Charles Darwin's theory of evolution offers an explanation for why biological organisms seem so well designed to live on our planet. This process is typically described as "unintelligent" – based on random variations with no direction. But despite its success, some oppose this theory because they don't believe living things can evolve in increments. Something as complex as the eye of an animal, they argue, must be the product of an intelligent creator. I don't think invoking a supernatural creator can ever be a scientifically useful explanation.

These questions originally appeared on Quora - the knowledge sharing network where compelling questions are answered by people with unique insights. Q: How should one start a career in machine learning? A: There is not just one way. You can start at any age. Some math background (in linear algebra, statistics, and calculus) is recommended, so take classes on these topics, if possible.

The concept of artificial intelligence has been around for a long time. In written fiction, AI characters show up in stories from writers like Philip K. Dick, William Gibson and Isaac Asimov. Sometimes it seems like it's touched on by every writer who has written sci-fi. While many predictions and ideas put forward in sci-fi have come to life, artificial intelligence is probably the furthest behind. We are nowhere near true artificial intelligence as exemplified by the characters mentioned above. Sometimes it seems like we've been waiting forever.

It's increasingly common for organisations to ask their customers how satisfactory their latest interaction was, often by asking them to participate in an automated survey at the end of a phone call, or by inviting them to complete an online feedback form after a physical interaction such as an airline flight or a virtual one such as using the company's web site. But by that time, it's too late to head off any negative outcomes - the interaction is complete, so all you can do is try to stop problems occurring again or provide the customer with some sort of compensation to make up for it. So customer service provider Zendesk has added its new Satisfaction Prediction feature to the enterprise plan, but only for clients who receive at least 500 satisfaction ratings a month. The feature has been in beta test for five months ago, and in that time has analysed more than 1.82 million customer interactions. Satisfaction Prediction uses hundreds of signals - including text description, number of replies and total wait time - to calculate the likelihood of a positive satisfaction rating.

Under the slogan "Be the First Mover in the Era of Knowledge and Information," South Korea has emerged as one of the world's IT powerhouses in just six years. Incheon International Airport, the epitome of IT convergence, has been named the world's best airport for 11th consecutive years. The S. Korean financial industry, which had finished 86th behind Uganda, has risen to the world's 7th largest, easing regulations on the separation of industrial and financial capital and granting Kakao and KT preliminary licenses to run the nation's first online-only banks. The Go-playing AI AlphaGo had the brand value of Google leapfrogging over that of Samsung Electronics instantly. It was all the work of software.

I have previously argued that ITIL has difficulties keeping up with the new iterative, Agile development methodologies that are transforming IT departments. That is not the only problem ITIL faces – arguably an even bigger issue is'Lack of success' from a maturity standpoint. According to Gartner, Overall, IT vendor management maturity for the approximate 1,000 assessments conducted since September 2010 is at a Level 2.4 (repeatable)" out of a scale of five[1]. This is after 30 years of ITIL, millions of certified practitioners, 100s of certified ITSM solutions, and countless consulting organizations with practices around ITIL. While there are numerous reasons for lack of success and suggestions for improvements, they all tend to go back to project or program management, executive sponsorship and ongoing measurement.

Former top executives from IBM Watson, GE Digital, Infosys and MicroStrategy announced last week that they have joined forces with TPG Growth to launch Noodle Analytics, Inc., the Enterprise Artificial Intelligence company. Enterprise AI represents a major step forward in merging human learning and machine learning, all fueled by big data. Enterprise AI solutions combine expertise in human-centered design, business process engineering and artificial intelligence technologies. Today's artificial intelligence technologies include machine learning, predictive data analytics and data science. "Over the next three to five years, artificial intelligence technologies and big data will be the most significant competitive differentiators in business. We are excited to be a pioneer in Enterprise Artificial Intelligence, offering timely, valuable, and affordable solutions to clients. We have the right team, an optimized business model, and the right partners to create extraordinary value," says Stephen Pratt, CEO of Noodle.ai.

We are looking for companies who operate in both the business to consumer and business to business technology sectors. Your product(s) or service(s) should demonstrate artificial intelligence or machine learning behaviour. If your company would like to exhibit at the Showcase 2016 Event, please contact us for more information. We will be sending out exhibitor information packs early next year. We have different packages available suitable for both startups and large corporates.

There has been much discussion in the last few days about the announcement by the World Economic Forum that it predicts it will take 117 more years until we achieve gender parity in the workplace. It seems crazy that in today's workforce, which is driving developments like self-driving cars, gaming-genius AI, and making hoverboards a reality, we still don't have gender equality. Research published recently by EY makes a compelling case for businesses to do more in terms of tackling existing inequalities: data shows that more diverse company boards command higher share prices and improved financial performance; balanced leadership increases a company's productivity and nationally a country's GDP can be lifted by reducing the gender gap. Another piece of research that looked at start-ups receiving Series A funding in the Bay Area in 2015, showed that only 8% of firms were led by women - that's 16 out of 204 start-ups. And this figure was down by 30% from the previous year.

Deep learning is a new buzzword among machine learning researchers, both in academia and industry. It deals with making machines learn to solve complex real world tasks using approaches similar to the ones adopted by their human counterparts. Computers are good at following instructions without even a single bit of deviation. The programs we write are simply a collection of instructions, which need to be executed in a pre-determined order. Is that good or bad?