Will the computers know everything eventually? Is the “Turing Test” within reach for artificial intelligence? With Turing turning a century-old this year, would he be happy or disappointed on how AI development has paced since he breathed life into a test that will scale machines’ capability to think like humans?

AI on the Brink of Passing Turing Test

AI has been at the core of numerous studies of industry big names and neophytes alike. The idea of creating a precise simulation of the human brain has fueled activities and researches around artificial intelligence for decades now. But, what appeared to be just an absurd idea has gradually reached center stage and is now on the brink of passing the “Turing Test”, according to a report.

Robert French, a cognitive scientist at the French National Center for Scientific Research, in an Apr. 12 Science essay, wrote: “Two revolutionary advances in information technology may bring the Turing test out of retirement. The first is the ready availability of vast amounts of raw data — from video feeds to complete sound environments, and from casual conversations to technical documents on every conceivable subject. The second is the advent of sophisticated techniques for collecting, organizing, and processing this rich collection of data.”

Creativity is an element that computers currently appear to lack (or at least human aesthetics), so fiddling with generative algorithms to attempt to mimic human creativity may be the first step towards “thinking” styles. Today, there have been a great deal of number of machines that can perform human tasks, but none of these has passed the “Turing Test”—created by the great late Mathematician, Alan Turing. The assessment just simply implies: if you can converse with a human being logically, then you are intelligent. The increasing pace of technology and how the barriers to allowing actively expert systems, is becoming less of an issue.

Adafruit, which has long been a supporter of AI and instrumental to Microsoft’s Kinect technology in 2010, featured a blog by William Hertling. He argued that open platforms can dissolve major challenges of AI technology including cost—which is arguably the biggest there is. Some people think that unless you have $3 million dollars or so to replicate IBM’s Watson, then you are bound to fail when you talk about your future in robotics and AI.

But Hertling sees no more truth to this. He said, “Between the exponential growth of computing power and the work of groups like DIY Drones, the cost barrier to participation in robotics and AI is falling away. When that happens, open source robotics will take off.”

Hertling added, “And contrary to what some observers have argued, openness can be profitable. Every tech startup in the last 10 years has used open source in some way. Facebook and Apple’s iPhone owe much of their success to their open app platforms. Red Hat, one of the leading Linux providers, is an $11 billion company, with revenues of more than $1 billion. The trick for robotics and AI companies will be to figure out the right mix of what’s proprietary and what’s open.”

A very interesting take on the approaches and future of robotics, AI, neuroscience engineering, intelligence theory and cyborgs was presented by Dr. Hugo de Garis in a video found here. Before retiring from his directorial post in Xiamen University, he was building China’s first artificial brain.

AI On Big Data

Data mining and filtering fits back to Big Data and involves some artificial intelligence research divisions. IBM’s Watson runs through super computing technology that interprets queries in natural language whilst consulting vast volume of unstructured data quickly and provides answers with a definite level of assurance. At this day and age where data science is becoming a sport, every advancement and innovation in the field means a score for you. Big data is a huge thing now and are being utilized in hundreds and thousands of ways to monetize and power industries. In this light, several units are making paving their ways to big data and analytics, including the powerhouse U.S. government agencies and departments. The pledges on flood of digital data research reached a whopping $200 million.

In a NY Times article, Tom Kalik, deputy director of the White House Office of Science and Technology Policy, drops brief but meaty statements: “This is that level of importance. The future of computing is not just big iron. It’s big data.”

The Ubiquity of AI

Artificial intelligence is no longer limited to robots shaking hands, talking, walking, or interacting with another person. In the 50’s and 60’s, the grand vision of AI dissipated into smaller fragments. AI could be anything from GPS to IBM Watson, Apple’s Siri, Google Glass and virtual healthcare assistants.

I openly admitted in my previous article on artificial intelligence that I fear the moment when I’d go to work and sit beside a humanoid in a subway train. I disgust the idea of a world filled with pseudo-me or you just like what TIME magazine described as a robot with human skeleton. But, AI has outgrown that grotesque idealism and has become a tool for modern science to actually help humankind in various ways, especially with healthcare.

A recent biomed article explained how web-based tool via artificial intelligence has produced an accurate diagnosis on autism. Researchers at Harvard Medical School have found a way to significantly reduce detection of autism from years in a matter of hours and minutes. The computational algorithms or “machine-learning algorithms” are forms of AI where data is analyzed leading to a resulting diagnosis for autism that can be made efficiently eliminating the potential for skewed human error.

Dennis Wall, associate professor of pathology and director of computational biology initiative at the Center for Biomedical Informatics at Harvard Medical School, said: “This approach is the first attempt to retrospectively analyse large data repositories to derive a highly accurate, but significantly abbreviated classification tool. This kind of rapid assessment should provide valuable contributions to the diagnostic process moving forward and help lead to faster screening and earlier treatment.” He added, “We believe this approach will make it possible for more children to be accurately diagnosed during the early critical period when behavioral therapies are most effective.”

And it looks as if IBM is ready to take Wall-Street employee Watson to another level as they take an aim in diagnosis and treatment for cancer. This is a huge leap from just beating three Harvard whiz in Jeopardy a year ago. A serious health menace of the society, early detection and cure of the Big C could be a monumental feat for the Big Blue and its AI project. According to BBC, Memorial Sloan-Kettering Cancer Center in New York and IBM will team up to collaborate on developing a Watson-based service that will aid doctors with cancer diagnosis and will eventually suggest treatment options by digging through the most current and comprehensive information available.

Martin Kohn, IBM’s chief medical scientist, the massive amount of efficiency that Watson can bring to the table: “Physicians require a lot more information to make the proper decision as we learn more about the biology of cancer. (Using Watson) we have access to much more information than we could possibly accomplish by reading on our own, or even 100 people reading.”

At present, Watson is being fed with Oncology data and programmed to respond to questions just like what it did during the Jeopardy quiz. This AI-use in biomedical technology does not only impose big importance on the healthcare system, but also within economic circumstance.

Mobility has also tapped AI to propel groundbreaking technologies in devices. Recently, SOTI introduces BlitFire 10X to power up Remote Control performance on all platforms including Android, iOS, Blackberry, Windows and more. As the name implies, the speed would be ten times faster than the normal. It leverages a combination of algorithms that embrace AI techniques to deliver faster response times and more efficient bandwidth usage.

An emerging company in the robotics industry, GeckoSystems Int’l has revealed shipments of the new version of BaseBot™ to ZMP in Japan. BaseBot will bring the latter a technology that pushes for “loose crowd” level self-sufficiency, autopilot seek, cognizant navigation, and reactive, proactive and contemplative averting behaviors. These are the functional benefits will enable behaviors like errand running and patrolling.

GeckoSystem’s CEO Martin Spencer comments on this new endeavor: “We are very pleased to send this latest configuration of our BaseBot to ZMP. We now have a demonstration unit that can be readily shipped to third parties for independent testing and evaluation of our SafePath mobile robot solutions. The BaseBot is compact and readily demonstrates our ‘loose crowd’ level of mobile robot autonomy. The BaseBot will also be useful to OEM manufacturers when developing products designed for SafePath navigation.”

The defense arm of the U.S. government has been trying to maximize the use of AI to create next-gen robots that can be of assistance during rescue operations when disasters strike. In this light, Pentagon has created a Disaster zone robot competition that offers $2 million for the best technology they will find. Contest opens this October for software engineers, video game developers and experts from in and out robotics to partake in diversifying innovative solutions in the defense panel.

With the aggressive progression in AI, there is no doubt that Turing Test will resign sooner or later. Programming artificial intelligence systems with whatever values, interests, and morals innovators and inventors choose, my stand on this issue may seem dreamy but holds true: wherever technology brings us, the social human power will reign supreme over machines. Not because we can think better than them, but because of the will power that humans possess, that up to this day neurological science cannot explain.