Subscribe to the O'Reilly Radar Podcast to track the technologies and people that will shape our world in the years to come: Stitcher, TuneIn, iTunes, SoundCloud, RSS In this week's episode, David Beyer, principal at Amplify Partners, co-founder of Chart.io, and part of the founding team at Patients Know Best, chats with Risto Miikkulainen, professor of computer science and neuroscience at the University of Texas at Austin. They chat about evolutionary computation, its applications in deep learning, and how it's inspired by biology. Also note, David Beyer's new free report "The Future of Machine Intelligence" is now available for download. We talk about evolutionary computation as a way of solving problems, discovering solutions that are optimal or as good as possible. In these complex domains like, maybe, simulated multi-legged robots that are walking in challenging conditions--a slippery slope or a field with obstacles--there are probably many different solutions that will work.

Television today is full of shows that raise questions about the ethics of artificial intelligence (AI): Westworld. These shows provoke dialogue over the rights and responsibilities we must take when creating AI, but the issue few are addressing is what happens to all the people displaced by AI. Every time I go to a large chain store I notice more self checkouts and less live humans working there. The transition to AI coupled with blockchain replacing human services is happening before our very eyes, but nobody is aware this is happening. It's not that masses of workers are being fired and removed from jobs, it's that new workers are not hired when existing employees quit.

As financial institutions race to implement artificial intelligence solutions, there is the potential to miss less robust applications that the consumer expects today, while also slowing the development of more sophisticated AI solutions for the future. Subscribe to The Financial Brand via email for FREE!When The Jetsons premiered in 1962, the notion of a robot maid was considered an imaginative dream about a futuristic life as opposed to something that might actually happen within the viewer's lifetime. That same year, the U.S. was heavily focused on the space race to the moon, still more than six years away from the historic Apollo 11 landing. More than 50 years ago, the world began to dream in terms previously unimaginable. As a result, some of the Jetson generation traded their Saturday morning bowls of sugary cereal for mechanical and software engineering degrees -- and in just 56 years, have created a world their parents might have argued was impossible. While the common U.S. household may not have a Rosie yet, consumer robots and artificial intelligence (AI) have never been more commonplace than they are today.

Drones have quickly become a technology almost everyone is familiar with. Whether it's professional photographers capturing wild landscapes or amateurs racing mini quadcopters around their living room: drones are here to stay. But not all drones are the same. If your mission is to use the power of a drone to capture your most unmissable moments, then the Airlango Mystic Drone is your answer. The Airlango Mystic Drone sets itself apart from its competition by incorporating a range of technologies to make it easy for anyone to be a professional drone photography pilot.

Late in an early episode of Castle Rock, the show chooses a humorless moment to poke a little fun at the audience. Henry Deaver (Andre Holland) sits in halting conversation with a mysterious young man (Bill Skarsgård), their bodies separated by glass and their voices joined by jailhouse phones. Or Deaver's voice, at least--the young man opposite him has whispered only a few words since first being freed from captivity underneath Shawshank Prison, and is utterly silent now. Deaver, an attorney, outlines what he imagines their legal strategy to be; "You understand?" he finishes. Then speaks, his voice creaking with disuse: "Has it begun?"

Artificial Intelligence is the new buzzword in town. To many digital marketers, it seems so promising but so far away at the same time. Though it's true AI "as seen in the movies" is not here, below are six AI applications that a savvy digital marketer can make use of right now. Personalization Professional services websites are a wealth of information for both the user and the marketer. Analytics are captured for every visit and session.

Advancements in technology, from artificial intelligence to 3D printing, have revolutionized prosthetic design. State-of-the-art prosthetics enable their wearers to complete tasks most of us take for granted. And since the goal of prosthetics is to enable their wearers to complete tasks important to their daily lives, it is common to find prosthetics customized for various activities, from running to cycling, and even for dancing. Prosthetics design requires skills from various disciplines, such as biomedical engineering, robotics, mechanical engineering, computer science--and music. Runners need to run, and drummers need to drum.

In June of last year, five researchers at Facebook's Artificial Intelligence Research unit published an article showing how bots can simulate negotiation-like conversations. While for the most part the bots were able to maintain coherent dialogue, the researchers found that the software agents would occasionally generate strange sentences like: "Balls have zero to me to me to me to me to me to me to me to." On seeing these results, the team realized that they had failed to include a constraint that limited the bots to generating sentences within the parameters of spoken English, meaning that they developed a type of machine-English patois to communicate between themselves. These findings were considered to be fairly interesting by other experts in the field, but not totally surprising or groundbreaking. A month after this initial research was released, Fast Company published an article entitled AI Is Inventing Language Humans Can't Understand.

The great strength of CNN architectures is their capability to automatically learn a hierarchy of feature detectors in order to solve some task. What it has been observed is that regardless of the architecture, the dataset and the target semantic space (and of course the initialization assuming it's random), the first layers seem to always converge to specific kinds of feature detectors: the Gabor Filters. This is actually a very interesting and important phenomenon as it seems to suggest the Gabor Filters are the most efficient way to start the semantic extraction process from an image. It would mean Gabor Filters block is a sort of "generic building block" which could be used to design NN aimed at solving computer vision problems This is one of the main goal of Transfer Learning: finding "building blocks" which can be composed to build a NN and fine tuned, instead of trained from scratch, on the Dataset Being able to properly understand how the CNN specializes while training is important to get to Transfer Learning: "transferring" the network "capability of solving a problem" which means basically adapting its weights properly, to another similar problem in a Data Efficient Way The data efficiency is in fact one of the most important aspects of transfer learning: it is well known that Supervised Learning is an effective way to make a certain, typically big, NN become able to solve a problem but it scales badly in terms of data as it typically requires A LOT OF supervision signal which, in case of manual annotation, is expensive to collect as it relies on humans to provide it. Furthermore the more the task is difficult, the more the annotations need to be provided by human experts instead of normal people and the former one's time is more expensive than the latter ones

The Mystic is designed to give the ultimate aerial video and photography experience, creating breathtaking imagery without the need to learn complicated film techniques. The Mystic automatically detects objects and avoids obstacles using the cutting-edge motion intelligence similarly found in the self-driving car. With gesture interaction, you can take stunning aerial selfies, using poses to control the drone. The Mystic recognizes each pose as a specific command and will follow your instructions, moving forward and backward, side to side, and taking photos. The Mystic is the first drone to support up to 6 different gestures, all of which can be customized to your personal preference.