Designing Intelligence with Brains

In recent years, the best-performing systems in artificial-intelligence research have come courtesy of neural networks, which look for patterns in training data that yield useful predictions or classifications. A neural net might, for instance, be trained to recognis e certain objects in digital images or to infer the topics of texts. But neural nets are black boxes. After training, a network may be very good at classifying data, but even its creators will have no idea why. With visual data, it’s sometimes possible to automate experiments that determine which visual features a neural net is responding to. But text-processing systems tend to be more opaque. VIRTUAL BRAIN Neural networks are so called because they mimic — approximately — the structure of the brain. They are composed of a large number of processing nodes that, like individual neurons, are capable of only very simple computations but are connected to each other in dense networks. In a process referred to as ...

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix’s algorithms to make movie suggestions based on movies you have watched in the past or Amazon’s algorithms that recommend books based on books you have bought before. Machine learning algorithms can be divided into 3 broad categories —  supervised learning, unsupervised learning, and reinforcement learning.Supervised learning is useful in cases where a property ( label ) is available for a certain dataset ( training set ), but is missing and needs to be predicted for other instances. Unsupervised learning is useful in cases where the challenge is to discover implicit relati...

Researchers from MIT’s Computer Science, Artificial Intelligence Laboratory (CSAIL) and the machine-learning startup PatternEx have demonstrated an artificial intelligence platform that predicts cyber-attacks with 85% accuracy. Named as AI2, this artificial intelligence platform is roughly three times better than present security systems, and also reduces the number of false positives by a factor of 5. Drawbacks in the present Security systems The present security systems are either  Human or Machine-centric . The human based Security systems rely on the existing rules created by living experts and therefore miss any attacks that don’t match the rules. Similarly, the machine reliant systems rely on “anomaly detection,” which tends to trigger false positives that both create distrust of the system and end up having to be investigated by humans, anyway. However,  AI2  is a platform that makes use of human intelligence and machine capabilities simultaneousl...

What exactly is machine learning? The simplest definition i can give :-   "Machine Learning it the branch of AI that explores ways to improve decision making capability of computers i.,e,performance based on experience."  Let’s break that down to set some foundations on which to build our machine learning knowledge. Branch of AI:  Artificial intelligence is the study and development by which a computer and its systems are given the ability to successfully accomplish tasks that would typically require a human’s intelligent behaviour. Machine learning is a part of that process. It’s the technology and process by which we train the computer to accomplish the said task. Explores ways:  Machine learning techniques are still emerging. Some models for training a computer are already recognised and used (as we will see below), but it is expected that more will be developed with time. The idea to be remembered here is that different models can be used when t...

Unlike conventional computers, with separate memory and processing, neural networks serve as both memory and processor. And since processing can occur in localized sections throughout, brains are also much better at multitasking. Traditional computers have to do most of that multitasking in a sequence, so it takes ages. Spaun would do much better running on hardware that works more like a neural network does. Many consider artificial neural networks implemented on chips to be the next leap in computing, allowing faster processing with lower power needs for tasks like handling images, audio and video.  Hardware is facing bottlenecks because we can’t keep making devices faster and faster. This has forced people to reexamine neuromorphic approaches. Qualcomm and IBM are right on this with the new chips Zeroth and True North. These chips are hardwired with versions of neurons and synapses in traditional computing parts, but a relatively new electronic component enables a more di...

Technology certainly seems smarter than it was a decade ago. Most smartphones can now listen and talk. Computers are getting much better at interpreting images and video. Facebook, for instance, can recognize your face if you’re tagged in enough photos. These advances are largely thanks to machine learning, the technique of writing algorithms that can be “trained” to recognize images or sounds by analyzing many examples. Let’s start at the bottom. Much is known about the brain’s connections at the cellular level. Each neuron gathers electrical signals from those to which it is connected. When the total incoming current is high enough, it sends out an electrical pulse. That pulse is the neuron firing, also called spiking. When a neuron fires, it provides input to the neurons connected to its outgoing “wires.” In terms of computers, that’s a processing behaviour – the neurons filter their incoming signals and decide when to send one out. But the connections between the neurons, call...

As we have seen in Terminator series that machine takes over the Humans, same in the matrix series also. Did you ever thought can this be ever possible? If yes then how we will gonna control that change?Did you ever thought that how script writers can think something like that without being known to all this? Well this all  can possible with AI(Artificial Intelligence) or now days it's called as Machine Learning. Machine Learning is the new concept by which machine can learn human behavior and provide information as per requirement and they can change their behavior person to person. So big question is that how they can do that? This is concept completely related to Human Brain. Human Brain is the most complex structure to understand. Scientist isn't able to understand completely, as they tries to resolve mystery of this, they find something new in this segment. According to research analysis our brain consist of 10 billion's of neural network or it can be more. So jus...