MIT

We thought Stanford, MIT, and Harvard were leading in AI. There is a Chinese university that surpasses them all

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To the northwest of Beijing there is a university campus that is not only the most prestigious in the country, it is also one of the most influential universities in the world in science and technology, even surpassing institutions of the stature of MIT or Stanford. It is called Tsinghua and some of the most important technological projects of the moment are being developed there. Change of focus. Tsinghua has been in operation since 1911, although it was not until 1952 when it became a polytechnic university. Among its former students there are figures of the stature of Nobel Prize in Physics Chen-Ning Yang and President Xi Jinping himself. From its inception, Tsinghua’s focus was the training of Chinese students who were going to continue their studies in the United States. Today that approach has completely changed. In the midst of an AI career, there is a nationalistic spirit and students tend to stay and develop projects in their native country. Leaders. They count in Bloomberg that Tsinghua University stands toe-to-toe with the best universities in the world. According to the US News rankingis the best university in the world in engineering, chemical engineering and electronic engineering; has second place in civil engineering and nanotechnology; It is third in materials science and fourth in computer science. There it is nothing. Intellectual property. Tsinghua is also the university with the most papers on AI among the 100 most cited and leads in patent registration, outnumbering MIT, Stanford, Princeton, and Harvard combined. According to LexisNexis data analyzed by Bloomberghave registered 4,986 patents on AI and machine learning in the last 20 years. In 2024 alone they registered 900 patents. However, according to the Stanford AI Indexthe most influential patents remain in American hands. Startups. The university not only focuses on training, it also has a startup incubator called X-Lab from which at least 900 startups have already emerged since it was created in 2013. They are currently very focused on projects related to artificial intelligence. The founders of startups such as Moonshot AIthe creators of the model Kimi K2either Sapient Inca startup that develops “hierarchical reasoning models” based on how the human brain works. They affirm that it is the way to achieve AGI, a different approach to that pursued by companies like OpenAI with LLM or WLM (world models). that LeCun recently defended. Chip war. Efforts are also being made in Tsinghua to give China a boost in the technological war with the United States. The clearest example is the chip created by a group of university scientists and it is 3.7 faster than NVIDIA’s A100. Not only that, the chip, called ACCEL, is also much more efficient. At the moment its mass production has not been achieved, but the innovation is there. Image | Tsinghua University In Xataka | Four decades ago, China decided to invest in training millions of engineers. Today that plan gives it an advantage in the race for AI

The danger of using AI chatbots for everything is real: MIT has discovered the “cognitive debt”

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A MIT study He has shown that chatgpt and similar tools generate what they call “cognitive debt”: students who resort to them for total use end up writing better, but thinking worse. Why is it important. The study contradicts the belief that AI is like a calculator: a simple support that frees us for more complex reasoning. Actually, these tools can atrophy the brain connections that build critical thinking. The facts. 54 university students have spent months writing essays, divided into three groups: Grupo LLM, which used Chatgpt. Search motor group, which used Google. And group Solo-Cerebro, without external tools. The researchers measured their neuronal activity with electroencephalograms and the results have been overwhelming: those who used a neuronal connectivity systematically lower in all frequency bands. Compared to the group that only used its brain, there was a lower activation in key networks that connect parietal, temporal and frontal regions, fundamental for attention, memory and semantic processing. In Xataka 81% of interviewers suspected the traps with AI in interviews: 31% have confirmed it without a doubt and they have put a brake The contrast. The essays generated with AI received better notes, both from teachers and evaluating algorithms. But their authors remembered worse what they had written minutes before and felt a minor authorship about their texts. When they forced the usual users to write without help, their brain patterns showed that dependence on external support. They had lost ability to reactivate the necessary neural networks to write independently. How to walk without support after years doing it with crutches. Yes, but. The students who learned to write without ia and then used it for the first time maintained their engagement neuronal They even showed better memory and reactivation of broad brain areas. The key difference: You need to know how to think before you can think with machines. In perspective. This pattern replicates what we see in other professions: The subway driver who feels alienated because the train drives alone. Translators turned into machine editors. 3D creatives that only retouch what the AI ​​generates. {“Videid”: “X9R6K72”, “Autoplay”: False, “Title”: “Chatgpt Pulse”, “Tag”: “Technology”, “Duration”: “67”} The threat. The study also analyzed university students who already had developed writing skills. The effects could be more severe in adolescents who are still building these cognitive abilities. As a Dartmouth teacher said: we run the risk of creating “an educated generation with AI shortcuts” that lacks independent thinking skills. And now what. The sequence matters more than technology. First, you learn to think. Then, you learn to think with machines. The brain needs to build those Neuronal highways before being able to delegate selectively in AI. The study concludes that educational interventions should “combine the assistance of AI tools with learning phases without tools” to optimize both immediate skill and long -term neuronal development. Outstanding image | Xataka In Xataka |What happens if the software doesn’t matter when you are the largest company in the software world (Function () {Window._js_modules = Window._js_modules || {}; var headelement = document.getelegsbytagname (‘head’) (0); if (_js_modules.instagram) {var instagramscript = Document.Createlement (‘script’); }}) (); – The news The danger of using AI chatbots for everything is real: MIT has discovered the “cognitive debt” It was originally posted in Xataka by Javier Lacort .

The MIT has just placed us closer to the great milestone in quantum computers: error correction

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The rapid development you are experiencing Quantum computing He is gradually dismantling the opinions that question the potential of this discipline. One of the biggest challenges to those who face is the need for quantum computers to be able to amend your own mistakesand three different studies defend how close we are to achieve. A Australian quantum research group, another Dutch and a third Japanese team published in Nature In January 2022 as many scientific articles in which they explain in detail the procedure they used to put superconductor cubits that have precision greater than 99%. When errors are so rare it is much easier to correct them. In the other saucer of the balance, Gil Kalai remains erect, an Israeli mathematician and teacher at Yale who He has predicted that quantum computers will never be able to amend their mistakes. According to this researcher, the increase in the number of states of quantum systems and their complexity will cause them to end up behaving like classical computers, so the superiority of the former will end up evaporating. The MIT has taken a firm step forward Before we investigate the achievement of scientists from the Massachusetts Institute (Mit) It is worth briefly reviewing what one of the companies that is contributing the most contributing to the development of quantum computers: IBM has achieved in the field of errors. The itinerary that published in December 2023 He anticipated that before the end of 2024, the Heron (5K) platform endowed with error mitigation would be ready. And this company He fulfilled his promise. The main problem facing quantum computers in the field of error correction is noise, understood as the disturbances that can alter the internal state of the cubits and introduce calculation errors. The strategy for which many of the research groups that are involved in the development of quantum computers are opting for monitoring the operations carried out by the cubits for Identify real -time errors and correct them. The problem is that from a practical point of view this strategy is very challenging. The mitigation of errors allows the cubits to carry out their calculations even if they have errors and only at the end of the process it is inferred what the correct result is However, there is an alternative path. It is known as ‘error mitigation’, and, very broadly speaking, instead of monitoring in real time what happens in the cubits allows them to carry out their calculations even if they have errors and only at the end of the process it is inferred what the correct result is. This technique is already delivering very promising results. In fact, this characteristic is what allows the quantum processor to argue the other quantum chips developed by IBM so far. What MIT researchers propose in the article in the article that they have published in Nature Communications It is a different approach to the correction of errors. In fact, in their text they describe how they have achieved Attach artificial atoms and photons with the purpose of using this mechanism to process quantum information at a higher speed than the prototypes of current quantum machines. This peculiar type of coupling between light and matter can be used to make very robust cubits and capable of processing information up to ten times faster than a quantum processor such as those currently available. Yufeng Ye, the main author of this article, He maintains that “This technology would eliminate one of the bottlenecks of quantum computers. It is usually necessary to measure the results of the calculations between error correction rounds.” In this statement this scientist has done something very important: he has established a relationship between the strong coupling of light and matter that can presumably be used to produce a new type of cubits and error correction. “This strategy could accelerate the moment in which we will reach quantum tolerant to failures and we can develop real applications with practical value,” says Ye. It sounds really good, although we should not overlook that what these scientists have done at the moment is a demonstration of fundamental physics. The challenge from now on is to bring this technology to practice. Image | IBM More information | Nature Communications In Xataka | We already touched the quantum internet with the tip of the fingers. This German experiment is a successful

MIT has measured for the first time the geometry of electrons in the quantum world

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The paths of quantum physics are inscrutable. In my opinion this appointment of Richard FeynmanNobel Prize in Physics for their contributions to quantum electrodynamics and one of the most admired scientists of the twentieth century, condenses very well The complexity of this discipline: “If you think you understand quantum physics, you don’t really understand quantum physics.” Quantum mechanics study the laws that govern The world of the very smallof the particles, as well as the interactions to which the atomic and subatomic structures are exposed. Most of these rules are radically different from the laws we have become familiar with in the world in which we live. In the macroscopic world. Many physicists have spent the last century trying to understand how known quantum phenomena work, and also striving to identify unknown quantum rules. The problem is that working with the extremely small, with the particles, is very difficult. However, this does not mean that they are not successful. He Mit (Massachusetts Technological Institute) has just been a bit very important. Physicists now better understand the quantum properties of the materials A group of MIT researchers has managed to measure accurately at the quantum level the geometry of electrons in solid materials. Expressed in this way it does not seem much, but it is a very relevant discovery. Until now, physicists had managed to measure the energy and speed acquired by these elementary particles in crystalline materials, but not their geometry at the quantum level. According to Riccardo CominProfessor of Physics at the MIT and leader of this research, “this discovery allows us to understand and manipulate the quantum properties of the materials.” Quantum geometry allows physicists to determine the geometric characteristics of the wave function Before moving forward we are interested in briefly investigating the concept of ‘quantum geometry’ to be able to understand with some precision what we are talking about. Its purpose is to describe the structure of a quantum system such as the forming, for example, by The interaction of electrons In a solid material. In practice this knowledge serves to elaborate a map that describes the probability of finding an electron in a given position. Rigorously this “map” is known as wave function. However, this is not all. Quantum geometry also allows physicists to determine the geometric characteristics of the wave function. This simply means that with this information you can know how precisely the electrons behave in a material and to what extent their properties condition. Quantum geometry helps scientists, in short, to predict the behavior of materials and design new elements or combinations of elements that can be used in aeronautics, Quantum computing or robotics, among many other disciplines. Riccardo Comin assures that “in essence we have done is to develop a plan to obtain completely new information (about the materials) that until now could not be collected.” And Mingu Kang, another of the physicists who have signed the article published in Nature Physics, duck That “this knowledge It can be applied to any type of quantum material“. The technique that these scientists have used to develop their strategy is known as photo emission spectroscopy resolved at an angle. In broad strokes it is an experimental procedure that serves to study the electronic structure of materials in a thorough way and know their fundamental properties. Image | Generated by Xataka with Ia More information | Nature Physics In Xataka | The CERN has an ambitious plan: it wants to demolish the special theory of Einstein’s relativity

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