Many technology commentators got all excited a few months ago when Microsoft launched how-old.net, a website where users could upload a photo and the site would guess the age of the person in the picture. The service was a great way to showcase the opportunity that applying artificial intelligence to a problem set introduces. Insilico hopes to deliver a similar sort of an offering, but with a far more important purpose. Insilico Medicine is an organization focused on aging research. Headquartered at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, it has R&D resources in Belgium, Poland, Russia and China employing 39 scientists worldwide.

As stated in my previous article, I want to show next where AI is taking us in the future. However, I need to describe first how AI has evolved during its short life. I have written three articles that develop this theme. In this first article, I briefly outline the background context with what has been achieved up until the start of the millennium. In the next article, I describe the impact that machine learning paradigms such as genetic algorithms and neural networks have made in the last 20 years. Finally, in the third article, I outline our future in a world dominated by AI.

Hosts, BootstrapLabs, launched the Applied Artificial Intelligence Conference in 2016. The event was decent and, with about 400 registered attendees, was reasonably well-attended. Last year's speakers included representatives from IBM Watson, FaceBook, Uber, and Accenture. The conference intends to gather researchers and scientist as well as A.I. practitioners. It felt like a first time event last year for sure, but we can see this event growing in stature in 2017 given the location (San Francisco) and the fact that the theme is becoming more popular.

It's been an interesting day. The 45th President of the United States of America took office just two hours ago, and he is clearly unlike any other President that has gone before him. So just for fun, I thought I might feed his inauguration speech into Watson in real-time, in order to see what the smartest computer in the world had to say about it. Would he notice any anomalies, or insights that the professional political commentators might have missed? Might we some people respect Trump a little more if they looked at his speech more analytically than emotionally?

Plentiful high-quality data is the key to great machine learning models. But good data doesn't grow on trees, and that scarcity can impede the development of a model. One way to get around a lack of data is to augment your dataset. Smart approaches to programmatic data augmentation can increase the size of your training set 10-fold or more. Even better, your model will often be more robust (and prevent overfitting) and can even be simpler due to a better training set.

For the last 5 to 10 years, connectivity and mobility have been on top of the agenda for many industries, both are essential enablers for a digital transformation. But while mobility and connectivity continue to be important enablers to expand the internet of things, there is something much bigger at stake that starts to emerge now. As more devices get connected you also start to collect more data and gain more insights and intelligence on how to optimize and automate tasks and processes. So here are a few questions related to the impact these changes could have on our society. How many of the tasks done today by various types of employees can be fully automated?

I often get asked on how to get started with Machine Learning. Most of the time, people have troubles understanding the maths behind all things. And I have to admit, I don't like the maths either. Math is an abstract way of describing things. And I think the way machine learning is described is too abstract to understand it easily. I probably try to describe things with foo code or a bit of JS to explain what I'm talking about.

When Facebook (NASDAQ: FB)suggests you "tag" a friend in a photo, it generally suggests that friend's name. That small interaction provides a glimpse into the world of an emerging and powerful aspect of artificial intelligence (AI) in action -- image recognition. With its treasure trove of words and pictures from 1.79 billion monthly active users,it is using that data, combined with recent advancements in AI, to propel this and other technological advances. Facebook may well have the lead in facial recognition, even extending a step further into the realm of facial verification. It released a research paper in 2014 in which it reported 97.35% accuracy, which approaches human levels of recognition.So accurate, in fact, that Facebook removed the feature for European Union citizens at the EU's request to protect privacy.

AMD has traded at this level on only two other occasions before: Q2-Q3 of 2000 and Q4 2005 - Q1 2007. The rise in market capitalization in both occasions came with the release of a competitive CPU processor/architecture. AMD in 2016/2017 is beginning to look a lot like AMD's most successful periods in 2000 and 2006. I'd like to examine catalysts then and now to gain insight on where AMD may be headed. In June 1999 AMD debuted their K7 Athlon processor.

F-35s, F-22s and other fighter jets will soon use improved artificial intelligence to control nearby drone wingmen that will be able to carry weapons, test enemy air defenses or perform intelligence, surveillance and reconnaissance missions in high risk areas, senior Air Force officials said. "This involves an attempt to have another platform fly alongside a human, perhaps serving as a weapons truck carrying a bunch of missiles," Zacharias said in an interview with Defense Systems. An F-35 computer system, Autonomic Logistics Information System, uses early applications of artificial intelligence that help computers make assessments, go through checklists, organize information and make some decisions by themselves – without needing human intervention. "We are working on making platforms more autonomous with multi-infusion systems and data from across different intel streams," Zacharias explained. ALIS serves as the information infrastructure for the F-35, transmitting aircraft health and maintenance action information to the appropriate users on a globally-distributed network to technicians worldwide, said Lockheed Martin, the contractor that built the system. However, despite the promise of advancing computer technology and increasingly levels of autonomy, Zacharias emphasized that dynamic human cognition is, in many respects, far more capable than computers.