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Combinatorial problems often arise in puzzles, origami, and metamaterial design. Such problems have rare collections of solutions that generate intricate and distinct boundaries in configuration space. Using standard statistical and numerical techniques, capturing these boundaries is often quite challenging. Is it possible to flatten a 3D origami piece without causing damage? This question is one such combinatorial issue. As each fold needs to be consistent with flattening, such results are difficult to predict simply by glancing at the design. To answer such questions, the UvA Institute of Physics and the research center AMOLF have shown that researchers may more effectively and precisely respond to such queries by using machine learning techniques.

Despite employing severely undersampled training sets, Convolutional Neural Networks (CNNs) can learn to distinguish these boundaries for metamaterials in minute detail. This raises the possibility of complex material design by indicating that the network infers the underlying combinatorial rules from the sparse training set. The research team thinks this will facilitate the development of sophisticated, functional metamaterials with artificial intelligence. The team’s recent study examined the accuracy of forecasting the characteristics of these combinatorial mechanical metamaterials using artificial intelligence. Their work has also been published in the Physical Review Letters publication.

The attributes of artificial materials, which are engineered materials, are governed by their geometrical structure rather than their chemical makeup. Origami is one such metamaterial. The capacity of an origami piece to flatten is governed by how it is folded, i.e., its structure, and not by the sort of paper it is made of. More generally, the clever design enables us to accurately regulate a metamaterial’s bending, buckling, or bulging. This can be used for many different things, from satellite solar panels that unfurl to shock absorbers.

The micro-robots consist of a special kind of bacteria.

Scientists have conceived of a new way to deliver cancer-killing compounds, called enterotoxins, to tumors using bionic bacteria that are steered by a magnetic field, according to a report by Inverse.

“Cancer is such a complex disease, it’s hard to combat it with one weapon,” said Simone Schürle-Finke, a micro-roboticist at the Swiss Federal Institute of Technology in Zürich, Switzerland, and one of the authors of the new study.


Wildpixel/iStock.

These bacteria function as “micro-robots” that can hunt down and rally around a specific tumor. They then release their own naturally produced anti-cancer chemicals and shrink the tumor.

Artificial Intelligence (AI) is rapidly changing the world. Emerging technologies on a daily basis in AI capabilities have lead to a number of innovations including autonomous vehicles, self-driving flights, robotics, etc. Some of the AI technologies feature predictions on future and accurate decision-making. AI is the best friend to technology leaders who want to make the world a better place with unfolding inventions.

Whether humans agree or not, AI developments are slowly impacting all aspects of the society including the economy. However, some technologies might even bring challenges and risks to the working environment. To keep a track on AI development, good leaders head the AI world to ensure trust, reliability, safety and accuracy.

Intelligent behaviour has long been considered a uniquely human attribute. But when computer science and IT networks started evolving, artificial intelligence and people who stood by them were on the spotlight. AI in today’s world is both developing and under control. Without a transformation here, AI will never fully deliver the problems and dilemmas of business only with data and algorithms. Wise leaders do not only create and capture vital economic values, rather build a more sustainable and legitimate organisation. Leaders in AI sectors have eyes to see AI decisions and ears to hear employees perspective.

A new study by Missouri S&T researchers shows how human subjects, walking hand-in-hand with a robot guide, stiffen or relax their arms at different times during the walk. The researchers’ analysis of these movements could aid in the design of smarter, more humanlike robot guides and assistants.

“This work presents the first measurement and analysis of human arm stiffness during overground physical interaction between a robot leader and a human follower,” the Missouri S&T researchers write in a paper recently published in the journal Scientific Reports.

The lead researcher, Dr. Yun Seong Song, assistant professor of mechanical and aerospace engineering at Missouri S&T, describes the findings as “an early step in developing a robot that is humanlike when it physically interacts with a human partner.”

I’ve funded Ukraine media, the Ukraine army, and now I just funded the Ukraine navy. The navy part is extra interesting because it is “the world’s first naval fleet of drones”. That is pretty futuristic!

As Elon Musk said, “Future wars are all about the drones.”


Small and fast unmanned ships 3 russian vessels were damaged, including the Admiral Makarov, flagship of the russian Black Sea Fleet. This is the first case in history where the attack was carried out exclusively by unmanned vessels.

The result of this daring operation was incredible — russia has lost its undeniable advantage on the water. The killers of Ukrainian civilians — warships armed with missiles — became targets themselves.

Today, Ukraine starts assembling the world’s first Naval Fleet of Drones!

Aspiring bakers are frequently called upon to adapt award-winning recipes based on differing kitchen setups. Someone might use an eggbeater instead of a stand mixer to make prize-winning chocolate chip cookies, for instance.

Being able to reproduce a recipe in different situations and with varying setups is critical for both talented chefs and , the latter of whom are faced with a similar problem of adapting and reproducing their own “recipes” when trying to validate and work with new AI models. These models have applications in ranging from climate analysis to brain research.

“When we talk about data, we have a practical understanding of the digital assets we deal with,” said Eliu Huerta, scientist and lead for Translational AI at the U.S. Department of Energy’s (DOE) Argonne National Laboratory. “With an AI model, it’s a little less clear; are we talking about data structured in a smart way, or is it computing, or software, or a mix?”

Large AI networks like language models make mistakes or contain outdated information. MEND shows how to update LLMs without changing the whole network.

Large AI models have become standard in many AI applications, such as natural language processing, image analysis, and image generation. The models, such as OpenAI’s GPT-3, often have more diverse capabilities than small, specialized models and can be further improved via finetuning.

However, even the largest AI models regularly make mistakes and additionally contain outdated information. GPT-3’s most recent data is from 2019 – when Theresa May was still prime minister.

Commercial Holograms may soon get into the hand of regular consumers with the help of the biggest Hologram company called Lightfield. Holography is a technique that enables a wavefront to be recorded and later re-constructed. Holography is best known as a method of generating three-dimensional images, but it also has a wide range of other applications. In principle, it is possible to make a hologram for any type of a light field.

TIMESTAMPS:
00:00 No longer just Science Fiction.
00:45 What is a hologram?
02:28 How do these new Holograms work?
05:56 The Future of Entertainment?
08:17 Last Words.

#holograms #ai #technology

In this bonus interview for the series Science Uprising, computer scientist and AI expert Selmer Bringsjord provides a wide-ranging discussion of artificial intelligence (AI) and its capabilities. Bringsjord addresses three features humans possess that AI machines won’t be able to duplicate in his view: consciousness, cognition, and genuine creativity.

Selmer Bringsjord is a Professor of Cognitive Science and Computer Science at Rensselaer Polytechnic Institute and Director of the Rensselaer AI and Reasoning Laboratory. He and his colleagues have developed the “Lovelace Test” to evaluate whether machine intelligence has resulted in mind or consciousness.

Watch episodes of Science Uprising, plus bonus video interviews with experts from each episode at https://scienceuprising.com/.

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