15 robots powered by AI and their insane demo videos

 Elon Musk, recently showcased his latest creation, the Optimus Gen-1. Following advancements in large language models, it seems the race to create the most powerful AI-backed robot is intensifying. The Tesla Optimus account shared a demo video of Optimus Gen-1, which triggered a conversation around AI robots.

Robotics and its confluence with Artificial Intelligence are fascinating domains. In the last couple of years, numerous robotics companies around the world have experimented with AI to showcase their stellar robots. These robots are not only scientific marvels but also can be potential assistants for humans, as seen in popular Hollywood sci-fi movies. Here’s a look at some recent stellar robotics demonstrations, similar to Musk’s Optimus Gen-1.

International Research Awards on Mechanics of Functional Materials and Structures

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Mechanical engineering Prof. Ryan Rosario earns $200,000 NSF award

Two-year grant will fund Rosario and two student-researchers as they study potential models for predicting, and preventing, tendon and ligament failure

Ryan Rosario, assistant professor of mechanical engineering, was recently awarded his first National Science Foundation (NSF) grant for his research on the mechanics of ligament and tendon failure. In addition to providing funding for laboratory equipment and supplies, the two-year, $200,000 award also will provide support for student-researchers to work alongside Rosario on the project. This is Rosario’s first NSF award as a principal investigator.

“I feel excited, proud, and validated that a panel of experts in my field chose me and my project for this honor,” Rosario says.

Rosario’s study will look at the different components that make up ligaments and tendons—the tissues that connect bone to bone, and muscle to bone, respectively—and the potential role each component plays in the failure of these tissues. “We will be utilizing a simulation model, camera-based measurement system, and universal mechanical testing system to analyze sheep tendons and get a better understanding of how failure might initiate. This, in turn, could give us an idea of how we can potentially prevent that failure—and related injuries—from happening in humans,” Rosario says

The study also will be one of the first of its kind: “The way that I’ll be thinking about tendon and ligament mechanics, and measuring their properties, is different from what any other researcher is doing,” Rosario says. “By using a computational tool to separate out the different components, I’ll be taking the first steps I’ve seen to understand the whole tissue as two separate component parts rather than one homogenous structure.”

During the first half of this summer, Rosario will be working with two student-researchers—Jacob Hinnes ’26 and Jack Blackmar ’26—to complete the designing and building of the simulation model and measurement system, which was initiated last year with the help of Hinnes and Will Sherwood ’25. Rosario, Hinnes, and Blackmar will spend the remainder of the summer conducting test runs and collecting preliminary data.

“It’s amazing to be able to conduct lab research with a professor as a second- and third-year undergraduate student,” says Hinnes, who has a major in integrative engineering with a focus in bioengineering. “I’ve gained a lot of experience: tendon dissection, proper lab technique and maintenance, 3D modeling and printing, and team collaboration with my peers.” Rosario also will be using his NSF funding to send his student-researchers to scientific conferences to present their work. “Giving me the opportunity to put these on my resume at my age truly sets Lafayette apart from other institutions,” Hinnes says.

For Rosario, the most rewarding part of the research process, he says, is working with the students and seeing them grow as independent researchers: “I want to be able to instill that sense of excitement for discovery—the understanding that science isn’t some inaccessible thing that only certain people can do. [Participating in research] gives students confidence in their own ability, intellect, and problem-solving skills, which is an experience that can sometimes be hard to get from courses.”

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Artificial intelligence at Bosch for a better future

 This year, the Bosch Tech Compass, a representative survey on the acceptance of technologies, examined the topic of artificial intelligence (AI) in seven different countries. This focus topic takes a look at the key findings of the analysis, while also highlighting how Bosch is already using AI to make the world a better place

The world is not well prepared for AI! Or is it?

Since the epic victory of a chess computer over world champion Garri Kasparov in 1997, the development of artificial intelligence has accelerated rapidly. Today, this technology is making inexorable inroads into our everyday lives. AI is an opportunity for everyone and it is also a key technology for Bosch. The company has been working on AI-based products and methods for years. In 2020, Bosch introduced guidelines for the use of artificial intelligence in the development of products and services. The aim: to create intelligent and trustworthy AI products that live up to the motto of “Invented for life” and combine innovation with social responsibility.

In the past five years, Bosch has filed patent applications for more than 1,000 AI inventions making it one of the leading AI patent applicants in Europe. Machine learning is also becoming increasingly important in development and production. All Bosch products and solutions now contain AI or have been developed or produced with the help of AI. At the end of 2023, the company's internal AI search engine "AskBosch" went live, giving associates very fast access to a wide variety of data sources, such as those distributed on the intranet, via natural language queries.

Bosch was quick to recognize the potential of AI for many everyday products. The Series 8 oven, for example, is constantly learning to improve baking results. The oven has sensors that collect anonymized data on baking and roasting processes — such as temperature, humidity and settings — and send it to the cloud. There, artificial intelligence analyzes the user's preferences and calculates the optimal cooking time for each dish. This creates a database that ultimately benefits all households with networked Bosch ovens. Half-cooked or burnt baking and roasting results are now a thing of the past. This intelligent technology has already convinced food influencer Saliha “Sally” Özcan of the YouTube channel “Sally’s World” that Bosch can use AI to make the world a better place.

For Bosch, a better world always means a safer world. This is especially true in road traffic, for example in a scenario that no driver would want to happen: a ball rolls onto the road, and in the next moment, children could run onto the road without paying attention to the traffic. A human driver can assess this situation using contextual knowledge. Current assisted and automated driving systems, however, have yet to learn how. Bosch is investigating how generative AI can be used to improve automated driving functions. The company is also working with Microsoft to find solutions for how future cars can use generative to better assess critical traffic situations and react accordingly to better protect road users. In addition, Bosch researchers have already developed a software prototype for test drives with highly automated vehicles as part of the joint “KIsSME” project. With the help of artificial intelligence, critical traffic situations can be distinguished from non-critical ones, recognized, stored, and analyzed.




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Data centres: Balancing AI needs with sustainability

 

If AI has worsened an energy and emissions problem, it may also be helping solve it in a proverbial double-edged sword. In particular, the AI factor could help in data centre management, which requires sensors and cooling systems

New Delhi: In 2016, Facebook flipped the switch at its Luleå data centre facility on the edge of the Arctic Circle in northern Sweden, utilising freezing cold arctic air and hydroelectric plants as renewable power sources. Microsoft’s Project Natick shifted data centres underwater, but after nine years of trying 117 feet below the North Sea, the company shut down that experiment last summer.

The rise of generative artificial intelligence (AI) experiences added to the demand for more computing power and data processing. Khalid Wani, senior director for sales in India at Western Digital, told HT, “AI is now essential in data centre operations through machine learning and predictive analytics. It’s for real-time infrastructure monitoring, proactive issue identification, resource optimisation, and equipment failure prediction.”

Statista Market Insights research estimated the global generative AI market would be worth $207 billion by 2030, up from $44.89 billion in 2023.

If AI has worsened an energy and emissions problem, it may also be helping solve it in a proverbial double-edged sword. In particular, the AI factor could help in data centre management, which requires sensors and cooling systems. Wani added that a reduction in errors means more efficiency because of “reduced downtime and enhanced security via threat detection.”

Data centres could be cooled using various methods, including perimeter cooling, close-coupled cooling, and newer direct liquid cooling (DLC) methods. According to the Uptime Institute’s 2023 Global Data Center Survey, 56% of 1,575 surveyed data centres globally still relied on perimeter cooling, but they believed the continued increase in silicon power would necessitate a switch to DLC methods.

Newer generation AI-optimised chips played a crucial role. Google confirmed in its latest sustainability report that Trillium, its sixth-generation Tensor Processing Unit (TPU), was 67% more energy-efficient than its predecessor.

Kate Brandt, chief sustainability officer at Google, said, “A Google-owned and operated data centre is, on average, approximately 1.8 times as energy efficient as a typical enterprise data centre. In 2023, the average annual power usage effectiveness for our data centres was 1.10.”

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Diving Deep Into Quantum Computing: Computing With Quantum Mechanics

Quantum mechanics enables us to build computers that are, in some ways, much more powerful than classical computers. Small, gated quantum computers and experimental quantum computers already exist, but the world might soon see the arrival of quantum computers capable of demonstrating quantum advantage over their classical counterparts. When that happens, it will leave little time for the lengthy process of migrating to new cryptographic algorithms, so it’s best to plan ahead and consider post-quantum cryptography now.

In this entry, the second on post-quantum cryptography, we delve into the history of quantum computing, its foundation in quantum mechanics, and the kind of complex problems quantum computers will be able to solve.

Brief history of computing

To better comprehend quantum mechanics, it helps to understand how mathematics evolved over time, and with it, our understanding of nature.

Early in history, people’s mathematical understanding of the world was simpler than now: at first, only natural numbers (1, 2, 3, 4, 5, etc.) were used to count. Later, negative numbers (…, -3, -2, -1, 0, 1, 2, 3, ….) were incorporated as well. Eventually, multiplication and division were needed, and these required the concept of fractions created from positive integers. These were classified as rational numbers.

Rational numbers serve well in many practical applications of physics or classical mechanics, where the goal is to measure or approximate something to a sufficient degree of accuracy. However, when the ancient Egyptians wanted to calculate the area of a circle, they tried using fractions in their formula, but the results were not quite accurate. Further examination revealed that a certain number, which will eventually be called pi (symbolized by π and has the value of 3.14159…), can instead be used for this operation. This sparked the idea that there are numbers that cannot be represented by fractions. We call such as real numbers because there’s a tacit assumption that they describe how nature works. So, for a long time, people believed that the world exists on a continuum of scales.

However, the advent of nuclear physics in the late 19th and early 20th centuries started to challenge this view. The smallest unit of matter was initially thought to be the atom, thus it was so named — the ancient Greek “atomos” translates to “indivisible,” or more literally “uncuttable.” In the late 19th century, however, Sir Joseph John Thompson discovered a sub-atomic particle, the electron, and proposed the ‘plum pudding’ model of an atom. In the early 20th century, Ernest Rutherford first theorized the existence of protons and neutrons in an atom’s nucleus, a fact then proven by James Chadwick. Rutherford proposed a model of the atom where the electrons orbited the nucleus like planets around the sun.


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