Apple locks down iOS, so you can't just launch right into Google Now like you can by saying "Hey Siri," but it's worth the effort of opening the app. Plus, you can add a widget to Google, so the assistant is always just one swipe away. You can use Siri to launch apps or do things like silence your phone -- things you can't do with Google Assistant -- but I've never used Siri in that manner. I think those functions are helpful but not really a measurement of a machine's intelligence. Google Assistant also lets you type in queries, so you don't have to speak out in public if you don't want to, and you can make sure every query is dead-accurate.

It's scary to think about the rise of automation as it is developing so quickly. Science-fiction, and even some real-life experts, have primed us to fear the potential dangers of artificial intelligence (AI). Much of this concern regarding automation is because of impending job loss. The demographic that these losses will likely hit first, and perhaps the hardest, are lower-skilled positions. However, the automation revolution isn't likely going to stop with factory work, other professions may soon have to contend with automated competition as well.

Say you have a thousand columns and a million rows in your data set. Whichever way you look at it – small, medium or big data – you won't be able to actually look at it. Blame human nature but most of us understand a subject better when they get to see a bigger picture. Is there a way to put your data in one image and navigate it almost like you would do with a map? Deep Learning combined with Topological Data Analysis can do exactly that and more.

Artificial intelligence isn't just confined to assistants like Siri. AI is also getting even better at adding color to black and white photos; it's cool tech, but makes the photography nerds at Popular Science cringe at the thought of famous photos with added hues.

In 2016, we find ourselves awash in news about machine learning. Driving this wave of interest, a number of breakthroughs - many due to deep learning - have pushed the state-of-the-art in computer vision, speech recognition and natural language processing. Per Google Trends, searches for machine learning are up four-fold while searches for deep learning are up ten-fold over the last five years. These advances have cracked open viable paths towards primitive but economically impactful systems. Responding to this demand, our news outlets, blogs, technical magazines and newspapers alike, have struggled to keep up.

The Artificial Intelligence Market Forecasts 2016 -2025 across 27 Industry Sectors has provided an overview of numerous Artificial Intelligence use cases, which includes Machine Learning, machine reasoning, Deep Learning, NLP, computer vision, and many other allied technologies. According to this study, food services, consumer products, advertising, and defense (along with others mentioned above) will significantly benefit from the growth of AI in the coming years.

Spotify has announced the acquisition of Niland, a machine learning startup based out of Paris. The music company made the announcement itself this week, explaining that Niland shares its'passion for surfacing the right content to the right user at the right time.' Spotify plans to use the company's technology and know-how to improves its own recommendation abilities, doing so with the power of artificial intelligence behind it. Spotify announced the acquisition on Wednesday, saying that the Niland team will be joining the music company's own team in its New York office. The terms of the deal weren't revealed, such as how much Spotify paid for the company or when the deal was finalized. We do know, however, that personalized recommendations on Spotify are about to get much better than to the startup's work in machine learning and artificial intelligence.

Lars Rasmussen, co-creator of Google Maps, presents his new venture Weav at Techstars Music on May 18, 2017 at El Rey Theatre in Los Angeles. We all know that the growth of music distribution is moving fast from transaction to streaming subscriptions. The music value chain is adapting. With millions of songs streamed trillions of times, advanced technologies are necessary for consumers to find and discover their favorite songs and for music artists to find their fans and interact with them. Will the music industry be able to leverage digital technologies to adapt and be profitable?

An AI algorithm developed by researchers at Salesforce generates snippets of text that describe the essence of long text. These tools can help writers skim through a lot of articles and find relevant topics to write about. "Since new semantic technologies are now mature enough to read human language, journalists and professional writers can finally go back to writing for people," Cuofano says. "The next revolution (which is already coming) is the leap from NLP to a subset of it called NLU (Natural Language Understanding)," Cuofano says.

Artificial Intelligence (AI) was a movie in 2001 telling a story about a childlike android programmed with the ability to love. Set in a post climate change world of the 22nd Century the movie was ahead of its time. Dial ahead just 16 years, not a whole century, and AI is being talked about a lot, mainly through fear of the unknown and its impact on jobs. In other recent AI news Elon Musk announced Neuralink a venture to merge the human brain with AI, adding this to his SpaceX retrievable rocket technology and the Tesla cars we are now seeing on New Zealand's roads. Leading media including The Wall Street Journal, McKinsey Quarterly, Harvard Business Review and Financial Times all have a plethora of articles about AI.