Video has taken the world by storm with a myriad of intelligent devices continuously capturing vast amounts of data about how people live and what they do. At the end of 2014, IHS Technology estimated over 245 million operational cameras were active globally. London alone has 500,000 cameras dotted throughout the city, which works out at about one camera for every 16 people. Thanks to smart cameras, CCTV devices, and even drones mounted with intelligent cameras, users are able to record videos at an unprecedented scale and pace. This vast store of data-rich content is used for a range of purposes – from gaming and law enforcement to crowd management at large events.

"How to choose the best topic model?" is the #1 question on our community mailing list. At RaRe Technologies I manage the community for the Python open source topic modeling package gensim. As so many people are looking for the answer, we've recently released an updated gensim 0.13.1 incorporating several new exciting features which evaluate if your model is any good, helping you to select the best topic model. Topic modeling is a technique for taking some unstructured text and automatically extracting its common themes, using machine learning. It is a great way to get a bird's eye view on a large text collection.

A team of scientists have developed a model that can predict the likelihood of bat species carrying Ebola and other filoviruses using a machine learning algorithm. Filoviruses are a group of long filament shaped viruses that encode their genome on a single-stranded RNA. Ebola is the most well-known example; other filoviruses include Marburg disease. Both are lethal viruses that are spread by coming into contact with bodily fluids from an infected person. The last Ebola outbreak happened in 2014 and resulted in 11,310 deaths, according to the World Health Organisation.

THE TERM "artificial intelligence" has been associated with hubris and disappointment since its earliest days. It was coined in a research proposal from 1956, which imagined that significant progress could be made in getting machines to "solve kinds of problems now reserved for humans…if a carefully selected group of scientists work on it together for a summer". That proved to be rather optimistic, to say the least, and despite occasional bursts of progress and enthusiasm in the decades that followed, AI research became notorious for promising much more than it could deliver. Researchers mostly ended up avoiding the term altogether, preferring to talk instead about "expert systems" or "neural networks". But in the past couple of years there has been a dramatic turnaround.

Google's recent victory against top-ranked Go player Lee Sedol marks another milestone in artificial intelligence development, and though this might be considered "old" news by today's standard, it's still a fresh achievement for the AI world. As much as this gameboard conflict between man and machine has encouraged conversation about competition, it has also sparked increasing conversation around the potential collaborative possibilities. "I think the main reaction from the Go community will be, as indeed happened after IBM computer Deep Blue achieved grandmaster status in chess, is that people want to get hold of the software and use it in their own games to work out where they went wrong." This kind of industry-specific technology has the potential to be used to further thinking, strategy, and goals within the game; however, Google's Go algorithm still can't manage a daycare or compose a nostalgic sonnet--and there are still many tasks best done by human beings. By utilizing and combining the individual strengths of both humans and AI, the collaborative possibilities are limitless, and are quickly becoming applicable in much more than board games.

Google plans to use more than one million anonymized eye scans to teach computers how to diagnose ocular disease. The Menlo Park, Calif.-based company has signed a deal with a British eye hospital to use artificial intelligence to learn from the medical records of 1.6 million patients in London hospitals. The goal is to teach a computer program to recognize the signs of two common types of eye disease, diabetic retinopathy and age-related macular degeneration. That's something humans are surprisingly imperfect at. Physicians diagnose these ailments by analyzing medical charts and interviewing patients, yet still get it wrong 10 to 20% of the time.

The artificial intelligence software is learning how to recognize early signs of two eye diseases.Video provided by Newsy Newslook A scan of a human eye. SAN FRANCISCO -- Google plans to use more than one million anonymized eye scans to teach computers how to diagnose ocular disease. The Menlo Park, Calif.-based company has signed a deal with a British eye hospital to use artificial intelligence to learn from the medical records of 1.6 million patients in London hospitals. The goal is to teach a computer program to recognize the signs of two common types of eye disease, diabetic retinopathy and age-related macular degeneration. That's something humans are surprisingly imperfect at.

Recently I heard two quote about the future that really put things into perspective. This week, Startup Festival was taking place in Montreal. I had the pleasure of interviewing Tobi Lutke (Founder and CEO of the 3 billion company, Shopify), and I was also able to spend a lot of time listening to those who are inventing the future, thinking about the future and investing in those who are building the future. It's been a fascinating three day experience. One of the main stage presentation was Tim O'Reilly (CEO of O'Reilly Media). Tim coined the phrase Web 2.0, is helping to push the maker movement and has spent decades being at the bleeding edge of technology.

However, the new Microsoft is directed towards building more intelligent apps and services, where the company's future seems bright once again. Microsoft's CEO Satya Nadella has expressed his fascination with HoloLens, the company's most exciting product in years. Even though it will take some time until we see the full potential of this platform, we can already see what it's capable of. After all, HoloLens is highly futuristic, innovative, and intelligent – and this is exactly what the new Microsoft hopes to become. What is important to consider is how different tech giants are trying to implement the next-generation technology into their products and services.

This course will help you to gain the skills to use one of the fastest growing mobile technologies, Chatbots. Now you too can learn to build sophisticated Chatbots for your customers all with NO Coding. I will show you examples of travel bots, entertainment bots, productivity bots, and retail bots. Come join us for what is a fun course to learn a technology with a lot of profit potential.