How much progress has Facebook co-founder and CEO Mark Zuckerberg made in fulfilling his New Year's resolution for 2016? Zuckerberg said in a Jan. 3 Facebook post that his personal challenge for 2016 was to use artificial intelligence to create a personal assistant, which he described as his own version of Jarvis from Iron Man. On Monday, he offered a detailed update on Jarvis, and highlights follow. So far this year, I've built a simple AI that I can talk to on my phone and computer; that can control my home, including lights, temperature, appliances, music and security; that learns my tastes and patterns; that can learn new words and concepts; and that can even entertain Max. It uses several artificial intelligence techniques, including natural language processing, speech recognition, face recognition and reinforcement learning, written in Python, PHP and Objective C. In this note, I'll explain what I built and what I learned along the way. Before I could build any AI, I first needed to write code to connect these systems, which all speak different languages and protocols.

Presbyterian reverend Thomas Bayes had no reason to suspect he'd make any lasting contribution to humankind. Born in England at the beginning of the 18th century, Bayes was a quiet and questioning man. He published only two works in his lifetime. In 1731, he wrote a defense of God's--and the British monarchy's--"divine benevolence," and in 1736, an anonymous defense of the logic of Isaac Newton's calculus. Yet an argument he wrote before his death in 1761 would shape the course of history.

What programming language should one learn to get a machine learning or data science job? It is debated in many forums. I could provide here my own answer to it and explain why, but I'd rather look at some data first. After all, this is what machine learners and data scientists should do: look at data, not opinions. So, let's look at some data.

Over 3/4 of Marketing Leaders believe the future belongs to Artificial Intelligence. In October 2015, in my post entitled "The Future Of Sales Is AI: Are Your Sales Teams Prepared?" I shared a bold prediction from LeadGenius cofounder Anand Kulkarni: "In just 10 years most salespeoples' jobs will be replaced by artificial intelligence." As I wrote then and as I believe today, sales is not going away. Salespeople are not going away.

At some point in the course of pregnancy, a woman is likely to suspect that the baby she is incubating has somehow hijacked her brain. New research suggests that, in some sense, she's right, and that pregnancy itself is altering her brain like no other experience she's had since adolescence. The places where a pregnant woman's brain shrinks are very specific, the research says. The structural renovations wrought by pregnancy appear to overlap almost perfectly with the brain regions that play a key role in how we understand and interpret the actions, intentions and feelings of others. And the brain of a first-time mother stays changed -- for at least two years after she has given birth, according to the new research, published Monday in the journal Nature Neuroscience. Pregnant women did not lose intellectual ground, the researchers found: as a group, their working memory and memory for words was no better or worse than before pregnancy.

According to Tech Spot, the concept of having a machine capable of reacting in an intelligent way has been until very recently a matter of science fiction. However, this concept is certainly very compelling and scientists were working on transform this into reality. We are now on the verge of creating this new reality. The general public, however, is not yet informed of what concepts such as neural networks, artificial intelligence and deep learning represent. Much of the current efforts in the field of deep learning technology are related from the simplest level to the very rapid recognition and classification of objects.

Me: I'd like to order a pizza Chatbot: What kind would you like? Me: What toppings do you have? Chatbot: I have pepperoni, sausage, Canadian bacon, ham, pineapple, mushrooms, peppers. Would you like to hear more? Me: Yes Chatbot: I also have ground beef, onions, spinach, tomatoes, cherry tomatoes, parmesan, and extra cheese, Would you like to hear more? Chatbot: What size would you like?

Why does deep learning work now, but not 20 years ago, even though many of the core ideas were there? In one sentence: We have more data, more compute, better software engineering, and a few algorithmic innovations (many layers, ReLUs, better initialization and learning rates, dropout, LSTMs). But why does gradient-based optimization work at all in neural nets despite the non-convexity? One possible, partial answer is overprovisioning: There are generally many hidden units, and there are many ways a neural net can approximately implement the desired input-output relationship. You only need to find one.

PanARMENIAN.Net - AT&T's new chat bot is named Atticus, designed to talk at you about pop culture for hours. He has all kinds of fun trivia about television programs, and according to a video he's "a goofball!" Also according to this promotional video, "It's hard to believe he's not real!" In Atticus' own words about himself: "If the Dunphy family is looking for another kid, I'd be happy to join them. Especially since I don't physically exist. We'd be a real Modern Family."

When Google launched Penguin 4.0 some folks speculated that it was using some sort of machine learning (or RankBrain) to get better by itself. I mean, it sounds nice and all but no where in Google's announcement did it mention machine learning - and trust me - Google wants to use ML in their marketing and PR as much as possible. Well, Google's Gary Illyes told Jennifer Slegg that Google is not using Machine Learning in Penguin. This was via a simple Twitter exchange where Jennifer asked "Is Penguin a machine learning algorithm, or use any kind of supervised or unsupervised learning?" Gary Illyes responded, in short, "nope."