Can Computers be Creative? How? How can [a creative idea] arise, then, if not by magic? And how can one impossible idea be more surprising, more creative, than another? How can creativity happen?
– from Margaret Boden. Creativity and Unpredictability. Stanford Electronic Humanities Review 4(2), 1995.
Data has become the most valuable currency in business. But without the right tools or intelligence, its true value will not be realised. According to a MiQ survey, 43 per cent of US and UK brand marketers think that the lack of measurement of business impact, such as sales or growth, is the main hurdle to investing more in data analytics. But if marketing metrics are not the same as business goals, why are campaigns measured against them? Marketing should align with the same goals as the rest of the company, in order to measure tangible business results.
In the popular TV show Sherlock, visual depictions of our hero's deductive reasoning often look like machine algorithms. And probably not by accident, given that this version of Conan Doyle's detective processes tremendous amounts of observed data--the sort of minutiae that the average person tends to pass over or forget--more like a computer than a human. Sherlock's intelligence is both strength and limitation. His way of thinking is often bounded by an inability to intuitively understand social and emotional contexts. The show's central premise is that Sherlock Holmes needs his friend John Watson to help him synthesize empirical data into human truth.
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.
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.
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.
Intelligent behaviors commonly associated with humans but exhibited by machines and applied to tasks like problem-solving, automatically completing forms or parsing medical images to recommend diagnoses. In theory, true AI should be able to think like and interact with other humans seamlessly. An application of AI that uses algorithms to find patterns in data without instruction. Machine learning automates a system's ability to learn, so it can improve from experience without being programmed for each task it completes. A machine learning model is "trained" on relevant examples from diverse data sources.
Sling TV's line up of available channels is getting bigger. The streaming TV service is adding nine new channels from Discovery Networks that offer live and on-demand content, including the flagship Discovery Channel and MotorTrend. The best news for Sling subscribers: some of the channels will be added to your package for free. Access to the channels will be split across Sling's two separate service packages, both of which cost $25 per month. Sling Blue will get Discovery Channel, Investigation Discovery and TLC.