Like Beyoncé, we now know, Hillary Clinton has hot sauce in her bag. She said so on New York's Power 105.1, so it must be true. Still, Donald Trump doesn't believe her, nor do Rush Limbaugh, Laura Ingraham nor many of Fox News' talking heads. Even Power 105.1 host Charlamagne Tha God kind of accused her of pandering. I think she just likes hot sauce -- and not just because she's on record as a chilehead in interviews going back at least to 2008.

Machine learning has come of age in public health reporting according to researchers from the Regenstrief Institute and Indiana University School of Informatics and Computing at Indiana University-Purdue University Indianapolis. They have found that existing algorithms and open source machine learning tools were as good as, or better than, human reviewers in detecting cancer cases using data from free-text pathology reports. The computerized approach was also faster and less resource intensive in comparison to human counterparts. Every state in the United States requires cancer cases to be reported to statewide cancer registries for disease tracking, identification of at-risk populations, and recognition of unusual trends or clusters. Typically, however, busy health care providers submit cancer reports to equally busy public health departments months into the course of a patient's treatment rather than at the time of initial diagnosis.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

In the US, over one million children suffer from autism. These children find it difficult to recognize emotions through facial expressions, making social interactions very challenging. While patients can gain an understanding through behavioral therapy, this can be both time-consuming and expensive. Now, Autism Glass is a wearable aid from researchers at Stanford University, that uses Google Glass, machine learning and real-time social cues to provide those on the autism spectrum with another option. To use, patients put on the wearable glasses, which incorporate an outward-facing camera.

This post contains my answers from a Quora session I did on machine learning and artificial intelligence. Each section contains a link to the original Quora question, the overall session can be found here. Think carefully about what you actually want to achieve with it. Most fall into the latter camp, but it seems everyone fancies themselves as containing a bit of the former (particularly if they think they're going to solve AI). To do the former well, in the international community, requires really good foundations (particularly in mathematics) followed by a PhD with a supervisor who has experience of how that community works. Doing the second well is much easier from the perspective of learning machine learning. A data generator would often be a scientist or company that is working in a particular application and wants answers. They need access to machine learning researchers or statisticians to give advice on how to answer those questions. They should try and collaborate with experts in data analytics and data science, but they should be careful, there is a lot of hype around the term'big data' at the moment. It's a difficult area to navigate. Data generators typically need an interface to consume machine learning (or statistics) effectively, if this interface is poorly chosen a lot of wasted resource can result (things get very expensive very quickly for a lot of data generators!). A data consumer is where the largest demand is right at the moment, and should probably be the starting point for someone who wants to move in the right direction. An MSc in Data Science would be a good starting point. You can also use this experience to see if you want to transit into a machine learning generator (that's basically what happened to me). What are you passionate about? That is the route in to any subject. Is it a particular approach to learning or a particular application?

A team of scientists at the California NanoSystems Institute at UCLA recently developed a new technique using artificial intelligence to efficiently detect cancer cells without damaging blood samples. Despite the latest reports claiming the development of artificial intelligence (AI) could end humanity within decades, it recently proved its use in cancer diagnosis. University of California Los Angeles researchers found a new method of detecting cancer cells faster and more accurately without destroying them. In the study published in the journal Nature Scientific Reports, scientists at the California NanoSystems Institute at UCLA revealed they've developed a new device that combines a special microscope with an artificial intelligence algorithm. This innovation aimed to identify cancer non-destructively, Popular Science notes.

Artificial intelligence has dominated headlines recently, highlighting the best and worst of its capabilities and suggesting there is still work to be done and improvements to be made. News of Microsoft's Tay, an artificially intelligent bot which was created to mimic the personality of a 19-year old woman, quickly turned sour as it seemed to transform into a'bitter racist' on the social media website twitter. When Microsoft was asked to confirm whether the bot had been shut down, it responded: "The AI chatbot Tay is a machine learning project, designed for human engagement. "As it learns, some of its responses are inappropriate and indicative of the types of interactions some people are having with it. A more successful venture into AI was seen in Google's AlphaGo artificial intelligence after it defeated Go world champion Lee Se-dol twice. Se-dol said after the second defeat: "I am quite speechless… I feel like AlphaGo played a nearly perfect game."

Whether we have been in a tech bubble or not is frankly not that interesting. What is interesting is that the foundation for innovation is as strong as we've ever seen and entrepreneurs are bringing the future to reality at an amazing pace. Here are a few of my predictions for what we'll see in 2016: So far most conversations around self-driving cars focus on personal vehicles. It's unlikely we'll take a fully autonomous car for our daily commute for quite a few years, but commercial trucking will see self-driving vehicles emerge far sooner. One company, Peloton, is already making this a reality.

And I immediately think they will die irrelevant.

Hackathon[3]: "New Realities" examined what's real in the shrinking gap between our physical and digital lives. In terms of existing and emerging technology, reality is whatever we are capable of. We can talk to our TV with Siri, live inside a game with Oculus Rift or travel anywhere through Google Street View. There's never been a time of more reality-challenging innovation, as our Hackathon[3] teams demonstrated in a quick-turn all-or-nothing competition built on the latest forms of what's possible.] "Knack," the winning project, made sales empathy a reality. Knack is a product that demonstrates how artificial intelligence and organic intelligence empower a sales force to sell to the person and not to the script.