Category: AI

A set of Veeve AI-powered cars at the Albertsons store in Eagle, Idaho. Photo: Don Day/BoiseDev

By Don Day

At the Albertsons store in Eagle, shoppers are trying out a new technology that could mark a significant change to the in-store shopping experience: a high-tech cart.

The shopping cart is a fundamental part of the experience of going to the grocery store and has been for decades. But other than a place for little ones to sit, the invention hasn’t changed much over the decades.

Seattle-based startup Veeve and Boise-based Albertsons Companies hope to change that. Albertsons is trialing Veeve’s AI-powered shopping cart, complete with a large iPad-style screen, scale, cameras, and other gadgets designed to transform the shopping experience.

By Arthur Cole

AI thrives on data. The more data it can access, and the more accurate and contextual that data is, the better the results will be.

The problem is that the data volumes currently being generated by the global digital footprint are so vast that it would take literally millions, if not billions, of data scientists to crunch it all — and it still would not happen fast enough to make a meaningful impact of AI-driven processes.

It’s like precrime, for psychedelics.

By  Brad Bergan

New drugs are created all the time.

And many are extremely dangerous.

This is why researchers trained computers to predict what designer drugs will emerge onto the scene before they hit the market, according to a recent study published in the journal Nature Machine Intelligence.

With highly-addictive drugs flooding regions throughout the U.S., this program could save countless lives. But it could also unlock an entire “dark matter” world of unknown psychoactive possibilities.

Aichi Cancer Center and Fujitsu jointly developed new AI solution to support physicians in efficiently choosing medical treatment

Aichi Cancer Center and Fujitsu have announced the development of an artificial intelligence (AI) based solution able to select effective medical treatment from a wide range of drugs based on patients’ individual cancer types and various genomic variants.

The effectiveness of the new solution has been verified in clinical trials by physicians at Aichi Cancer Center.

With current cancer genomic medicine in Japan, treatment plans are considered based on the patients’ unique circumstances, including the type of cancer and the actionable genomic variants detected in cancer cells.

Quris, an artificial intelligence (AI) company operating in the pharmaceutical space, launched this week and announced a $9 million in seed funding.

By MAAYAN JAFFE-HOFFMAN 

Chips from Quris’ AI technology.(photo credit: COURTESY QURIS)AdvertisementRobert Langer, the co-founder of Moderna and a lauded MIT professor, said, “We are at the tipping point of the modernization of drug discovery” and that the “Quris platform could be a significant value to pharma companies and the health of society at large.”

Langer is a member of the scientific advisory board of Quris, which officially launched this week and announced $9 million in seed funding to support its efforts.Nobel laureate Aaron Ciechanover is the chairman of the company’s scientific advisory board.

By Julie Kiefer
An artificial intelligence-based technology rapidly diagnoses rare disorders in critically ill children with high accuracy, according to a report by scientists from University of Utah Health and Fabric Genomics, collaborators on a study led by Rady Children’s Hospital in San Diego. The benchmark finding, published in Genomic Medicine, foreshadows the next phase of medicine, where technology helps clinicians quickly determine the root cause of disease so they can give patients the right treatment sooner.

“This study is an exciting milestone demonstrating how rapid insights from AI-powered decision support technologies have the potential to significantly improve patient care,” says Mark Yandell, co-corresponding author on the paper. Yandell is a professor of human genetics and Edna Benning Presidential Endowed Chair at U of U Health, and a founding scientific advisor to Fabric Genomics.

Worldwide, about 7 million infants are born with serious genetic disorders each year. For these children, life usually begins in intensive care. A handful of NICUs in the U.S., including at U of U Health,are now searching for genetic causes of disease by reading, or sequencing, the 3 billion DNA letters that make up the human genome. While it takes hours to sequence the whole genome, it can take days or weeks of computational and manual analysis to diagnose the illness.

For some infants, that is not fast enough, Yandell says. Understanding the cause of the newborn’s illness is critical for effective treatment. Arriving at a diagnosis within the first 24 to 48 hours after birth gives these patients the best chance to improve their condition. Knowing that speed and accuracy are essential, Yandell’s group worked with Fabric to develop the new Fabric GEM algorithm, which incorporates AI to find DNA errors that lead to disease.

AI Collaboration Proves NFTs Aren’t Just Capable of Communicating Directly with Humans, but Also with Each Other

This week, Avastars, the first fully on-chain profile picture NFT project, collaborated with Alethea AI, creator of the intelligent NFT (iNFT) category, to stage the first conversation between iNFTs.

While Alethea AI’s technology was recently used to generate a conversation between an iNFT and a human, namely Avastar #102, Pandora, and NFT42 Founder Jimmy McNelis, this new collaboration marks the first time that Alethea AI’s technology has been used to enable iNFTs to communicate directly with each other.

Avastars #101, Salvatar, and #102, Pandora, converse with one another in a new collaboration between Avastars and Alethea AI.

Collaboration between Avastars and Alethea AI marks the first conversation between intelligent NFTS (iNFTS.)

Nanowear, a hospital-at-home and remote diagnostic platform informed by proprietary cloth nanotechnology and AI, today announced that it received its third FDA 510(k) clearance and first software-only clearance as an end-to-end digital platform, illustrating unique capabilities available to enterprise customer channels across a broad spectrum of diagnostic and monitoring verticals.

This clearance enables Nanowear to implement standalone AI and deep learning algorithms that will inform remote diagnoses as Software-as-a-Medical Device (SaMD). Future clearances include, but are not limited to, diagnosing or monitoring of hypertension, COPD, sleep apnea, worsening heart failure and post-surgical recovery.

The new artificial intelligence tool has already led to the discovery of four new materials.

Researchers at the University of Liverpool have created a collaborative artificial intelligence tool that reduces the time and effort required to discover truly new materials.

Reported in the journal Nature Communications, the new tool has already led to the discovery of four new materials including a new family of solid state materials that conduct lithium. Such solid electrolytes will be key to the development of solid state batteries offering longer range and increased safety for electric vehicles. Further promising materials are in development.

The tool brings together artificial intelligence with human knowledge to prioritize those parts of unexplored chemical space where new functional materials are most likely to be found.

Discovering new functional materials is a high-risk, complex, and often long journey as there is an infinite space of possible materials accessible by combining all of the elements in the periodic table, and it is not known where new materials exist.

The new AI tool was developed by a team of researchers from the University of Liverpool’s Department of Chemistry and Materials Innovation Factory, led by Professor Matt Rosseinsky, to address this challenge.

By NAVEEN JOSHI

Genomic diagnostic is an area that can benefit hugely from the capabilities of AI. The involvement of AI in healthcare can potentially be beneficial in genetic diagnostics.

Ironically, rare diseases are fairly common in the world, with nearly half a billion people suffering from some or the other kind of lesser-known ailments. Such diseases can be notoriously tricky to diagnose as standard clinical tests may not uncover several underlying details regarding them. Additionally, almost all rare diseases are caused due to genetic issues in individuals. So, fast and accurate gene-based ailment diagnostics is the need of the hour in healthcare today. However, according to a study, such diseases can take nearly five years on average to be diagnosed accurately, meaning that almost a third of the children suffering from one or the other type of rare genetic disorder will pass away before they even turn five.