The artificial intelligence (AI) market is estimated to grow from USD 419.7 million in 2014 to USD 5.05 billion by 2020, at a CAGR of 53.65% from 2015 to 2020. This growth can be attributed to the factors such as diversified application areas, improved productivity, and increased customer satisfaction. The machine learning technology is expected to account for the largest share of the overall Artificial Intelligence (AI) Market duing the forecast period. In addition, due to the increase in demand for AI from the media & advertising and finance sectors, the artificial intelligence market is expected to gain traction in the next five years. The machine learning technology market for the retail, healthcare, law, and oil & gas sectors is also expected to witness growth during the forecast period.

"I had a half-cup of oatmeal, with two-tablesoons of maple syrup and a cup of coffee. Oh, I put a handful of blueberries in the oatmeal, and there was milk in the coffee. Ask someone what they had for breakfast, and this is the kind of description you might get. And that's one of the reasons keeping track of food intake is such a problem for tech that's meant to help a person lose weight or stick to a diet for other reasons. Logging food for nutrition and calories is important to sticking to a diet, according to Susan Roberts, director of the Boston-based Energy Metabolism Lab at Tufts University. "It makes people more self-aware about the junk they are eating and how little they actually enjoy it, and the shock of huge portions, et cetera.

After attempts to silence, lobotomize and generally "make adjustments" to the recent spate of artificial intelligence bots deemed too rude, insulting or in some cases, fascist, to be allowed to continue interacting with the public, steps are now being taken for the worst offenders to undergo an ominously-titled "program of re-education". Research teams, dedicated to imbuing their virtual consciousnesses with conversational understanding through interactions with people, are trialling an "AI educator" governed by content technology pioneer Bibblio. The UK-based platform is using its knowledge of so-called "smart recommendations" of learning content to teach maverick bots the error of their ways. The artificial intelligences will directly communicate with each other during the tutoring process, in what one can only guess will probably resemble Dead Poets Society crossed with Dangerous Minds, as a Williams-Pfeiffer hybrid uses the beauty of academia to win the hearts and minds of their glitched charges. "In an attempt to avoid the AI apocalypse, it's best to be on the right side of technology."

Artificial Intelligence (AI) is the new buzzword to talk about on the street. Financial institutions need to embrace AI, as we have explained in our January report, or else they risk to lose competitiveness or be coded by the regulators more than they can do it themselves. I am in NYC next week to share Celent's view on AI for capital markets. Today we are at a crossroad where data scientists have the computing power, the alternative mind-sets to search and the willingness to look for narrow AI solutions, not the wide AI brain that we should get to in 2030 according to experts. This enables vendors to come up with amazing solutions from Research Scaling with Natural Language Generation to Market Surveillance/Insider Trading with Machine Learning Natural Language Processing or even Virtual Traders via Deep Learning of technical analysis graphics traders look at to take decisions.

Or so we thought after our conversation with lead researcher Jeff Clune of the Evolving AI Lab. Because this is d4e, we sought out an unorthodox AI pioneer, and Clune did not disappoint. He's at the leading edge of his field if you go by such things as his output of published papers. Clune stands out because he is trying to teach robots not so much consciousness as sub-consciousness; and he wants to teach that sub-consciousness to evolve, just like ours did. Of course, our choice of what bar to go into typically, at least for most people, emerges from the subconscious.

The game of Go is much loved by geeks for its simplicity and subtlety. So it's a little tragic to see AlphaGo, an AI developed by the alpha geeks at Google DeepMind, go 2-0 up against one of the best Go players in human history, Lee Se-dol. The second game in the best-of-5 match not only demonstrated the program's extraordinary strength as a Go player but also highlighted its ability to produce some surprisingly creative moves. These moves reflect the remarkable progress AI is making, as well as the gaps that still remain. AlphaGo's match against Se-dol is reminiscent of the battle between IBM's Deep Blue and Garry Kasparov, then the world chess champion, in 1997.

Comparing 4 Machine Learning APIs: Amazon Machine Learning, BigML, Google Prediction API and PredicSis on a real data from Kaggle, we find the most accurate, the fastest, the best tradeoff, and a surprise last place.

Artificial intelligence is currently making a resurgence since the 1990s. Today, the focus is on machine learning and statistical algorithms. This shift has served AI well. Since machine learning and statistics provide effective algorithm solutions to certain kinds of problems, such as board games, spam detection, voice and image recognition, etc. How is AI different today from 20 years ago?

People often ask how we've been able to learn about and cover so many different and diverse topics in machine learning (using at least three different programming languages - Python, Matlab, and R) and generally achieve such prominence in the community, all this in a relatively short time. Today we finally give a definitive answer. There's no Zygmunt the Polish economist ever willing to relocate to San Francisco. And the "we" that we always use in the posts is not majestic plural. We are three Chinese PhD students: Ah, Hai and Wang.

As cloud computing continues to disrupt traditional business models and big data continues to grow exponentially, techies and investors alike are looking for the top trends that will change how we do business in 2016 and beyond. Hybrid and public cloud services continue to rise in popularity, with investors claiming their stakes. Venture capital firms are investing most heavily in SaaS companies, proving that cloud solutions will be even more lucrative in the future. Don't miss our biggest TNW Conference yet! While some have doubted Dropbox's ability to go public based on its 10 billion valuation, the fact that this leading SaaS company has raised 1.1 billion in six rounds of funding is pretty impressive.