Lifeboat Foundation

Bias in AI systems is proving to be a major stumbling block in efforts to more broadly integrate the technology into our society.

A new initiative that will reward researchers for finding any prejudices in AI systems could help solve the problem.

The effort is modeled on the bug bounties that software companies pay to cybersecurity experts who alert them of any potential security flaws in their products.

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Topological materials are a special kind of material that have different functional properties on their surfaces than on their interiors. One of these properties is electrical. These materials have the potential to make electronic and optical devices much more efficient or serve as key components of quantum computers. But recent theories and calculations have shown that there can be thousands of compounds that have topological properties, and testing all of them to determine their topological properties through experiments will take years of work and analysis. Hence, there is a dire need for faster methods to test and study topological materials.

A team of researchers from MIT, Harvard University, Princeton University, and Argonne National Laboratory proposed a new approach that is faster at screening the candidate materials and can predict with more than 90 percent accuracy whether a material is topological or not. The traditional way of solving this problem is quite complicated and can be explained as follows: Firstly, a method called density functional theory is used to perform initial calculations, which are then followed by complex experiments that involve cutting a piece of material to atomic-level flatness and probing it with instruments under high vacuum.

The new proposed method is based on how the material absorbs X-rays, which is different from the old methods, which were based on photoemissions or tunneling electrons. There are certain significant advantages to using X-ray absorption data, which can be listed as follows: Firstly, there is no requirement for expensive lab apparatus. X-ray absorption spectrometers are used, which are readily available and can work in a typical environment, hence the low cost of setting up an experiment. Secondly, such measurements have already been done in chemistry and biology for other applications, so the data is already available for numerous materials.

More and more companies and scientists are working to equip contact lenses with applications that not long ago still seemed like science fiction, such as the ability to record videos or diagnose and even treat diseases. Mojo Vision, an American startup, is one company that has been improving its prototypes since 2015. It is currently developing an ambitious project involving augmented reality lenses that, in addition to correcting your vision, will let you consult all kinds of information, from the trails on a ski slope to your pace when you run, all through microLED displays the size of a grain of sand.

“In the short term, it sounds like a futuristic idea, but 20 years ago we couldn’t even imagine many of the technological advances that we have today,” says Ana Belén Cisneros del Río, deputy dean of the College of Opticians-Optometrists in the Spanish region of Castilla y León, of the Mojo Vision project. However, Daniel Elies, a specialist in cornea, cataract and refractive surgery and medical director of the Institute of Ocular Microsurgery (IMO) Miranza Group in Madrid, does not believe that this type of contact lens will become part of everyday life anytime soon, “especially due to cost issues.”

One of the companies interested in manufacturing augmented reality contacts is Magic Leap. Sony, for its part, applied a few years ago for a patent for lenses that can record videos, and Samsung did the same for lenses equipped with a camera and a display that projects images directly into the user’s eye. Some researchers are trying to create robotic lenses that can zoom in and out with the blink of an eye, and yet others are working on night vision contact lenses, which could be useful in military applications.

Their research was published Sept. 26 in the journal Optics Express.

The five dimensions in question aren’t new or hidden spatial dimensions. Instead, a team headed by Tingting Wu, a Ph.D. student in the McKelvey School of Engineering’s imaging sciences program, was able to design a system that could tell the orientation of a molecule in 3D space as well as its position in 2D: five parameters from a single, noisy, pixelated image.

Anthony Levandowski, the engineer at the heart of the Uber/Google lawsuit, is serious about his artificial intelligence religion.

Optimus, also known as Tesla Bot, is a general-purpose robotic humanoid under development by Tesla. The first prototype was announced at the company’s Artificial Intelligence (AI) Day event in September 2022!

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“China was leading the global recovery after the Covid-19 pandemic and accounted for half of worldwide robot installations in 2021,” said Marina Bill, President of the International Federation of Robotics. “Growth is strong across all industries with electrical and electronics being the dominant sector – up 30% to 81,600 installations. The automotive industry also showed a strong recovery. This was mainly driven by electric vehicle manufacturing in China. It rose by 89% in 2021 with 50,700 installations.”

Chinese government supports robotic automation

In China aging population’s demographics causes shortage of labor and drives the growth of robotic automation. The continued robotization of industries has been announced earlier this year by the government. The Five-Year plan for the robotics industry, released by the Ministry of Industry and Information Technology (MIIT) in Beijing, focuses on promoting innovation — making China a global leader of robot technology and industrial advancement.

Stability AI, the venture-backed startup behind the text-to-image AI system Stable Diffusion, is funding a wide-ranging effort to apply AI to the frontiers of biotech. Called OpenBioML, the endeavor’s first projects will focus on machine learning-based approaches to DNA sequencing, protein folding and computational biochemistry.

The company’s founders describe OpenBioML as an “open research laboratory” — and aims to explore the intersection of AI and biology in a setting where students, professionals and researchers can participate and collaborate, according to Stability AI CEO Emad Mostaque.

“OpenBioML is one of the independent research communities that Stability supports,” Mostaque told TechCrunch in an email interview. “Stability looks to develop and democratize AI, and through OpenBioML, we see an opportunity to advance the state of the art in sciences, health and medicine.”