scientist Archives - usatoday24

The scientist who made the AI we know today possible has just raised 1 billion. His new goal is to teach him to see space

February 20, 2026 by usatoday24

Fei-Fei Li, known as the godmother of AIjust closed a $1 billion round for World Labs, his startup dedicated to teaching machines to understand the world in three dimensions. Behind this bet are large companies such as NVIDIA, AMD, Autodesk or the Andreessen Horowitz fund, among others. Li, like other important figures in the field of AI, believes that world models are the way to go, instead of the AGI. Who you are and why what you do matters. Li is one of the people who made it possible for the Generative AI as we know it today existed. He was part of the team that developed ImageNet, a database of millions of images that allowed computers to learn to recognize objects in photos. That academic work was the trigger for the leap towards deep learning that gave rise to everything that came after: from voice assistants to generative models of text and images. Now, from Stanford University, where he directs the Institute for Human-Centered Artificial Intelligence, and from World Labs, the startup he founded in 2024, Li points to what he considers the next big unsolved problem in AI: that machines understand the physical world, not just text or flat images. The problem you want to solve. The great language models like GPT either Claude They are extraordinarily good at processing text. But the real world is not text, or at least it is not only text: it is three-dimensional, it has physics, it has geometry, it has objects that move and relate to each other. “If AI is to be truly useful, it must understand worlds, not just words,” counted Li in his statement. That is what so-called spatial intelligence, the central focus of World Labs, pursues. Unlike working with two-dimensional data, the models the startup works on are designed to perceive, generate and interact with three-dimensional environments. The idea is that an AI with spatial intelligence can reason about how things work in space, where an object is, how it moves, what will happen if it is pushed, how it fits into a larger environment, etc. What already exists and what is coming. In November of last year released Marbleits first commercial product. It is a model that generates editable and downloadable 3D environments from text, images, videos or panoramas. The user can create a virtual world, modify it, expand it and export it in different formats. The startup positions it mainly for video games, visual effects and virtual reality, or sectors with a huge demand for 3D content in which there are few tools to put them into operation. With this new round of financing, the focus also expands to robotics. And in this field, spatial intelligence is especially critical, since a robot that understands the space around it can plan actions before executing them, process different ways of completing a task or adapt to changing environments without needing to be reprogrammed for each situation. Autodesk has put 200 million at your table. It really makes perfect sense. It is the company that makes the design software used by architects, engineers, animation studios and manufacturers around the world. Your business is, by definition, thinking in three dimensions. And if Li’s models can generate and reason about 3D environments, Autodesk tools can also benefit from what the startup aims to offer. Daron Green, chief scientist at Autodesk, explained to TechCrunch that the collaboration between both companies will initially focus on entertainment and audiovisual production. The idea is that design workflows can be combined with AI-generated worlds. In this way, a user designs an object in Autodesk and places it in an environment created by World Labs, or the other way around. “You might anticipate that we will consume their models or that they will consume ours in different contexts,” Green said. You are not alone in this race. World Labs is not the only commitment to world models. Google DeepMind works on your family of Genie modelscapable of generating and simulating 3D environments. Yann LeCun, who was chief AI scientist at Meta, just founded AMI Labs with the same approach. Startups like Decart and Odyssey They also move in this spacealthough with products still in the demo or research phase. However, there are differences in their respective approaches. LeCun, for example, defends that to build true world models a completely new AI architecture will be needednot generative. Li, from World Labs, is committed to advancing with current generative models and improving from there. Cover image | World Labs and Andria Lo In Xataka | We’d love to tell you that ‘Her’ hasn’t come true and there aren’t people dating an AI, but we can’t.

Only once did he bet on a scientist and help us understand it better

February 2, 2026 by usatoday24

If today we think of an astronaut, we usually imagine someone with advanced scientific training, prepared to live for weeks or months in a challenging environment, master complex systems, robotics and even several languages. But in the sixties, when the space race was a race of speed and prestige, the mold was different: NASA was looking for operational profilespeople capable of making decisions under pressure and flying machines that no one had flown before. That was the pattern that marked almost the entire Apollo program.. And yet, there was one exception that broke the norm: for the first and only time, one of those who set foot on the Moon was specifically selected as a scientist, and that influenced what we learned about it. The protagonist of this exception was Harrison H. “Jack” Schmittand his case is unique within the lunar program. On Apollo there were astronauts with doctorates or advanced technical training, yes, but that does not automatically make them “scientist-astronauts.” The difference is in the selection criteria. Buzz Aldrinfor example, had a doctorate in astronautics, but entered the astronaut corps through the usual route of the military pilot (Group 3), like so many others. In June 1965, according to NASA, a specific group was selected to incorporate scientists, Group 4, and Schmitt was the only member of those members who ended up assigned to a moon landing mission, Apollo 17. The astronaut who came to be a scientist Before becoming an astronaut, Schmitt was already working, literally, with the Moon in mind. According to the USGSin 1964 he joined the Astrogeology team at the Flagstaff Science Center as a geologist after receiving his doctorate from Harvard. participated in lunar geological mapping and led the Lunar Field Geological Methods project, focused on how to do field geology applied to satellite exploration. That experience put him in a unique position within the program: He was not a newcomer to lunar science. After joining NASA, his contribution went beyond flight. The Florida Institute for Human and Machine Cognition highlights who organized the lunar scientific training of the Apollo astronauts, represented the crews during the development of hardware and procedures for exploring on the surface, supervised the final preparation of the descent stage of the Apollo 11 lunar module, in addition to serving as a mission scientist. Apollo 17 was not just another mission within the program. NASA defined it as the last of the three J-type missions, a series characterized by greater hardware capacity, more scientific load and the use of the Lunar Roving Vehiclethe electric rover that expanded the real exploration radius. That explains why the exploration of the Taurus-Littrow valley was not chosen at random. The objective was ambitious: to work in an area where rocks older and younger than those recovered in previous missions could be found. Added to this scientific ambition was an operational design with room to deploy and activate surface experiments, perform sampling, and complete photographic and experimental tasks both in lunar orbit and upon return to Earth. In an interview with the Japanese space agency (JAXA)Schmitt explains that a specialist comes with years of accumulated experience, and that allows him to decide much more quickly what is important and what is not. Schmitt recalls that NASA trained its pilot astronauts to observe well and understand the problems they were working on, but insists that there is no substitute for experiencewhether in geology, medicine or any other discipline. That is the practical logic that sustains their presence in Apollo 17: when the objective is no longer just to arrive, but to interpret an environment and choose samples judiciously, having someone on the ground who has done field geology for years changes the quality of the decisions. And there appears one of the most memorable episodes of Apollo 17. In the middle of the field work in Taurus-Littrow, Schmitt and Eugene Cernan identified the so-called “orange soil”a finding that generated great expectation in the scientific community. Within the framework of the mission, this material has been described as volcanic glass or pyroclastic material, and is interpreted as especially clear evidence of ancient explosive volcanism on the Moon. It wasn’t just a color oddity. It was a clue about the thermal and geological history of the satellite, and a perfect example of why the mission had looked for a place where different materials could appear, older and also younger than those brought by other expeditions. If Schmitt’s story seems strange it is because, within the same group of scientist-astronauts, he was the only one with a lunar destiny. The USGS notes that, From more than 1,000 applicants, six were selectedand that three of them, Joe Kerwin, Owen Garriott and Edward Gibson, would end up flying in Skylab in 1973 and 1974. That is, science, yes, but far from the moon landing. NASA wanted to reinforce the scientific component of manned flight, but the priority of the lunar program remained different and the space for “specialists” was limited. In this context, Schmitt stands out not only for stepping on the Moon, but for what it implies: even within a group created to add science, the moon landing remained almost exclusive territory of the operational profile. Schmitt’s story has value precisely because it is not just a biographical oddity, it is a mirror. In Apollo, the ideal astronaut was an operator, and only once, in the last moon landing, that mold was opened to integrate someone selected for their scientific profile. As we have seen, currently, astronaut training is designed for long and complex missions, with different requirements. And right now, when the moon race looms again, that question makes sense. Since Apollo 17, in 1972, humans have not returned to the surface, but NASA proposes a way back with Artemis, with Artemis II as a manned flyby and Artemis III as the planned moon landing if plans are fulfilled. With China also targeting the satellite, the return is no longer read only in a historical key. Returning … Read more

The scientist who was in prison for creating the first genetically modified babies. Now he wants to do it again

January 24, 2026 by usatoday24

In 2018, a scientist took to a stage in Hong Kong to announce that he had crossed the Rubicon: the birth of the first genetically modified babies in history. Today, after serving three years in prisonHe Jiankui is back. But he does not seek forgiveness. With financing of 50 million yuan (about 7 million euros) and an increasingly messianic aesthetic, the man nicknamed the “Chinese Frankenstein” plans to rewrite the code of life again. This time, with an even greater promise: eradicating Alzheimer’s. “I know what it feels like to be God!” shouted Professor Frankenstein—played by Colin Clive—in the film Frankenstein (1931), forever establishing the myth of the scientist who crosses all limits. Upon his release in 2022, He Jiankui appears to have assumed that role without irony. In a recent interview with WIREDhe no longer presents himself as a reckless researcher who learned his lesson, but as a “pioneer of gene editing”, a term he demanded as a condition of being interviewed. On social networks, he is defined as the “Chinese Darwin” or the “Oppenheimer of China”and often posts photos in a pristine coat, posing alone in a lab. Isolated from international academiaI have assured WIRED that investors “come to him every week.” He has established an independent laboratory in the south of Beijing and, although Chinese law expressly prohibits the genetic editing of embryos for reproductive purposes, he claims to operate within a gray area: “philanthropic” research, financed by private entrepreneurs and desperate patients. What happened to the babies? The original 2018 experiment sought to make babies immune to HIV by modifying the gene CCR5. The result, according to geneticists and bioethicists, was a technical and ethical failure. The researcher Lluís Montoliu detailed in The Conversation that the girls born from that experiment are “genetic mosaics”: not all their cells were edited in the same way, and unwanted mutations were also detected —off-target— in other regions of its genome. Despite this, He Jiankui maintains a defiant stance. As stated to the Wall Street Journalall three girls—including a third born in 2019—are healthy and attending primary school today. “I don’t have to apologize to anyone,” he said. However, experts warn that this statement rests on a huge information gap since the real impact of genetic alterations on your immune system, the long-term effects and the psychological consequences of growing up knowing – or one day discovering – that they were humanity’s first genetic experiment are unknown. The new frontier: Alzheimer’s. He Jiankui’s new target is Alzheimer’s, a disease with a personal component: his mother no longer recognizes him due to this pathology. As explained to WIREDtheir plan is to introduce a genetic mutation into human embryos —APP-A673T— discovered in the Icelandic population, which appears to confer natural protection against cognitive decline. The scientific consensus is devastating. Kari Stefansson, the Icelandic geneticist who participated in the identification of that mutation, warned in the Wall Street Journal that He’s approach is “very high risk.” Manipulating the genome of an embryo means that any error, no matter how small, will not only affect one individual, but will be transmitted to all future generations. There is no going back. Still, far from moderating his ambition, He is already planning the next step. confessed in the interview that their ultimate goal is to make up to 12 simultaneous genetic modifications in a single embryo to prevent cancer, HIV and cardiovascular diseases. “The children born will be much healthier and may live longer than us,” he says. For many scientists, that phrase sums up the problem: a totalizing promise based on a still immature technology. Science without borders. How does a scientist disqualified by his own country plan to execute this plan? The answer is a transnational structure that some experts describe as “guerilla science.” In China, He limits his work to human cell lines and experiments with mice and monkeys. In the United States, as revealed by South China Morning Postplans to operate – through his wife, businesswoman Cathy Tie – a laboratory in Austin (Texas), where private financing allows research with embryos discarded from in vitro fertilization. The final destination would be South Africa, a country that relaxed its ethical guidelines in 2024 and that, according to He, would be very interested in authorizing human trials. The financing of this network is as ambitious as it is opaque. While the Wall Street Journal points out that He refuses to reveal the identity of his sponsors, the SCMP reports that even Alternative avenues have been explored such as cryptocurrencies promoted by their environment to raise funds. The uncomfortable mirror of Silicon Valley. The most controversial part of He Jiankui’s speech is his frontal attack on the American technology elite. “Some Silicon Valley billionaires are pushing to improve IQ in babies. I think it’s a Nazi eugenic experiment,” stated in WIRED. However, the border between what He does and what is already happening in California is increasingly blurred. Startups like Nucleus Genomics or Orchid Health they do not edit DNAbut they do allow embryos to be selected based on genetic scores associated with intelligence, obesity or risk of Alzheimer’s. The technical difference is real; The underlying logic—optimizing the human being before birth—is eerily similar. While tycoons like Jeff Bezos and Peter Thiel invest billions in biotechnologies that promise to slow down or reverse aging, the human body has become in one more financial asset. He maintains that he edits to prevent disease, while Silicon Valley selects to optimize. For global ethics, both models raise the same fundamental question: who decides what “best” means? Science versus myth. There is an essential point that is often lost among promises and figures: DNA is not a destiny. Genetic predictions about intelligence or success explain only 5% to 10% of the real variability between people. Additionally, there is a critical technical risk: Analyzing a few cells from an embryo requires amplifying its DNA, a process that can introduce errors and lead to decisions based on flawed data. Behind … Read more

The “godfather of AI” believes that AI LLMs are a dead end. Meta has turned him into a vase scientist

November 17, 2025 by usatoday24

Yann LeCun has been warning for years that Generative AI is stupid. The current models, he claimed a year ago, are no more intelligent than a domestic cat. This speech has become especially uncomfortable especially because LeCun, considered one of the godfathers of AI, was until now one of the most responsible for this segment in Meta. Now everything seems to point to an imminent departure that will see LeCun found his own startup. Why is it important. While AI companies strive to train AI models by collecting more data and spending billions of dollars on computing power, LeCun is clear that this strategy is a dead end. It is something we have been talking about for a long time and that other experts like Andrej Karpathy have also have warned: This scaling of resources previously allowed notable leaps in performance. Not now. He knows what he’s talking about. In 2003 LeCun joined New York University and later founded the institution’s Data Science Center. In 2013, Mark Zuckerberg recruited him to lead his new AI division at Facebook called FAIR (Fundamental AI Research). In 2018, LeCun, along with Geoffrey Hinton and Yoshua Bengio, won the Turing Awardthe highest honor in computer science, for his contribution to the study of neural networks. LLMs must give way to “world models”. LeCun has prophesied that within three to five years no one in their right mind will be using today’s LLMs. Instead of them, the architecture that will triumph will be that of the so-called “world models”which learn from the environment through visual information, similar to how a baby does, in contrast to LLMs, which are predictive models based on vast text databases. Internal tension. That vision of LeCun has ended up being a problem in Meta. Mark Zuckerberg does not seem to have the same opinion, and in recent months he has made it clear. with a bet multimillionaire in which ended up signing talent and creating its new superintelligence division that precisely reinforced the role of the LLM that LeCun sees as useless. An uncomfortable situation. These signings have caused the FAIR Group that LeCun led to lose prestige, resources and weight in the organization compared to that new AI research organization led by the new rising star, Alexandr Wang. Exit in sight. Last week the first rumors appeared that LeCun is planning his departure from Meta to create his own startup. Precisely this new company would explore the creation of those models of the world that this scientist and researcher wants to develop in depth. If he executed that step, it is very likely that the investment world would support that vision and offer him sufficient funds to work on it. It has happened with startups Ilya Sutskever and Mira Muratithat without having visible product They have achieved multi-million dollar financing rounds. LeCun seems to be right. The evolution of LLMs seems to confirm LeCun’s theory that they are not the valid way to achieve truly notable advances in the field of AI. What current models do is not so much solve problems as locate past instances of solved problems to use probability and apply answers. Don’t even think about pursuing LLMs.. In recent months, LeCun’s work in Meta has become more blurred and he has been seen participating in several conferences. In one of them gave a message clear to those aspiring to get into this field: “if you are a PhD student in AI, you should never work with LLMs.” Image | Goal In Xataka | The only advantage Apple could have in AI was its private cloud. It has been copied by the person we least expected

Meta’s star AI scientist plans to leave the company, according to the FT. The new goal is eating the old goal.

November 12, 2025 by usatoday24

The head of artificial intelligence at Meta, Yann LeCun, would be preparing to leave the company to found his own startup, according to inform Financial Times. The departure of the prestigious researcher, winner of the Turing Award and considered one of the fathers of modern AI, symbolizes the radical change that Mark Zuckerberg is giving to Meta’s strategy around AI. The changing of the guard. LeCun, who led the Fundamental AI Research Laboratory (FAIR) since 2013, is now in an uncomfortable position within Meta. This summer, Zuckerberg hired Alexander Wang28, to lead a new “superintelligence” team, paying $14.3 billion to take 49% of Scale AI, the data labeling startup Wang had founded. As a result of this restructuring, LeCun went from reporting to chief product officer Chris Cox to reporting to Wang, according to account Financial Times. A philosophical divorce. The tension is not only organizational, but conceptual. LeCun has long publicly defended that the language models on which Zuckerberg has focused his strategy are “useful” but will never be able to reason or plan like humans. His bet from FAIR has been different: the so-called “world models”AI systems that learn from the physical environment through videos and spatial data, not just language. A path that, according to LeCun himself, could take a decade to bear fruit. Meta’s problems with AI. Zuckerberg’s reorganization comes after several setbacks. The launch of Call 4 It has not gone as the company would have liked, falling below the most advanced proposals from OpenAI, Google and Anthropic. Additionally, Meta AI, the company’s chatbot, has also not gained traction among users. Meanwhile, Zuckerberg has hired dozens of engineers and competing researchers with pay packages of up to $100 million, creating a dedicated team called TBD Lab to accelerate the development of new versions of its language models. The cost of pivoting. The shift toward practical AI appears to have generated internal chaos. Sources cited by TechCrunch In August they revealed the frustration of new hires when facing the bureaucracy of a large company, while the previous generative AI team saw its scope reduced. In October, Meta laid off 600 people of its AI research unit to cut costs and accelerate product launches. Also in May Joelle Pineau left the companyvice president of AI research, who joined Canadian startup Cohere. What’s coming now. According to two sources Cited by the Financial Times, LeCun’s new project will focus on continuing his work on world models, and he has already started talks to raise funding. His departure, scheduled for the coming months, represents more than the departure of a brilliant scientist: it is confirmation that Meta’s old long-term focus has been relegated by the urgency of competing in the short term with more practical solutions. As Wall Street pressures Zuckerberg to justify an investment in AI that could exceed $100 billion In 2025, the company would be losing one of its most recognized brains along the way. Cover image | Goal and AFP In Xataka | AI was supposed to reduce costs and reduce staff. The Coca-Cola ad illustrates how much we were wrong

A young computer scientist was looking for work. So “hacked” LinkedIn to always receive offers first

May 10, 2025 by usatoday24

The youth of generation Z face serious difficulties in starting their work career in a labor market so competitivein which for Each job offer hundreds or thousands of candidates are presented. Find The slightest advantage To highlight in job requests it is fundamental. Michael Yan, a 25 -year -old founder and CEO from Simplify, has shared A trick on LinkedIn which allowed him to receive job offers from large companies such as Meta, Microsoft and Google. This method allowed him to access before the rest of vacancies candidates, thus increasing the possibilities of being hired Faced with other candidates. Yan’s trick. Like Yan told to Business InsiderIn 2018, the young manager was in his first year of computer science at Stanford University and was looking for companies to do his first practices. Given its technological training, Yan warned that the URL address of the LinkedIn Employment Section showed an “86400”. That number is not accidental: it is the number of seconds that have 24 hours a day. Therefore, when Yan asked LinkedIn the job offers of “the last 24 hours”, he always showed him those that had been published the day before, not in the last hours. A simple change to be the first. From that discovery, Yan accessed LinkedI’s employment tab and made a search for the professional profile that demanded and applied the filter “publication date” to “last 24 hours”. Then, the number “86400” of the URL address in the browser bar for “3600” changed, which is the seconds that have an hour. In this simple way, the young candidate “hacked” LinkedIn’s job search obtaining the offers published in the last hour, so that always He was one of the first candidates in postulating for vacancies. “I got job offers in Meta and Google because I postulated offers a few hours after they were published,” said the young manager in his publication. Access to better opportunities. Yan discovered that manually modifying these URLs could access the newest offers before other users, which placed their curriculum among the first in the list, causing their hiring options to improve considerably. Although this trick does not guarantee that a company hires someone for a position for which It is not preparedit does offer an important advantage in the selection process. Many companies establish an order of arrival to review the candidacies, so being among the first to apply will place you among the first to do your job interview. That served him to do your practices In the best technological companies. Any advantage is welcome. According to a report of Handshake of 2024, 57 % of the Z generation that will be incorporated into the labor market in 2025 is pessimistic about the start of its careers. 63% ensure that pessimism comes from an extremely competitive labor market. The data suggests that these newly graduated young people have already sent 24 % more employment requests than last year students of the previous year. Although skills and experience remain crucial, response time can be decisive to advance the selection. According The published by Business InsiderAndrew McCashill, expert in professional racing in LinkedIn, said that “being one of the first to run, especially for jobs you really want or for those who are super qualified, should undoubtedly be part of a job search strategy.” In Xataka | A LinkedIn function opens a debate that divides recruiters: the #Pentowork label Image | Unspash (Sign Pratama)

Log In

Sign In

Forgot password?

Your password reset link appears to be invalid or expired.

Log in

Privacy Policy

Add to Collection

No Collections