The majority of us know our age thanks to the birthday we celebrate each and every year. Yet there are poor orphans around the world who have their birth date shrouded in a mystery. Some of them would love to know when they were born in the first place. A new form of blood test may predict with 100% accuracy what the blood donor's chronological age is. AI is being used to test blood and find out the age of the patients who have had samples of their blood taken for analysis.

When Bob Greifeld became Nasdaq's CEO in 2003, he was presented with outdated tools and a company that was bleeding cash and rapidly losing market share. Thirteen years later, Nasdaq has the largest market share for options and equities of any exchange in the US. Through acquisitions and partnerships, Greifeld has shaped Nasdaq into what he primarily views as a cutting-edge technology company. During a recent interview with Business Insider, Greifeld discussed his vision for the future of Nasdaq and how it fits into the exchange industry. What follows is that portion of our interview, edited for length and clarity.

Professor Damith Herath will speak about artificial intelligence and robotics at King O'Malley's Pub on May 25 as part of Canberra's first Pint of Science series. Canberra will raise a glass to a fresh take on politics in the pub this week as the Pint of Science festival debuts in the capital. The national series, funded by the Australian Department of Industry, Innovation and Science and the ACT government, brings some of the most brilliant scientists into city pubs to discuss their latest research and field questions about their findings. The action will begin on Monday at King O'Malley's in Civic. For just 5 punters can delve into how we learn and the power of the brain at Beautiful Mind from 7pm. At the same time on Tuesday evening ANU professor of physics Daniel Shaddock and ANU vice-chancellor Brian Schmidt will explain how we listen to and measure things in space at Ever Expanding Gravitational Pull.

Toyota Motor Corp. said it will work with Dean Kamen, inventor of the Segway human transporter, to develop advanced wheelchairs for disabled people and aging populations worldwide. The agreement announced Saturday gives the world's largest automaker a license to use balancing technology that Kamen has installed in prior generations of wheelchairs for medical rehabilitative therapy and other purposes. The agreement will also help Kamen introduce a new version of his iBOT wheelchair, which used two sets of powered wheels to walk up and down stairs and help disabled people stand face-to-face with companions. Kamen stopped selling the iBOT in 2009. "It is important to help older adults and people with special needs live well and continue to contribute their talents and experience to the world,'' said Osamu Nagata, executive vice president of Toyota North America.

As the Internet of Things (IoT) blurs the line between products and services, taxation may have a bigger impact than many expect. Companies are taxed differently depending on whether they sell a product or service, and are taxed as a regulated utility if what they sell is deemed to be'telecommunications.' To address IoT-related tax challenges effectively, an organization's tax leader should have an understanding of the new products and services being brought to market and consider joining the development process early.

LONDON, ENGLAND - NOVEMBER 29: An iCub robot built by the Italian Institute of Technology tracks a ball in the Robotville exhibition at the Science Museum on November 29, 2011 in London, England. Artificial intelligence (AI) is one of the most used technology today. You can find it in schools, offices, mobile applications and even financial firms. According to reports, banks will be using AI to handle compliance overload. According to the Wall Street Journal banks have added tens of thousands of compliance officers but are now turning to AI to handle the ever-changing regulatory landscape.

Google held its I/O Developer Conference this week, and much of the focus was on machine learning and related technologies. One of the new products the Internet giant showed off was a new custom chip that runs artificial technology, but as always, there was lots to see. UBS analyst Eric Sheridan said one of the most important announcements was Google Assistant, which is a new digital personal assistant that appears to be much more advanced than Google Now. Interactions with Assistant will take on a more human-like nature as it will offer two-way conversational dialogue using the company's natural language processing technologies. Jefferies analysts said the company is far ahead of others in speech recognition and contextual conversation.

One day last week at 9.29am I hunched nervously over my keyboard and prepared to do battle with an entity called Emma. We were each primed to write about the official UK employment data at 9.30am and file our stories to my editor. I was sure Emma would be quicker than me, but I really hoped I would be better. Her creator, a start-up called Stealth, calls her an "autonomous artificial intelligence" designed to deliver professional services such as research and analysis. Since it is fashionable to predict that AI will supplant white-collar workers including journalists, I wanted to put it to the test.

We've made it to what we've all been waiting for, Q-learning with neural networks. Since I'm sure a lot of people didn't follow parts 1 and 2 because they were kind of boring, I will attempt to make this post relatively (but not completely) self-contained. In this post, we will dive into using Q-learning to train an agent (player) how to play Gridworld. Gridworld is a simple text based game in which there is a 4x4 grid of tiles and 4 objects placed therein: a player, pit, goal, and a wall. The player can move up/down/left/right ( a \in A \{up,down,left,right\}) and the point of the game is to get to the goal where the player will receive a numerical reward. Unfortunately, we have to avoid a pit, because if we land on the pit we are penalized with a negative'reward'.

K Means Cluster will be our introduction to Unsupervised Machine Learning. What is Unsupervised Machine Learning exactly? Well, the simplest explanation I can offer is that unlike supervised where our data set contains a result, unsupervised does not. Think of a simple regression where I have the square footage and selling prices (result) of 100 houses. Taking that data, I can easily create a prediction model that will predict the selling price of a house based off of square footage.