The idea of the intellectual immortality of generations is knocking at the door of the next stage of the AI revolution. To give a first impression of what we are talking about, let me recall a counter-intuitive statistic on road safety by age groups: the safest drivers, by far, are seventy-year-olds. In other words, it takes people roughly half a century to truly learn how to drive safely. And then, all too soon, they pass away — with no opportunity to share that hard-won skill … not even with their own grandchildren, who must begin learning from scratch and often pay the ultimate price for their mistakes. This is not a unique situation. In fact, it is emblematic of a deeper human condition. All verbalized knowledge amounts to only a thin, transparent surface layer floating on the vast ocean of human knowledge & skills. That ocean is formed by a lifetime of accumulated experience, most of which remains inaccessible to others … felt only by the individual, stored in tactile, muscular, motor, and emotional memory rather than in any kind of sharable words. As for knowledge formalized in computers and other automated systems — that is merely a thin film on the surface of this immense ocean. Keeping all of the above in mind, I coined the term AUTOFORMALIZATION and described its meaning in an article: “Autoformalisation - Knowledge & skill acquisition” netvalley.com/cgi-bin/librar… From my more recent experience, I see that today’s most popular AI products — LLM services such as GPT — hold the potential to become effective tools for helping people extract their intuitive knowledge: first by verbalizing it, and then by autoformalizing it. Some people have asked me why I coined the term AUTOFORMALIZATION at a time when there were no tools capable of scaling the process it describes. My usual answer is a quotation from Heinrich Neuhaus book: “The Art of Piano playing” ‘To give a thing a name is the beginning of understanding it’

“OpenAI…have made 3 new major scientific discoveries in mathematics, computer science, & physics.” Small correction but huge difference: not physics, but theoretical physics In other words, since Greg began to win Erdos race openAI continues to burn money by competing with prominent professors & faculties in three math domains: the math, applied math / computer science, and math in physics / theoretical physics

Grok sometimes demonstrates superhuman wisdom:

“Only a very small minority of people, maybe 0.01% of the world, … understand what AI is, and how it will utterly transform the world.” Only a tiny fraction of airline passengers understand aerodynamics. Yet they understand perfectly well what air travel makes possible. Likewise, a billion GPT users do not need to understand neural networks to recognize what AI can do for their work and lives at the rapidly growing number of the domains. Understanding how a technology works, understanding its practical value, and predicting its future consequences are three different things. Airpower’s importance was recognized before WWII. As well as Drones’ military usefulness was known before recent war in Europe. But recognizing their importance did not amount to predicting the scale and form of their impact on warfare. The same applies to AI. Safety concerns are hardly new. Yet recent developments have prompted leaders of OpenAI and Anthropic to advocate for unprecedented steps of slowing development of the entire AI industry so safety measures can catch up. Dario Amodei explicitly describes how developments over the preceding few months changed his position. Elon Musk added: “Dario is right.” Even the people building a technology can be surprised by what becomes its most urgent problem. There is nothing uniquely AI-related about that. Failing to foresee a technology’s full consequences does not mean failing to understand it —and an above quoted unexplained “0.01%” does not establish otherwise.

Next frontier would be expected to arrive in Silicon Valley from SA:

Google stopped eating ChatGPT’s breakfast, perhaps realizing just in time what exactly Charles IX did mean when said that “horses and poets should be fed, but not overfed.”

“many are leaving to create their own startup” This is the way the Silicon Valley netvalley.com/silicon_valley… was created and still exists:

Now people are learning to understand the media special terminology: youth, students, genocide, disproportional response, etc.

Hinton, Sutskever, AlexNet, and the GPT moment Given the scale of the changes humanity is now undergoing, Geoffrey Hinton is the only real AI godfather still alive, and his words should be treated accordingly. After all, he taught Ilya Sutskever, who served as OpenAI’s chief scientist from day one through the GPT moment of the current AI revolution. Together with Alex Krizhevsky, Hinton and Sutskever co-authored the landmark 2012 paper: “ImageNet Classification with Deep Convolutional Neural Networks”, which described the neural network later known as AlexNet. It became one of the most-cited papers in AI and helped lay the scientific foundations for that GPT moment. Hinton later summed up their roles for the Computer History Museum: “Ilya thought we should do it, Alex made it work, and I got the Nobel Prize.” The AlexNet breakthrough was one of the most significant achievements in AI’s 75-year history —part of the scientific legacy Ilya brought with him to OpenAI at its founding in 2015, where that theoretical foundation was developed further toward the GPT moment.

In the context of the unavoidable confrontation with the CCP, something like the WWII Manhattan Project should be created sooner or later anyway. Sam is just trying to anticipate one of the likely pretexts for it and the form it might take: “one approach to AI safety could involve merging the biggest AI labs into a single organization.”

Exactly. And this obvious fact ot real life needs to become the Tesla’s main foundation of its marketing policy. Because elderly just do not have any other choices: — FSD from v14 and further or zero mobility. That’s it and nothing else.

Temporary. The situation in the mobile communications market will change rapidly, just as it has in the car market since FSD v14. Customers’ choices will narrow to the services offering the best price-performance ratio.

There is always a well-known solution to every human problem … -- neat, plausible, and wrong.

“Tesla is now generating $92 million per month, or $1.1 billion per year, from FSD subscriptions.” Good, but not enough. Tesla still underestimates FSD v14’s sales potential. Meanwhile, anyone who has ridden in a Tesla with FSD ‘on‘ can no longer imagine choosing any other car brand on the US market. xitter.cf/ntvll/status/211301760…