During the last Australian election we ran an ambitious project that tracked campaign spending and political announcements by monitoring the Facebook pages of every major party politician and candidate. The project, dubbed the "pork-o-meter" (after the term pork-barreling), was hugely successful in being able to identify distinct patterns of spending based on vote margin, or incumbent party, with marginal electorates receiving billions of dollars more in campaign promises than other electorates. All up, we processed 34,061 Facebook posts, 2,452 media releases, and published eight stories (eg here, here and here) in addition to an interactive feature. We also used the same Facebook data to analyse photos posted during the campaign to break down the most common types of photo ops for each party, and how things have changed since the 2016 election. We were able to discover more than 1,600 election promises, amounting to tens of billions of dollars in potential spending.

Thanks to electronic banking, there are millennials who have never written a paper cheque. And whilst the overall volume of paper cheques continues to plummet by 10 per cent to 15 per cent a year, NatWest Group still sometimes processes as many as 500,000 cheques per day and needs to do so as quickly, accurately and cost-effectively as possible. The UK recently introduced legislation requiring that all banks switch to image exchange of cheques. The new legislation means that banks now capture images of cheques and exchange these instead of the physical paper cheques. NatWest Group decided that instead of doing the bare minimum to comply with the image-clearing cheque system requirements, it would take the initiative and work with long-time outsourcing partner DXC Technology to completely transform the cheque-processing system.

Ekincare, an artificial intelligence-based healthcare startup, has raised $3.6 million (Rs 25.81 crore at current exchange rates) in a Series A funding round led by a new investor. The latest funding takes the total capital that ekincare, operated by Aayuv Technologies Pvt. Ltd, has raised so far to $5.6 million, the company said in a statement on Wednesday. It didn't disclose the name of the new investor. Other investors that participated in the funding round include existing investors such as venture capital firm Venture East, Eight Roads Ventures and Hyderabad-based Touchstone Equities.

With increased awareness about the transformative power of AI, the adoption of AI is now being seen across many industries. From large banks like HDFC Bank to ecommerce players like Pepperfry, AI is being used for a variety of use cases. HDFC Bank uses an intelligent AI-enabled bot for improving the efficiency of the credit decision process. Eye balling is of paramount importance in the credit decision process, and the bot mimics a human by eye balling the customer demographics for those who have applied for loans against the already existing base. For the signature verification process for clearing cheques, the bank is using machine learning with almost 80 per cent accuracy to process more than 2.5 lakh cheques a day.

AI is transforming how we do business at an unprecedented pace, but the transition to becoming AI-driven is easier than you think. Now is the time to invest and remain at the top of your game. A few weeks ago Artificial Intelligence was thrown into the spotlight as the winners of this year's Turing award, widely known as computing's "Nobel Prize", were announced. Yoshua Bengio, Geoffrey Hinton and Yann LeCun were recognized for their pioneering work over a 30-year period on AI. In the 80s, when AI research was very unfashionable, the trio were motivated by the idea of creating algorithms that could operate, at least at the level of metaphor, like a brain. Neurons in the brain work as an ensemble, together learning internal representations of the input they observe, and these researchers believed their artificial neural networks could do the same.

In May, SenseTime Group, a Chinese technology company specialising in artificial intelligence (AI) and facial recognition, raised $620 million in a funding round led by Fidelity International, Hopu Capital, Tiger Global Management and Silver Lake Partners. The three-year-old startup, arguably the world's most valuable startup in AI, was valued at $4.5 billion. The funding came at a time when the Chinese government is pulling all the stops to make the country a global leader in AI over the next seven years. By 2025, the Chinese government intends to grow AI industry's value over $60 billion. In India, the picture is different.

Nowadays Machine learning is a very hot topic, everyone is talking about Machine learning and discussing how it can be useful in their business or in his or her career. Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that machines should be able to learn and adapt through experience. Many big industries have already started implementing Machine learning for their business. For example, I recently participated in a well-known bank hackathon where the themes of the hackathon were mainly on Machine learning and AI.

A quantum upgrade could make old-fashioned cheques the most secure way to send money. Researchers have proven that quantum computers could in theory create and cash cheques that are nearly impossible to forge. Quantum computers store information using qubits which, unlike the ones and zeros of classical computing, can exist in two states simultaneously. This is known as quantum superposition. But it's impossible to observe a qubit while it's in a superposition – it collapses into either a one or zero as soon as you measure it.

Ben Robinson, chief strategy & marketing officer at banking software firm Temenos, explains how the future of finance will be shaped by artificial technology. Google's DeepMind triumph this year over one of the world's highest ranked champions at Go is a sign: computers with artificial intelligence (AI) are learning how to outperform us. If computers can learn to beat us at a game, why not at things that we can't afford to get wrong – medical diagnostics, risk analysis, legal and investment advice? And what effect over time – say 20 years – will this have on the way a host of services, such as banking, are delivered? "Service will be all about data and algorithms," David Brear, co-founder and CEO at 11:FS recently suggested.

Most of us have wondered what we might do if we didn't need to work – if we woke up one morning to discover we had won the lottery, say. We entertain ourselves with visions of multiple homes, trips around the world or the players we would sign after buying Arsenal. For many of us, the most tantalising aspect of such visions is the freedom it would bring: to do what one wants, when one wants and how one wants. But imagine how that vision might change if such freedom were extended to everyone. Some day, probably not in our lifetimes but perhaps not long after, machines will be able to do most of the tasks that people can.