A few short months ago, Intel acquired Nervana Systems for 400 million dollars with the intention of using the technology they developed in order to be competitive in the deep learning market currently dominated by GPU-based solutions from NVIDIA. Artificial Intelligence is a big market for Intel and the company sees it as a pivotal ground that they must put a stake in or risk falling behind like they did on the mobile front. With Nervana's technology, Intel is expecting to produce "a breakthrough 100-fold increase in performance in the next three years to train complex neural networks", says Intel CEO Bryan Krzanich in a recent editorial. Nervana's technology will be a PCIe add-in card expected to hit be out sometime around the first half of 2017, codenamed Lake Crest and incorporates HBM technology that is directly targeting current GPU solutions. Intel believes that GPGPU architecture is not uniquely advantageous for AI and that their approach can support much larger models and is much more highly scalable.

Over the past decade, B2B marketing has undergone a massive transformation. According to Forrester Research, the entire B2B sector represents more than $1 trillion in digital commerce every year, more than double the size of the B2C economy. Is artificial intelligence the rocket fuel to take us through the next decade of marketing technology? AI is not about inventing a new task or a new way of being intelligent, but simply mimicking human intelligence. Given that it's a machine doing the work, AI can be done at infinite scale since it can read and process billions of data points with perfect memory.

Nintendo Reports Second Quarter Losses But 3DS Sales Are Up Thanks To'Pokmon GO' Increasingly, the world is becoming an intelligent, digitally enabled mesh of people, things and services. Technology will be embedded in everything in the digital business of the future, and ordinary people will experience a digitally-enabled world where the lines between what is real and what is digital blur. Rich digital services will be delivered to everything, and intelligence will be embedded in everything behind the scenes. We call this mesh of people, devices, content and services the intelligent digital mesh, and this forms the basis for our Top 10 Strategic Technology Trends for 2017. Artificial Intelligence (AI) and machine learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing or application.

Summary: If you want to capitalize on all the amazing advancements in data science take a look at these two hot growth areas for IoT. It's likely that these will be where a lot of venture capital is invested over the next year or two. A lot of well deserved attention is being directed at speech, image, and text processing. The tools in this area are the CNNs and RNNs we've reviewed in recent articles. We'll continue to exploit and refine these capabilities probably for several more years but if you want to get out in front you really need to be looking for the next wave.

Numerical Optimization is one of the central techniques in Machine Learning. For many problems it is hard to figure out the best solution directly, but it is relatively easy to set up a loss function that measures how good a solution is - and then minimize the parameters of that function to find the solution. I ended up writing a bunch of numerical optimization routines back when I was first trying to learn javascript. Since I had all this code lying around anyway, I thought that it might be fun to provide some interactive visualizations of how these algorithms work. The cool thing about this post is that the code is all running in the browser, meaning you can interactively set hyper-parameters for each algorithm, change the initial location, and change what function is being called to get a better sense of how these algorithms work.

CLO-WTSP: 16,703 labeled audio clips captured by remote acoustic sensors deployed in Ithaca, NY and NYC over the fall 2014 and spring 2015 migration seasons. Each clip is labeled to indicate whether it contains a flight call from the target species White-Throated Sparrow (WTSP), a flight call from a non-target species, or no flight call at all. CLO-SWTH: 179,111 labeled audio clips captured by remote acoustic sensors deployed in Ithaca, NY and NYC over the fall 2014 and spring 2015 migration seasons. Each clip is labeled to indicate whether it contains a flight call from the target species Swainson's Thrush (SWTH), a flight call from a non-target species, or no flight call at all. CLO-WTSP: 16,703 labeled audio clips captured by remote acoustic sensors deployed in Ithaca, NY and NYC over the fall 2014 and spring 2015 migration seasons.

The medical profession is under increasing pressure. A global shortfall in healthcare workers will reach 12.9 million by 2035, according to the World Health Organization. And in China, the shortage of healthcare professionals is even more acute. In response to this, Chinese search engine Baidu launched a medical chatbot named Melody, designed to speed up the process of diagnosing patients. Melody, announced in October, was created for Baidu's Doctor mobile app.

I will update this article regularly. An old version can be found here and has many interesting links. All the material presented here is not in the old version. This article is divided into 11 sections. A laptop is the ideal device. I've been using Windows laptops for years, and I always installed a Linux layer (acting as an operating system on top of Windows), known as Cygwin. This way, you get the benefits of having Windows (Excel, Word, compatibility with clients and employers, many apps such as FileZilla) together with the flexibility and pleasure of working with Linux. Note that Linux is a particular version of UNIX. So the first recommended step (to start your data science journey) is to get a modern Windows laptop (under $1,000) and install Cygwin. Even if you work heavily on the cloud (AWS, or in my case, access to a few remote servers mostly to store data, receive data from clients and backups), your laptop is you core device to connect to all external services (via the Internet). Don't forget to do regular backups of important files, using serives such as DropBox. Once you installed Cygwin, you can type commands or execute programs in the Cygwin console.

There are huge numbers of variants of deep architectures as it's a fast developing field and so it helps to mention other leading algorithms. The list is intended to be comprehensive but not exhaustive since so many algorithms are being developed [1] [2][1],[2]. LAMSTAR is Large memory storage and retrieval neural networks. Google DeepMIND uses this and it is based on reinforcement learning which is a major branch of psychology, aside from evolution. LAMSTAR are increasingly being used in medical and financial applications.

While these have their benefits, will this eventually begin the rise of AI overlords? Deep learning systems are becoming a growing trend in some of the world's largest tech companies. This allows AI systems to be able to "see" and learn for themselves depending on how they are programmed. These are new technologies alongside cloud computing and even speech recognition, among others. However, According to Wired, it appears a lot of companies are being re-oriented toward focusing on AI.