The apple blossoms are sprouting, the sun is finally rising before your alarm goes off, and Google CEO Sundar Pichai is wiping down the lenses of his Gemini-powered smart glasses. You know what that means: It's once again time for Google I/O. Google is going all out for its annual I/O developer conference, which begins on Tuesday, May 20. The event is taking place at Shoreline Amphitheater in Mountain View, California, just down the road from Google's headquarters. The keynote starts at 10 am PDT on Tuesday, and as usual, it will be livestreamed.

Humans have firmly retained their lead over robots at table tennis for over 40 years, but recent advancements at Google DeepMind suggest our days of dominance may be numbered. As detailed in a preprint paper released on August 7, researchers have designed the first-ever robotic system capable of amateur human-level performance in ping pong--and there are videos to prove it. Researchers often opt for classic games like chess and Go to test the strategic capabilities of artificial intelligence--but when it comes to combining strategy and real-time physicality, a longtime robotics' industry standard is table tennis. Engineers have pitted machines against humans in countless rounds of ping pong for more than four decades due to the sport's intense computational and physical requirements involving rapid adaptation to dynamic variables, complex motions, and visual coordination. "The robot has to be good at low level skills, such as returning the ball, as well as high level skills, like strategizing and long-term planning to achieve a goal," Google DeepMind explained in an announcement thread posted to X.

Google is expected to announce artificial intelligence integrations for the company's search engine on February 8 at 8:30 am Eastern. It's free to watch live on YouTube. "We're starting with AI-powered features in Search that distill complex info into easy-to-digest formats, so you can see the big picture, then explore more," Google CEO Sundar Pichai wrote on Twitter in the lead-up to the event. Despite recent layoffs, the company remains an assertive force in Silicon Valley. The viral success of other generative AI models, specifically OpenAI's ChatGPT, put pressure on the company to expedite its experimental research for public use.

To advance the state-of-the-art in this domain, researchers at Google, Stanford, and Columbia recently investigated a machine learning system dubbed Form2Fit, which aims to teach a picker robot with a suction arm the concept of assembling objects into kits. "If robots could learn'how things fit together,' then perhaps they could become more adaptable to new manipulation tasks involving objects they have never seen before, like reconnecting severed pipes, or building makeshift shelters by piecing together debris during disaster response scenarios," wrote research intern Kevin Zakka and robotics research scientist Andy Zeng in a blog post. "It helps to increase the efficiency with which we perform tasks, like assembling DIY furniture kits or packing gifts into a box." As Zakka and Zeng explain, Form2Fit learns to recognize how objects correspond (or "fit") to each other mainly through trial and error. One component -- a two-stream matching algorithm -- infers three-dimensional point representations that communicate not only an object's geometry, but its texture and contextual task-level knowledge.

Another AI-generated video of Trump singing karaoke has made its way to YouTube. If you're a regular reader of Futurism, you may have spotted a previous video in which YouTuber "Coding Elite" used an AI algorithm built by Google engineers to make Trump sing Eminem's "Lose Yourself." Our article about the song received critical acclaim, such as one Facebook comment that read "I want my two minutes back." Now Coding Elite is back, and now the neural net synthesized Trump's voice to make it sound like he's singing Eurythmics' "Sweet Dreams." This time around, a video accompanies the song, where video footage of Trump is automatically altered by "Coding Elite" to make it look as though he's actually singing along.

If you missed out on Google's I/O 2017 keynote earlier today, don't fret. We've cut down all of the noteworthy news on Google Lens, AI, Google Assistant, Google Home, Daydream, Android O and more into a quick TK-minute clip. Just sit back, relax and catch up on all of the news in way less time than we spend taking in the 2-hour presentation this afternoon. For all the latest news and updates from Google I/O 2017, follow along here. A tech writer by day and a graphic designer by night, Billy was ushered into the gadget world by an Atari and its vices: Frogger and Grand Prix.

The A.I. also learns extremely quickly. In the video at the top of this page, it takes only four tries to clear the first room of Montezuma's Revenge, an Atari 2600 game. "Poor old Deep Q scored a big fat zero," Wired wrote. Games like Montezuma's Revenge pose a particular challenge because they require more than just reaction, like Pong or Breakout. To succeed, players need to plan how to clear a room, and then execute that plan.

It may have fared badly in the recent robo-olympics, causing hilarity with a series of unexpected falls, but Google has revealed its humanoid robot has been set free in the woods to learn how to run free. The Atlas robot created by Google-owned firm Boston Dynamics is a formidable figure at 6ft 2in tall and weighing in at 330lb. In the video, it is shown struggling to stay upright - but managing to traverse a forest path without falling. It may have fared badly in the recent robo-olympics, but Google has revealed its humanoid robot has been set free in the woods to learn how to run through terrain. According to Google owned Boston Dynamics, Atlas is a'high mobility, humanoid robot designed to negotiate outdoor, rough terrain.

For a while now, Google's company DeepMind has been working on an artificial intelligence (AI) which plays Atari games better than you remember your older brother playing them in the 1980s. The AI is not only extremely proficient at playing these cult classics but has also learned to play 49 of them completely on its own. Despite this impressive feat, the DeepMind's creation isn't perfect and some games have simply proved to be too complicated for it to learn them on its own, Montezuma's Revenge being one of them. However, the Google-owned company has recently been hard at work correcting the flaws in its AI which has finally mastered the unforgiving 1984 platformer developed by the now-defunct Utopia Software. As its developers explain it, they had to make the AI "curious enough" for it to want to actually win the game.

If we want to create artificial intelligence that can teach itself how the world works, it needs to be curious. This has been a recurring theme in the world of AI in recent years, and newly published research from Google's DeepMind division shows exactly why this quintessentially human quality is important for making computers smart. Curiosity means rewarding the AI agent's exploration In the video above you can see DeepMind's AI agent tackling the infamously difficult Atari game Montezuma's Revenge. Unlike bots playing Unreal Tournament or StarCraft, the agent doesn't have access to all the information in the game, but is learning to play the same way humans do -- by looking at the screen, pushing buttons, and seeing what works. If this setup sounds familiar, it's because last February DeepMind unveiled an earlier iteration of the same agent, but when that bot tried to take on Montezuma's Revenge, it couldn't score a single point.