In the elegant quiet of the café at the Church of Sweden, a narrow Gothic-style building in Midtown Manhattan, Daniel Cohen is taking a break from explaining genetics. He moves toward the creaky piano positioned near the front door, sits down, and plays a flowing, flawless rendition of "Over the Rainbow." If human biology is the scientific equivalent of a complicated score, Cohen has learned how to navigate it like a virtuoso. Cohen was the driving force behind Généthon, the French laboratory that in December 1993 produced the first-ever "map" of the human genome. He essentially introduced Big Data and automation to the study of genomics, as he and his team demonstrated for the first time that it was possible to use super-fast computing to speed up the processing of DNA samples.

LONDON, May 3 (Reuters) - Over the last two years a series of unexpected events has scrambled global supply chains. Coronavirus, war in Ukraine, Brexit and a container ship wedged in the Suez Canal have combined to delay deliveries of everything from bicycles to pet food. In response, a growing group of startups and established logistics firms has created a multi-billion dollar industry applying the latest technology to help businesses minimize the disruption. Interos Inc, Fero Labs, KlearNow Corp and others are using artificial intelligence and other cutting-edge tools so manufacturers and their customers can react more swiftly to supplier snarl-ups, monitor raw material availability and get through the bureaucratic thicket of cross-border trade. The market for new technology services focused on supply chains could be worth more than $20 billion a year in the next five years, analysts told Reuters.

LONDON – Over the last two years a series of unexpected events has scrambled global supply chains. Coronavirus, war in Ukraine, Brexit and a container ship wedged in the Suez Canal have combined to delay deliveries of everything from bicycles to pet food. In response, a growing group of startups and established logistics firms has created a multibillion dollar industry applying the latest technology to help businesses minimize the disruption. Interos Inc., Fero Labs, KlearNow Corp. and others are using artificial intelligence and other cutting-edge tools so manufacturers and their customers can react more swiftly to supplier snarl-ups, monitor raw material availability and get through the bureaucratic thicket of cross-border trade. The market for new technology services focused on supply chains could be worth more than $20 billion a year in the next five years, analysts told Reuters.

Criminals are getting smarter and the healthcare industry is no exception. In 2021 alone, the Department of Justice (DOJ) recovered more than $5.6 billion from civil fraud and false claims cases. This is the DOJ's biggest haul since 2014, but a drop in the bucket compared to the estimated $380 billion is lost every year to fraud, waste, and abuse. These numbers add up to higher premiums and out-of-pocket expenses for consumers, as well as reduced benefits or coverage. What's more, relaxed telehealth mandates put into place during the COVID-19 pandemic, the increased digitization of health, and the emergence of telehealth platforms have made it easier than ever for fraudsters to operate are all contributing to a growing problem.

The above scenario may not be the stuff of sci-fi blockbusters, but in its own waypoints to an exciting shift in the relationship between citizens and governments. To some degree, we are already seeing this transformation taking shape--government agencies using machines to crunch data, say, or to improve citizen outreach programs. In our daily lives, meanwhile, AI makes countless decisions on our behalf-- though these are rarely more urgent than what to watch on Netflix tonight. The idea that a smart network might, without prompting, take decisive action in order to save human lives, however, is potentially a very big deal. This might be a way off, but the prospect of AI-enhanced government has led to what one observer describes as "a global race among nations," with several Gulf countries--particularly Saudi Arabia and the UAE-- very much in the running.

In brief A synthetic enzyme designed using machine-learning software can break down waste plastics in 24 hours, according to research published in Nature. Scientists at the University of Texas Austin studied the natural structure of PETase, an enzyme known to degrade polymer chains in polyethylene. Next, they trained a model to generate mutations of the enzyme that work fast at low temperatures, let the software loose, and picked from the output a variant they named FAST-PETase to synthesize. FAST stands for functional, active, stable, and tolerant. FAST-PETase, we're told, can break down plastic in as little as 24 hours at temperatures between 30 and 50 degrees Celsius.

One of the first steps in many text-based social science studies is to retrieve documents that are relevant for the analysis from large corpora of otherwise irrelevant documents. The conventional approach in social science to address this retrieval task is to apply a set of keywords and to consider those documents to be relevant that contain at least one of the keywords. But the application of incomplete keyword lists risks drawing biased inferences. More complex and costly methods such as query expansion techniques, topic model-based classification rules, and active as well as passive supervised learning could have the potential to more accurately separate relevant from irrelevant documents and thereby reduce the potential size of bias. Yet, whether applying these more expensive approaches increases retrieval performance compared to keyword lists at all, and if so, by how much, is unclear as a comparison of these approaches is lacking. This study closes this gap by comparing these methods across three retrieval tasks associated with a data set of German tweets (Linder, 2017), the Social Bias Inference Corpus (SBIC) (Sap et al., 2020), and the Reuters-21578 corpus (Lewis, 1997). Results show that query expansion techniques and topic model-based classification rules in most studied settings tend to decrease rather than increase retrieval performance. Active supervised learning, however, if applied on a not too small set of labeled training instances (e.g.

The Covid-19 pandemic has led to infodemic of low quality information leading to poor health decisions. Combating the outcomes of this infodemic is not only a question of identifying false claims, but also reasoning about the decisions individuals make. In this work we propose a holistic analysis framework connecting stance and reason analysis, and fine-grained entity level moral sentiment analysis. We study how to model the dependencies between the different level of analysis and incorporate human insights into the learning process. Experiments show that our framework provides reliable predictions even in the low-supervision settings.

Artificial Intelligence has managed to infiltrate many industries and sectors, including the defence sector and different military operations. Artificial Intelligence is used by almost all nations for managing the defence sector and military operations. Currently, a huge investment is made in this niche to further strengthen the defence sector of any country. Here are seven roles of artificial intelligence in the defence sector. Without an actual war, how would one teach the soldiers about actual war life situations?

Mental health and prayer apps have some of the worst privacy protections, a Mozilla study claims, finding they'track and share' users intimate thoughts and feelings. The findings, released to coincide with May's Mental Health Awareness Month, were published as part of the annual Mozilla'Privacy Not Included' guide. The researchers examined privacy and security practices for 32 mental health and prayer apps on iOS and Android, including Talkspace, Better Help, Calm and Glorify. The six worst offenders, according to Mozilla, that is those with the very worst privacy and security, were Better Help, Youper, Woebot, Better Stop Suicide, Pray.com, and Talkspace. 'Their flaws entail incredibly vague and messy privacy policies, sharing personal information with third parties, and even collecting chat transcripts,' Mozilla said.