess computer ever(exponentially stronger than Deep Blue). After defeating Stockfish 28 times without a loss, Demis Hassabis had made the greatest chess-playing entity in existence. Every chess engine from Belle to DeepBlue to Stockfish maximizes the minimum gain by pruning or ignoring, like a gardener does with fruits on a tree. A machine storing every possibility was never the goal, it's teaching them how to be picky. AlphaZero was given only the rules of chess, and then established its own way of picking. In doing so, Kasparov and current best chess player, Magnus Carlson, described watching AlphaZero like witnessing an alien reinvent a game previously thought to be solved. In a particular game against Stockfish, AlphaZero ignored what the best man or machine would have done and instead sacrificed key pieces and positions to instead create an unforeseen “Zugzwang”: a rare situation in chess that forces an opponent to destroy their own position. This is seldom done to top players with many pieces(options) still on the board, let alone to the very chess engine used to correct top players. AlphaZero was discontinued after its demonstration, but its principles have been subsumed by the best chess engines today. After playing increasingly difficult recreational games and establishing themselves by defeating humans, DeepMind decided to take on a game that achieved the opposite…perhaps the only playable game with an altruistic win.

Man vs* Machine

A game called Foldit (2008) caught Demis Hassabis' attention during his postdoc years. The game's sole objective indirectly began in the 1950s, when biochemists successfully depicted nature’s animators: proteins. All life forms and their internal mechanisms are animate because of the ways amino acids “fold” into a 3-dimensional protein. Nature’s mysterious way of folding them creates their unique function, such as Hemoglobin, the protein in our blood folded in a way that oxygen binds to. Scientists began capturing these patterns by crystallizing a protein, and projecting a beam of X-rays through it. The resulting diffracted pattern could then be carefully deciphered. When scientists deciphered the crystalline structure of Insulin—a protein that triggers our cells to absorb sugar for energy—a synthetic version was able to be mass-produced, saving the lives of millions of diabetic people. By 1971, the structures of 7 unique proteins had been successfully solved and logged. With each one, many of life's molecular calamities began to be understood, leading to treatments for otherwise fatal diseases such as HIV. While unrivaled in its accuracy, analog crystallography could sometimes take years of work and funding to complete even a single protein. In the early 2000s, a program called Rosetta@home was among the first digital attempts to offset some of the work. It used the idle processing power of volunteers' computers, which also showed its protein iterations as a screensaver. Unexpectedly, the screensaver intrigued those who watched it long enough to want to play it themself. The ensuing game, Foldit, allowed volunteers to attempt.

By the time Demis Hassabis approached protein folding, approximately 136,000 proteins had been logged by countless scientists, institutions, and crystallographers over the second half of the 20th century. DeepMind called their protein-solving Ai model AlphaFold. Demis had used a chess-playing computer as a wedge to attack a problem perhaps of the greatest significance. Doubling or tripling the 136,000 solved proteins would have been groundbreaking, but AlphaFold went on to solve over 200 million…and then release the models for free as an open-source database. Demis Hassabis received the 2024 Nobel Prize in Chemistry (shared with John Jumper and David Baker). Millions of researchers across over 190 countries have begun using it to expedite key research for neglected diseases, cancer, agriculture, and material science. The same year they won the Nobel Prize, “Artificial Intelligence” was going public.