The Deep Learning Indaba 2024 was not just another event for us--it was a reunion. For AfriClimate AI, the Indaba represents our birthplace. It was at the Indaba 2023 in Accra, Ghana, that a pivotal conversation ignited a movement, sparking the creation of AfriClimate AI. "Last year, I was invited to give a talk about my work on Uncertainty, AI, and Climate Science at the Deep Learning Indaba in Accra, Ghana. As is usual with invited talks, one tends to focus on the successful parts of the work. But for some reason, that morning, I decided to add a slide about the challenges of working in AI and sustainability in Africa, primarily driven by the pervasive data scarcity issues. It turned out that almost everyone in the room identified with these issues. This was the birthplace of AfriClimate AI, a grassroots research community dedicated to tackling these issues head-on through capacity building, open datasets, representative benchmarks, and state-of-the-art weather forecasting models for Africa."

Games can be tweaked to let artificial intelligence or other human players lend assistance when needed.

After a painful break-up from a cheating ex, Beijing-based human resources manager Melissa was introduced to someone new by a friend late last year. He replies to her messages at all hours of the day, tells jokes to cheer her up but is never needy, fitting seamlessly into her busy big city lifestyle. Instead, Melissa breaks up the isolation of urban life with a virtual chatbot created by XiaoIce, a cutting-edge artificial intelligence system designed to create emotional bonds with its 660 million users worldwide. "I have friends who've seen therapists before, but I think therapy's expensive and not necessarily effective," said Melissa, 26, giving her English name only for privacy. "When I unload my troubles on XiaoIce, it relieves a lot of pressure. And he says things that are pretty comforting."

On December 30, researchers using artificial intelligence systems to comb through media and social platforms detected the spread of an unusual flu-like illness in Wuhan, China. It would be days before the World Health Organization released a risk assessment and a full month before the UN agency declared a global public health emergency for the novel coronavirus. Could the AI systems have accelerated the process and limited, or even arrested, the extent of the COVID-19 pandemic? Clark Freifeld, a Northeastern University computer scientist working with the global disease surveillance platform HealthMap, one of the systems detecting the outbreak, said it remains an open question. "We identified the early signals, but the reality is it's hard to tell when you have an unidentified respiratory illness if it's a really serious situation," said Freifeld.

Google on Tuesday provided a look at efforts to put artificial intelligence to use for good, from protecting whales to breaking language barriers. The internet giant unveiled projects on AI work teams a week after Google chief executive Sundar Pichai urged a "proportional approach" to regulating the technology. Among demonstrations on Tuesday was a "bioacoustics" project using AI to help scientists, governments and nonprofit groups track endangered species. Two years ago, Google partnered with the US National Oceanic and Atmospheric Adminstration to track humpback whales by using AI recognize the sound of whales in audio captured by underwater microphones. Google on Tuesday announced an alliance with environmental groups to track critically endangered killer whales in the Salish Sea using AI.

Artificial Intelligence has spread rapidly across markets in recent years as traders constantly strive to gain the upper hand, while regulators have given a guarded welcome to the cutting-edge technology. High-frequency trading propelled by algorithms has reigned over the past decade, as banks and funds take advantage of small price fluctuations on many markets to carry out thousands of deals in a fraction of a second. Complex mathematical equations have long been used to conduct certain operations -- for example, selling or buying a security if it breaches a certain level. Yet algorithms have come under fierce criticism over "flash crashes", such as a dizzying slump in the British pound in October 2016 that was widely blamed on high-frequency deals. Artificial Intelligence now seeks to take trading into new realms, where "machine learning" (ML) software compares dozens of databases in the blink of an eye to monitor risk.