- self-learning artificial intelligence

Intel’s Self-Learning Artificial Intelligence Chip Codenamed Loihi

What comes to mind when you hear the words “self-learning artificial intelligence”? How do you imagine that the future could look in a world where complex decisions are made based on much more than a raw mathematical calculation?

Is the thought of machine learning something that horrifies you, or are you excited about the possibilities in a world where artificial intelligence has the ability to enhance our lives?

The scope of application of such technology seems more than limitless, and some may agree that it’s difficult to cast imagination as far as ‘the potential for a future reality’.

Imagine a situation like this

The emergency services attend a call to provide service at the scene of a motor vehicle accident. The moment they arrive they are able to instantly determine the extent of injuries, and the most effective means of extrication.

Without any chance of error, they then determine the percentage of success of various treatment methodologies to provide the most effective outcome for preserving life in fractions of a second. On top of that, where complexities arise, they are able to include emotional factors in the equation. Enter stage left; Intel’s self-learning chip, codename Loihi.

With the most recent advances in technology, and the capability for self-learning artificial intelligence to make more frequently accurate, and mindbogglingly more intuitively, almost emotively effective decisions, anything is possible.

What is really unstructured organic or biological data, more clearly painted as human thought and emotion-based responses is becoming less of an anomaly to self-learning artificial intelligence. Our thoughts and feelings that trigger our reactions are becoming more and more predictable to technology.

We are at a stage where there is a building need for the harvesting of data to provide a basis for quicker and more effective analysis in order to keep abreast of the wave coming our way as a species. Intel’s Loihi, a project of six years, is touted as being that little piece of magic that will take AI and neuromorphic computing to the next level.

Professor Carver Mead collaborates with Intel

Intel’s work in neuromorphic computing draws upon over ten years of collaboration and research which started with Professor Carver Mead, yes, the same Professor Carver Mead who is known for his work in the designing of the semiconductor. Today, Loihi, as a neuromorphic chip, is a groundbreaking leap in the self-learning artificial intelligence space.

As self-learning artificial intelligence, Loihi gets smarter and smarter as time goes on. With each encounterLoihi becomes more intuitive and capable of understanding and responding to the comparatively chaotic human mind.

Even though artificial intelligence is still in its infancy, with the adaptations in architecture methods, like that of Loihi, the bar will continue to be raised with neuromorphic computing.

The inspiration behind neuromorphic computing is taken from our current comprehension of the architecture of the human brain, and its associated computation methods. As the neural network relays information through spikes or pulses, it is the timing of these spikes or pulses that are key. - self-learning artificial intelligence - Professor Carver Mead collaborates with Intel
Deep Mind is no match for Loihi

Deep Mind and other machine learning projects have made significant advancements through the use of data sets to reorganize events and objects. However, when they have encountered anomalies in these data sets previously, the unexpected has caused some disruptions to the accuracy, and in cases, ability to maintain computation.

This has been the case where their training data sets have not accounted for a specific situation, element or circumstance. As a result, these particular machine learning systems like Deep Mind, don’t function well when required to generalize.

With the scope of possibilities behind self-learning chips and neuromorphic computing, the potential benefits in a range of fields such as medical, automotive, cybersecurity and the financial sector are limitless.

Loihi is designed with the big picture capacity to mimic the brain’s fundamental mechanics, resulting in this phase in machine learning showing an increase in speed and efficiency, with a need for much less power than anything before it. Rather than being tethered to updates from the cloud, Loihi gives machine learning the capacity to be able to autonomously learn on the go and adapt to a range of situations in real time.

The future and self-learning artificial intelligence

2018 is set to be a very exciting year with Loihi being shared with a select group of leading universities and research institutions that already have an active focus on AI. Based on Intel’s 14nm technology, Loihi is completely asynchronous comprising 130 thousand neurons, and 130 million synapses, and is capable of communicating with thousands of other neurons.

The impact of AI on society is something that will no doubt take place on a spectacular scale. Unprecedented innovation ushered in through the advancements in self-learning artificial intelligence will no doubt improve the collective quality of life across borders and generations.

The present-day application of AI within more and more businesses across various industries has reduced the workload of individuals considerably. Less time is being actively spent on processes that have been able to benefit from automation.

We will continue to follow the exciting installments from Intel over the coming months; eager to see how the self-learning artificial intelligence changes on the horizon will shape the economy of tomorrow.

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