Deal activity in artificial intelligence has now hit record highs for two quarters straight. Deal count had already leapt to 24 in Q4'15, ten more deals than the previous quarter. The trend continued in Q1'16, with deals reaching a 5-year quarterly high, and passing the 25-deal threshold. However, total funding dropped 18% to 83M from 101M in Q4'15, when over 20 companies raised funds. Our artificial intelligence category covers startups primarily focused on developing AI technologies, across areas including image processing, natural language processing, machine learning, deep learning, and predictive APIs, among other core applications.

Salesforce, creators of the world's leading CRM platform, has acquired MetaMind, a deep learning startup to leverage its expertise in artificial intelligence (AI) to better tailor and automate customer support. Founded in late 2014, by Richard Socher, MetaMind focused on creating recursive neural networks which Socher actively worked on while pursuing his Ph.D. at Stanford University. The terms of the deal are yet to be disclosed, but the acquisition was backed by Marc Benioff, Co-Founder and CEO, Salesforce. Richard Socher, Co-Founder, CEO, MetaMind, wrote in his blog, "With MetaMind and Salesforce coming together, we'll be able to offer customers real AI solutions with breakthrough capabilities that further automate and personalize customer support, marketing automation, and many other business processes. We'll extend Salesforce's data science capabilities by embedding deep learning within the Salesforce platform."

SAN JOSE, Calif.--Nvidia for much of its two-plus decades of life made most of its money by manufacturing and selling GPUs for gaming systems. While the bulk of the company's revenues still come from its mainstream graphics technologies, Nvidia over the past several years has been aggressively pushing into new growth areas, particularly virtual reality (VR), connected cars, and deep learning and artificial intelligence (AI). That pivot into these emerging markets has been on full display here this week at the company's GPU Technology Conference (GTC), an event whose growth has mirrored the rise in importance of GPUs in such areas as accelerated computing and high-performance computing (HPC). In 2012, 2,350 people attended GTC; this year, more than 5,000 are here. In his keynote address April 5, CEO Jen-Hsun Huang made announcements in all the new target areas, from technologies designed to make VR worlds more real to products aimed at accelerating innovation in deep learning.

In the third issue of this monthly digest series you can find out how Microsoft is bringing AI to the visually impaired, how to colorize your grayscale images, why a Google car caused a crash for the first time, and much more. Last Thursday, Microsoft showed off its Seeing AI app for the first time. It's still under development, but it looks extremely promising. Using a smartphone camera or a pair of camera-equipped smart glasses, the Seeing AI app can identify things in your environment--people, objects, and even emotions--to provide important context for what's going on around you. By a swipe of hand, the user can instruct the app to take a snapshot of the current visual scene and run it through image recognition software.

Jen-Hsun Huang, CEO of the chipmaker Nvidia, is either very prescient or very lucky. His company was built around graphics processing units (GPUs) for video games. But those same chips are now widely used in artificial-intelligence projects such as efforts to build self-driving cars. Nvidia's chips turned out to be especially efficient for training the neural networks used in a technique called deep learning that has recently made software much smarter and caused tech giants and investors to pile money into machine-learning research. This week the company announced a new chip designed specifically for the task (see "A 2 Billion Chip to Accelerate Artificial Intelligence").

AI or Artificial Intelligence recently made global news when an AI program beat a human opponent at GO (a Chinese board game). This win underscores the significant progress made in machine learning and the ability of a computer to model human logic. The game is so complex that up until this point experts had thought that it would take ten more years before a computer could beat humans at GO. Unbeknownst to many, Google is behind DeepMind, the company which built the AlphaGo computer program that won the game. Google is very public about their devotion to using machine learning in their products and services. With access to vast resources of data to draw upon, Google has become one of the biggest corporate sponsors of AI, investing heavily in it for videos, speech, translation and search.

Chatbots, also called Conversational Agents or Dialog Systems, are a hot topic. Microsoft is making big bets on chatbots, and so are companies like Facebook (M), Apple (Siri), Google, WeChat, and Slack. There is a new wave of startups trying to change how consumers interact with services by building consumer apps like Operator or x.ai, bot platforms like Chatfuel, and bot libraries like Howdy's Botkit. Microsoft recently released their own bot developer framework. Many companies are hoping to develop bots to have natural conversations indistinguishable from human ones, and many are claiming to be using NLP and Deep Learning techniques to make this possible.

There's already plenty of angst out there about the prospect of jobs lost to artificial intelligence, but this week, artists got a fresh reason to be concerned. A new "Rembrandt" painting unveiled in Amsterdam is not the work of the Dutch master Rembrandt van Rijn at all, but rather the creation of a combination of technologies including facial recognition, AI, and 3D printing. Essentially, a deep-learning algorithm was trained on Rembrandt's 346 known paintings and then asked to produce a brand-new one replicating the artist's subject matter and style. Dubbed "The Next Rembrandt," the result is a portrait of a caucasian male, and it looks uncannily like the real thing. One particularly interesting detail about The Next Rembrandt project, which was a collaboration among several organizations including Dutch bank ING and Microsoft, is how the algorithm chose the subject for its painting, since it had to be entirely new.

There's already plenty of angst out there about the prospect of jobs lost to artificial intelligence, but this week, artists got a fresh reason to be concerned. A new "Rembrandt" painting unveiled in Amsterdam is not the work of the Dutch master Rembrandt van Rijn at all, but rather the creation of a combination of technologies including facial recognition, AI, and 3D printing. Essentially, a deep-learning algorithm was trained on Rembrandt's 346 known paintings and then asked to produce a brand-new one replicating the artist's subject matter and style. Dubbed "The Next Rembrandt," the result is a portrait of a caucasian male, and it looks uncannily like the real thing. One particularly interesting detail about The Next Rembrandt project, which was a collaboration among several organizations including Dutch bank ING and Microsoft, is how the algorithm chose the subject for its painting, since it had to be entirely new.

Nvidia has announced its DGX-1 Deep Learning System at the 2016 GPU Technology Conference. That might not mean much to the average PC fan, but in context that is over twelve times the graphics performance of the Nvidia Titan X, it's most expensive and powerful graphics card on the market. The Tesla GP100 is based on TSMC's 16nm FinFET manufacturing process, and uses High Bandwidth Memory (HBM2) for the first time. Nvidia is the first to adopt both features, before Intel or AMD, though Samsung has been using the 16nm manufacturing process since late 2015. Rather than make the GPU slimmer with the new manufacturing process, Nvidia has added a lot more transistors to the card.