The World Economic Forum (WEF) annual meeting kicked off in the Swiss resort city of Davos on Monday, with global figures from politics, business, academia and civil society attending the five-day event. The annual forum that attempts to shape global agendas comes at a time of massive global upheaval. United States President Donald Trump will attend the annual event along with other global leaders. His attendance comes amid strained US ties with its European allies over his threat to take over Greenland, a semi-autonomous territory of Denmark. Here is more about the WEF and what to expect at the meeting.

A key feature of human theory-of-mind is the ability to attribute beliefs to other agents as mentalistic explanations for their behavior. But given the wide variety of beliefs that agents may hold about the world and the rich language we can use to express them, which specific beliefs are people inclined to attribute to others? In this paper, we investigate the hypothesis that people prefer to attribute beliefs that are good explanations for the behavior they observe. We develop a computational model that quantifies the explanatory strength of a (natural language) statement about an agent's beliefs via three factors: accuracy, informativity, and causal relevance to actions, each of which can be computed from a probabilistic generative model of belief-driven behavior. Using this model, we study the role of each factor in how people selectively attribute beliefs to other agents. We investigate this via an experiment where participants watch an agent collect keys hidden in boxes in order to reach a goal, then rank a set of statements describing the agent's beliefs about the boxes' contents. We find that accuracy and informativity perform reasonably well at predicting these rankings when combined, but that causal relevance is the single factor that best explains participants' responses.

For some years now, China's annual gathering of its national legislature had been an increasingly disciplined and choreographed affair -- its muted vibes practically an echo of deepening concern about domestic stagnation. The National People's Congress seven-day gathering, which concludes Tuesday in Beijing, came on the heels of a breakthrough in artificial intelligence by China's home-grown startup DeepSeek that's fired up investors, politicians and even regulators. It also followed Chinese President Xi Jinping's high-profile meeting with business chiefs including Jack Ma.

Cross-lingual adaptation has proven effective in spoken language understanding (SLU) systems with limited resources. Existing methods are frequently unsatisfactory for intent detection and slot filling, particularly for distant languages that differ significantly from the source language in scripts, morphology, and syntax. Latent Dialogue Action (LaDA) layer is proposed to optimize decoding strategy in order to address the aforementioned issues. The model consists of an additional layer of latent dialogue action. It enables our model to improve a system's capability of handling conversations with complex multilingual intent and slot values of distant languages. To the best of our knowledge, this is the first exhaustive investigation of the use of latent variables for optimizing cross-lingual SLU policy during the decode stage. LaDA obtains state-of-the-art results on public datasets for both zero-shot and few-shot adaptation.

In July, the California Department of Fair Employment and Housing sued video-game giant Activision Blizzard, alleging, more or less, that the company has a workplace environment from hell. Regulators said a two-year investigation into the company revealed an alcohol-drenched "frat boy" culture that included inappropriate conduct by executives, men openly joking about rape, and a general "breeding ground for harassment and discrimination against women." The company called the lawsuit "truly meritless and irresponsible" (though it seemed to have some trouble figuring out how to respond), and more than 2,000 current and former employees responded by putting their names on an open letter that said, "We no longer trust that our leaders will place employee safety above their own interests." In early August, employees shared their salaries en masse, Bloomberg reported, to pressure the company into confronting pay inequities. One executive, Blizzard head J. Allen Brack, resigned.

A team of researchers showed that artificial intelligence (AI) could help predict the type of bacteria that caused the infection in patients with pneumonia. The research is presented at ASM Microbe Online, the annual meeting of the American Society for Microbiology. "This research highlights the potential of AI as a supplementary tool for physicians in identifying causal pathogens of pneumonia, even before sputum culture results are available," said Joowhan Sung, M.D., hospitalist at MedStar Southern Maryland Hospital. "We demonstrated that physicians could be assisted by AI to decide appropriate antibiotics." In the study, investigators showed that AI could use the information available in the emergency room and predict if the patient has MRSA or pseudomonas so that physicians can immediately prescribe specific antibiotics targeting specific bacteria.

When Dan Lopresti and his colleagues talk about the future of artificial intelligence (AI) during their upcoming panel at the annual meeting of the American Association for the Advancement of Science (AAAS), be prepared to imagine a better world. In this world, the full potential of AI is unleashed to benefit society: health care is personalized and accessible through a friendly robot companion; education is customized to offer individualized plans for retraining and skills-building; and, businesses, large and small, operate with previously unheard-of efficiency and provide a level of customer service that can only be dreamed of today. "The question is what are we going to see over the next ten or twenty years break loose as a result of the research, which is assuming the research gets done because of investments made," says Lopresti, a professor of computer science and engineering at Lehigh University. Lopresti is also the incoming Vice Chair of the Computing Community Consortium (CCC) Council which, along with the Association for the Advancement of Artificial Intelligence (AAAI), spearheaded the creation of "A Twenty-Year Community Roadmap for Artificial Intelligence Research in the U.S." Lopresti will participate in a panel with the authors of the Roadmap and leaders of the initiative that led to it, Yolanda Gil (University of Southern California and President of AAAI) and Bart Selman (Cornell University and President-Elect of AAAI), on Saturday, February 15th at the AAAS annual meeting in Seattle. The Roadmap lays out a case for the best use of resources to fulfill the promise of AI to benefit society.

In 1971, the inaugural European Management Symposium was held in Davos, a ski resort in the Swiss Alps, the event a precursor to what would later become the World Economic Forum's annual meeting in Davos. "I felt the future should not be based on animosity and controversy. It should be based on reconciliation," WEF founder and Executive Chairman Klaus Schwab told The Japan Times during a 2013 interview, recalling the early years of the Davos conference. "In 1971, I published a book on multistakeholders, which means problems should always be solved through dialogues among the stakeholders, among all those people who are interested in the problems. So, I created a platform for multistakeholders to come together."

At the annual meeting of the Scientific Advisory Committee on Alternative Toxicological Methods (SACATM; see sidebar), committee members enthusiastically supported advances in new nonanimal testing technologies, such as computational tools and microphysiological systems (MPS), also known as tissue chips. The committee urged regulators to provide clear guidance on how these technologies should be used and what data from them would be accepted. Members also stressed the importance of having high-quality reference data from both human and animal tests to clearly demonstrate the ability of new methods to identify toxic chemicals. Experts from academia, industry, and animal welfare organizations debated how best to use these new technologies in the Sept. 19-20 meeting. The committee meets annually to advise the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM).

Editor's note: Noah Wang is co-founder and chief marketing officer of TOP Network, a Silicon Valley-based tech firm developing a business-friendly public blockchain and the world's first blockchain-based cloud communication network. The article reflects the author's views, and not necessarily those of CGTN. Earlier in January, at the annual World Economic Forum in Davos, Switzerland, Bloomberg released the 2019 Bloomberg Innovation Index, which ranks the most innovative countries using criteria including R&D investment, manufacturing capability, and patent activity. China jumped three spots to the 16th compared with a year before, beating the UK for the first time. However, Bloomberg index showed that China lagged far behind its innovative peers such as six-time champion the Republic of Korea as well as the U.S. and Japan, which secured their places among the top 10.