Andrew Beam, PhD is an assistant professor in the Department of Epidemiology at the Harvard T.H. Chan School of Public Health, with secondary appointments in the Department of Biomedical Informatics at Harvard Medical School and the Department of Newborn Medicine at Brigham and Women's Hospital. His research develops and applies machine-learning methods to extract meaningful insights from clinical and biological datasets, and he is the recipient of a Pioneer Award from the Robert Wood Johnson Foundation for his work on medical artificial intelligence. Previously he was a Senior Fellow at Flagship Pioneering and the founding head of machine learning at Generate Biosciences, Inc., a Flagship-backed venture that seeks to use machine learning to improve our ability to engineer proteins.

Game theory is known to be a useful tool in the study of Machine Learning (ML) and Artificial Intelligence (AI) Multi-Agent interactions. One basic component of these ML and AI systems is the exploration-exploitation trade-off, a fundamental dilemma between taking a risk with new actions in the quest for more information about the environment (exploration) and repeatedly selecting actions that result in the current maximum reward or (exploitation). However, the outcome of the exploration-exploitation process is often unpredictable in practice and the reasons behind its volatile performance have been a long-standing open question in the ML and AI communities. Dr Stefanos Leonardos and Assistant Professor Georgios Piliouras, researchers from the Singapore University of Technology and Design (SUTD), applied analytical tools from the theory of dynamical systems in the study of multi-agent systems and established a deep connection between exploration-exploitation and Catastrophe Theory (Figures 1 and 2). The latter is a branch of mathematics that formally explains phase transitions in all kinds of natural systems ranging from the transition from water to ice and disease outbreaks to collapses of financial markets.

What is new is how quickly malicious actors can spread disinformation when the world is tightly connected across social networks and internet news sites. We can give up on the problem and rely on the platforms themselves to fact-check stories or posts and screen out disinformation--or we can build new tools to help people identify disinformation as soon as it crosses their screens. Preslav Nakov is a computer scientist at the Qatar Computing Research Institute in Doha specializing in speech and language processing. He leads a project using machine learning to assess the reliability of media sources. That allows his team to gather news articles alongside signals about their trustworthiness and political biases, all in a Google News-like format. "You cannot possibly fact-check every single claim in the world," Nakov explains. Instead, focus on the source. "I like to say that you can fact-check the fake news before it was even written." His team's tool, called the Tanbih News Aggregator, is available in Arabic and English and gathers articles in areas such as business, politics, sports, science and technology, and covid-19. Business Lab is hosted by Laurel Ruma, editorial director of Insights, the custom publishing division of MIT Technology Review. The show is a production of MIT Technology Review, with production help from Collective Next. This podcast was produced in partnership with the Qatar Foundation. "Even the best AI for spotting fake news is still terrible," MIT Technology Review, October 3, 2018 Laurel Ruma: From MIT Technology Review, I'm Laurel Ruma, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace.

Artificial Intelligence (AI) has made a massive impact in the modern world. The use of AI at any level has proved to be fantastic. It automated a significant number of tasks, reducing human effort and has led everyone to believe that there is even more to come. Infigon Futures is a company that empowers the lives of individuals who are seeking educational and career goals to help them make decisions for a brighter future. Speaking with Analytics Insight, Omkar Patil, CEO, Infigon Futures, provides insight into how the education and career planning platform is helping individuals ranging from 11 to 30 in age and what solutions the company offers to improve their lives significantly.

We consider a rank regression setting, in which a dataset of $N$ samples with features in $\mathbb{R}^d$ is ranked by an oracle via $M$ pairwise comparisons. Specifically, there exists a latent total ordering of the samples; when presented with a pair of samples, a noisy oracle identifies the one ranked higher with respect to the underlying total ordering. A learner observes a dataset of such comparisons and wishes to regress sample ranks from their features. We show that to learn the model parameters with $\epsilon > 0$ accuracy, it suffices to conduct $M \in \Omega(dN\log^3 N/\epsilon^2)$ comparisons uniformly at random when $N$ is $\Omega(d/\epsilon^2)$.

Microsoft is known as one of the more inclusive companies in the technology industry, with products including an adaptive Xbox controller and initiatives such as hiring people with autism and funding startups that use artificial intelligence to help people with disabilities. The company is also one of the few that has a chief accessibility officer, having created the role in 2010. Jenny Lay-Flurrie assumed the post in 2016 as Microsoft restructured the accessibility division to make it more central to the company. Ms. Lay-Flurrie, who is deaf and who initially hid her disability by relying on lip reading, spoke to the Experience Report by video call about her role and the moves she and others with her remit should be making. This interview has been edited for length and clarity.

Artificial intelligence (AI) is everywhere. Embedded into our everyday lives, from our ridesharing apps to the algorithms on our social media channels, AI has the potential to revolutionize every industry. However, there are a number of challenges that many technologies still need to overcome before they can actually implement AI -- and that's especially the case in the risk management industry. Today, companies across every industry rely on environment, health and safety (EHS) procedures to promote a safer and more compliant workplace. Essential to companies' risk management strategies, EHS programs are commonly used to help companies avoid unwanted events.

Electric vehicles are becoming increasingly popular, and self-driving cars are also on the way. When will they be mature enough to meet climate challenges and take to the roads en masse? Writes about the impact of new technologies on society: are we aware of the revolution in progress and its consequences? Many countries are seeking to achieve carbon neutrality within the coming decades. In Europe, the Green DealExternal link has laid down a plan to achieve zero emissions by 2050, and Switzerland has set itself the same deadline. This is an ambitious goal that puts the spotlight on the transport sector, which is responsible for around 16% of global CO2 emissions.External link So what will mobility look like in the future?

Not so long ago, watching a movie on a smartphone seemed impossible. Vivienne Sze was a graduate student at MIT at the time, in the mid 2000s, and she was drawn to the challenge of compressing video to keep image quality high without draining the phone's battery. The solution she hit upon called for co-designing energy-efficient circuits with energy-efficient algorithms. Sze would go on to be part of the team that won an Engineering Emmy Award for developing the video compression standards still in use today. Now an associate professor in MIT's Department of Electrical Engineering and Computer Science, Sze has set her sights on a new milestone: bringing artificial intelligence applications to smartphones and tiny robots.

The arrival of The Mitchells vs. the Machines on Netflix feels like the detonation of a confetti bomb--it's a colorful, inventive, and all-around delightful movie. In fact, as my colleague Sam Adams wrote for Slate, it's the first great animated movie of 2021. Directed by Mike Rianda and co-directed by Jeff Rowe, the movie stars Abbi Jacobson as Katie, a girl about to head to college, and Danny McBride, Maya Rudolph, and Rianda respectively as her father, mother, and younger brother Aaron, all of whom join her on a road trip in an attempt at a last hurrah before she flies the coop. That trip hits a bit of a road bump, however, when a robot uprising threatens the entire human race. One of the biggest--and funniest--set pieces of the film involves the Mitchell family having to fight a horde of Furby dolls.