AI has already made a lasting impact in the practice of law. Contracts, e-discovery and overall legal research have all changed thanks to AI, but as computers driven by ever-increasing processing power exhibit extraordinarily intelligent behaviour we can only assume such advances are far from over. Whether within the enterprise, partners, customers, opposing litigants or elsewhere, legal assets cannot hide from the likes of Watson, HAL, or other budding or to-be-conceived AI platforms. Empirical evaluation has found that a continuously adaptive machine learning approach can help lawyers keep an eye on ever-changing legal data, according to Jeremy Pickens, senior applied research scientist, Catalyst Repository Systems, which hosts and services document repositories for large-scale discovery and regulatory compliance. "Implementing a continuous protocol involves more than occasionally retraining an existing machine learning classifier, but rather integrating it into the machine learning system at a native level," Pickens says.

Siri co-founder and CEO Dag Kittlaus has been quietly working on a much-anticipated voice assistant powered by artificial intelligence, machine learning and integrations with third-party services. This product is called Viv and, in a world-first, Kittlaus just gave us a demo at TechCrunch Disrupt NY that shows off the power of what they've built with Viv. Like with Siri, Viv wants to build a conversational and smart layer that lets you interact with various services. But Viv is taking everything one step further. More importantly, there's a developer platform to add more services.

Many of the experiences and interactions people have on Facebook today are made possible with AI. When you log in to Facebook, we use the power of machine learning to provide you with unique, personalized experiences. Machine learning models are part of ranking and personalizing News Feed stories, filtering out offensive content, highlighting trending topics, ranking search results, and much more. There are numerous other experiences on Facebook that could benefit from machine learning models, but until recently it's been challenging for engineers without a strong machine learning background to take advantage of our ML infrastructure. In late 2014, we set out to redefine machine learning platforms at Facebook from the ground up, and to put state-of-the-art algorithms in AI and ML at the fingertips of every Facebook engineer. In some of our earliest work to leverage AI and ML -- such as delivering the most relevant content to each person -- we noticed that the largest improvements in accuracy often came from quick experiments, feature engineering, and model tuning rather than applying fundamentally different algorithms.

Bots and virtual assistants are here to help us with everyday tasks, but because they are scattered across networks and devices, their usefulness remains limited. Now a new product from the developers behind Apple's Siri is looking to connect them and create the world's first virtual assistant marketplace. In Viv's first live demo, Dag Kittlaus demonstrated Viv working across the apps of their "friends" at Weather Underground, Venmo, ProFlowers, Hotels.com and Uber while onstage at TechCrunch Disrupt NY, the annual tech conference held this year in Brooklyn. "I just did four transactions in about two minutes, by talking," Kittlaus said simply after completing the demo. "What I just showed you is a small slice of where we see it headed. For developers, this is going to be the next big marketplace, the marketplace that works with the next generation of devices."

We are continuing to announce the speakers for Data Day Seattle 2016. We have 20 more speakers yet to announce. Check back regularly for updates. If you wish to speak at Data Day Seattle, there is still time to submit a proposal. John Akred is the Founder and CTO of Silicon Valley Data Science. In the business world, John Akred likes to help organizations become more data driven. He has over 15 years of experience in machine learning, predictive modeling, and analytical system architecture. His focus is on the intersection of data science tools and techniques; data transport, processing and storage technologies; and the data management strategy and practices that can unlock data driven capabilities for an organization. A frequent speaker at the O'Reilly Strata Conferences, John is host of the perennially popular workshop: Building A Data Platform.

As we age, we feel we've acquired wisdom from life's varied experiences. Machine learning is a form of artificial intelligence designed to recognize patterns that escape our attention. IBM Watson is assisting Swiss Re by enhancing understanding of potential loss exposures. Chubb 4D, a cognitive computing system, can discern possible fraudulent activities by third parties and identify factors affecting claims severity. Machine learning offers the means for insurance carriers and brokerages to augment the knowledge needed to make sharp underwriting, claims management, customer service and other profit-making decisions.

The Smart Data Online Conference will bring together the insights and training that are helpful in navigating new technologies shared across data management topics such as machine learning, cognitive computing, and artificial intelligence to name a few. It is in this event that we can connect you, the attendee, with the speakers who are working successfully with these new technologies in their daily positions.

As algorithm, machine learning and of course big data are more and more making the headlines and considering that we are inherently very much into what will be the next revolution, we wanted to gather our best readings on these hot topics right here. Our "Algorithm Weekly" will allow you to have an overview of what happened in the world of algorithms this week. To do so, we will pick the 5 best links from our Deep Algo Twitter account (feel free to join us now if you cannot wait for our Friday digest to come). Let's start with this week' selection: a first issue about human emotions, the future of publishing, a potentially deprecated UK banking application and science against poverty. Three developers have created an algorithm able to read human emotions with 99% accuracy.

In partnering with Knorr, we developed an online insights tool which helps consumers understand more about their personal flavour profile and provide them with tailored recipe recommendations. As Knorr already has over 178 years' worth of experience in the art of flavour, cognitive technology was the best fit to leverage this understanding, to identify the complex connection between flavour, our taste preferences and recipes. Interestingly, the cognitive technology that is behind the Knorr Flavour Profiler was recently designed at the Network and Information Sciences International Technology Alliance (ITA). The Cognitive Era is the next step in the application of science to understand nature and improve the human condition.

Singletons looking for love online often boil down their basic criteria to age, sex and location. But perhaps the first question they should be asking is what flavours they like. After all, our taste preferences are far more complex and individual to us, than a mere geographical location or number. The ability to analyse our individual taste preferences, match these with flavour and identifying recipes that suit our personal palate is actually a very complex problem to navigate. This is exactly what Knorr, Unilever's largest brand, has done with the launch of the Knorr Flavour Profiler.