Imagine a team of physicians using a neural network to detect cancer in mammogram images. Even if this machine-learning model

Quantum computers made from the same raw materials as standard computer chips hold obvious promise, but so far they’ve struggled with high error rates. That seems set to change after new research showed silicon qubits are now accurate enough to run a popular error-correcting code. The quantum computers that garner all the headlines today tend […]

In September 2020, researchers at Aalto University and VTT revealed that they had developed a high-speed nano-scale radiation

Researchers have compared the electron distribution below the oxide layer of two semiconductors. The investigation is part of an effort to develop particularly stable quantum bits - and thus, in turn, particularly efficient quantum computers.

Researchers at PSI have compared the electron distribution below the oxide layer of two semiconductors. The investigation is part of an effort to develop particularly stable quantum bits -- and thus, in turn, particularly efficient quantum computers.

If you can recognize a dog by sight, then you can probably recognize a dog when it is described to you in words. Not so for today’s artificial intelligence. Deep neural networks have become very good at identifying objects in photos and conversing in natural language, but not at the same time: there are AI…

Researchers at PSI have compared the electron distribution below the oxide layer of two semiconductors. The investigation is part of an effort to develop particularly stable quantum bits—and thus, in turn, particularly efficient quantum computers. They have now published their latest research, which is supported in part by Microsoft, in the journal Advanced Quantum Technologies.

Social robots can support teachers in, for example, individual second language lessons where gestures increase children's engagement and promote learning. They can thus relieve the pressure on overloaded classrooms. Robots, unlike other technological education, have the additional advantage of being physically present where the teaching takes place. Researcher Jan de Wit, of the Tilburg School of Humanities and Digital Sciences, defends this research for his Ph.D. on 28 January.

In a recent study published in the journal ACS Applied Nano Materials,  researchers developed a novel technique for automatically classifying the Raman spectra of twisted bilayer...

Gate set tomography used to discover and validate 2 innovations in the area of quantum computers published in

New research paves the way for large silicon-based quantum processors for real-world manufacturing and application.

Gate set tomography used to discover and validate 2 innovations published in Nature A precision diagnostic developed at

Researchers have proven that near error-free quantum computing is possible, paving the way to build silicon-based quantum devices compatible with current semiconductor manufacturing technology.

A precision diagnostic is emerging as a gold standard for detecting and describing problems inside quantum computing hardware.

Researchers have achieved a key milestone toward the development of a fault-tolerant quantum computer. They were able to demonstrate a two-qubit gate fidelity of 99.5 percent -- higher than the 99 percent considered to be the threshold for building fault-tolerant computers -- using electron spin qubits in silicon, which are promising for large-scale quantum computers as the nanofabrication technology for building them already exists.

Researchers at QuTech—a collaboration between the Delft University of Technology and TNO—have taken an important step for semiconductor spin qubits by surpassing the 99% barrier for two-qubit gate fidelity. They report on their findings in Nature on 19 January 2021 and are featured on the issue's cover. Two independent works from groups at UNSW Sydney and at RIKEN report similar results in the same issue of Nature.

Artificial intelligence helps build physical infrastructure like modular housing, skyscrapers, and factory floors. “…many problems that we wrestle with in all forms of engineering and design are very, very complex problems…those problems are beginning to reach the limits of human capacity,” says Mike Haley, the vice president of research at Autodesk. But there’s hope with…

UNSW Sydney-led research paves the way for large silicon-based quantum processors for real-world manufacturing and application.

Researchers from RIKEN and QuTech—a collaboration between TU Delft and the Netherlands Organisation for Applied Scientific Research (TNO)— have achieved a key milestone toward the development of a fault-tolerant quantum computer. They were able to demonstrate a two-qubit gate fidelity of 99.5 percent—higher than the 99 percent considered to be the threshold for building fault-tolerant computers—using electron spin qubits in silicon, which are promising for large-scale quantum computers as the nanofabrication technology for building them already exists. This study was published in Nature.

A precision diagnostic developed at the Department of Energy's Sandia National Laboratories is emerging as a gold standard for detecting and describing problems inside quantum computing hardware.

For years, intermediate measurements made it hard to quantify the complexity of quantum algorithms. New work establishes that those measurements aren’t necessary after all. The post Computer Scientists Eliminate Pesky Quantum Computations first appeared on Quanta Magazine

In a recent study published in the journal Chemistry of Materials, a group of researchers has reported an intense gradient boosting (XGBoost) framework for directing the manufacturing of carbon...

Researchers have created a method to help workers collaborate with artificial intelligence systems. In a busy hospital, a

A single blood sample from a critically ill COVID-19 patient can be analyzed by a machine learning model which uses blood plasma proteins to predict survival, weeks before the outcome, according to a new study.

Scientists have developed a new machine learning model for the discovery of genetic risk factors for diseases such as Motor Neurone Disease (MND).

Researchers have successfully demonstrated proof-of-concept of using their multimodal transistor (MMT) in artificial neural networks, which mimic the human brain. This is an important step towards using thin-film transistors as artificial intelligence hardware and moves edge computing forward, with the prospect of reducing power needs and improving efficiency, rather than relying solely on computer chips.

Most quantum computers are based on superconductors or trapped ions, but an alternative approach using ordinary atoms may have advantages

Evaluating models for natural language understanding is a hard task. While state-of-the-art models achieve human parity, they still

AI can spot antibiotic resistance as much as 24 hours faster than previous methods. That could help treat serious infections more efficiently.

Few topics divide opinions as much as COVID-19 control measures, including vaccinations. Myths, conspiracy theories, lies and misinformation

A fresh approach to generating images based on text descriptions with AI, called a diffusion model, effectively un-destroys new images into existence

Few topics divide opinions as much as COVID-19 control measures, including vaccinations. Myths, conspiracy theories, lies and misinformation

Long-term investment in the stock market refers to buying stocks whose inherent value is higher than their current

Time crystals. Microwaves. Diamonds. What do these three disparate things have in common? Quantum computing. Unlike traditional computers

Artificial intelligence can make medical care personalized, precise, cost-effective, and more effective. However, the real-life applications of Machine

Using artificial intelligence (AI) researchers have found that between 2007 and 2016 online sentiments around climate change were uniform, but this was not the case with vaccination.

Leveraging a pre-trained neural network and fine-tuning it to solve a target task is a common and effective

KI researchers have together with international collaborators completed a comprehensive international validation of artificial intelligence (AI) for diagnosing

Penn researchers found that using wearable devices, especially those on the wrist, and machine learning approaches could predict

Researchers have developed an artificial intelligence platform to analyze potentially cancerous lesions in mammography scans to determine if a patient should receive an invasive biopsy. But unlike its many predecessors, the algorithm is interpretable, meaning it shows physicians exactly how it came to its conclusions.

Researchers have completed a comprehensive international validation of artificial intelligence (AI) for diagnosing and grading prostate cancer. The study shows that AI systems can identify and grade prostate cancer in tissue samples from different countries equally well as pathologists. The results suggest AI systems are ready to be responsibly introduced as a complementary tool in prostate cancer care, researchers say.

In the first two parts of this technology.org series on Dialog Systems, we presented dialog systems from the

Thank you for joining us on “The cloud hub: From cloud chaos to clarity.” As enterprises embrace the cloud, AI and deep data analytics, existing jobs, and workplaces will go through a fundamental shift. This transformation will shape the present and future of talent. Srikantan Moorthy, executive vice president, Infosys, shares his thoughts on the…

In the first two parts of this technology.org series on Dialog Systems, we presented dialog systems from the

Flat materials that can morph into three-dimensional shapes have potential applications in architecture, medicine, robotics, space travel, and much more. But programming these shape changes requires complex and time-consuming computations. Now, researchers have developed a platform that uses machine learning to program the transformation of 2D stretchable surfaces into specific 3D shapes.

Researchers developed a holistic approach, which predicts both Li-ion storage and supercapacitive properties and hence identifies various important electrode materials that are common to both devices, may pave the way for next-generation energy storage systems. By leveraging the big-data generated by the computational pipeline, the team trains crystal graph-based machine learning models and demonstrates how this data-driven model could be helpful for the rapid discovery of potential materials from other databases.

NTT Corp., in collaboration with the University of Tokyo and RIKEN, has developed an optical fiber-coupled quantum light source. Such a light source that can produce squeezed light is considered to be a crucial component to realizing a fault-tolerant, large-scale universal optical quantum computer. To achieve a large-scale universal fault-tolerant optical quantum computer, the light source would require highly squeezed quantum noise and photon number parity that is maintained even in high-photon-number components. For instance, a squeezing level of more than 65% is required to generate time-domain multiple quantum entanglement, or two-dimensional clustered states, that can be used for large-scale quantum computation. The newly...

To many of us antibiotic-​resistant bacteria seems like a problem in the distant future. However, it is very

Researchers have developed a platform that uses machine learning to program the transformation of 2D stretchable surfaces into specific 3D shapes.

Computer simulations of clouds of atoms and molecules must always trade scale for accuracy, but a new technique shows that both are possible at once using AI and clever coding

Manufacturing artificial intelligence company Landing AI named David L. Dechow vice president of outreach and vision technology. Dechow previously served as principal vision systems architect at Integro Technologies. He is a member of the A3 Vision & Imaging Technical Advisory Board and the A3 Vision & Imaging Education Committee. David L. Dechow. Courtesy of Landing AI. "We're thrilled to have David join Landing AI and bring his hands-on expertise to helping manufacturers use cutting-edge deep learning," said Andrew Ng, founder and CEO of Landing AI. "The next era of AI is one in which companies in all industries access the benefits of AI. David's deep knowledge of machine vision and automation will help us get there." ...

A study under co-​leadership of the ETH Zurich has shown that computer algorithms can determine antimicrobial resistance of

Researchers have perfected a technique for embedding single atoms in a silicon wafer one-by-one. Their technology offers the potential to make quantum computers using the same methods that have given us cheap and reliable conventional devices containing billions of transistors.

In 2.C01 at MIT, George Barbastathis demonstrates how mechanical engineers can use their knowledge of physical systems to

Researchers from the Department of Computer Systems Engineering at Universidad Politécnica de Madrid,in collaboration with the University of Strathclyde (UK), used a deep learning approach that had previously shown promising performance in other forecasting problems, to forecast the F10.7 solar radio flux over days-ahead timescales relevant to space operations.

NASA's Curiosity rover has been exploring the Red Planet's surface for nearly a decade, with its main mission being to determine whether Mars was once habitable. While the rover's investigations have indeed confirmed that Mars was once a watery world filled with potentially life-sustaining chemistry, there's still much to learn. Curiosity's mountains of data offer an opportunity to use machine learning algorithms to investigate the planet's surface in even more detail.

A University of Melbourne-led team has perfected a technique for embedding single atoms in a silicon wafer one-by-one. Their technology offers the potential to make quantum computers using the same methods that have given us cheap and reliable conventional devices containing billions of transistors.

Scientists have demonstrated the power of artificial intelligence to predict which viruses -- like SARS-CoV-2, the virus that led to the COVID-19 pandemic -- could infect humans, which animals host them, and where they could emerge.

A collaboration between computer scientists and physicists at the University of Chicago broke through one of the key obstacles for large-scale quantum computing by figuring out how to move their control signals "inside the fridge."

The iMolecule group from Skoltech has developed an artificial intelligence-driven solution that uses data on the structure of RNA or DNA molecules to identify sites on them where interaction with potential drug candidates can occur. Knowledge of these binding sites allows pharmaceutical companies to discover new medications—including antiviral agents—in a much more focused and efficient manner. The new solution is also more accurate than prior approaches, because it accounts for how the shape assumed by a nucleic acid molecule affects which binding sites are exposed. The study came out in Nucleic Acid Research: Genomics and Bioinformatics.

Researchers developed an artificial intelligence-driven solution that uses data on the structure of RNA or DNA molecules to identify sites on them where interaction with potential drug candidates can occur. Knowledge of these binding sites allows pharmaceutical companies to discover new medications - including antiviral agents - in a much more focused and efficient manner.

The iMolecule group from Skoltech has developed an artificial intelligence-driven solution that uses data on the structure of RNA or

Prompted by the increasing prominence of artificial intelligence (AI) in society, researchers investigated public attitudes toward the ethics of AI. Their findings quantify how different demographics and ethical scenarios affect these attitudes. As part of this study, the team developed an octagonal visual metric, analogous to a rating system, which could be useful to AI researchers who wish to know how their work may be perceived by the public.

Whether for squats or sit-​ups, the software based on artificial intelligence algorithms created by the start-​up VAY alerts

MIT researchers are testing a simplified turbulence theory’s ability to model complex plasma phenomena using a novel machine-learning

Citizen scientists have helped researchers discover new types of galaxies, design drugs to fight COVID-19, and map the

Atomic environment fingerprints, or structural descriptors, are used to describe the chemical environment around a reference atom. Encoding information such as bond-lengths to neighboring atoms or coordination numbers, these fingerprints are used, for example, as inputs in machine learning approaches or to eliminate redundant structures in structural searches  

A Case Western Reserve University-led team of scientists has used Artificial Intelligence (AI) to identify which patients with

Quantum computing is expected to revolutionize a broad swathe of industries. But as the technology edges closer to commercialization, what will the earliest use cases be? Quantum computing is still a long way from going mainstream. The industry had some significant breakthroughs in 2021 though, not least IBM’s unveiling of the first processor to cross […]

When the coronavirus crisis erupted in 2020, it became apparent that the medical emergency was accompanied by severe shortages, especially in some medical devices.

Warnings have emerged about the unreliability of the metrics used to detect whether an audio perturbation designed to fool AI models can be perceived by humans. Researchers show that the distortion metrics used to detect intentional perturbations in audio signals are not a reliable measure of human perception, and have proposed a series of improvements. These perturbations, designed to be imperceptible, can be used to cause erroneous predictions in artificial intelligence. Distortion metrics are applied to assess how effective the methods are in generating such attacks.

Totaling 4,233 universe simulations, millions of galaxies and 350 terabytes of data, a new release from the CAMELS project is a treasure trove for cosmologists. CAMELS—which stands for Cosmology and Astrophysics with MachinE Learning Simulations—aims to use those simulations to train artificial intelligence models to decipher the universe's properties.

Recent advances in supervised neural models enabled improvements in automatic speech recognition (ASR). In order to make ASR

AI presents a roadmap to define new materials for any need, with implications in green energy and waste

According to a 2009 study, U.S. adults look at weather forecasts nearly 300 billion times a year. Reliable forecasts can predict hazardous weather―such as blizzards, hurricanes, and flash floods―as early as 9–10 days before the event. Estimates value these forecasts at $31.5 billion per year.

All living organisms use proteins, which encompass a vast number of complex molecules. They perform a wide array of functions, from allowing plants to use solar energy for oxygen production to helping your immune system fight against pathogens to letting your muscles perform physical work. Many drugs are also based on proteins.

To make fusion energy a viable resource for the world's energy grid, researchers need to understand the turbulent motion of plasmas: a mix of ions and electrons swirling around in reactor vessels. The plasma particles, following magnetic field lines in toroidal chambers known as tokamaks, must be confined long enough for fusion devices to produce significant gains in net energy, a challenge when the hot edge of the plasma (over 1 million degrees Celsius) is just centimeters away from the much cooler solid walls of the vessel.

Researchers in the UK and China have developed an artificial intelligence (AI) model that can diagnose COVID-19 as

Reasoning and creativity challenge the USC artificial intelligence researchers who are working to improve human-centric AI. Common sense

An interdisciplinary team led by USC computer science researchers is creating a faster, more reliable and more accessible

The DarkNPS algorithm has predicted the formulas of millions of potential drugs -- Read more on ScientificAmerican.com

Is that really you on your driver’s licence or passport photo? That is the question facing border security

When successfully implemented in healthcare, Machine Learning can impact the lives of patients and clinicians in a significant

When a master chef develops a new cake recipe, she doesn’t try every conceivable combination of ingredients to

While COVID-19 forced an emergency transformation to online learning at universities, learning how to teach efficiently and effectively online using different platforms and tools is a positive addition to education and is here to stay.

Ultra-precise lasers can be used for optical atomic clocks, quantum computers, power cable monitoring, and much more. But all lasers make noise, which researchers from DTU Fotonik want to minimize using machine learning.

AI has tremendous applications in healthcare and beyond. It could make our existing systems faster, more efficient, and

Machine learning (ML) can take over a lot of manual tasks that we do, such as recruitment, selling

"Google and other research teams have proved that quantum computers can operate faster than a regu-lar machine, but in 2022 we might actually see them tackle useful problems

Superconducting uranium ditelluride is a promising material in the race to create fault-tolerant quantum computers, but physicists are rethinking how superconductivity arises in the material in light of puzzling new experimental evidence.

Machine learning algorithms have had tremendous success in various fields, including speech recognition, image classification, machine translation, etc.

Recent large deep learning models trained with big data have made significant breakthroughs in natural language understanding; however,

Researchers have successfully applied machine learning to guide the synthesis of new nanomaterials, eliminating barriers associated with materials discovery. The highly trained algorithm combed through a defined dataset to accurately predict new structures that could fuel processes in clean energy, chemical and automotive industries.

When Hongzhi Gao was young, he lived with his family in Gansu, a province located in the center of northern China by the Tengger Desert. Thinking back to his childhood, he recalls the constant, steady wind of dirt outside their house, and that during most months of the year it didn’t take more than a…

It’s Monday morning of some week in 2050 and you’re shuffling into your kitchen drawn by the smell

Artificial Intelligence holds great potential. But only if it is used correctly. Theoretically, of AI is used incorrectly,

A recent paper on arXiv.org shows that Al can be used for the task of facial emotion recognition.

Sound engineers used custom-made artificial intelligence to strip out unwanted audio from footage of the band in the studio

Author(s): Philip BallAn experiment shows that errors in quantum computation can be repeatedly corrected on the fly. [Physics 14, 184] Published Thu Dec 23, 2021

Technologies that take advantage of novel quantum mechanical behaviors are likely to become commonplace in the near future. These may include devices that use quantum information as input and output data, which require careful verification due to inherent uncertainties. The verification is more challenging if the device is time dependent when the output depends on past inputs. For the first time, researchers using machine learning dramatically improved the efficiency of verification for time-dependent quantum devices by incorporating a certain memory effect present in these systems.