Anima Anandkumar is giving a talk at Strata Hadoop World San Jose and a tutorial and talk at Strata Hadoop World London. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the Data Show, I spoke with Anima Anandkumar, a leading machine learning researcher, and currently a principal research scientist at Amazon. I took the opportunity to get an update on the latest developments on the use of tensors in machine learning.

Google has already carved out a niche for itself in machine learning with projects like TensorFlow and Google Brain. Now, it's adding data science provider Kaggle, which runs contests related to machine learning and provides services for data discovery and analysis, to the fold. The company also is moving ahead with other machine learning projects, including an API providing intelligence for video. Google Cloud is gaining access to Kaggle's community of more than 850,000 data scientists and vice versa. Kaggle and Google Cloud will continue to support machine learning training and deployment, while the community gets the capability to store and query large data sets.

As robots continue to play a growing role in our daily lives, white collar jobs in many sectors including accounting and financial operations are quickly becoming a thing of the past. Business are gravitating towards software to automate bookkeeping tasks, saving considerable amounts of both time and money. In fact, since 2004, the number of full-time finance employees at large companies has declined a staggering 40% to roughly 71 employees for every $1 billon of revenue, down from 119 employees, according to a report by top consulting firm The Hackett Group. These numbers show that instead of resisting change, companies are embracing the efficiencies of this new technology and exploring how individual businesses can leverage automation and, more importantly, artificial intelligence – aka robots. As technology becomes more sophisticated and particularly with the use of Artificial Intelligence (AI) we're able to automate multiple steps in a process.

Although China could initially only observe the advent of the Information-Technology Revolution in Military Affairs, the People's Liberation Army might presently have a unique opportunity to take advantage of the military applications of artificial intelligence to transform warfare. When the United States first demonstrated its superiority in network-centric warfare during the first Gulf War, the PLA was forced to confront the full extent of its relative backwardness in information technology. Consequently, the PLA embarked upon an ambitious agenda of "informatization" (信息化). To date, the PLA has advanced considerably in its capability to utilize information to enhance its combat capabilities, from long-range precision strike to operations in space and cyberspace. Currently, PLA thinkers anticipate the advent of an "intelligentization Revolution in Military Affairs" that will result in a transformation from informatized ways of warfare to future "intelligentized" (智能化) warfare.

No longer the subject of science fiction, Artificial Intelligence (AI) is profoundly transforming our daily lives. While computers have been mimicking human intelligence already for some decades using logic and if-then kind of rules, massive increases in computational power are now facilitating the creation of'deep learning' machines i.e. algorithms that permit software to train itself to recognize patterns and perform tasks, like speech and image recognition, through exposure to vast amounts of data. These deep learning algorithms are everywhere, shaping our preferences and behaviour. Facebook uses a set of algorithms to tailor what news stories an individual user sees and in what order. Bot activity on Twitter last year suppressed a protest against Mexico's now-president by overloading the hashtag used to organize the event.

A camera shield for a computer, which allows the user to block the camera when not in use. SAN FRANCISCO – So it looks as if the CIA could potentially break into most smart phone or computer networks, at least according to the stolen documents released by WikiLeaks on Tuesday. Whether you have anything to hide or not, it's a good reminder that in a digital age, keeping your life private requires some work. Here's a list of nine things everyone should be doing already to keep their information relatively confidential, plus four more for the truly paranoid. The most common way the CIA's cyber tools, and hackers for that matter, get into your devices are via phishing emails or texts.

This is my Machine Learning Flipboard. It is updated frequently and brings many issues to the forefront on the topic. Machine learning is perhaps the hottest of the AI subgroups since that is what we all want, our devices to learn our tendencies and help us then to either avoid the event or take advantage of it.

One area of business that stands to benefit from machine learning is customer service. Technologies like natural language processing and sentiment analysis can help companies better understand how to respond to customer feedback and questions. At the 2017 Google Cloud Next conference in San Francisco, Apoorv Saxena, a product manager on the Google Cloud team, hosted a breakout session explaining how organizations can use Google products to improve their customer service. He began by outlining the two different approaches that companies can take to machine learning. The first approach, Saxena said, is to use pre-trained models in the form of APIs to handle the machine learning needs of the company.

Artificial intelligence is everywhere: your smartphone, on streaming platforms such as Spotify and Netflix and even in some smart home appliances. But can the technology, which has seemingly caught the attention of most VCs across the world, be used in the realm of healthcare to drive efficiency and optimise patient outcomes? We take a look at some of the UK's most promising companies using AI to transform the healthcare space. No list of this kind would be complete without a mention of DeepMind, a British artificial intelligence company founded in 2010 and acquired by tech giant Google for a reported £400m four years later. DeepMind Health is leveraging machine learning technology – a form of AI – to boost the medical research field.

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