"What I cannot create, I do not understand." The first glimmers of human-like intelligence appeared a few million years ago on the African continent, and continued to evolve, eventually culminating in the brain of our species Homo sapiens about 100,000 years ago. As modern humans, we can only imagine what our ancient ancestors experienced as they peered out into the night sky to contemplate the very nature of physical reality, as well as introspectively peered within themselves to ponder the very nature of their own mental reality. In the last few hundred years, our species has made immense intellectual progress in developing a precise understanding of physical reality, by discovering fundamental mathematical laws governing the behavior of space, time, matter and energy, now codified in the grand frameworks of quantum mechanics and general relativity. However, we are at the very beginnings of our quest to understand the nature of our mental reality. In particular how does human intelligence emerge from the biological wet-ware of 100 billion neurons connected by 100 trillion synapses? The modern disciplines of neuroscience, psychology and cognitive science have made important progress over the last 100 years, laying the foundations for attacking this grand question.

One could be forgiven for thinking that machines are creative. Numerous artificial intelligence projects appear to demonstrate that machines are capable of creating intricate works of art that rival those created by their inferior human creators. Just recently, IBM Watson created a movie trailer for the horror film Morgan (IBM). Google's DeepDream AI fascinated the world with its eerie superimpositions of eyeballs, cats, birds, and iguanas onto everyday images in a seemingly creative way. The image below was transformed with this very net.

We are living in an age of technological revolution where Artificial intelligence has embarked on its journey of transforming the entire world around us. There is an estimation that it will soon change the way we communicate, conduct our daily activities and work. Recent years have witnessed AI making significant advancement, however, its origin goes back to more than a period of six decades. It was given birth with the aim of making machines intelligent so that they can function on its own with proper foresight required for functioning in its environment. AI is a broad concept encompassing many sub-topics like robotics, computer vision, machine learning, collaborative systems and much more.

Once you're called a "genius," what's left? No, getting called a "genius" is the final accolade, the last laudatory label for anyone. At least that's how several members of Mensa, an organization of those who've scored in the 98th percentile on an IQ test, see it. "I don't look at myself as a genius," LaRae Bakerink, a business consultant and a Mensa member, said. "I think that's because I see things other people have done, things they have created, discovered, or invented, and I look at those people in awe, because that's not a capability I have."

Comparison between artificial intelligence (AI) and human intelligence has been a heated debate ever since Turing envisioned thinking machines. In all these questions and others, the focus is on shaping the future of AI. But why don't we think about improving human intelligence by looking into AI? I can feel your suspicion, don't worry and bear with me, this is not a post about genome editing to upgrade the brain. Human intelligence is not just about the brain, education is an essential part of our intelligence too and we can improve human intelligence with better education. But it seems like we are much more successful in training machines than we are in training humans.

Retaining clients is the third activity. Einstein monitors client-related activities to spot patterns that indicate which clients are at risk for leaving the adviser. IBM's Watson Client Insight for Wealth Management solution provides a similar forecast. "We're able to predict with a high degree of accuracy when clients are going to leave the firm -- 30, 60, 90 days ahead of time," says Stanich. Smaller firms are also integrating AI into private wealth management. ForwardLane in London and New York City is combining quantitative investment models and financial planning. Responsive Capital Management in Vancouver offers its Alpha Digital Advisor Platform and AI Research Platform. And New York City-based Synechron has developed its Neo suite of AI services for financial advisers, which includes natural language processing, chatbots, machine learning, robo-advisers, and other services.

Artificial intelligence has seen its highest growth rate of 70% this year and has proven to be a great success in disrupting all areas of business from streamlining work processes to reducing the time spent on administrative tasks and improving predictive analysis and projections. With this significant change, the debate around artificial intelligence replacing human intelligence is only getting stronger. Whilst the concerns surrounding AI remain, largely around it rendering many jobs obsolete, may sound legitimate at first, many of them are layered with confusion of AI actually is, the automation process and they also quickly forget how remarkably complex this technology is. Indeed, automation is designed to make repetitive tasks become executed by robots which will increase processes' speed and efficiency; as a two-year study from McKinsey Global Institute suggests that by 2030, intelligent agents and robots could eliminate as much as 30% of the world's human labour. However, what is important to remember is that it does not exclude humans from the equations altogether.

Last week, the world's leading experts in artificial intelligence converged on the Canadian city of Montreal for one of the biggest gatherings in their field. On Saturday, the 2018 Conference on Neural Information Processing Systems (NeurIPS) hosted a workshop titled "AI for Social Good". The assembled crowd were not treated to the usual conference staples of robot demonstrations or video presentations showcasing new algorithms that promise to revolutionise healthcare systems. Instead, they were greeted with a solo performance by the superstar cellist Yo-Yo Ma, followed by a session on artificial intelligence, ethics and the arts. The history of artificial intelligence is littered with algorithms that were supposed to mimic the most complex feats of human creativity, from problem-solving to writing poems, composing music and painting portraits.

The common view that our creativity is what makes us uniquely human suggests that incorporating research on human creativity into generative deep learning techniques might be a fruitful avenue for making their outputs more compelling and human-like. Using an original synthesis of Deep Dream-based convolutional neural networks and cognitive based computational art rendering systems, we show how honing theory, intrinsic motivation, and the notion of a 'seed incident' can be implemented computationally, and demonstrate their impact on the resulting generative art. Conversely, we discuss how explorations in deep learn-ing convolutional neural net generative systems can inform our understanding of human creativity. We conclude with ideas for further cross-fertilization between AI based computational creativity and psychology of creativity.

AI systems are now used in everything from the trading of stocks to the setting of house prices; from detecting fraud to translating between languages; from creating our weekly shopping lists to predicting which movies we might enjoy. This is just the beginning. Soon, AI will be used to advance our understanding of human health through analysis of large datasets, help us discover new drugs and personalise treatments. Self-driving vehicles will transform transportation and allow new paradigms in urban planning. Machines will run our homes more efficiently, make businesses more productive and help predict risks to society.