Monday 10th of August 2026

AI vs искусственный интеллект....

Beginning in the 1950s, the Soviet Union launched an ambitious programme aimed at developing artificial intelligence. While the history of AI today seems to be shaped by the giants of Silicon Valley, ideas originating from behind the Iron Curtain had a significant influence, although they remain largely overlooked. 

 

AI before AI: The forgotten Soviet programme (1/3)

By: Sébastian SEIBT

 

American chess genius Bobby Fischer defeated the reigning world champion Russia's Boris Spassky in 1972 in what has been called "the most exciting world chess championship ever".

But the Eastern Bloc got its revenge on August 8, 1974, when Kaissa, a Soviet computer, checkmated its opponent, securing the very first World Computer Chess Championship title for the Soviet Union. Russian artificial intelligence had crushed its capitalist competitor.

The victory proved to the world that the Soviets also had a say in the field of AI, which had until then mostly been developed at top US universities.

AI, a ‘bourgeois science’?

In the early 1950s, AI – which was not yet known by that name – was viewed behind the Iron Curtain with suspicion. The Soviets viewed what was to become AI primarily through the lens of cybernetics, a field of research that was very much in vogue for studying human-to-machine or machine-to-machine behaviour.

Some saw cybernetics as a “false bourgeois science”, while others thought it held great promise for scientific advancement.  

“Cybernetics almost became a sort of official philosophy of scientific research in the USSR,” said Olessia Kirtchik, a sociologist at the European Centre for Sociology and Political Science who has worked on the history of AI in the Soviet era.

The hallways of research institutes and universities were then filled with mathematicians, philosophers and other researchers, tasked with ensuring the communist regime reaped the benefits of cybernetics. While it fell out of favour in the US by the late 1950s, giving way to computer science and what eventually became AI, the Soviets remained committed to cybernetics, particularly the concept of the “thinking machine”.

The gold mine of Soviet AI

One of the leading figures in Soviet AI to go down in history was Alexander Kronrod, a mathematician who was, among other things, in charge of the team that developed the Kaissa chess programme. For some, Kronrod was even the Soviet “father of artificial intelligence”.

But before him, another mathematician had a considerable influence on the development of AI. His name was Dmitry Pospelov.

Pospelov brought prestige to the discipline by “fostering and supporting the artificial intelligence research community for years”, said Kirtchik. This “lobbying” work culminated in the creation of the Russian Association for Artificial Intelligence in 1989.

Pospelov’s pro-AI campaign within Moscow’s corridors of power also illustrates how the field was not immune to the ideological battle of the Cold War era. The Russian mathematician strongly criticised the Western approach to AI, which he deemed too “reductionist”. In his view, American researchers were reducing the human brain to a sort of supercomputer, performing rigorous but disembodied calculations. For him, intelligence had to be conceived as a social activity dependent on its environment, rather than as a purely logical process.

In the Soviet Union, AI was expected to solve practical problems, and the USSR primarily “used algorithms to optimise the management of the socialist economy”, according to Kirtchik.

The oil and gas industries, for example, used it to improve their operations.

 Are we in an AI bubble?

Algorithms even proved to be a gold mine for Moscow – quite literally, given that in the 1960s authorities were trying to identify where to dig in Soviet territory to find gold deposits. To achieve this, Yuri Zhuravlyov, one of the most highly decorated mathematicians of the Soviet era, developed an algorithmic approach. Using data on the known locations of gold mines around the world, Zhuravlyov built a programme in 1966 that successfully identified where to find gold within the Soviet Union.

This may have been one of the first practical success of “machine learning”, the ability of an algorithm to learn from the data it is given. Others see it as proof that AI does not necessarily need huge datasets to find the right answers.

“With clever methods, small data can move mountains – or in this case, reveal them,” Valery Manokhin, a machine learning specialist, wrote in a blog post on Medium on the Soviet gold rush.

When Russian AI inspired Apple

Some of Silicon Valley’s big names also have Soviet AI to thank. Apple might never have released its Newton tablet in 1993 without the work of Shelia Guberman, the Soviet mathematician who solved a puzzle that had been troubling many Western AI specialists: how to get machines to recognise handwriting.

“He achieved this by adopting an approach known as Gestalt (a form of pattern recognition), which had been overlooked in the West,” Kirtchik said.

Guberman's solution was adopted by Soviet entrepreneur Stepan Pachikov for the Paragraph company. His handwriting recognition software was used by Apple to develop the Newton personal digital assistant; the technology was subsequently sold to Microsoft and used by the US Postal Service.   

Other ideas that were developed in the Soviet Union are now enjoying a resurgence, including the “automaton” conceived by Michael Tsetlin in the early 1960s. These ideas inspired Norwegian computer scientist Ole-Christoffer Granmo, who in 2024 introduced the idea of the “Tsetlin machine”, designed to be a more energy-efficient alternative to today’s large language models like ChatGPT.   

But Tsetlin's ideas would likely annoy tech bros of today like Sam Altman and Elon Musk, however. For Tsetlin, “the workings of these automata had to be perfectly transparent, unlike the black boxes that are today’s AI models”, Kirtchik said.

The Soviets were not short of ideas, but as was often the case during the Cold War, they simply did not have the same resources as the West.

The practical applications of Soviet research often remained “marginal", Kirtchik said, "since the computers at their disposal were often incapable of performing the necessary calculations”.

This article has been translated from the original in French.

https://www.france24.com/en/technology/20260730-ai-before-ai-forgotten-soviet-programme ==================== 

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dartmouth....

 

The Dartmouth Workshop: The $7,500 investment that gave birth to AI (2/3)

By: Sébastian SEIBT


Some 70 years before the current frenzy of record-breaking fundraising by modern AI giants such as OpenAI and Anthropic, the Rockefeller Foundation made what may have been the first investment in the history of AI. With a $7,500 grant from the foundation in 1956, four eminent mathematicians organised the Dartmouth Workshop, where the term “artificial intelligence” was first coined.

Billions of dollars are now pouring into artificial intelligence, and AI start-ups have little trouble convincing investors to back them financially.

But back in 1955, the Rockefeller Foundation rejected a $13,500 request to fund a conference submitted by John McCarthy, a young American mathematician who, although promising, was still at the start of his career. 

Rockefeller Foundation administrators balked at approving so much money – the equivalent of more than $160,000 today – to organise a workshop for a field of research that did not yet exist. What was “artificial intelligence”, and why devote two summer months to it at New Hampshire's Dartmouth College?

Nevertheless, McCarthy was backed by some high-profile figures and had teamed up with Marvin Minsky, another young mathematics prodigy. The two rising stars managed to convince other heavyweights to join the project. Nathaniel Rochester, who invented the first commercial computer for IBM, was one of the co-signatories of the funding application. At the time, the few computers in existence resembled large cupboards overflowing with electrical wires and bore little resemblance to today's modern computers.

McCarthy and Minsky also managed to secure the involvement of Claude Shannon, whose reputation as a mathematician was already well established following his seminal 1948 paper on the mathematical theory of communication. Shannon ranks among the names most frequently cited when discussing early AI pioneers alongside Alan Turing and John von Neumann, according to Philippe Mathieu, director of the Multi-Agent Systems and Behaviour team at the University of Lille

They promised to explore topics at the conference including automatic computers, neural networks, the creation of a computer “programmed to use a language” and even the “self-improvement” of intelligent machines – which might today be described as “deep learning”.  

The birth of AI  

One man at the Rockefeller Foundation offered a ray of hope: Warren Weaver, director of the Division of Natural Sciences, had already approved funding for several landmark projects of the time, including in genetics, molecular engineering and agriculture. Weaver had also written an analysis of Shannon’s work.

“Weaver was a friend of Shannon's, which is why the application was addressed directly to him,” said Rudolf Seising, who specialises in the history of science and technology at the Deutsches Museum in Munich.

But although Weaver found the proposal interesting, he felt it was focused on how the brain works, and that brain research sounded more like medicine than mathematics, according to Seising. “He therefore forwarded it to Robert S. Morison, the director of medical research at the foundation,” he added.

Morison decided to award $7,500 to this biomathematics project, making the first AI investment in history.   

The term “artificial intelligence” was still not yet a fait accompli. In a joint article written with Shannon, McCarthy suggested referring to “Intelligent Machines”, but “Shannon felt the term was much too big,” Seising said. They eventually settled on “Automata Studies”, which McCarthy found less promising. 

“‘Artificial intelligence’ was a good term for raising money and to interest the public and policymakers. But it was not purely a marketing decision, as it also served to define a common vision; it was the starting point for a community of researchers on artificial intelligence,” said Hartmut Hirsch-Kreinsen, a sociologist who specialises in technology.   

That was the aim of the Dartmouth Summer Research Project on Artificial Intelligence. The group of four – McCarthy, Minsky, Shannon and von Neumann – wanted to bring together mathematicians, philosophers and economists alike to work on the future of AI. 

Disappointing results?

In June 1956, the team took up residence at Dartmouth College apartments for five weeks. The true significance of the research programme is debated to this day: was this really the founding moment of AI, or were the results disappointing overall?   

The conference itself yielded little of substance. Its organisers had hoped for an exchange of ideas that would in the near future enable them to demonstrate in concrete terms that “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it”, as McCarthy wrote.

In reality, the various accounts of this historic conference show that most of the participants – the exact number of whom is not known – interacted with one another only very sporadically and were present for just a few days, sometimes simply to make use of the computers

But the Dartmouth workshop went down in history, and the 50th anniversary of AI was celebrated in 2006.

And at least one breakthrough was unveiled at the conference: the “Logic Theorist”, considered to be the very first AI programme, was presented by its creators, Allen Newell and Herbert Simon, to the Dartmouth assembly.

Many of the workshop's participants went on to have brilliant careers, and several went on to win Turing Awards, the equivalent of the Nobel Prize for AI.

The conference even influenced the silver screen in the 1968 film, “2001: A Space Odyssey”. Director Stanley Kubrick consulted Minsky as he was developing his concept for the HAL 9000 – the hyper-rational, potentially deadly AI computer and centerpiece of the film's spaceship.

This article has been translated from the original in French.

https://www.france24.com/en/technology/20260801-the-dartmouth-workshop-the-7-500-investment-that-gave-birth-to-ai-2-2

 

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cybernetics....

The story of the founding fathers of artificial intelligence almost always features British mathematician Alan Turing and his computing machine. John von Neumann is often presented as the mastermind behind programmable computers.

Names from the Dartmouth group – such as John McCarthy or Marvin Minsky – are also sometimes cited as the “inventors” of artificial intelligence.

 

AI before AI: The legacy of Norbert Wiener’s cybernetics (3/3)

By: Sébastian SEIBT

British mathematician Norbert Wiener, who founded the field of cybernetics in the 1940s, may deserve a place alongside artificial intelligence founders Alan Turing and John von Neumann. FRANCE 24 revisits this overlooked visionary who was also one of the first to warn against the automation of society.

 

However, another figure is often overlooked or relegated to the category of second-rate pioneers: Norbert Wiener, the founding father of cybernetics in the 1940s.

ChatGPTClaude and other AI chatbots can be regarded as the offspring of his ideas.

But it's uncertain whether Wiener – with his particular moral, political and scientific convictions – would claim any credit for these modern large language models.

A young prodigy

Wiener was born on November 26, 1894, in Columbia, Missouri, into a family of Jewish immigrants from Eastern Europe.

His father Leo Wiener, a highly strict professor of Slavic languages of Lithuanian origin, would “behave somewhat like Pygmalion and attempt to mould his son in his own image", said Pierre Cassou-Noguès, a philosopher at Paris 8 University and author of a fictionalised account of the mathematician’s life.

"At least, that is how Wiener describes it in his autobiography,” he added. 

Thus, Wiener became “a young scientific prodigy moulded by his father”, agreed Mathieu Triclot, a philosopher specialising in the history of technology at the Belfort-Montbéliard University of Technology.

He learned to read before the age of four, graduated from high school at 11, earned a bachelor’s degree in mathematics at 14 and completed his PhD in mathematics at Harvard at 18.

A few years later, the Massachusetts Institute of Technology (MIT) appointed him as one of its youngest professors.

It was in this role that, after World War II, Wiener developed his ideas which would “have an impact on many fields related to artificial intelligence such as robotics, control engineering and multi-agent systems”, said Philippe Mathieu, an artificial intelligence specialist at the University of Lille.

Weinter laid the foundations for the new field of cybernetics as early as 1943 in a seminal article and further developed his ideas in the book “Cybernetics or Control and Communication in the Animal and the Machine”, published in 1948. 

Cybernetics studies “certain phenomena of control and information transmission in the same way in humans, in the animal kingdom and in the world of machines”, Cassou-Noguès said.

In other words, for Wiener and “cyberneticists”, it is possible to draw parallels between the way human and animal brains and machines process information.

Cybernetics, a ‘super-science’ attracting the biggest names in AI

In practical terms, these principles inspired Wiener to work on a new kind of anti-aircraft defence system during World War II.

He aimed to create a system capable of adapting in real time to the movements of missiles or aircraft and of learning from its mistakes. These were the very first tentative steps towards what we would now call “machine learning”.

“The central theme of cybernetics is understanding how an entity adapts to its environment and to the information available. Intelligence is seen as the result of interactions between an entity [living or not] and its environment,” Mathieu said.

“Logic, mathematics and electrical engineering, information theory, brain research and psychology – a whole bundle of scientific disciplines influenced the events that led to AI," writes Rudolf Seising, who specialises in the history of science and technology at the Deutsches Museum in Munich.

"In the first half of the 20th century, interdisciplinary considerations and, above all, transdisciplinary approaches to AI were mainly found under the umbrella of cybernetics, a ‘super science’.”

This “jack-of-all-trades” aspect of cybernetics may also explain why Wiener is less often seen as the “father of AI” than Turing or von Neumann, who had a more direct and immediate impact on the development of computer science.

But for Triclot, cybernetics’ “indirect influence” on AI is considerable.

A series of ten meetings known as the Macy Conferences on Cybernetics brought together scientists interested in Wiener’s ideas between 1946 and 1953.

Some of the biggest names in the history of AI, including von Neumann and Claude Shannon, took part and identified themselves with cybernetics at the time.

One of the founding members of the Macy Conferences was psychologist Joseph Carl Robnett Licklider, “one of the central figures in the history of American computing”, Triclot said.

He later became the head of the US Defense Advanced Research Projects Agency. Licklider "played a key role in the funding and development of the internet and also took an interest in human-computer interface technologies in the 1960s”, Triclot added.

At MIT, Wiener also supervised the work of Walter Pitts, a researcher and logician who was pivotal to the development of modern AI.

In the 1940s, Pitts laid the foundation for the first neural network model.

Against the Manhattan Project

This work, which is rooted in cybernetics, is essential to understanding today’s large language models.

While cybernetics itself may now seem to be a relic of the past, it paved the way, alongside neural networks, for the emergence of the branch of AI known as “connectionism”, which lies at the heart of the rise of ChatGPT and other 21st-century AI systems.

Wiener not only provided an “intellectual cradle” for AI, but “he was also one of the first to warn of its dangers”, Cassou-Noguès said.

Known for his strong-willed character and notorious outbursts of anger, Wiener understood why certain areas of scientific research were dangerous. Consequently, he refused to take part in the Manhattan Project, which led to the development of the first atomic bomb.

Following the bombings of Hiroshima and Nagasaki, Wiener even published a famous open letter in which he stated his intention to no longer publish research that could be misused for creating weapons of mass destruction.

Albert Einstein supported the move at the time. 

But with cybernetics, "as early as 1948" Weiner also foresaw “the possibility of a fully or almost fully automated society – a development which, in his view, could just as easily lead humanity to a world free from the constraints of work or the social hell of mass unemployment,” Cassou-Noguès said.

Wiener concluded that he should continue his work in order to influence the direction research in the field was taking.

Often labelled as politically left-wing – US authorities suspected that he was sympathetic to the Soviet bloc during the Cold War – Wiener was thus one of the first to warn of the risk of social upheaval linked to the advent of machines.

In this sense, “cybernetics is a profoundly political endeavour, preoccupied with the fear of technological unemployment caused by machines that could replace workers”, Triclot said.

For him, it is “striking to read this as early as 1947”, a time when computers were still very rare.

But for Wiener, this risk would only materialise “if we fall into the trap of treating human beings inhumanely”, said Triclot.

In other words, according to Wiener, robots would only be able to replace humans if humans were reduced to having the status of robots by denying everything that distinguishes them from machines.

Although the term “cybernetics” seems to have fallen out of use, the ideas of its founder are relevant today, at a time when companies are citing the triumph of AI to justify layoffs.

This article has been translated from the original in French.

https://www.france24.com/en/technology/20260805-ai-before-ai-the-legacy-of-norbert-wiener-s-cybernetics-3-3

 

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SEE ALSO: https://yourdemocracy.net/drupal/node/30130