Those who have a robot vacuum on their gift list this year can pick up a few iRobot machines for less right now. Arguably the best for most people is the Roomba 694, which is 27 percent off at Amazon (which now owns iRobot) and down to only $199. While this model has dropped to $179 in the past, this is the best deal we've seen on it since June. Also discounted are the higher-end Roomba j7 and Roomba s9, which are going for $599 and $799, respectively. The Roomba 694 topped our list of best budget robot vacuums because it combines all of the essential features you'd expect in one of these machines with a relatively slick design and an easy-to-use mobile app.

At a certain point in my gaming life, everything changed. After spending most of my twenties marathoning titles for hours on end, emerging bleary-eyed from all-day gaming stints, my priorities shifted. I can't binge-play now, even if I still hear the call of the console and yearn to be swept up into a game. Moderation is key, but finding a way to unlearn unhealthy gaming habits is tough. Or, at least, it was until The Legend of Zelda: Breath of the Wild.

Built on top of scikit-learn, it allows you to rapidly create active learning workflows with nearly complete freedom. What is more, you can easily replace parts with your custom built solutions, allowing you to design novel algorithms with ease. With the recent explosion of available data, you have can have millions of unlabelled examples with a high cost to obtain labels. For instance, when trying to predict the sentiment of tweets, obtaining a training set can require immense manual labour. But worry not, active learning comes to the rescue!

Discovering meaningful molecules in the vast combinatorial chemical space has been a long-standing challenge in many fields from materials science to drug discovery. Recent advances in machine learning, especially generative models, have made remarkable progress and demonstrate considerable promise for automated molecule design. Nevertheless, most molecule generative models remain black-box systems, whose utility is limited by a lack of interpretability and human participation in the generation process. In this work we propose Chemical Space Explorer (ChemSpacE), a simple yet effective method for exploring the chemical space with pre-trained deep generative models. It enables users to interact with existing generative models and inform the molecule generation process. We demonstrate the efficacy of ChemSpacE on the molecule optimization task and the molecule manipulation task in single property and multi-property settings.

We are seeking a Market Data Engineer to help design, build and maintain the market data and associated analytics that will be used throughout the Trading Hub products and platforms. Successful candidates will work alongside Pricing Quants and Risk Strats to productionise new data and help industrialise the current market data environment. The role will require candidates to gain an excellent understanding of financial markets and TradingHub's products and thus should attract someone who is comfortable working with complex architectures and are keen to apply their development and problem-solving skills in a practical setting. TradingHub is committed to providing equal opportunities and supporting diversity in employment. Diverse teams are the best teams!

Tesla's (TSLA) Optimus robot that danced on a stage this past weekend was widely panned by critics for being behind the robots developed by automation leader Boston Dynamics. But one analyst argued that the underlying technology could be a big win for the automaker's autonomous driving software. "What we're excited about is the learning cycles that we're seeing the company execute on the AI side," Oppenheimer's Tesla analyst Colin Rusch said on Yahoo Finance Live (video above). "That's where I think the real value is." Rusch noted that if Tesla opens up its AI software to other companies, it could bring in "a couple billion" in sales at a relatively "high margin."

Robots and machines have become integral to almost every human endeavour now and now, they are set to enter the human body, blood vessels in particular. Now, after taking inspiration from plants and fungi, scientists have come up with a method which can make soft robots travel the tricky pathways in the body. "We were really inspired by how plants and fungi grow. We took the idea that plants and fungi add material at the end of their bodies, either at their root tips or at their new shoots, and we translated that to an engineering system," Matthew Hausladen, one of the author of the paper published in the Proceedings of the National Academy of Sciences of the United States of America and a PhD student at the University of Minnesota, revealed. This team of researchers at the University of Minnesota invented soft robots which can travel in difficult terrain by growing in length, prompting it around corners and other turns.

While a few firms--the digital giants--are winning big from digital technology, many large firms are investing heavily in digital, by recruiting IT specialists and spending on digital technology--including artificial intelligence, cloud computing, machine learning, and algorithmic decision making, yet getting disappointing returns. As noted in a previous article, 'How To Understand Your Digital Transformation" firms must realize is that digital transformation is only partly to do with technology. The chief obstacle is the fundamental change in the way the firm is managed--from industrial-era management to digital age management. Thus, over the last two decades, it has become increasingly apparent that the most successful firms at digital transformation are being run very differently from industrial-era. They have a different set of principles, including a goal of co-creating value for customers, a business model that generates profits as a result; team-based and network structures. These principles are supported by processes that are quite different from those of industrial-era management.

Much like how varying sections of the brain are responsible for different functions of the body, LeCun suggests a model for spawning autonomous intelligence that would be composed of five separate, yet configurable modules. One of the most complex parts of the proposed architecture, the "world model module" would work to estimate the state of the world, as well as predict imagined actions and other world sequences, much like a simulator. But by using this single world model engine, knowledge about how the world operates can be easily shared across different tasks. In some ways, it might resemble memory.

Headlines were made earlier this year when a new rapper dropped new music on – where else – TikTok. Tens of millions of followers signed up to listen to songs powered not by artistic nous but artificial intelligence (AI). Are rappers just the latest cohort of the jobs market to fall foul of AI and its staggering potential? We have been warned for years that AI is poised to take over the world of work, with many jobs simply ceasing to exist as machines finally win the war against man. We already know it can beat us at chess.