Marco Arment, the former lead developer for Tumblr and creator of Instapaper, this weekend (May 21) argued in a blog post that Apple risks succumbing to the same fate as BlackBerry, which saw its business evaporate when Apple's iPhone changed the game. Arment contends that Apple is unprepared for the shift if consumers begin favoring services rooted in artificial intelligence being developed by other internet giants. "Today, Amazon, Facebook, and Google are placing large bets on advanced AI, ubiquitous assistants, and voice interfaces, hoping that these will become the next thing that our devices are for. Today, Apple's being led properly day-to-day and doing very well overall. But if the landscape shifts to prioritize those big-data AI services, Apple will find itself in a similar position as BlackBerry did almost a decade ago: what they're able to do, despite being very good at it, won't be enough anymore, and they won't be able to catch up."

At the top of the corporate world, Apple and Google are in a back-and-forth battle to be number one. It's not clear which of the two Silicon Valley giants will emerge on top in a contest which highlights the contrast of very different business models. Apple then regained, lost and recovered the leader position in May in a battle that appears set to continue for some time. At the close Friday, Apple was worth some 522 billion, to 496 billion for Alphabet. The two companies have both been hugely profitable in recent years, for different reasons. Apple has delivered a line of must-have iPhones and other gadgets that have set trends around the world but now "appears to be a little bit immobile," says Roger Kay, analyst at Endpoint Technologies Associates.

Really cool stuff, exactly what I was looking for.

Artificial Intelligence and machine learning are hot topics at every technology conference I go to, and the recent DLD NYC conference was no exception. Ramin Assadollahi of ExB Group, a German company dealing with cognitive computing in healthcare, focused on a variety of ways new computer techniques can help us learn "how to heal with software." Addressing many of the terms that are thrown around today, he noted that AI does not have to be cognitive computing, cognitive computing does not have to be machine learning, and big data is a separate issue entirely. Assadollahi focused on ways AI could improve the field of medicine. He noted that a pathologist looking at tissue data typically sees 200,000 samples in his or her work lifetime, but with deep learning and modern graphics cards, a computer system can process that many in two weeks.

One possible explanation is that this is another manifestation of the curse of dimensionality. As the dimension of a space increases it is well known that the volume of a hypersphere becomes increasingly concentrated at its surface. Given that the decision boundaries of a deep neural network are in a very high dimensional space it seems reasonable that most correctly classified examples are going to be close to the decision boundary - hence the ability to find a misclassified example close to the correct one, you simply have to work out the direction to the closest boundary.

Deeplearning4J is an Apache 2.0-licensed, open-source, distributed neural net library written in Java and Scala. Deeplearning4J integrates with Hadoop and Spark and runs on several backends that enable use of CPUs and GPUs. The aim is to create a plug-and-play solution that is more convention than configuration, and which allows for fast prototyping. The most recent stable release in Maven Central is 0.4-rc3.9, For more on working with snapshots, see this page.

Artificial neural networks were inspired by the human brain and simulate how neurons behave when they are shown a sensory input (e.g., images, sounds, etc). They are known to be excellent tools for image recognition, any many other problems beyond that - they also excel at weather predictions, breast cancer cell mitosis detection, brain image segmentation and toxicity prediction among many others. Deep learning means that we use an artificial neural network with multiple layers, making it even more powerful for more difficult tasks. This time they have been shown to be apt at reproducing the artistic style of many famous painters, such as Vincent Van Gogh and Pablo Picasso among many others. All the user needs to do is provide an input photograph and a target image from which the artistic style will be learned.

"I don't know what you mean - how about a web search for it?" If you want the latest football scores, to add meetings to your calendar or launch an app, today's virtual assistants are relatively good at understanding your voice and doing what's asked. But try to have the type of natural conversation seen in sci-fi movies featuring artificial intelligence systems - from HAL in 2001 to the sultry-voiced operating system Samantha in Spike Jonze's Her - and you'll find your device about as smart as a waterproof teabag. "Google and Apple are painfully aware that their systems are not getting better fast enough because right now Siri and Google Now and the other personal assistant type applications are all programmed by hand," says Steve Young, professor of information engineering at the University of Cambridge. "If you speak to Siri about baseball it seems relatively intelligent, but if you ask it something much less common it doesn't really do anything except for a web search. "That's an indication that the programmers have been busy trying to anticipate what people want to ask about baseball but haven't thought about people who ask about, for example, GPU chips because you don't get many queries about that." Microsoft doesn't yet have a virtual assistant on its Windows Phone platform, but the company is experimenting with AI in lifts and reception desks at its headquarters. Eric Horvitz, managing director of Microsoft's research unit, believes part of the solution involves allowing computers to look beyond questions posed. "The ability of a system to understand more broadly what the overall context of a communication is turns out to be very important," he told the BBC. "There are some critical signals in context.

Michael Schmidt recently wrote in TechCrunch, "Artificial intelligence. But despite all the talk around AI, no one seems to really understand what it is or how companies can use it… Many people think of AI as the blending of humans and machines. They're not far off, but AI is an incredibly broad term -- more of an umbrella term, really -- that simply means making computers act intelligently. It is one of the major fields of study in computer science and encompasses subfields such as robotics, machine learning, expert systems, general intelligence and natural language processing." Schmidt goes on, "Apple's Siri, Google's self-driving cars and Facebook's image recognition software are standard examples of AI. While these applications are all powered very differently and achieve different goals, they all roll up into the umbrella term of artificial intelligence."

If Google is right about the future, there are troubling signs to suggest Apple could meet the same fate as BlackBerry, according to top Apple follower Marco Arment. In a blog post, Arment argues that BlackBerry was great at creating phones and dominated the market before Apple released the iPhone. The problem was that the iPhone release didn't just create a better smartphone -- it changed what people used them for entirely. BlackBerry was great at creating at a device for email and phone calls, but Apple unleashed the App Store and now there's an app for everything. It fundamentally changed the definition for a smartphone, and BlackBerry couldn't ever play catch-up.