What Direction Will Artificial Intelligence Turn in 2017?

With a brand new year very nearly here, it’s a time to look at what we know and what we are dealing with now to see what will be for the foreseeable future. Regarding AI, everyone is jumping on the bandwagon and recognizing the potential that can be had from integrating it into their business models. But what areas, in particular, will we see AI develop in most in 2017? Read on for the top 5 predictions for 2017’s world of AI and what we can expect to see.

• Universal standards will start to be created for AI to AI communications. Without everyone following the same rules, it would be complete chaos and carnage.

• Companies will expect to see a *ROI from their AI. It’s clear that AI is worth the $1049 million that was invested in it in 2016, but it’s nice to see the proof sometimes too.

• People will come to put their trust in AI more. Human interaction with AI will be ramped up tenfold as elements of communication such as timing, tone, word choice, visual clues, and sentiment are introduced into the machine technology. Also, by increasing the transparency of how these systems work will increase people’s trust in them. An extract from Stanford’s recent study on AI over the next 100 years explains it well, “Design strategies that enhance the ability of humans to understand AI systems and decisions (such as explicitly explaining those decisions), and to participate in their use, may help build trust and prevent drastic failures, it’s critical that engineers and designers create systems that communicate freely about how they work.”

• AI bias’ needs monitoring. If the future of AI is to remain active, then systems that are subjected to bias or bias of conflicting goals need to be addressed as not to hinder its overall progress.

• Conversational interfaces will develop further and soon interacting with technology will become part of everyday life. Google and Bing have both made significant progress in this area, and Facebook too is following shortly behind. But 2017 will bring a boom in this area and take us one step closer to that futuristic world we all envisage.

*Return on Investment (ROI) is the benefit to an investor resulting from an investment of some resource. A high ROI means the investment gains compare favorably to investment cost. As a performance measure, ROI is used to evaluate the efficiency of an investment or to compare the efficiency of a number of different investments. In purely economic terms, it is one way of considering profits in relation to capital invested.

The Rise of Codeless Computer – An End of Programming Elitists!?

Right, let’s dive into it. Computer programming is a hot trend. However, this demand is going down the drain as we continue training instead of coding latest computer systems. Technology and discovery have come a long way. Back in the day, experimental psychologists had ruled the brain as an unknown black box. Fast forward to modern day, not only as the brain been dissected into sections but its deepest innermost stimuli and responsive neurons are constantly under study.

Over the 1950s, a group of psychologists, linguists, information theorists, and early artificial intelligence researchers came up with a different conception of the mind. This became known as a cognitive revolution which argued that people not only collected responses absorbed over time but the information was absorbed, processed and acted upon. The brain functioned like a computer.

Using this discovery, psychologists started describing thoughts as programs. As time passed, Marc Andreessen recognized that software was eating the world as humans started surrounding themselves with machines that convert thoughts, actions, and emotions into data. As Panasonic unveiled an invisible TV that doubles as the heart of the connected home. Life began being seen as ruled by a series of instructions. In fact, the creator of Facebook Mark Zuckerberg suggests that a fundamental mathematical law might be the connection in human relationships governing the balance of emotions.

In 2013, Craig Venter announced that even after decoding the human genome, he was writing code that will allow the creation of synthetic organisms. Someday, a synthetic human. As a matter of fact, big tech companies n silicon valley aggressively pursue machine learning as an approach to computing. Modern computer systems have a way of learning similar to the way humans learn. Applications such as Facebook use this approach to gathering and organize newsfeed, advertise, and run other bot networks.

Additionally, building the world’s first 1000 core CPU has helped change the game. It is no longer necessary to write laws that govern computer systems. This is a technique also used in the android operating system. A new machine learning chip architecture developed by Knupath helps peak into deep neural networks without the need to linearly write programs.

Furthermore, mainstream A1 research has also developed and machines are now powerful enough to affect systems. In fact, the creator of google’s self-driving car Sebastian Thran recognizes that neural nets operated only on numbers thus alienated a lot of people. Technology keeps on outsmarting systems. Even great minds including Stephen Hawking, Elon Muck, and Bill Gates have realized that a new era is dawning whereby machines outsmart humans. In the long run, machine learning will have authoritative influence. Ultimately, machines are getting more enhanced, smarter, and even though humans are responsible for this, they are surely being overtaken.

Pushing The Boundaries Of Brain Science For See the Possibilities in Computer Science

The Federal Government of the USA has provided over $28 million to SEAS at Harvard University to allow them to develop machine learning algorithms that are advanced and thereby pushing forward the research in neuroscience.

Intelligence agencies have to deal with a great deal of data and dealing with it all in a sensible timescale is not possible. Even though humans are used to patterns, they cannot cope, and machines are even less capable. The hope is that a system can determine why the brain is so efficient and then build a computer that can reach the same level of interpretation.The virtual cortex of the brain will be studied then carry out a detailed map then reverse engineer the information they get provide improved computer algorithms. The Leader of the project, David Cox believes that the scientific importance of recording many neurons and then mapping out their connections is a massive project, but this is just the beginning. After pushing the science of the brain, they hope to push the science of the computer.

“THIS PROJECT IS NOT ONLY PUSHING THE BOUNDARIES OF BRAIN SCIENCE, IT IS ALSO PUSHING THE BOUNDARIES OF WHAT IS POSSIBLE IN COMPUTER SCIENCE.” — HANSPETER PFISTER

When completed, the systems would be capable of activities as diverse as driving a car or reading MRI images. Rats will be used to recognize items on a computer screen, and their visual neurons will be studied. Later a section of the brain will be scanned, and the hope is that it will be possible to study the cerebral cortex.

This research can lead to improvements in the vision of robots and allow them to navigate new places. Cox accepts this is a massive undertaking.

New Study Shows How Human Intelligence May be a Product of a Basic Algorithm

There is a theory that suggests human thoughts and functionality result from a basic algorithm N=2^i–1. Artificial neural network operate similarly to the brain, thus applying this formula might as well be the key to true intelligence, making this a huge break for Artificial Intelligence (AI).

Given that the human brain is the most sophisticated organ, the AI model is inspired by the brain. The Frontiers in Systems Neuroscience Journal recently published a study linking human intelligence as a product of a basic algorithm.

According to Joe Tsien, neuroscientist research author at Augusta University, Georgia; “relatively simple mathematical logic underlies our complex brain computations;” found in the Theory of Connectivity. Tsien first proposed the Theory of Connectivity in October 2015.

The Theory of Connectivity suggests that knowledge acquisition, ability to generalize as well as conclude from these generalizations, is a result of billions of neurons assembling and aligning. Tsien amended that there is evidence that the brain is able to operate on a pretty simple mathematical logic.

Post the Theory of Connectivity, there is the brain’s formula. Basically, clusters of similar neurons form a complexity of cliques to collectively handle information or basic ideas. These groups come together into functional connectivity motifs (FCM). FCM deals with every possible combination of ideas. With complex situations, more cliques get involved.

Tsien and team investigated and documented the algorithm functionality in 7 different brain regions. Each selected region was responsible for basic functions such as fear of mice, and liking food. The results indicated how many cliques correspond to a certain FCM, a power-or-two-based permutation logic (N=2i–1).

Four food types (rice, milk, rodent biscuits and pellets) were given to animals in the study. The scientists connected electrodes to specific brain areas and heard the neuron’s responses. As a result, all 15 individual combinations of neurons and cliques that responded to the assorted food were identified, as predicted by the Theory of Connectivity.

Since AI neural networks already match the brain’s structural wing, it is possible for the (N=2i–1) algorithm to be applied.

As 3D Printing Takes Off, Who Are The Leaders in the Software Market?

3D printing is here to stay. It’s all around us in manufacturing, and there are a few companies that seem to know what they’re doing when it comes to 3D printing software and have a good hold on the market. The following will take you through a quick guide of some of the top names to look out for (i.e. the big players) and what makes them so hot.

Autodesk:  This company is mainly known for its 3D modeling software, but when it acquired Netfabb in 2015 that gave Autodesk the power to tackle the 3D printing industry too.  Netfabb is a great 3D printing software that offers both a free version that can repair damaged files or holes in models and a pro version that allows the optimization of 3D printed structures too.  There’s also free software called Meshmixer that’s available from Autodesk that’s been designed to work best with low-end 3D printers.

Materialise: This is a Belgian company that works in close cooperation with HP, as well as many others in the 3D printing world. With over 25 years experience in developing 3D printing software and providing these services, the team at Materialise certainly know what they’re doing. They make their own Build Processor available to a range of manufacturers and have also developed software that effectively manages 3D printer networks and prepares medical data for printing among a whole heap of other functions.

3DSIM:  Private startup, 3DSIM is working on algorithmic software that has the ability to perform physics simulations during the printing process. This allows operators to effectively predict problems such as how the laser will affect printing depending on what material is used.

 

Cloud-based Software:  3DPrinterOS is a startup that focuses on managing 3D printer networks from the cloud while also utilizing 3D printing apps and is probably the leader in this area. Another company that is also popular is Authentise, who again offer 3D printer management, but unlike 3DPrinterOS, they charge a hefty fee for their services.

Desktop Print Management Software:  One of the leading companies in this area is Ultimaker with their open source program, Cura. It’s for use in desktop 3D printing and is used by many. Another that is very similar is Simplify3D that allows great control over printing and the ability to anticipate problems before the process begins, but is a paid alternative.

Could An Algorithm Really Mimic Our Way Of Thinking?

Research carried out suggests that no more than an algorithm is needed in order to replicate a human person’s way of thinking, and is the key to true artificial intelligence.  These findings were confirmed in a recent paper published in the journal Frontiers in Systems Neuroscience and were found to be in connection with the “Theory of Connectivity,” where human intelligence is based on a logic of the power of two algorithms that can create general knowledge, perceptions, actions, and memories.

This theory largely supports the fact that the way in which we acquire and process knowledge can be defined through the interaction and alignment of different neurons within the brain.   The logic algorithm proposed in the paper is N=2i-1, and it corresponds to how similar groups of neurons all join forces to tackle tasks such as recognizing threats, shelter, and food.  These cliques of neurons then cluster together to form functional connectivity motifs (FCMs).  In order for the researchers to be able to decide how many cliques are needed to create an FCM, they analyzed the results of how well the algorithm performed in seven different regions of the brain.

The team managed to document a total of 15 unique combinations of neuron clusters in the end.  The scientists stated, “The fundamental mathematical rule even remained largely intact when the NMDA receptor, a master switch for learning and memory, was disabled after the brain matured.”   This research is a fantastic way to get a true insight into the workings of the brain and will hopefully be applied to further AI projects shortly.

Is it Really Possible to Create a Livable Atmosphere Up on the Moon?

As more plans are put in place in preparation for the colonization of Mars, it leads us to think what other planets or satellites we could conquer. Another place in our solar system that’s always captured the fascination of many is the moon. But, is it really possible to create a livable atmosphere on the moon just as here on Earth?

For quite some time, scientists thought the moon had no atmosphere, but they have since been proved wrong. It’s not an atmosphere like the one we experience here on Earth. On the moon, the atmosphere is thin (called an exosphere) and is a lot less dense than ours. But, does that mean that it can’t be done?

Pretty much, I’m afraid. Although I am a big believer that anything is possible, it would be rather difficult to make this one happen. In order to maintain a decent, livable atmosphere, there needs to be enough gravity in place, to begin with, to keep everything in its place. And, there also needs to be some force field in place to ward off the solar winds. Unfortunately, the moon doesn’t have either of these.

It may be possible to create a livable atmosphere on the moon, but due to the unstable conditions up there, it’s unlikely to stay that way for long. However, volatile ingredients would be needed in large quantities that could only be found at the edge of the solar system in the form of comets, so this could prove quite tricky to use. So, for now, at least, it looks like scientists and others will have to stick to Mars as the next place to colonize.

Watch the video. URL:https://youtu.be/ksvlHp–TgA

Clothing Now Being Made From Synthetic Spider Silk of All Things!

Last month, New York unveiled the world’s first outdoor wear made from synthetic spider silk at a press event held at The North Face store on Fifth Avenue. It’s aptly named the Moon Parka and is being dubbed as a novelty item that’s the first of its kind in the world, being that it’s made from synthetic spider silk.

The Moon Parka has been made as a joint effort between North Face and start-up Spiber who specialize in biotech. The special synthetic spider silk is supplied by Spiber, while the fabulous design comes from the designers at North Face. As part of the unveiling, the prototype has also been around various North Face stores in Japan.

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The marketing executive at Spiber, Daniel Meyer, said “Spider silk is the toughest material that is known, either in nature or otherwise. To boil down the advantages of our technology as simple as possible, it’s a protein material made through an entirely biological process like any other protein material; we have the advantage of being able to use a synthetic process to form that material.”

Revolutionizing the World with Genetic Material Computers

A new nanostructure has been created by researchers for conducting electricity using DNA and gold plating. The new nanostructure has the potential to be used for future electronics after improvements. These DNA origami nanostructures are fascinating. Using DNA as construction material capable of holding scar folds of molecules and atoms has been a huge step for modern nanostructures.

Scientists from the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) and Paderborn University recently developed gold-platted nanowires. As published in the journal Langmuir, the gold plated nanowires independently assemble themselves from single DNA strings.

Artur Erbe from the institute of Icon Beam Physics and Material Research explained that nanowires are able to conduct electricity because of their gold-platting. Two electrical contacts connected the Nano-sized structures. What is even more intriguing is the use of modified DNA strings. These were used as stable double strands combined through their base pairs. Thus, they allowed structures to independently take any desired form. Therefore, complex structures were developed.

According to Erbe, using this approach (which resembles Japanese paper folding technic origami hence the name DNA-origami) will allow the creation of tiny patterns. The ‘top down’ method i.e. developing Nano sockets using base material that is chiseled until desired structure is formed. The new ‘bottom up’ method is set to change the usual method of making these electric components.

However, there is a stumbling block. Erbe pointed out that “Genetic matter doesn’t conduct a current particularly well.” Furthermore, conductive materials need better melding. Not to mention the use of cheaper standard wire coating and not gold. Overall, this is a promising research. If successful, this Nanowire technology could become the future of electronics.

How Neuroscience is Revolutionizing Sports?

Football is known as one of the games determined by high-speed decision making. Everyone is born without a talent. This includes the world’s greats Cristiano Ronaldo (Cr7) and Lionel Messi. These amicable players have had to train their brains through hours of cruel practice.

This has led to the realization of untapped potential by pioneering coaches. Thus, new and advanced technology based on neuroscience and psychology is being developed. Fascinating experiments conducted by Mick Clegg under Manchester United involved players like Cr7, Roy Keane, and Rud Van Nistelrooy. Clegg’s experiment spanned over ten years and depended on the importance of brain power.

According to Clegg, the idea to develop the brain gym based on an industrial estate in Ashton came from the realization of “Rapid cognition. Rapid cognition. Rapid cognition.” Additionally, a key observation was how most players look for speed over strength. The answer on how to develop power with speed as the main ingredient generates from the brain.

 

Clegg’s gym has metal frames with lights and switches that test reaction time, peripheral vision, and under tarpaulin stands, two huge USD $85000 machines—Nike SPARQ Sensory Performance. There is also a NeuroTracker that is now being used by dozens of leading clubs including those in EPL. The NeuroTracker is designed for training multiple object tracking. Thus, useful for not only the footballer but the entire team.

The Footbonaut is a square of AstroTurf with four metal frame sides split into squares by LED grid lights. Mario Gotze is one of the leading players who is a huge fan of the Footbonaut. With multiple objects tracking training supported by the HELIX, players in Hoffenheim get tested on executive function and other mental abilities. The team’s sports psychologist Dr. John Mayor uses the HELIX.

Football keeps on getting faster. And according to Mayor, Germany finished third in the 2006 World Cup with a player spending an average 2.9 seconds on the ball each touch. In 2014, the number dropped to just 0.9 seconds. Clearly, quick decision making and brain tracking paid off for the Germany national team as 15% improvement was indicated in on-field decision making. It is only a matter of time before brain the athletic brain is used in international sports globally.