If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
With all the hype surrounding artificial intelligence, you would be forgiven for thinking that developing the algorithms powering deep learning are where the toughest challenges in the industry are. The actual challenge for most algorithms though is not their mathematics, but rather their inputs -- collating high-quality data that is well-labeled and allows for the training of these models as quickly and efficiently as possible. That's where DefinedCrowd comes in. The company, which is based in Seattle and Portugal, was founded in 2015 by Daniela Braga, a data scientist and natural language processing expert, and Amy Du, who has since moved on from the company to start a global entrepreneurship network. We've talked about the company back when it participated in Microsoft's startup accelerator and also when it was featured in the Battlefield at TechCrunch Disrupt New York this past year.
To create anything that will be powered by AI, technologists inherently have to start with the data that will be used to train the AI and ultimately create these amazing AI-powered tools and services. This process is usually driven by engineers -- the experts that actually know how to model the intelligence and enable it to take action based on data. The problem with that is that teams usually pick the first problem that technology can be applied to, without validating it with real users. Is that technology solving a real user need? It's the same story when the concept of mobile apps came up in the late 2000s.
Sheng Fu founded Cheetah Mobile in 2010, and it found a business making security apps such as Security Master for smartphones. Now it is a publicly traded company valued at $2.2 billion, with revenues of $707 million in 2016. It is targeted almost $800 million for 2017 revenues, after expanding into a variety of other areas, including utilities such as Clean Master for both smartphones and the PC. I met with Fu when the company opened its Silicon Valley office in 2016, and we met once again at CES 2018, the big tech trade show in Las Vegas this week. He told me that the company will shift into the unknown landscape of products that makes use of artificial intelligence.
As chief architect at Kontiki Labs, I wear two hats - one as a AI researcher looking at new developments in AI and bringing that into the main body of capabilities of our company, as needed. The second role is an AI evangelist / Product Management role where I work with businesses to understand there needs or problems and suggest the right AI powered solutions for them. Needless to say I am constantly toggling between developer and business roles and looking for workflows to optimise my available dev time. During business travel, I tend to use my Sundays for some lock-down research and development around ML or AI. This is the narrative of a typical AI Sunday, where I decided to look at building a sequence to sequence (seq2seq) model based chatbot using some already available sample code and data from the Cornell movie database.
The world's top 32 drone pilots will compete Saturday in Las Vegas for the world champion title in the International Drone Racing Assn.'s top challenge. Semi-professionals wearing virtual reality headgear compete for a $50,000 cash prize in the Challengers Cup Final on Friday and Saturday at the South Point hotel-casino at 9777 S. Las Vegas Blvd. Competitors qualified during 2017 races that began in Buenos Aires, Argentina, and concluded in Manila, the Philippines. Visitors can buy tickets to watch for $20. You'll be admitted to Friday's practice runs and the competition on Saturday afternoon. The elimination round will get underway at 12:30 p.m. with the finals set for 3:20 p.m. Saturday.
Scaling up VR to areas larger than your living room is a focus for a number of game developers right now, but Microsoft is working on expanding the size capabilities of the tech for a much more important reason: disaster management. In a lecture video, the Microsoft Research team explains how it's reconstructing entire buildings in a VR sphere to help occupants learn how to act in disaster scenarios, such as earthquakes or flooding. Using a mobile robot equipped with a laser-range sensor, an RGB depth camera and a 4K panoramic image camera, the team can virtually reproduce the interiors of buildings in what it calls "Building-scale VR". The mobile robot also scans individual physical objects by moving around them automatically. In the disaster simulations, both the building and objects can be manipulated, giving the VR headset wearer the opportunity to safely experience potentially dangerous situations, which according to the researchers is just as, if not more, effective than real world training.
The course is broad and pretty decent introductory course, but there is a number of presentation and course design flaws. First, while I'm not sure whether it is solely a Coursera's typical marketing approach to prevent users from refusing the course just because of the minimum amount of time required, or authors' unintended misestimations, but the actual time needed to complete the course is a way more than listed at the course home page, especially assignments. Often the time needed only to run an assignment training with no coding exceeds the given estimate. To get the value from the course one should be prepared to allocate much more time (2x-3x in total). Second, the course is too broad to be called an introductory one but too shallow in terms of math/practical/reasoning details to be named a deep one.