The Next Big Challenge for Chipmakers Is AI

The Next Big Challenge for Chipmakers Is AI Welcome to a Laptop AC Adapter specialist of the IBM Ac Adapter
Both IBM (IBM -1.47%)and Qualcomm (QCOM -0.51%)are trying to think about how to scale the awesome power of AI to fit on a battery-powered smartphone. Qualcomm’s answer its Zeroth technology, which basically runs a neural network on a chip. For example, it offers image recognition using a digital signal processor that is part of a number of chips sold as the brains inside mobile phones. Much like some of the dedicated processors for speech recognition on the iPhone or other handsets, this isn’t as impressive as what IBM is attempting.
IBM’s strategy is more ambitious. It wants to create a chip that mimics the human brain and will perform similar AI-level tasks on a smartphone. It’s using the human brain as a model because the brain is the most efficient computer we know of with adapter like IBM Thinkpad G40 AC adapter, Lenovo IdeaPad Y550 AC adapter, Lenovo IdeaPad Y710 AC adapter, Lenovo IdeaPad Y730A AC adapter, Lenovo IdeaPad Y450 AC adapter, Lenovo IdeaPad Y530 AC adapter, Lenovo IdeaPad U110 AC adapter, Lenovo IdeaPad U330 AC adapter, Lenovo IdeaPad U350 AC adapter, Lenovo IdeaPad U450 AC adapter, Lenovo 3000 Y510 AC adapter, Lenovo 3000 G430 AC adapter, using only 20 watts of power. In comparison, the new Nvidia “low-power” GPU consumes between 50-75 watts of power, which would drain your battery faster than you could say neural network.
So far, the resulting synaptic chip is still at the early stages, but it does exist in silicon, which was a big deal when IBM launched it in 2014. We won’t see this in smartphones anytime soon. For now, the heavy lifting of AI on our battery-powered devices will be shuffled off to dedicated silicon trained on one, or maybe two, specific types of neural networks.
With IBM, Nvidia, Qualcomm, and even Micron (which has a new processor called the Automata Processor that does pattern recognition) investing in artificial intelligence and deep learning, where’s the world’s largest chipmaker?
Intel (INTC -1.40%)recently made headlines with its purchase last month of an AI startup called Saffron, but the chip giant has been remarkably quiet when it comes to discussing its efforts around machine learning. The closest it comes is when it’s justifying its $16.7 billion purchase of Altera, a company that makes programmable chips. At an event in August Intel said it can use a combination of those programmable chips plus its own Xeon processors to run specialized algorithms such as those used to train neural networks.
This relative silence is troubling, given that silicon advancements require years planning. Intel has surprised the community with new technologies that it has developed in secret, such as its 3-D transistors from 2011, but in the chip community its lack of machine learning products are a gaping hole in its portfolio. “In chips, we have to plan two to four years out, so you have to figure out, what are the key apps,” said Jim McGregor, principal analyst with semiconductor research firm Tirias Research. “Intel missed out on mobile. It doesn’t want to miss out on this.”
Meanwhile, as the giants in the technology world invest in machine learning, the chip world is trying to give them a silicon platform that will allow them to deliver results both in the data center and on our handsets.