Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification. ConvNets have been successful in identifying faces, objects and traffic signs apart from powering vision in robots and self driving cars. In Figure 1 above, a ConvNet is able to recognize scenes and the system is able to suggest relevant tags such as'bridge', 'railway' and'tennis' while Figure 2 shows an example of ConvNets being used for recognizing everyday objects, humans and animals. Lately, ConvNets have been effective in several Natural Language Processing tasks (such as sentence classification) as well. ConvNets, therefore, are an important tool for most machine learning practitioners today. However, understanding ConvNets and learning to use them for the first time can sometimes be an intimidating experience.

At the recent Spark & Machine Learning Meetup in Brussels, François Garillot of Skymind delivered a lightning talk called "DeepLearning4J and Spark: Successes and Challenges." Specifically, François offered a tour of the DeepLearning4J architecture intermingled with applications. He went over the main blocks of this deep learning solution for the JVM that includes GPU acceleration, a custom n-dimensional array library, a parallelized data-loading swiss army tool, deep learning and reinforcement learning libraries--all with an easy-access interface.

My name is Victoria, and I'll be your conference operator today. Welcome you to the NVIDIA Financial Results Conference Call. All lines have been placed on mute. After the speakers' remarks there will be a question-and-answer period. I will now turn the call over to Arnab Chanda, Vice President of Investor Relations at NVIDIA. You may begin your conference. With me on the call today from NVIDIA are Jen-Hsun Huang, President and Chief Executive Officer, and Colette Kress, Executive Vice President and Chief Financial Officer. I'd like to remind you that our call is being webcast live on NVIDIA's Investor Relations website. You can hear a replay by telephone until the 17 November, 2016. The webcast will be available for replay up until next quarter's conference call to discuss Q4 financial results. The content of today's call is NVIDIA's property. It cannot be reproduced or transcribed without our prior written consent. During this call, we may make forward-looking statements based on current expectations. These forward-looking statements are subject to a number of significant risks and uncertainties and our actual results may differ materially. For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today's earnings release, our most recent Form 10-K and 10-Q, and the reports that we may file on Form 8-K with the Securities and Exchange Commission. All of our statements are made as of today, the 10th of November, 2016 based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During this call, we will discuss non-GAAP financial measures. You can find a reconciliation of these non-GAAP financial measures to GAAP financial measures in our CFO commentary which is posted on our website. Revenue reached a record in the third quarter, exceeding $2 billion for the first time. Driving this was success in our Pascal-based gaming platform and growth in our datacenter platform, reflecting the role of NVIDIA's GPU as the engine of AI computing.

"Algorithm" might be one of the most popular terms that almost no one understands. Not many people have PhDs in data science, and even those experts don't always know what's happening. "It's not clear even from a technical perspective that every aspect of AI algorithms can be understood by humans," says Guruduth Banavar, IBM's chief science officer for cognitive computing, which is what IBM calls AI. Artificial intelligence is making decisions by reviewing people's medical tests in hospitals, credit histories in banking, job applications in some HR systems, even criminal risk factors in the justice system. Yet it's not always clear how the computers are thinking.

Microsoft is teaming up with Elon Musk's OpenAI, the non-profit artificial intelligence research company. OpenAi announced on Tuesday it will work with Microsoft to start running the cloud platform Azure, making it the primary cloud system that OpenAI uses for deep learning and artificial intelligence, a move Microsoft said it was "excited" about. "OpenAI chose Microsoft due to our deep learning research and ongoing commitment to AI, along with Azure's support for open source technologies and its unique combination of high performance computing, big data and intelligence capabilities such as Azure Batch, Azure Machine Learning and the Microsoft Cognitive Toolkit (formerly CNTK)," said Microsoft in a statement. The partnership will work on "democratizing AI and making it accessible to everyone," Microsoft says. The company plans to make this happen by taking that intelligence and infusing it into everyday devices and apps.

Harry Shum (left), Microsoft AI and research group executive vice president, and Sam Altman, co-chair of OpenAI, will be working together on artificial intelligence. Microsoft has formed a partnership with OpenAI, an Elon Musk-based company, to research artificial intelligence. The two companies will focusing on "making significant contributions to advance the field of AI" and will work on their "mutual goal of using AI to tackle some of the world's most challenging problems," Microsoft said Tuesday in a blog post. Microsoft add that it is "committed to democratizing AI and making it accessible to everyone." AI is one of the hottest trends in tech right now, fueled by powerful chips, fast networks and the massive trail of data we all leave behind us as we go about our digital days.

On its own front, Microsoft has been keen to get more folks developing AI, enough to recently open-source the deep learning tools it used to build Skype Translate and Cortana for users to train their own AI. It's also opened its arms to other tech companies, partnering with Google, Amazon, IBM and Facebook in a coalition to trumpet the benefits of AI and agree on best practices. The initiative left out the Elon Musk and Peter Thiel-backed OpenAI, a research project dedicated to democratizing artificial intelligence. But today, the nonprofit announced a separate team-up with Microsoft to run large-scale experiments on the software giant's Azure cloud platform. Azure's open-sourced tools appealed to the nonprofit, as well as its computation-boosting Batch and machine learning capabilities, Microsoft said in a blog post.

IBM's latest Power servers come with an AI twist. Optimized for deep learning, a new so-called PowerAI toolkit will "help train the systems to think and learn in a more human-like way, at a faster pace," as announced at SC16, the International Conference for High Performance Computing, Networking, Storage and Analysis. I spoke with Hillery Hunter, IBM Research's director of Systems Acceleration and Memory and Memory Strategist, about her team's contribution to the software behind the world's fastest deep learning servers. Hillery Hunter: In this case, AI refers to a collection of deep learning frameworks and algorithms. Today's launch represents our first public offering in hardware-software co-optimization for deep learning.

Among the many areas that IBM is pushing forward with its Power architecture is in deep learning. Today IBM announced a new tool called PowerAI that aids in helping organizations learn things faster in a bid to generate advanced artificial intelligence capabilities. "PowerAI contains the major machine, deep-learning open-source software that we have optimized and compiled for our POWER8 with NVIDIA GPU servers," Gupta told ServerWatch. "We are optimizing and getting the best performance out of the Power8 NVLink server and also from a cluster of these servers." The Power8 NVLink capabilities were first announced in September and provides improved I/O capabilities that come from NVIDA.

Microsoft's continued investment in artificial intelligence and machine learning technology is paying dividends. The company has partnered with OpenAI, a non-profit company founded earlier this year to advance the field of machine intelligence for the benefit of humanity. As part of the deal, announced Tuesday, OpenAI will use Microsoft Azure as its primary cloud provider, an important win for Microsoft as it competes with the likes of Amazon, Google, and IBM to power the next generation of intelligent applications. OpenAI is backed by the likes of Tesla CEO Elon Musk, controversial investor Peter Thiel, LinkedIn co-founder Reid Hoffman, and Y Combinator Partner Jessica Livingston. On top of that, Microsoft also launched a set of cloud services all aimed at furthering intelligent applications. The new Azure Bot Service makes it easier for people to spin up intelligent chat bots in Microsoft's cloud, while Azure Functions lets customers run compute functions without provisioning servers.