Save on a Roomba ahead of the Black Friday shopping rush. If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA Today's newsroom and any business incentives. The holidays are right around the corner, which means we'll all have to attend to our hosting duties for Friendsgivings, holiday parties, and fancy dinners. If you want your home looking spiffy for when the guests arrive, there's no better time to invest in a robot vacuum to keep your floors clean of dirt, pet hair, and dust bunnies.

Has it ever happened to you that you try to achieve something but the end result was totally unanticipated? Sometimes good things are an accident – Electricity, Discovery of America, Gravity, and PHP. Actually, PHP was never intentionally designed. Rasmus Lerdorf, a Danish software engineer attempted to design an easy common gateway interface by using the C language that would help him track views on his CV. Little did he know what he had created for such a menial task is going to change the face of web applications. As for Python, the language has its own fan following spread worldwide.

A CT scan in action. Britain's National Health Service currently faces a critical shortage of cancer doctors, making it increasingly difficult to provide specialist care to seriously ill patients. According to stats from the Royal College of Radiologists, 7.5% of consultant roles at 62 major U.K.-based cancer centers are vacant. Because of this, they've become reliant on overtime. However, Swedish AI firm Peltarion worked with a radiotherapy company to develop a deep learning model that targets tumors for radiotherapy.

Inc said on Tuesday it would use artificial intelligence (AI) technology from Amazon.com Inc's cloud computing unit to improve customer service apps. Salesforce makes software systems that businesses use to house customer information, like which products or services a customer has purchased and how long they have been a customer. Agents use the information to solve customer issues. Salesforce said it will use technology from Amazon Web Services to turn the customer's spoken words into text, where it can be translated into different languages or analyzed to determine whether the customer is angry or satisfied, all in real time.

Good code has both substance and style. It provides all necessary information, without extraneous details. It is accurate, succinct and eloquent enough to be read and understood by humans. But by the late 1960s, advances in computing power had outpaced the abilities of programmers. Many computer scientists created programs without thought for design.

The evolution of modern finance was closely linked to the evolution of computers, communications, and financial mathematics. Two main changes happened in the 1970s with the beginning of derivative trading and after the crisis of 2007 with the massive introduction of fintech. Derivatives pricing started with the celebrated Black and Scholes equation and formulas in 1974, followed by a wealth of mathematical methods to compute the prices of derivatives. Still, even the 1980s derivative pricing required supercomputers, giving big firms a major competitive advantage – before the 2007 crisis, the trading volume was close to 1 trillion dollars a day. The prevailing opinion was that derivatives had enabled us to complete financial markets so that any stream of cash flows could be engineered.

By some estimates, the world generates 2.5 quintillion bytes of data every day. Yet only a sliver of that volume, much of it residing on enterprise servers, is fully leveraged to drive a deep understanding of the enterprise and how to improve it. What value lies untapped within all that data? As business leaders grapple with these questions, they rely increasingly on emerging cognitive technologies like artificial intelligence, machine learning and blockchain. When these technologies are coupled with cloud-based multi-enterprise networks, thought-leading companies are able to unearth, analyze and act upon critical insights across business lines and foster the emergence of intelligent enterprises.

In our initial publication, we used RoboTurk to collect a large dataset using robot manipulation tasks developed using MuJoCo and robosuite. However, there are several interesting tasks that cannot be modeled in simulation, and we did not want to restrict ourselves to those that could. Thus, we extended RoboTurk to enable data collection with real robot arms, and used it to collect the largest robot manipulation dataset collected via teleoperation. The dataset consists of RGB images from a front-facing RGB camera (which is also the teleoperator video stream view) at 30Hz, RGB and Depth images from a top-down Kinectv2 sensor also at 30Hz, and robot sensor readings at 100Hz. We collected our dataset using 54 different participants over the course of 1 week.

Wait, change that, go ahead and panic. Sometimes people momentarily lose their minds and opt to panic. This primal urge can be handy as it invokes the classic fight-or-flight instinctive reaction to a situation. If you suddenly see a bear up ahead while in the woods, it could be that rather than carefully trying to plot out all of the myriad of options about what to do, entering instead into a panic mode might get your feet moving and you'll have run far from the bear before it has had a chance to do anything to you. On the other hand, it could be that your effort to run away is not wise and the bear easily catches up with you, allowing the bear to win and perhaps an untoward result for you. Not many of us will likely get into a circumstance of confronting a bear, and so let's consider something that might be higher odds of happening to any of us. Suppose you are in an airplane and the plane is on the ground and engaged in fire. Presumably, with or without panic, you'd realize that you should get out of the burning airplane. How can you get out of the burning airplane? I'm sure you've all sat through the flight attendants telling you to figure out beforehand the nearest exit to your seat. I'd bet that most people don't look to see where that exit is, and instead just kind of assume that when there's an emergency they'll figure out where the exit is.

Upon meeting for the first time at a dinner at Stanford earlier this year, Fei-Fei Li and Jennifer Doudna couldn't help but note the remarkable parallels in their experiences as scientists. Stanford's Fei-Fei Li and Jennifer Doudna of UC Berkeley will discuss the ethics of artificial intelligence and CRISPR technology. Both women helped kickstart twin revolutions that are profoundly reshaping society in the 21st century – Li in the field of artificial intelligence (AI) and Doudna in the life sciences. Both revolutions can be traced back to 2012, the year that computer scientists collectively recognized the power of Li's approach to training computer vision algorithms and that Doudna drew attention to a new gene-editing tool known as CRISPR-Cas9 ("CRISPR" for short). Both pioneering scientists are also driven by a growing urgency to raise awareness about the ethical dangers of the technologies they helped create.