The industry and users have a love/hate relationship with UVM. It has quickly risen to become the most used verification methodology and yet at the same time it is seen as being overly complex, unwieldy and difficult to learn. The third day of DAC gets started with breakfast with Accellera to discuss UVM and what we can expect to see in the next 5 years. The discussion was led by Tom Alsop, principle engineer at Intel. Alsop's first question to the panelists was, where do you see UVM in the next 5 years?

A new release out of the company reports, "Romonet today announced it is filing for a number of new patents for the next phase of its data center intelligence platform, utilizing the applications of Machine Learning. The company is known as the leader in data center analytics and this development enhances the value of Romonet's already patented solution. 'We have been working on advanced data handling and Machine Learning algorithms for over a year, focusing predominantly on enhancing our solution to learn and become as proficient as our human data scientists are today at identifying anomalies, and tracking down the cause behind the symptom. This capability provides powerful operational and business insight into data center systems and component level performance,' said Liam Newcombe, Romonet's co-founder and CTO."

What do you get when you take the former head of platform at Facebook, a former Mozilla engineer, veterans of other companies like Microsoft and Amazon, and an interest in building an assistive chatbot that stands apart from competitors in the space? The answer is Ozlo, a chatbot in the form of a cute, blue critter that answers questions from users with cards that contain deep links to relevant apps and websites. The company built around the service – headed up by CEO Charles Jolley, the former Facebook platform head – has offices in Palo Alto and Seattle and a workforce of 28. MUST READ: iPhone 7: Seriously, this phone sounds boring to you? And it landed a 14 million investment in May from Greylock and AME Cloud Ventures partly because Ozlo represents something a little different in a world that's starting to move from apps to more voice interaction with our devices.

The O'Reilly AI Conference will cover all the most essential--and intriguing--topics in applied AI. And you'll meet the brightest minds in applied AI, including keynotes from Microsoft's Lili Cheng, Peter Norvig of Google, and Facebook's Yann LeCun. Urs Muller from NVIDIA will address learning for autonomous driving. Google's Martin Wicke will dive into scalable machine learning. Hilary Mason will describe her work implementing AI at Fast Forward Labs.

On October 14-15, 2016, the NYU Center for Bioethics in conjunction with NYU Center for Mind, Brain and Consciousness will host a conference on "The Ethics of Artificial Intelligence". Recent progress in artificial intelligence (AI) makes questions about the ethics of AI more pressing than ever. Existing AI systems already raise numerous ethical issues: for example, machine classification systems raise questions about privacy and bias. AI systems in the near-term future raise many more issues: for example, autonomous vehicles and autonomous weapons raise questions about safety and moral responsibility. AI systems in the long-term future raise more issues in turn: for example, human-level artificial general intelligence systems raise questions about the moral status of the systems themselves.

Google's artificial intelligence division, DeepMind, has teamed up with a hospital in England on a research project that could lead to detecting vision loss and other eye problems sooner, Popular Mechanics writes. The article says the project calls for giving DeepMind's computer more than a million anonymous eye scans to let it learn patterns and make predictions. DeepMind's idea is to train AI to detect early signs of age-related macular degeneration as well as vision loss related to diabetes.

This spring, IBM opened a new center in Cambridge for its "cognitive intelligence" software, also known as Watson. Watson is ready to analyze vast quantities of data and spit out deep insights. All that intelligence, according to an IBM release from September, represents nothing less than "a new era in computing." Thirty years earlier, IBM was setting up another office a few blocks away to focus on the then-trendy realm of artificial intelligence. In the summer of 1986, IBM executive Herbert Schorr told an AI conference, "We look at artificial intelligence as an extremely timely technology that is ready for commercial applications."

Neural Networks are a family of Machine Learning techniques modelled on the human brain. Being able to extract hidden patterns within data is a key ability for any Data Scientist and Neural Network approaches may be especially useful for extracting patterns from images, video or speech. The following blog aims to explain at a high level how these methods work and key things to bear in mind. At first these weights should be randomized. In a basic neural network, you train the system by running individual cases through one at a time and updating the weights based on the error.

Seattle-based machine learning startup Dato, which originally launched as GraphLab, announced today that it has changed its name again. Now, the company is known as Turi, an ode to computer science legend Alan Turing. This past September, Turi -- then Dato -- found itself in a trademark infringement argument with fellow tech startup Datto after Dato changed its name from GraphLab in January 2015. Datto, which has been offering data backup and recovery services from its Connecticut headquarters since 2007, first complained about Dato's new name just weeks after the company finished its rebranding from GraphLab. Datto argued that Dato's new name would cause confusion.

Scientists are closer to creating a computer with emotions. Researchers in Russia are expected to reveal an emotional computer within a year and a half, which will be able to think like a person and build up trust, its creators say. The system, called'Virtual Actor', is being created by the National Research Nuclear University in Moscow. Computers are machines used for practical reasons, without any emotion involved. The AI, called'Virtual Actor', is expected to be online within the next year and a half.