The following two excerpts from Singularity Hub summarise weak-narrow AI:
"When you call the bank and talk to an automated voice you are probably talking to an AI…just a very annoying one. Our world is full of these limited AI programs which we classify as “weak” or “narrow” or “applied”. These programs are far from the sentient, love-seeking, angst-ridden artificial intelligences we see in science fiction, but that’s temporary. All these narrow AIs are like the amino acids in the primordial ooze of the Earth."
"We’re slowly building a library of narrow AI talents that are becoming more impressive. Speech recognition and processing allows computers to convert sounds to text with greater accuracy. Google is using AI to caption millions of videos on YouTube. Likewise, computer vision is improving so that programs like Vitamin d Video can recognize objects, classify them, and understand how they move. Narrow AI isn’t just getting better at processing its environment it’s also understanding the difference between what a human says and what a human wants."
http://en.wikipedia.org/wiki/Weak_AI
so there or here is some AI
Topic: Neurala has highly parallel GPU based neural networks for better AI (Read 991 times)
February 26, 2014, 06:43:23 AM
February 25, 2014, 12:58:44 PM
uhh man 
too much coffee ? 
but anyway it was realy nice to read.
I like AI news, but there is still one thing ...
There is no any AI
AI is Sci-Fi baby.
AI will be never created IF developers will not understand and somehow implement very important thing.
Intelligence is not a rule based system
When we born - we learn. We dont know what they are saying. We just see. Feel. And trying to think.
We are creating our own rules. We are building our brain. We are intelligent so we do not need to know everything before - we can figure out how things work without anyone who will tell us - "do this, do that".
So for me AI is just too much for now
And there is possibility that there will be never a true AI...
A robot who can learn, a robot that when you will turn it on and place in a cave - come back to the cave after 10 years you will see a intelligent creature who did learn to live in cave, its enviroment.
Thats what AI should be.
too much coffee ? but anyway it was realy nice to read.
I like AI news, but there is still one thing ...
There is no any AI
AI is Sci-Fi baby.
AI will be never created IF developers will not understand and somehow implement very important thing.
Intelligence is not a rule based system
When we born - we learn. We dont know what they are saying. We just see. Feel. And trying to think.
We are creating our own rules. We are building our brain. We are intelligent so we do not need to know everything before - we can figure out how things work without anyone who will tell us - "do this, do that".
So for me
AI is just too much for now And there is possibility that there will be never a true AI...
A robot who can learn, a robot that when you will turn it on and place in a cave - come back to the cave after 10 years you will see a intelligent creature who did learn to live in cave, its enviroment.
Thats what AI should be.
February 25, 2014, 06:37:27 AM
Neurala has highly parallel GPU based neural networks for better AI and self driving robotics
Networks (ANN) running on graphic processing units (GPU). The invention is seen as an important foundation for real-time artificial intelligence and robotics applications.
Humans outperform computers in many natural tasks, including vision and language processing, because the brain efficiently processes many inputs, learns, and recognizes patterns. Computers, however, process only one input at a time on each CPU core and then make sequential calculations. Therefore, even fast CPUs cannot match the power of the human brain.
Neurala’s breakthrough, which dates back to 2006, was to see that GPUs, which were originally designed for computer games and 3D graphics, could be used to process multiple inputs simultaneously and to simulate neural networks. Cutting-edge artificial intelligence and ANNs are dramatically accelerated on GPUs, which can handle many more instructions per clock cycle than a computer’s central processing unit (CPU). As a result, ANNs that can perform interesting tasks can be written to run in real-time using a low-cost graphic processing card found in many consumer products.
“Our invention makes it possible for robots and other devices to use artificial intelligence in situations in which execution time is critical. It will be fundamental for our effort to build brains for robots that interact with the world and with humans in real-time,” said Massimiliano Versace, CEO and co-founder of Neurala.
The robot's brain processes visual information in real time, enabling it to do more than simply navigate from one spot to another. This means robots could one day be trusted to make their own decisions when navigating changing terrain on Mars. The Neurala GPU networks are already ten times faster than regular CPU based networks.
* self driving flying drones
* self driving cars
* mostly self guided ground robots
Applied for navigating robots on Mars
Surface exploration of planetary environments with current robotic technologies relies heavily on human control and power-hungry active sensors to perform even the most elementary low-level functions. Ideally, a robot should be capable of autonomously exploring and interacting within an unknown environment without relying on human input or suboptimal sensors. Behaviors such as exploration of unknown environments, memorizing locations of obstacles or objects, building and updating a representation of the environment, and returning to a safe location, are all tasks that constitute typical activities efficiently performed by animals on a daily basis. Phase I of this NASA STTR focused on design of an adaptive robotic multi-component neural system that captures the behavior of several brain areas responsible for perceptual, cognitive, emotional, and motor behaviors. This system makes use of passive, potentially unreliable sensors (analogous to animal visual and vestibular systems) to learn while navigating unknown environments as well as build usable and correctable representations of these environments without requiring a Global Navigation Satellite System (GNSS). In Phase I, Neurala and the Boston University Neuromorphics Lab, constructed a virtual robot, or animat, to be developed and tested in an extraterrestrial virtual environment. The animat used passive sensors to perform a spatial exploration task. The animat started exploring from a recharging base, autonomously planned where to go based on past exploration and its current motivation, developed and corrected an internal map of the environment with the locations of obstacles, selected the shortest path of return to its recharging base before battery depletion, then extracted the resulting explored map into a human-readable format.(some videos and more)
http://nextbigfuture.com/2014/02/neurala-has-highly-parallel-gpu-based.html
Networks (ANN) running on graphic processing units (GPU). The invention is seen as an important foundation for real-time artificial intelligence and robotics applications.
Humans outperform computers in many natural tasks, including vision and language processing, because the brain efficiently processes many inputs, learns, and recognizes patterns. Computers, however, process only one input at a time on each CPU core and then make sequential calculations. Therefore, even fast CPUs cannot match the power of the human brain.
Neurala’s breakthrough, which dates back to 2006, was to see that GPUs, which were originally designed for computer games and 3D graphics, could be used to process multiple inputs simultaneously and to simulate neural networks. Cutting-edge artificial intelligence and ANNs are dramatically accelerated on GPUs, which can handle many more instructions per clock cycle than a computer’s central processing unit (CPU). As a result, ANNs that can perform interesting tasks can be written to run in real-time using a low-cost graphic processing card found in many consumer products.
“Our invention makes it possible for robots and other devices to use artificial intelligence in situations in which execution time is critical. It will be fundamental for our effort to build brains for robots that interact with the world and with humans in real-time,” said Massimiliano Versace, CEO and co-founder of Neurala.
The robot's brain processes visual information in real time, enabling it to do more than simply navigate from one spot to another. This means robots could one day be trusted to make their own decisions when navigating changing terrain on Mars. The Neurala GPU networks are already ten times faster than regular CPU based networks.
* self driving flying drones
* self driving cars
* mostly self guided ground robots
Applied for navigating robots on Mars
Surface exploration of planetary environments with current robotic technologies relies heavily on human control and power-hungry active sensors to perform even the most elementary low-level functions. Ideally, a robot should be capable of autonomously exploring and interacting within an unknown environment without relying on human input or suboptimal sensors. Behaviors such as exploration of unknown environments, memorizing locations of obstacles or objects, building and updating a representation of the environment, and returning to a safe location, are all tasks that constitute typical activities efficiently performed by animals on a daily basis. Phase I of this NASA STTR focused on design of an adaptive robotic multi-component neural system that captures the behavior of several brain areas responsible for perceptual, cognitive, emotional, and motor behaviors. This system makes use of passive, potentially unreliable sensors (analogous to animal visual and vestibular systems) to learn while navigating unknown environments as well as build usable and correctable representations of these environments without requiring a Global Navigation Satellite System (GNSS). In Phase I, Neurala and the Boston University Neuromorphics Lab, constructed a virtual robot, or animat, to be developed and tested in an extraterrestrial virtual environment. The animat used passive sensors to perform a spatial exploration task. The animat started exploring from a recharging base, autonomously planned where to go based on past exploration and its current motivation, developed and corrected an internal map of the environment with the locations of obstacles, selected the shortest path of return to its recharging base before battery depletion, then extracted the resulting explored map into a human-readable format.(some videos and more)
http://nextbigfuture.com/2014/02/neurala-has-highly-parallel-gpu-based.html
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