AI breakthrough allows machines to learn at speed of light
A recent breakthrough in artificial intelligence research has led scientists to believe that light can be used to power machine operations as opposed to electricity. This technology breakthrough will mean that operations can run smoother and quicker and improve the efficiency of machine learning neural networks
Current machine learning processes only allow for complex operations by the power required to process the data. The more intelligent the task, the more complex the data, and therefore the greater the power demands.The recent development will allow for this data to be processed quicker and with ease.
To overcome these limitations, researchers have found that using photons within the network could help create more powerful yet energy efficient artificial intelligence. The photons in the network are able to perform between 2 to 3 orders of magnitude higher than an electric TPU.
Potential applications include 5G and 6G networks in addition to data centres which process large quantities of data.
What do you think about this AI technology breakthrough?
What is machine learning?:
Simply put, machine learning is the study of computer algorithms that aim to improve themselves through experience.
Machine learning powers some of the tools that we use day to day that we may not even know about, for example Netflix uses machine learning, in addition to Twitter, Spotify and Google. Less shockingly, Siri and Alexa both utilise machine learning.
Each platform collects as much data about you as they can for example, what genres you like to listen to/watch, what links you click and even which statuses you interact with and react to most.
What is artificial intelligence?
Artificial intelligence is the simulation of human intelligence in machines that are programmed to think like humans and also mimic human actions. Artificial intelligence technology has many applications, the uses of it are endless. Such as self driving cars and even computers that play games like chess.
Artificial intelligence is also used in banking to help detect fraud and flag unusual activity.
Google is using AI to design faster and improved processors
Engineers at Google are now using artificial intelligence (AI) to design faster and more efficient processors, and then using its chip designs to develop the next generation of specialised computers that run the same type of AI algorithms.
Google designs its own computer chips rather than buying commercial products, this allows the company to optimise the chips to run its own software, but the process is time-consuming and expensive, usually taking two to three years to develop.
Floorplanning, a stage of chip design, involves taking the finalised circuit diagram of a new chip and arranging the components into an efficient layout for manufacturing. Although the functional design of the chip is complete at this point, the layout can have a huge impact on speed and power consumption.
Previously floorplanning has been a highly manual and time-consuming task, says Anna Goldie at Google. Teams would split larger chips into blocks and work on parts in parallel, fiddling around to find small refinements, she says.
Fast chip design
They have created a convolutional neural network system that performs the macro block placement by itself within hours to achieve an optimal layout; the standard cells are automatically placed in the gaps by other software. This ML system should be able to produce an ideal floorplan far faster than humans at the controls. The neural network gradually improves its placement skills as it gains experience, according to the AI scientists.
In their paper, the Googlers said their neural network is "capable of generalising across chips — meaning that it can learn from experience to become both better and faster at placing new chips — allowing chip designers to be assisted by artificial agents with more experience than any human could ever gain."
Generating a floorplan can take less than a second using a pre-trained neural net, and with up to a few hours of fine-tuning the network, the software can match or beat a human at floorplan design, according to the paper, depending on which metric you use.
"Our method was used to design the next generation of Google’s artificial-intelligence accelerators, and has the potential to save thousands of hours of human effort for each new generation," the Googlers wrote. "Finally, we believe that more powerful AI-designed hardware will fuel advances in AI, creating a symbiotic relationship between the two fields.