For years now, "artificial intelligence" has been a hot buzzword in the cybersecurity industry, promising tools that spot suspicious behavior on a network, quickly figure out what's going on, and guide incident response if there's an intrusion. The most credible and useful of services, though, have actually been machine learning algorithms trained to spot characteristics of malware and other dubious network activity. Now, as generative AI tools proliferate, Microsoft says it has finally built a service for defenders that's worthy of all the hype. Two weeks ago, the company launched Microsoft 365 Copilot, which builds on a partnership with OpenAI along with Microsoft's own work on large language models. The company is rolling out Security Copilot, a sort of security field notebook that integrates system data and network monitoring from security tools like Microsoft Sentinel and Defender and even third-party services.

But although the ServCity trial is clearly impressive, Mr Beiker thinks it will be years before use of self-driving cars in cities becomes widespread, because of the need to prepare infrastructure and develop high-definition 3D maps in every area they are to be used.

Let's start at the beginning. The term "artificial intelligence" gets tossed around a lot to describe robots, self-driving cars, facial recognition technology and almost anything else that seems vaguely futuristic. A group of academics coined the term in the late 1950s as they set out to build a machine that could do anything the human brain could do -- skills like reasoning, problem-solving, learning new tasks and communicating using natural language. Progress was relatively slow until around 2012, when a single idea shifted the entire field. It was called a neural network.

Google typically gets the blame for the lack of competition in web search. The US government is even suing to block the company from using allegedly monopolistic tactics, like making itself the default search engine in widely used software such as Android, Chrome, and Safari. But some upstart search engines trying to woo users with privacy protections or ad-free searches say their latest challenge doesn't come from Google. Search startups have long relied on licensing search results from Bing, tapping a web indexing operation larger than a small company could easily afford and adding their own features and ways of parsing queries. But Microsoft's rollout of a Bing search chatbot based on technology underlying OpenAI's ChatGPT has prompted concerns that Microsoft is unfairly squeezing out its search data customers as it launches a renewed attempt to bite off more market share from Google.

But while companies and executives see a clear chance to cash in, the likely impact of the technology on workers and the economy on the whole is far less obvious. Despite their limitations--chief among of them their propensity for making stuff up--ChatGPT and other recently released generative AI models hold the promise of automating all sorts of tasks that were previously thought to be solely in the realm of human creativity and reasoning, from writing to creating graphics to summarizing and analyzing data. That has left economists unsure how jobs and overall productivity might be affected. For all the amazing advances in AI and other digital tools over the last decade, their record in improving prosperity and spurring widespread economic growth is discouraging. Although a few investors and entrepreneurs have become very rich, most people haven't benefited.

The "jaws" of a Venus flytrap attached to a robotic arm Venus flytraps can be tricked into snapping shut on command, researchers have shown, effectively turning them into biological robots that can be controlled wirelessly. The Venus flytrap (Dionaea muscipula) is a carnivorous plant that catches its prey, such as flies, by snapping its circular leaves shut around it. The leaves' edges are studded with thin hairs that generate electrical impulses when an insect touches them – this burst of electricity causes the trap to close in as little as 0.1 seconds.

Early computer vision studies aimed at developing computerized driver intelligence appeared in the mid-1980s when scientists first demonstrated a road-following robot.36 Studies performed from the mid-1980s until 2000 established the fundamentals for automated driver intelligence in related tasks, including detection of pedestrians,39 lanes,3 and road signs.9 However, the vast majority of initial computer vision algorithms aimed at detecting objects required developers to manually program dedicated features. The increase in computational power available in recent years changed the way AI models are created: Features are automatically extracted by training various neural network architectures on raw data. Automatic feature extraction outperformed and replaced the traditional approach of manually programming an object's features.

Teleoperating a physical robot could become an important job in future, according to Sanctuary AI, based in Vancouver, Canada. The company also believes that this might provide a way to train robots how to perform tasks that are currently well out of their (mechanical) reach, and imbue machines with a physical sense of the world some argue is needed to unlock human-level artificial intelligence. Industrial robots are powerful, precise, and mostly stubbornly stupid. They cannot apply the kind of precision and responsiveness needed to perform delicate manipulation tasks. That's partly why the use of robots in factories is still relatively limited, and still requires an army of human workers to assemble all the fiddly bits into the guts of iPhones.

On the top floor of a squat Singapore industrial estate, wedged between a railway depot and water reclamation plant, is a young security firm that's shooting for the stars. Well, shooting for anything beneath the stars that shouldn't be there, technically speaking. TRD is one of the world's leading purveyors of anti-drone technology--a burgeoning industry worth some $1.1 billion last year and projected to grow to $7.4 billion by 2032. "Anti-drone is the hot topic right now," says TRD CEO Sam Ong, a former officer in the Singapore Armour Corps, where he specialized in tank technology. "Unmanned warfare is taking center stage, especially in the Ukraine war."

Google's long-awaited, AI-powered chatbot, Bard, is here. The company rolled it out to the public on Tuesday, and anyone with a Google account can join the waitlist to get access. Though it's a standalone tool for now, Google is expected to put some of this technology into Google Search in the future. But in contrast to other recent AI chatbot releases, you shouldn't expect Bard to fall in love with you or threaten world domination. Bard is, so far, pretty boring.