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Category: robotics/AI – Page 125

Elon Musk Drops BOMBSHELLS About Optimus Robots

Tesla is advancing towards a sustainable future through innovations in energy solutions, autonomous vehicles, and humanoid robots, while fostering a culture of safety and continuous improvement. ## Questions to inspire discussion s Future Production and Impact ” + 🚗 Q: How many vehicles does Tesla aim to produce by 2025? A: Tesla plans to produce over 10 million vehicles in 2025, up from just 20 in 2010, enabled by their compact, high-output factories.

S vision for Optimus humanoid robots? ” +A: Tesla envisions Optimus robots creating a future of abundance for all, producing goods and services with no limit when combined with solar energy and batteries.

🚕 Q: When will autonomous Teslas become widespread? A: Tesla expects autonomous vehicles to dominate roads within 5 years, with a software update enabling 10-100x more usefulness through robotaxi services. s Service and Energy Solutions ” + s approach to customer service? ” +s service team aims to provide a loveable experience, recognizing that future sales depend on service reputation and word-of-mouth marketing. ” + 🔋 Q: How do Megapack and Powerwall 3 benefit homeowners? A: Megapack and Powerwall 3 enable off-grid living and energy assurance, with Powerwall 3 and solar making homes self-sufficient during outages.

S unique about Teslas Supercharger network allows convenient road trips across the US, Mexico, Europe, and China, with charging speeds faster than a restroom break. ” +s AI and Manufacturing Innovations ” + s role in Teslas most powerful AI training systems. ” + s AI hardware compare to others? ” +s AI4 hardware is the most powerful and efficient AI inference computer, operating at very low power in all vehicles. ” + s innovative about TeslaA: The Cybertruck line aims to produce cars in under 5 seconds, using rapid liquid metal casting and automation, resembling a high-speed electronics line. ## Future of Transportation and Energy.

S full self-driving cars? ” +s self-driving cars achieve 10x human safety, never getting tired or distracted, and free up 10–12 hours per week for drivers. ” + s batteries contribute to grid stability? ” +A: Powerwall and Megapack batteries stabilize the grid by absorbing power spikes and filling drops, acting as a virtual grid in neighborhoods.

🚖 Q: How will the role of Uber and taxi drivers change? A: In the future, Uber and taxi drivers will manage fleets of self-driving cars instead of driving individually. ## Investment and Future Technologies.

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Space Force unveils strategic plan for AI integration

WASHINGTON — The U.S. Space Force released a new strategy blueprint outlining how it plans to integrate artificial intelligence (AI) into its operations and improve AI literacy among its personnel. The document, titled “Data and Artificial Intelligence FY 2025 Strategic Action Plan,” was published March 19 in response to Defense Department directives calling for a more data-driven and AI-enabled force.

“The Space Force recognizes the critical role that data and artificial intelligence will play in maintaining space superiority,” Col. Nathen Iven, acting deputy chief of space operations for cyber and data, stated in the document.

The strategic plan outlines initiatives to “foster data literacy, equip our guardians with cutting-edge technologies, and drive innovation,” according to Iven.

Chain of Draft approach allows AI models to carry out tasks using far fewer resources

A small team of AI engineers at Zoom Communications has developed a new approach to training AI systems that uses far fewer resources than the standard approach now in use. The team has published their results on the arXiv preprint server.

The new approach developed at Zoom is called Chain of Draft (CoD), an update of the traditional approach now in use called Chain of Thought (CoT). CoT uses a step-by-step approach to solving a problem, similar in many ways to human problem-solving. The research team noted that CoT tends to generate more steps than are needed to solve a problem and found a way to reduce them.

Humans do not usually think about every step involved in solving a problem, especially if they are writing them down, because some steps are seen as basic knowledge. Instead, they jump over or combine some of them. The result is a list of essential steps.

AI Will Not Replace Humans, but “AI-Powered Humans” Are the Future

Artificial Intelligence (AI) has made significant strides in recent years, transforming various aspects of our lives. From self-driving cars to personalized recommendations on streaming platforms, AI has become an integral part of our daily existence. However, the fear that AI will replace humans entirely is unfounded. Instead, a more nuanced perspective emerges: AI will augment human capabilities, leading to the emergence of “AI-powered humans.”

How AI is transforming medicine

Artificial intelligence in various forms has been used in medicine for decades — but not like this. Experts predict that the adoption of large language models will reshape medicine. Some compare the potential impact with the decoding of the human genome, even the rise of the internet. The impact is expected to show up in doctor-patient interactions, physicians’ paperwork load, hospital and physician practice administration, medical research, and medical education.

Most of these effects are likely to be positive, increasing efficiency, reducing mistakes, easing the nationwide crunch in primary care, bringing data to bear more fully on decision-making, reducing administrative burdens, and creating space for longer, deeper person-to-person interactions.

Concept for interstellar object encounters developed, then simulated using a spacecraft swarm

Interstellar objects are among the last unexplored classes of solar system objects, holding tantalizing information about primitive materials from exoplanetary star systems. They pass through our solar system only once in their lifetime at speeds of tens of kilometers per second, making them elusive.

Hiroyasu Tsukamoto, a faculty member in the Department of Aerospace Engineering in the Grainger College of Engineering, University of Illinois Urbana-Champaign, has developed Neural-Rendezvous—a -driven guidance and control framework to autonomously encounter these extremely fast-moving objects.

The research is published in the Journal of Guidance, Control, and Dynamics and on the arXiv preprint server.

Machine learning uncovers hidden heat transport mechanisms in organic semiconductors

Complex materials such as organic semiconductors or the microporous metal-organic frameworks known as MOFs are already being used for numerous applications such as OLED displays, solar cells, gas storage and water extraction. Nevertheless, they still harbor a few secrets. One of these has so far been a detailed understanding of how they transport thermal energy.

Egbert Zojer’s research team at the Institute of Solid State Physics at Graz University of Technology (TU Graz), in collaboration with colleagues from TU Vienna and the University of Cambridge, has now cracked this secret using the example of organic semiconductors, opening up new perspectives for the development of innovative materials with customized thermal properties.

The team has published its findings in npj Computational Materials.