If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
In 2020, Synced has covered a lot of memorable moments in the AI community. Such as the current situation of women in AI, the born of GPT-3, AI fight against covid-19, hot debates around AI bias, MT-DNN surpasses human baselines on GLUE, AlphaFold Cracked a 50-Year-Old Biology Challenge and so on. To close the chapter of 2020 and look forward to 2021, we are introducing a year-end special issue following Synced's tradition to look back at current AI achievements and explore the possible trend of future AI with leading AI experts. Here, we invite Mr. Brian Tse to share his insights about the current development and future trends of artificial intelligence. Brian Tse focuses on researching and improving cooperation over AI safety, governance, and stability between great powers. He is a Policy Affiliate at the University of Oxford's Center for the Governance of AI, Coordinator at the Beijing AI Academy's AI4SDGs Cooperation Network, and Senior Advisor at the Partnership on AI.
We mere mortals haven't truly been competitive against artificial intelligence in chess in a long time. It's been 15 years since a human has conquered a computer in a chess tournament. However, a team of researchers have developed an AI chess engine that doesn't set out to crush us puny humans -- it tries to play like us. The Maia engine doesn't necessarily play the best available move. Instead, it tries to replicate what a human would do.
Communication is more important than ever, with everything from college to CrossFit going virtual during the COVID-19 pandemic. Nobody understands this better than 2020 Marconi Prize recipient Andrea Goldsmith, who has spent her career making the wireless connections on which we rely more capable and stable. A pioneer of both theoretical and practical advances in adaptive wireless communications, Goldsmith spoke about her work on multiple-input and multiple-output (MIMO) channel performance limits, her new role as the incoming dean at Princeton University's School of Engineering and Applied Science, and what's next for networking. As an undergrad, you studied engineering at the University of California, Berkeley. What drew you to wireless communications?
Pratt Miller demonstrated its LAAD disinfecting robot at Gerald R Ford International Airport in Grand Rapids, MI, in July 2020. The impacts of the COVID-19 pandemic are likely to be felt for years to come, regardless of the presence and availability of a vaccine. Physical measures adopted by humans, such as social distancing or wearing masks, are likely to be utilized for years to come, along with technological developments deployed in both public and private spaces that are focused on enforcing social distancing, enabling more efficient cleaning and disinfecting of spaces, and driving more automation and intelligence to reduce humans' direct physical interaction with each other. Some companies and individuals feel the best way to avoid COVID-19 or other viruses is to simply avoid all unnecessary human contact. As such, many companies have introduced or fast-tracked the use of automation to lessen their reliance on human workers, as well as to enhance their responsiveness to customer queries.
Competition for mates between prehistoric human women may have contributed to'concealed ovulation' – a lack of any notable physical clues that a woman is fertile, experts say. Using computational models, US researchers found evidence that concealed ovulation in humans – which is unusual in the animal kingdom – evolved to allow women to hide their fertility status from other females. This would have helped avoid female conflict, perhaps driven by aggression towards potential rivals for male mates. Previously, scientists have thought women evolved to conceal ovulation from males to encourage them to help with looking after children. The new research shows that the origin of concealed ovulation might have actually have been much more female-oriented than previously thought. 'The study of human evolution has tended to look at things from a male perspective,' said senior study author Athena Aktipis, associate professor of psychology at Arizona State University in the US.
Hosted by Dylan Doyle-Burke and Jessie J Smith, Radical AI is a podcast featuring the voices of the future in the field of artificial intelligence ethics. In this episode Jess and Dylan chat to Meredith Ringel Morris about ability and accessibility in AI. What should you know about Ability and Accessibility in AI and responsible technology development? Meredith is a computer scientist conducting research in the areas of human-computer interaction (HCI), computer-supported cooperative work (CSCW), social computing, and accessibility. Her current research focus is on accessibility, particularly on the intersection of accessibility and social technologies.
Researchers trying to improve healthcare with artificial intelligence usually subject their algorithms to a form of machine med school. Software learns from doctors by digesting thousands or millions of x-rays or other data labeled by expert humans until it can accurately flag suspect moles or lungs showing signs of Covid-19 by itself. A study published this month took a different approach--training algorithms to read knee x-rays for arthritis by using patients as the AI arbiters of truth instead of doctors. The results revealed radiologists may have literal blind spots when it comes to reading Black patients' x-rays. The algorithms trained on patients' reports did a better job than doctors at accounting for the pain experienced by Black patients, apparently by discovering patterns of disease in the images that humans usually overlook.
Alan Kalton, Vice President and General Manager of Aktana Europe, is a leader in data analytics and manages all new Contextual Intelligence implementations and developments across Europe. He comes to Aktana from Cape Town, South Africa where he led a data analytics venture called BroadReach and prior was the Analytics Leader of EY in South Africa. He also held prominent executive leadership positions in data analytics at IBM, Elsevier, Cognizant, Steris, Novartis, GSK, and ZS Associates. He graduated with a BS and MSc of industrial and operations engineering from the University of Michigan. Kalton can be reached at email@example.com.
Hosted by Dylan Doyle-Burke and Jessie J Smith, Radical AI is a podcast featuring the voices of the future in the field of artificial intelligence ethics. In this episode Jess and Dylan chat to Moses Namara about the new Black in AI academic program. In this episode, we interview Moses Namara of Black in AI about the new Black in AI academic program, a program that serves as a resource to support black junior researchers as they apply to graduate programs, navigate graduate school, and enter the postgraduate job market. Moses Namara is a Facebook Research Fellow and Ph.D. candidate in Human-Centered Computing (HCC) at Clemson University. He uses interdisciplinary research methods from computer science, psychology, and the social sciences to understand the principles behind users' adoption and use of technology, decision-making, and privacy attitudes and behaviors.
Anewly designed artificial intelligence tool based on the structure of the brain has identified a molecule capable of wiping out a number of antibiotic-resistant strains of bacteria, according to a study published on February 20 in Cell. The molecule, halicin, which had previously been investigated as a potential treatment for diabetes, demonstrated activity against Mycobacterium tuberculosis, the causative agent of tuberculosis, and several other hard-to-treat microbes. The discovery comes at a time when novel antibiotics are becoming increasingly difficult to find, reports STAT, and when drug-resistant bacteria are a growing global threat. The Interagency Coordination Group (IACG) on Antimicrobial Resistance convened by United Nations a few years ago released a report in 2019 estimating that drug-resistant diseases could result in 10 million deaths per year by 2050. Despite the urgency in the search for new antibiotics, a lack of financial incentives has caused pharmaceutical companies to scale back their research, according to STAT. "I do think this platform will very directly reduce the cost involved in the discovery phase of antibiotic development," coauthor James Collins of MIT tells STAT.