Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It's incredible, but it can also be overwhelming. That's why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments.

Salience 6.2 also includes improvements in email processing, enabling systems to ingest email databases while stripping out headers and footers, eliminating duplicate emails, and analyzing email threads. Also included is improved named entity recognition, combining machine learning and known lists of people, places, and things. With these improvements, Lexalytics has increased its precision and recall scores, known as F1 scores, by up to 25 percent. The product has also been upgraded to better recognize people and place names from much of Asia, particularly China, Japan, and Korea. This follows Lexalytics's strong growth in that part of the world.

At first there were a lot of different opinions, but now, almost everybody agrees that big data was able to take over the whole business world. A lot of businesses are relying on it and improving the tools they use for taming big data on a daily basis. They all agree that the importance of big data is huge and that everyone who wants to stay competitive in the business world needs to pay a lot of attention to it. However, a lot of people are wondering what will be the next step? Will big data be able to grow in the future?

The currently ongoing Seizure Prediction competition--hosted by Melbourne University AES, MathWorks, and NIH--invites Kagglers to accurately forecast the occurrence of seizures using intracranial EEG recordings. This competition uniquely focuses on seizure prediction using long-term electrical brain activity from human patients obtained from the world first clinical trial of the implantable NeuroVista Seizure Advisory Sytem. In this blog post, you'll learn about the contest's potential to positively impact the lives of those who suffer from epilepsy, outcomes of previous seizure prediction contests on Kaggle, as well as resources which will help you get started in the competition including a free temporary MATLAB license and starter code. This competition is sponsored by MathWorks, the National Institutes of Health (NINDS), the American Epilepsy Society and the University of Melbourne, and organised in partnership with the Alliance for Epilepsy Research, the University of Pennsylvania and the Mayo Clinic. For many people with epilepsy, seizures reoccur at random times and greatly disrupt their cognitive and emotional state, their ability to work and drive, and their social and economic situation.

A popular method for exploring high-dimensional data is something called t-SNE, introduced by van der Maaten and Hinton in 2008. The technique has become widespread in the field of machine learning, since it has an almost magical ability to create compelling two-dimensonal "maps" from data with hundreds or even thousands of dimensions. Although impressive, these images can be tempting to misread. The purpose of this note is to prevent some common misreadings. We'll walk through a series of simple examples to illustrate what t-SNE diagrams can and cannot show.

The approach to life and the source of livelihood has a great potential of being reshaped, thanks to Artificial Intelligence (AI) and robotics. However, there is a need for supervision to be practiced as there are issues, which may arise as result of the technology being left untamed. The MPs who are in the science and technology committee have made a call for a thorough inspection to be done for any probable legal, societal or ethical impact. The committee sees it best that the government should look into establishing a competent commission that will address the issues adequately. This means that humans will need to acquire a new set of skills since artificial intelligence would have taken over their jobs and left them with no means of livelihood.

When we use our muscles, they produce heat as a byproduct. When we use them a lot, we need to actively cool them, which is why we sweat. By sweating, we pump water out of our bodies, and as that water evaporates, it cools us down. Robots, especially dynamic robots like humanoids that place near-constant high torque demands on their motors, generate enough heat that it regularly becomes a major constraint on their performance. One of the reasons that SCHAFT did so well at the DRC Trials, for example, was their fancy liquid-cooled motors that could put out lots of torque over an extended period of time without overheating.

The one product to watch from Google's hardware event is Google Assistant. At Google's hardware event on Tuesday, several products were released, including two phones, a smart home device, a wireless router, a VR Headset and a new Chromecast (Ultra). Each product is worthy of its own article, but they are mere fragments of the bigger picture, which is Google Assistant. As Sundar Pichai (CEO of Google) stated, there has been a big shift in computing approximately every decade since the PC was launched in the mid '80s. In the '90s, we got the Web and in the 2000s, the world got the smartphone.

As one of our mobility analysts at Blue Hill, I get (perhaps unduly) excited over any shiny new gadget, even though I've recently been disappointed by what seems like a lack of innovation in the mobile market (cue the "I miss the old Apple" rant). That's why I was excited, but skeptical, to cover Google's October 4th product announcement of its long anticipated "first" smartphone. But it's really not the hardware Google is focusing on with its most recent product launch, though it could certainly seem that way from its unveiling of the Pixel (the first Google branded smartphone), the Daydream View virtual reality (VR) headset, and the Google Home smart hub. No, it hasn't been about hardware for the past few years for mobile device manufacturers it certainly seems, with only small incremental changes being made to hardware (or, in the case of Apple's removal of the headphone jack, gigantic leaps and bounds of courage … but that's another story). Most of the focus of smartphone innovation instead has been coming from within: with the software, and most recently, artificial intelligence.