The more data you can feed a machine learning algorithm, the better it can spot patterns, make decisions, predict behaviours, personalise content, diagnose medical conditions, power smart everything, detect cyber threats and fraud; indeed, AI and data make for a happy partnership: "The algorithm without data is blind. Data without algorithms is dumb." Not everyone wants to share, at least, not under the current rules of digital engagement. Some individuals disengage entirely, becoming digital hermits. Others proceed with caution, using privacy-enhancing technologies (PETs) to plug the digital leak: a kind karate chop, digital self defense -- they don't trust website privacy notices, they verify them with tools like DuckDuckGo's Privacy Grade extension and soon, machine-readable privacy notices.

New research published in AI Magazine explores how advanced AI could hack reward systems to dangerous effect. Researchers at the University of Oxford and Australian National University analyzed the behavior of future advanced reinforcement learning (RL) agents, which take actions, observe rewards, learn how their rewards depend on their actions, and pick actions to maximize expected future rewards. As RL agents get more advanced, they are better able to recognize and execute action plans that cause more expected reward, even in contexts where reward is only received after impressive feats. Lead author Michael K. Cohen says, "Our key insight was that advanced RL agents will have to question how their rewards depend on their actions." Answers to that question are called world-models.

When a demo of the software was released in late August, users quickly found that certain words--both explicit mentions of political leaders' names and words that are potentially controversial only in political contexts--were labeled as "sensitive" and blocked from generating any result. China's sophisticated system of online censorship, it seems, has extended to the latest trend in AI. It's not rare for similar AIs to limit users from generating certain types of content. DALL-E 2 prohibits sexual content, faces of public figures, or medical treatment images. The ERNIE-ViLG model is part of Wenxin, a large-scale project in natural-language processing from China's leading AI company, Baidu.

The second edition of the Global AI Summit kicked off Tuesday morning in the Saudi capital Riyadh, bringing together various stakeholders and academics to discuss the future of artificial intelligence and the Kingdom's contribution to this field. Over 200 speakers representing 90 countries have come together for the global summit that will run until September 15 at the King Abdul Aziz International Conference Center and under the patronage of Saudi Crown Prince Mohammed bin Salman. The Global AI Summit, organized by Saudi Data & AI Authority (SDAIA), will touch on topics such as the impact of AI on the public and private sectors, healthcare, environment, transportation, smart cities and culture among other matters. For all the latest headlines follow our Google News channel online or via the app. SDAIA said on its website that "tech companies, startups, investors, and entrepreneurs [will] meet at the Global AI Summit to shape the future of AI." Speaking at the opening ceremony of the summit, Saudi Minister of Communications & Information Technology Abdullah Alswaha said that Saudi Arabia "has become the largest tech force of coders and data scientists," adding that there are currently more than 70,000 trainees in this field.

Lithium-ion batteries have become a key component in the rise of electric mobility, but forecasting their health and lifespans is limiting the technology. While they've proven successful, the capacity of lithium-ion batteries degrades over time, and not just because of the ageing process that occurs during charging and discharging -- known as "cycling ageing." Lithium-ion battery cells also suffer degradation from so-called "calendar ageing," which occurs during storage, or simply when the battery is not in use. It's determined by three main factors: the rest state of charge (SOC), the rest temperature, and the duration of the rest time of a battery. Given that an electric vehicle will spend most of its life parked, predicting the cells' capacity degradation from calendar ageing is crucial; it can prolong battery life and pave the way for mechanisms that could even circumvent the phenomenon.

Last month, Facebook parent Meta unveiled an artificial intelligence chatbot said to be its most advanced yet. BlenderBot 3, as the AI is known, is able to search the internet to talk to people about almost anything, and it has abilities related to personality, empathy, knowledge and long-term memory. BlenderBot 3 is also good at peddling anti-Semitic conspiracy theories, claiming that former US President Donald Trump won the 2020 election, and calling Meta Chairman and Facebook co-founder Mark Zuckerberg "creepy". It's not the first time an AI has gone rogue. In 2016, Microsoft's Tay AI took less than 24 hours to morph into a rightwing bigot on Twitter, posting racist and misogynistic tweets and praising Adolf Hitler.

DeepMind, a U.K.-based firm that is part of Alphabet, Google's parent company, has developed an artificial intelligence and machine learning system that can predict the three-dimensional structure of proteins, decoding the amino acids that make up each protein. Last year, the system had 350,000 entries. Then on July 28, DeepMind co-founder and chief executive Demis Hassabis announced the expansion of the company's database of folded proteins to more than 200 million -- nearly all catalogued proteins known to science, including those in humans, plants, bacteria, animals and other organisms -- and that the company is making them publicly available and free, accessible with no more effort than a Google search. The database is called AlphaFold, and it is the equivalent of a James Webb Space Telescope for biology, providing astounding new visuals of a world beyond.

In the Pixar movie Up, a cartoon dog called Dug sports a magical collar of sorts that can translate his barks and whines into fluent human speech. Elsewhere in the real world, very well-trained dogs can be taught to press buttons that produce human speech for simple commands like "outside," "walk," and "play." Humans have always been fascinated by the potential to communicate with the animals that they share the world with, and recently, machine learning, with its ever more advanced capabilities for parsing human speech, has presented itself as a hopeful route to animal translation. An article in the New York Times this week documented major efforts from five groups of researchers that looked at using machine-learning algorithms to analyze the calls of rodents, lemurs, whales, chickens, pigs, bats, cats, and more. Typically, artificial intelligence systems learn through training with labeled data (which can be supplied by the internet, or resources like e-books).

DeepMind's attempt to teach an AI to play soccer started with a virtual player writhing around on the floor--so it nailed at least one aspect of the game right from kickoff. But pinning down the mechanics of the beautiful game--from basics like running and kicking to higher-order concepts like teamwork and tackling--proved a lot more challenging, as new research from the Alphabet-backed AI firm demonstrates. The work--published this week in the journal Science Robotics--might seem frivolous, but learning the fundamentals of soccer could one day help robots to move around our world in more natural, more human ways. "In order to'solve' soccer, you have to actually solve lots of open problems on the path to artificial general intelligence [AGI]," says Guy Lever, a research scientist at DeepMind. "There's controlling the full humanoid body, coordination--which is really tough for AGI--and actually mastering both low-level motor control and things like long-term planning."

Autonomous driving company Cruise and US regulators said on Thursday that the General Motors subsidiary had recalled software deployed on 80 vehicles after a June crash in San Francisco involving a Cruise car operating autonomously injured two people. The incident occurred one day after the state of California granted Cruise a permit to start a commercial driverless ride-hail service in the state. The flawed software was updated by early July, Cruise said in a filing with the US National Highway Traffic Safety Agency. The crash occurred when a Cruise vehicle attempting to make an unprotected left turn across a two-lane street was struck by a car that was traveling in the opposite direction and speeding in a turn lane. Cruise said in its NHTSA filing that its software had predicted that the other car would turn right and determined that it was necessary to brake hard in the midst of its own vehicle's left turn to avoid a front-end collision.