Phones

Not A Flagship Prerogative: Project Trillium To Bring AI To Low-End Phones

project trillium low end phones

AI started with algorithms trying to trump humans at games of Go, decipher mysteries people couldn’t and get creative faster than us. Now, machine learning is reaching flagship phones, enabling advanced object recognition or saving up battery. But what if you want to enjoy the latest technology can offer yet can’t invest in a premium smartphone? Cue in Project Trillium. ARM told us their machine learning initiative will reach low-end mobile devices as well #mobilemagic

“What’s less obvious [about Project Trillium] is that it’s not just about the processors, but actually about a continuum of scalability, flexibility and options. […] Machine learning is going to be something that applies, to greater or lesser degrees, across the entire spectrum of computing over time, and so Project Trillium is really about completing that spectrum, […] enabling both high-end and low end mobile phones and devices even far beyond both ends of that.”, told us Dennis Laudick, the VP of Marketing ARM.

The ARM machine learning processor will match the amount of performance (power and silicon) OEM need and compliment the company’s spectrum of processors. By doing so, their initiative will reduce the gap between high-end and low-end devices and therefore, could raise the bar for the whole industry. On the other hand, the scalability of Project Trillium means that more consumers get to take advantage of AI solutions and in turn, their experiences and feedback can push the envelope of machine learning.

It’s not about the technology, it’s about humans and, more importantly, human society 

We asked Dennis how do robotics and IoT fit their plans for the future and how will they influence machine learning: “Robotics is the most advanced in developing useful applications and techniques for AI, and in many ways the lab for ML/AI. IoT is already seeing huge benefits from ML/AI. Examples might be identifying anomalies that are potential security threats or being able to make useful sense of vast amounts of individual IoT data.  All of these are going to be significant, of course, but […] AI/ML […] is a foundational technology and capability.”

Without a doubt, at the base of intelligent machines nowadays lies machine learning. As long as they’re assisting, working as auxiliary brains like we mentioned here, that’s fine. It’s more than fine – it’s admirable.

What will happen when they do more than that – when they learn to take decisions and become independent?

It’s going to be a while until we see our Sci-Fi dreams become reality, believes Dennis: “[…] although machine learning is a huge leap forward in terms of what computing can do, it’s still very long way away from something like Artificial General Intelligence (AGI).” We might see things from Space Odyssey taking shape now but Earth won’t be ruled by robots soon.

In fact, that scenario might never occur. If we want to speculate on the changes real artificial intelligence will bring to our world, we need look no further than ourselves. “The technology itself is inert.  It’s just technology; it doesn’t have any preference or propensity.  Like any technical or industrial advance in the past, it has the capability to be used for positive and negative purposes.  So in this sense, I don’t think it’s really about the technology, it’s about humans and the social norms we construct to allow that technology to be used.”, concluded Laudick.

We’ll let you mull it over and get back to us in the comment section below!

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