DeepMind, a research lab that was acquired by Google for £400 million, has become a well known entity in the field of artificial intelligence (AI) for building agents that can learn and master games such as arcade classic "Space Invaders" and the ancient Chinese board game of "Go". Over the last year, the five-year-old company, which employs approximately 250 people in London, has been branching out and applying its self-learning algorithms to fields such as healthcare and energy. On the latter, it's helped Google to slash the electricity bill in its data centres worldwide and it's now exploring how it can help the National Grid to predict demand. But Demis Hassabis, DeepMind's cofounder and CEO, announced on Sunday that the company isn't about to turn its back on the gaming field any time soon. In fact, Hassabis wrote on Twitter that DeepMind has been busy improving the AlphaGo [AG] agent that beat Lee SeDol, the world's best Go player, earlier this year.

Natural language processing has reached an important milestone. Sophisticated chatbots are now available as white label and open source offerings while larger technology companies are releasing Virtual Personal Assistants capable of performing complex tasks via voice commands, from ordering goods and services to acting as a smart hub for smart homes. These new categories of products and services are set to revolutionise customer care, search and discovery, and the provision of goods and third party services. Join pioneers from this exciting new space to learn how AI is set to radically transform how we interact with the world around us.

The secret of change is to focus all of your energy, not on fighting the old, but on building the new. Intel Corporation (NASDAQ:INTC), in the face of a declining PC market projected to decline still further, with disruptive factors at play in the data center market, and with the company's revenues across all business segments largely static over the last four quarters, is in the throes of developing responses to their significantly changing business environment. Despite a rise in Intel's overall revenue of 9.1% YoY in 3Q16 to a record high of $15.8 billion, largely due to unexpectedly high sales in the PC market, just two segments - the Client Computing Group and the Data Center Group - contributed 85% of the company's earnings. With the PC market in structural decline, increasing big cloud provider data center market control, and greatly increased data center competition, Intel is faced with shrinking defensive flexibility, which does not bode well for its long-term future. Performance in 4Q16 is expected to retreat from 3Q16 levels, as distribution channels reduce their stock.

Both Machine Learning and Artificial Intelligence has become poplar topics in the tech world recently. With the uprise of products using either Machine Learning or Artificial Intelligence, or both, there's bound to be more jobs popping up for people with those qualifications. Which makes this bundle pretty important. And right now we are offering up The Machine Learning and Artificial Intelligence Bundle for just $39, that's 91% off of the regular price, making it a great time to pick up this bundle. There are four courses included in this bundle, each are typically $120.

We build partnerships with leading global organizations to assemble complex datasets and gain insight into their business needs. We target scalable problems faced by many clients. We develop models that predict actionable insights for our partners. We use state-of-the-art machine learning techniques and infrastructure and apply rigorous measures of success. We iterate to transform models into standalone products.

San Francisco (AFP) - Mark Zuckerberg envisions a software system inspired by the "Iron Man" character Jarvis as a virtual butler managing his household. The Facebook founder's dream is about artificial intelligence, which is slowly but surely creeping into our daily lives, no longer just science fiction. Artificial intelligence or AI is getting a foothold in people's homes, starting with the Amazon devices like its Echo speaker which links to a personal assistant "Alexa" to answer questions and control connected devices such as appliances or light bulbs. Analyst Carolina Milanesi of the research firm Creative Strategies said that "2016 was the year about raising awareness, and exposing consumers to the idea of AI in a more mass market way." Milanesi said it may take time for the technology to fulfill its potential, noting that companies need "a strong hook" to bring large numbers of consumers into this world.

Technology is really a marvel. So often, as new advances come out that allow us to do things that were thought impossible in the past, we hear the phrase "The future is now." Popular Science and XPRIZE are teaming up to explore and explain technologies like these in a video series called Future First. Episode thirteen of Future First is titled "Brain Hacking With Video Games." In it, we take a look at how new technologies--including virtual reality--help us to track activity within the human brain in real time, how different experiences affect different parts of the brain, and how we can use that information to further our knowledge of the mind.

Although investors scrambled--and shelled out up to $185,000 a pop--for the chance to snatch up the new domains and profit as gatekeepers, uptake among end-users has been underwhelming. More than three years after the program's launch, roughly 26 million new generic top-level domains have been registered, compared with the 164 million registered "legacy" top-level domains. Cyrus Namazi, the vice president of domain-name services and industry engagement at ICANN, acknowledged that demand for new top-level domains won't eclipse that for legacies "any time soon." Yet Namazi believes registrations for the new extensions will continue to grow. "We are in the embryonic stages of the expansion," he said.

Among the many R packages, there is the outbreaks package. It contains datasets on epidemics, on of which is from the 2013 outbreak of influenza A H7N9 in China, as analysed by Kucharski et al. (2014): I will be using their data as an example to test whether we can use Machine Learning algorithms for predicting disease outcome. To do so, I selected and extracted features from the raw data, including age, days between onset and outcome, gender, whether the patients were hospitalised, etc. Missing values were imputed and different model algorithms were used to predict outcome (death or recovery). The thus prepared dataset was devided into training and testing subsets. The test subset contained all cases with an unknown outcome. Before I applied the models to the test data, I further split the training data into validation subsets.

Google Open Sources Data Visualization Tool for Machine Learning By Jaikumar Vijayan Posted 2016-12-12 Print Google's Embedding Projector web applications will give developers a way to visualize how well their machine learning systems are interpreting data. Google has open sourced its Embedding Projector, a web application that gives developers a way to visualize data that's being used to train their machine learning systems. Embedding Projector is part of TensorFlow, the machine learning technology behind some popular Google services like image search, Smart Reply in Inbox and Google Translate. The company released TensorFlow to the open source community last year in order to spur more development activity in the field. In a technical paper, Google researchers described the Embedding Projector as an interactive visualization tool that developers can use to interpret machine-learning models that rely on what are known as "embeddings."