In Huang’s vision of AI’s future, these models require more computing power from chips, not less.
Category: robotics/AI – Page 43
Which of these technologies excites you the most? CHAPTERS:00:00 20 Space Megastructures That Will Transform Our Future01:15:51 15 Robotics TechnologiesThat…
NVIDIA has just unveiled the Isaac GR00T N1, a foundation model that is revolutionizing humanoid robotics. This AI-driven system can learn tasks, make decisions, and adapt like never before!
At GTC 2025, NVIDIA CEO Jensen Huang revealed the Isaac GR00T N1, a next-generation AI model designed to train humanoid robots with unprecedented efficiency. It uses a dual-system approach—one for instant reactions and another for strategic thinking. NVIDIA also introduced Newton, a physics engine developed in collaboration with Google DeepMind and Disney, aiming to enhance robotic motion.
Additionally, NVIDIA’s Isaac GR00T Blueprint enables large-scale training with synthetic data. In just 11 hours, the system generated over 780,000 training examples, drastically improving robot accuracy. These advancements could reshape industries by making humanoid robots more intelligent and useful in real-world applications.
What do you think of NVIDIA’s latest robotics breakthrough? Let us know in the comments! Do not forget to like, subscribe, and turn on notifications for more updates on AI and robotics.
#NVIDIA #AI #Robotics.
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Artificial Intelligence and the “Great Machine” Problem: Avoiding Technology Oversimplification in Homeland Security and Emergency Management
Posted in cybercrime/malcode, education, robotics/AI | Leave a Comment on Artificial Intelligence and the “Great Machine” Problem: Avoiding Technology Oversimplification in Homeland Security and Emergency Management
This research note deploys data from a simulation experiment to illustrate the very real effects of monolithic views of technology potential on decision-making within the Homeland Security and Emergency Management field. Specifically, a population of national security decision-makers from across the United States participated in an experimental study that sought to examine their response to encounter different kinds of AI agency in a crisis situation. The results illustrate wariness of overstep and unwillingness to be assertive when AI tools are observed shaping key situational developments, something not apparent when AI is either absent or used as a limited aide to human analysis. These effects are mediated by levels of respondent training. Of great concern, however, these restraining effects disappear and the impact of education on driving professionals towards prudent outcomes is minimized for those individuals that profess to see AI as a full viable replacement of their professional practice. These findings constitute proof of a “Great Machine” problem within professional HSEM practice. Willingness to accept grand, singular assumptions about emerging technologies into operational decision-making clearly encourages ignorance of technological nuance. The result is a serious challenge for HSEM practice that requires more sophisticated solutions than simply raising awareness of AI.
Keywords: artificial intelligence; cybersecurity; experiments; decision-making.
Nvidia founder Jensen Huang kicked off the company’s artificial intelligence developer conference on Tuesday by telling a crowd of thousands that AI is going through “an inflection point.”
At GTC 2025—dubbed the “Super Bowl of AI”—Huang focused his keynote on the company’s advancements in AI and his predictions for how the industry will move over the next few years. Demand for GPUs from the top four cloud service providers is surging, he said, adding that he expects Nvidia’s data center infrastructure revenue to hit $1 trillion by 2028.
Huang’s highly anticipated announcement revealed more details around Nvidia’s next-generation graphics architectures: Blackwell Ultra and Vera Rubin—named for the famous astronomer. Blackwell Ultra is slated for the second half of 2025, while its successor, the Rubin AI chip, is expected to launch in late 2026. Rubin Ultra will take the stage in 2027.
The rapid evolution of artificial intelligence (AI) is poised to create societal transformations. Indeed, AI is already emerging as a factor in geopolitics, with malicious non-state actors exploiting its capabilities to spread misinformation and potentially develop autonomous weapons. To be sure, not all countries are equal in AI, and bridging the “AI divide” between the Global North and South is vital to ensuring equal representation while addressing regulatory concerns and the equitable distribution of benefits that can be derived from the technology.
Most G20 members have established comprehensive national AI strategies, notably technology giants like the United States, United Kingdom, China, and countries of the European Union. Global South nations such as Brazil, Argentina, and India, despite economic constraints, are demonstrating progress in leveraging AI in areas like social services and agriculture. Future strategies must anticipate emerging threats like Generative AI (GenAI) and Quantum AI, prioritising responsible governance to mitigate biases, inequalities, and cybersecurity risks.
The Top 10 Emerging Technologies of 2024 report highlights the technologies set to positively impact society within the next three to five years.
Organelles in cells were originally often independent cells, which were incorporated by host cells and lost their independence in the course of evolution. A team of biologists headed by Professor Dr. Eva Nowack at Heinrich Heine University Düsseldorf (HHU) are examining the way in which this assimilation process occurs and how quickly. They now describe their findings about an intermediate stage in this process in Science Advances.
Eukaryotic cells contain a large number of functional sub-units, so-called organelles. They perform important functions within the cell. Some organelles were independent, single-celled organisms at some point in the past. They were then taken up by a cell and have evolved over time in symbiosis with the host cell.
These “endosymbionts” lost their ability to function autonomously in the process. One well-known example of this type of organelle is the mitochondrion, which evolved from a bacterium.
Existing research indicates that the accuracy of a Parkinson’s disease diagnosis hovers between 55% and 78% in the first five years of assessment. That’s partly because Parkinson’s sibling movement disorders share similarities, sometimes making a definitive diagnosis initially difficult.
Although Parkinson’s disease is a well-recognized illness, the term can refer to a variety of conditions, ranging from idiopathic Parkinson’s, the most common type, to other movement disorders like multiple system atrophy, a Parkinsonian variant; and progressive supranuclear palsy. Each shares motor and nonmotor features, like changes in gait, but possesses a distinct pathology and prognosis.
Roughly one in four patients, or even one in two patients, is misdiagnosed.
