Milestone Reached in Brain Mapping Project

A CSH Lab news release says neuroscientists at the Brain Architecture Project have reached an important milestone. They've released the first installment of the 500 terabytes of data from the whole-brain wiring diagram of a mouse brain. The data is in the form of gigapixel whole-brain slice images. It's possible browse through the brain to the desired 20 micron-thick slice, then view the image, zooming it the level of individual neurons. Most importantly, the image data is being released in an open science initiative, freely available for anyone to view and use in their research. The technical approach used was developed by Partha P. Mitra.

"The pragmatic approach Mitra advocated and which is realized in this first data release, is to image whole mouse brains in a semi-automated, quality-controlled process using light microscopy and injected neural tracers (both viruses and classically used tracer substances). While the basic methodology has been available for some time, systematically applying it to a grid of locations spanning the entire brain, and digitizing and re-assembling the resulting collection of brains, is a new approach made feasible by the rapidly falling costs of computer storage."

For more details see the Mouse Brain Architecture Project Technical White Paper. This is just the first step in the overall brain architecture project. After the mouse brain, there's the Human Brain Architecture project which has the potential to do for the human brain what the human genome project did for our genes.

This is a cool project but if their goal is to create a mouse brain in a computer I really don't expect that they will be able to create a truly functioning mouse brain in a computer by scanning brain slices. It seems to me that the slicing process will either destructively cut neurons in half or can't truly map the axions since they go in every 3D direction, or because neurons are more complex then our current model of what a neuron is or it's really difficult to map the connection of one neuron on one squishy slice to a neuron on another squishy slice and make sure you have the right neuron or any number of other variables. If the goal of this project is just to map a mouse brain architecture, I think slicing and picture taking is the easy part and they've got their job cut out for them in really mapping. Other than that, it would be exciting to have a robot mouse until it started eating holes in the walls or whistling steamboat willy.

View the original article here

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Google Changes Search, Moves Closer To Becoming Artificial Intelligence Engine

Google began rolling out a feature that gives searchers in the United States the potential to access more relevant and in-depth responses to answers without leaving the page. The concept is built on something the company calls "knowledge graph," which ties together words to create relationships.

There are a multitude of sources behind this data. The search results page displays a variety of content related to keyword queries, bringing up a list of facts, photos, and landmarks, as well as quick links to other popular uses for the search term. Think of a Web beneath the user interface layer of the Internet that ties together all information across the Web.

Rob Garner, vice president of strategy at agency iCrossing, said Google's knowledge graph takes another step in the company's long transition to develop an artificial intelligence engine -- semantic search. "It's something Google's doing in parallel to Schema.org in terms of relating object, places and people," he said. "Looking at the schema for a person you can actually define the relationship with other people using schema vocabulary."

For example, someone looking for information on Marie Curie will see her birth and death dates, but also details on her education and scientific discoveries. The search engine understands much more about Frank Lloyd Wright than the word connecting the characters. It understands that Wright was an architect who was born June 8, 1867 in Richland Center, Wisconsin, and died on April 9, 1959, in Phoenix. It knows that his projects included Robie House and Taliesin West.

The change represents an effort by search engines to move away from text-based links in search results and serve up knowledge in fewer clicks. Last week, Microsoft rolled out a revamped version of Bing that will initiate new ad formats.

Garner said it's not clear what the advertising impact will be. "It will be interesting to see if there's a connection to better networking information around companies and product offerings, but they do that pretty well in standard Web results," he said.

Source : mediapost

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How artificial intelligence could create a personalised and perfect travel service

Feels a little creepy – doesn’t it? But, this is the future of air travel (and how we will interact with technology in general).

Airlines will know customer preferences, what “home” means for a traveler, if he likes aisle seats on morning flights, and – most importantly for use on third-party aggregators – what his preferred airline is.

The kicker: these conversations won’t be happening with live representatives drawing from a knowledge base. Passengers will instead converse with avatars, equipped with artificial intelligence and natural language understanding.

Recent news of life-sized holograms at three major New York airports has many passengers considering artificial intelligence and the technology’s real implications on their travel experience.

Minds go to fanciful extremes like the Terminator or Minority Report and they wonder: “What do these things do?” or “What’s coming next?”

Well to begin, the NY installations won’t be having true conversations with anyone.

And they also aren’t the first of their kind in the travel industry: Manchester Airport became the first to use holograms back in 2011 for security preparation.

United (via Alex) and Alaska Airlines (via Jenn) use enhanced conversational avatars online, to interact with customers, answer questions, and assist with the booking process.

Conversational avatars are already engaging with customers everyday and present the path towards (counter intuitively enough) personalized service.

The massive amounts of data that can be gleaned and analyzed from logged conversations give a true window into what customers really want.

Rather than operating within the confines of links and search terms – customers can simply ask for what they’re looking for. With that, airlines begin to measure customer desire and store preferences.

Transforming customer information into personalized service is a key factor in the future of customer loyalty.

Why do it?

Currently, passengers view flight as a commodity, where price and schedule are more important than brand. But beyond this hunt for the lowest fare, customers are searching for personalized service.

They want their individual needs to be recognized and will support a brand that demonstrates that itunderstands their expectations, needs, quirks, and specific requests.

At the same time, sensitivities around privacy and storing personal information, such as what “home” means, makes the integration a balancing act.

In order for artificial intelligence to be truly effective in building customer loyalty in the future, airlines must be sure that transparency is built in around the technology.

Building a strong customer relationship is contingent on the amount of passenger information an airline can store, understand, and act upon – but passengers want to know what information is being stored and have control over how their preferences are determined.

There is no other way to deliver this transparency other than showing a customer the process behind an avatar’s decision making process.

This is key to successful integration – rather than take control away from passengers, make the planning and booking process more transparent by engaging in conversation and revealing how actions are taken on the passenger’s behalf.

This is part of the foundation to making artificial intelligence effective; it’s not just about the technology driving it, success relies on the trust that customer’s must develop on their own.

The Manchester and NY holograms barely scratch the surface of the use of artificial intelligence in the travel industry.

The real benefits come when the conversations between customer and technology begin.

Airlines that interact and build relationships with passengers through customer experience technology will lead the brightest future in winning customer loyalty and the lifetime revenue that comes with it.

Source : This is a guest article by Dr Charles Wooters, chief scientist of Next IT.

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The brain and the Memory- Prediction framework theory

The full memory-prediction framework theory was first introduced by Jeff Hawkins in the book On Intelligence. The theory says that the physical arrangement of brain cortex tissue is uniform and means that there is a single principle that defines all brain and memory processing. It also notes that the brain's intelligence comes from the ability to predict future events by relying on past data.

Memory-prediction framework theoryThe memory-prediction framework gives a unified theory about complex behaviors and allows us to better understand what intelligence is.

This theory focuses on the cortex because we're only concerned about what makes us intelligent and not how our entire body works. After all we're trying to create intelligent software, not recreate human beings.

The Central Concept

Memory-prediction framework posits that inputs coming from the bottom of the hierarchy to the top are analyzed and ranked in a hierarchy of recognition. This then invokes a list of expectations ranked in order of potential. The framework comes into play when the brain has to compare and match up these inputs and expectations. The memory-prediction framework means that the brain does not have to consider every option at every level of the process because it uses past sequences as a guide to predict likely future sequences.

"Memory-prediction framework posits that inputs coming from the bottom of the hierarchy to the top are analyzed and ranked in a hierarchy of recognition."

The further up the framework, the longer the past sequences are and consequently the fewer options there are to finish them so the process actually accelerates as it nears the end. For example in looking at a scene, the brain first recognizes lines, then shapes and colors and finally recognizes them as objects. At the same time in the same framework, predictions about what to expect from these objects flows down to speed up our interpretation of the scene.

The framework changes as we age because we add new memories to the system. Since we start with none, as babies we truly see things for the first time. But as we age, we collect memories and this bank of expectations about the way things are and the way things work. This helps us to understand the world around us and to process external information and stimuli more rapidly, but it helps explains how different people can interpret the same situation differently because they bring different memory structures to the experience.

The Pioneer of the Memory-prediction framework theory

Jeff Hawkins originally trained as an electrical engineer and perhaps this gives us a bit of insight on how he approached the problems of brain theory and discovered the memory prediction framework theory. His theory is one of the brain as an organ capable of future predicting and error correction. The brain predicts future events by relying on past data.

"His theory is one of the brain as an organ capable of future predicting and error correction."

The system is a hierarchy so the steps of the analysis are performed in order and if the current even deviates from past experience at any level then a new string of events, or memory, is created. This string can then be used in the analysis of future situations. In this way, the system itself learns and evolves.

It continuously grows more complex and better at making predictions. Just as the theory describes a brain that is constantly adding details and sequences of understanding, the theory itself needs to grow and be fleshed out with details before it will be fully accepted.

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TalkTalk – The Future Search Engine?

 

Google,Yahoo and Bing are yet the top search engines in term of number of users and the popularity. They have a massive competition but, any of these 3 search engines will not win the battle and These traditional search engines will not be longer in the future. 


In 2035, according to News of the Future, the search engine will be like a friend.. your personal assistant, your  librarian whom you can talk online to ask what you want and ect. If there is a any question in your mind you can talk it out with TalkTalk.


TalkTalk is the search engine of future with Artificial Intelligence. The traditional search engines will turn into a talking machine just like a friend of yours.


TalkTalk is actually in the works today. Although 2035 is far from our time now, TalkTalk Search Engine is already getting massive reactions from people who are quite curious in technology and even doubtful if it will really happen in the future.


With Artificial Intelligence, Future Search engines will be like your personal assistant and your don't need to search it on internet, your friend will do it for you!


We don't know. Google (perhaps Yahoo or any other one)might be the first to launch a improved  Search Engine with AI less than we predicted. 

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AI Robotics.. [Part-2]

 

Nowadays, robotics has greatly taken the place of humans for activities that are deemed too risky or very repetitive. Robots are programmed with the use of artificial intelligence which allow them to think and act like humans. Some areas where these devices are of great significance include handling of lethal materials or substances, doing tasks in remote areas where people are unable to and working under intense heat.

The characteristics that an average robot has are: (1) a circuitry that has been pre-programmed that allows them to have thought processes similar to that of humans. A lot of these robots are in fact shaped like humans although there are some that are available in a wide array of shapes and sizes depending on their use; (2) built-in sensors that facilitate them in their navigation in the factory and perform different activities; (3) capability in decision-making while in their given environment as a result of the use of artificial intelligence; (4) robotics intelligence allow these devices to perform intricate movements especially hand motions.

Many demanding jobs that require speed and precision can be performed effortlessly by artificial intelligence robots. They are being used in many industries such as electronics and automobiles to replace human workforce leading to bigger production and gains at lesser costs.

No other industry has employed more number of robots than automobile assembly plants. In fact, these robots have virtually replaced human labor in many corporations at a ratio of 10:1. Another popular application of robotics can be found in industrial welding where they are known to function with speed and accuracy. Spray painting can be dangerous to one's health because of the chemicals being used but because of the advent of robotics, people no longer need to expose themselves to this health risk.

In general, robots are built to perform various functions and handle different situations. It is also programmed to either be stationary or have the ability to move around. A lot more aspects in our daily lives will be governed by robots in the future. However, the moral issue remains that unemployment has been increasing because of the use of robots to replace humans.

The latest progress in robotics includes a continuing research in cognitive robotics where a software that allows tasks that are complex and intuitive to be performed is being developed. On the other hand, an artificial brain is in the works at the laboratory. Project Blue Brain is one example where the human brain is being simulated via computer down to its molecular level.

Artificial intelligence robots have really gone a long way. Although robots that can pass for humans have not been built yet, the progress in robotics is growing steadily. A few decades from now, we may even come close and personal to the science fiction stories we used to watch or read about when we were much younger. Artificial intelligence in itself is a fast-growing industry that continues to develop until the time comes that a logical simulation of the human brain is accomplished.

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AI Robotics..

Lately Microsof company owner Bill Gates thrilled everyone by stating that robotics will be the largest and most important industry globally in just 20 years.
At this moment were observing an incredible away break during the enhancement together with using of systems. Those mechanized marvels have been completely performing a great job during community with setting up present-day motors that will beer making cider. Eventually the systems could invade real estate to carry out a number of the assignments the fact that these days persue an individuals times together with days or weeks out.
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This current year were observing tools for MIT together with other labs which can step. Despite the fact that running is certainly all natural that will persons, it is problematic to create by using a forex robot. Running systems are now specially designed that will take the place of a good soldier during eliminate or simply function shelter treatments during areas overly threatening meant for persons.
Were also unable to result in a process or simply a forex robot which can believe that or simply action our. However once in a while get magnified compared with the majority recognise. I'll tell you any of your current success.
Cognitive robotics. Doctors during this style try to get to generate software programs which can function challenging, user-friendly cognitive assignments the manner in which persons together with critters undertake. Despite the fact that not a soul has built software programs able of carrying out this during the real world, doctors own generated courses which can do it right from a labrador.
Computational intellect. Computationally sensible systems recognise behaviours together with come up with predictions. Chess courses happen to be plus the computational intellect.
Records mining. Records mining courses sort through massive amounts for records, research it all, together with purchase useful material. Records mining courses widely-used during money exploration providers, online business, law enforcement officials, and serps.
Fake mind. There are specific work during the succeeds to generate some sort of false neural. An example, Assignment Purple Neural, wishes to create a personal pc simulation within the mental faculties due to any molecular point.
Robotics. The brain should be an individual a natural part of setting up some sort of fake appearing. Certain systems have already been crafted which can deliver numerous facelift words and phrases. What's more, financial "per systems have already been engineered the fact that emulate temperament together with behavior.
Were also unable to put together systems which can circulate meant for our. However , success during robotics together with during false intellect is certainly earning dependable acquires, together with agencies, government authorities, and consumers take advantage of components of it all regularly. Its not at all weird that will assignment the fact that fake intellect could pursue to cultivate together with make improvements to before you can easliy produce good simulation within the mental faculties. Throughout a few more quite a few years or the other 100 years, any development fictional reviews the fact that appear to be not going at this time could become day to day realities.

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