An article from MIT Tech Review in collaboration with Aventine points out that although Musk claims Tesla Optimus will in the future be able to automate almost all human labor at as low as $20,000 per unit, and predicts it will go on sale to the public by the end of 2027, many robotics researchers are skeptical. Yann LeCun said at Davos that all companies making humanoid robots have no idea how to make robots smart enough to be useful. Google DeepMind tested Gemini Robotics with ALOHA 2, which can already complete multi-step tasks such as packing a lunch box, but researchers believe that language and image intelligence struggle to cope with the infinite variability of the physical world.
per unit, and predicts it will go on sale to the public by the end of 2027, many robotics researchers are skeptical. Yann LeCun said at Davos that all companies making humanoid robots have no idea how to make robots smart enough to be useful. Google DeepMind tested Gemini Robotics with ALOHA 2, which can already complete multi-step tasks such as packing a lunch box, but researchers believe that language and image intelligence struggle to cope with the infinite variability of the physical world.
The debate over whether the AI industry should slow its research and development pace continues to heat up. On September 12, Anthropic CEO Dario Amodei published an article calling on the industry to proactively slow the pace of capability improvements in frontier models, warning that recursive self-improvement could spiral out of control. OpenAI CEO Altman, xAI founder Musk, DeepMind founder Hassabis and others publicly expressed support. On September 16, Meta CEO Zuckerberg said that devoting the vast majority of compute to serving people rather than racing to pursue recursive self-improvement is one of the best ways to develop this technology safely, and said labs that do not focus on alignment will fall behind. Opposing voices are equally strong: Trump called AI safety concerns a hoax, and Nvidia CEO Jensen Huang believes innovation and safety can go hand in hand and that no new legislation is needed; while big short Michael Burry pointed out that executives talk about slowing down out of self-interest, and said large language models are not AI and will not become AGI.
proactively slow the pace of capability improvements in frontier models, warning that recursive self-improvement could spiral out of control. OpenAI CEO Altman, xAI founder Musk, DeepMind founder Hassabis and others publicly expressed support. On September 16, Meta CEO Zuckerberg said that devoting the vast majority of compute to serving people rather than racing to pursue recursive self-improvement is one of the best ways to develop this technology safely, and said labs that do not focus on al
According to a recent report in Nature, since the beginning of this year multiple teams have attempted to build retro LLMs whose training data is cut off before a certain historical point in time, to test whether the models can rediscover later scientific ideas. The results show that AI is still a considerable distance from Einstein-style scientific breakthroughs. Independent researcher Michael Hera trained Machina Mirabilis on pre-1900 data; when faced with the photoelectric effect, the model once proposed that light would break down into a large number of mutually independent pulses, but in most cases it failed and was merely imitating historical texts. Google DeepMind researcher Tom Zahavi points out in the paper "LLMs Don't Leap" that current LLMs cannot yet complete a reasoning leap like Einstein's, and that the abductive reasoning on which scientific breakthroughs depend often occurs on anomalous phenomena with very little data or in conflict with existing theories.
t, the model once proposed that light would break down into a large number of mutually independent pulses, but in most cases it failed and was merely imitating historical texts. Google DeepMind researcher Tom Zahavi points out in the paper "LLMs Don't Leap" that current LLMs cannot yet complete a reasoning leap like Einstein's, and that the abductive reasoning on which scientific breakthroughs depend often occurs on anomalous phenomena with very little data or in conflict with existing theories.
Satlyt, founded by Rama Afullo, a former Google Cloud and SpaceX Starlink engineer, has closed an $8 million seed round led by Houston-based Non Sibi Ventures, focusing on software that lets satellites run AI models in orbit. This year, its software ran Google DeepMind's Gemma model aboard a Momentus spacecraft, cutting the amount of data transmitted for a certain onboard software error by more than 60%; this week it launched aboard a SpaceX rocket alongside the first prototype of Google Project Suncatcher, serving three customers: NASA, Stellerian and TakeMe2Space.
k engineer, has closed an $8 million seed round led by Houston-based Non Sibi Ventures, focusing on software that lets satellites run AI models in orbit. This year, its software ran Google DeepMind's Gemma model aboard a Momentus spacecraft, cutting the amount of data transmitted for a certain onboard software error by more than 60%; this week it launched aboard a SpaceX rocket alongside the first prototype of Google Project Suncatcher, serving three customers: NASA, Stellerian and TakeMe2Space.