You may have heard before about Intel’s Loihi neuromorphic chips that mimic the way brains work, but what hasn’t been clear yet is how the chipmaker will make money from the experimental silicon.
In a recent roundtable with journalists, Intel Labs lead Rich Uhlig offered two possibilities: integrating Loihi in a CPU for PCs to perform energy-efficient AI tasks and potentially offering the its neuromorphic chips as a cloud service, although Uhlig was clear he wasn’t firming actual product plans, just projecting what could theoretically happen in the future.
“Right now with Loihi, we’re at that point where we think we’re onto something, but we don’t actually have product plans yet. We’re sort of earlier on in that work stream,” he said last month.
Intel’s Loihi neurochips have been in development for the past several years under the purview of Intel Labs, which is insulated from commercial pressures inside the semiconductor giant so that it can conduct advanced research of “everything from the circuits up,” as Uhlig put it. This includes everything from microarchitecture and system architecture to system software and compilers.
While Intel Labs’ budget is protected, the goal is to create technologies that will someday turn into products. The group has churned out plenty of commercial technologies in the past, including Thunderbolt, hardware-assisted virtualization, and Intel Software Guard Extensions.
Since Intel first revealed its Loihi chips in 2017, the company has pitched them as a new way to handle AI tasks faster using far less energy. This is made possible by the fact that the neurochips’ pin-like structures, which are meant to replicate neurons in a brain, only consume electricity when they contribute data. That’s in contrast to traditional processors, where energy is used regardless of whether all the circuits are processing information.
This breakthrough in energy-efficient computing allows Loihi, for instance, to handle image similarity searches 24 times faster than a CPU using only 30 times less energy. The neurochip can also solve complex optimization problems like Sudoku puzzles or train scheduling 44 times faster than a CPU using 2,800 times less energy, another example offered by Intel.
Recently, researchers at the United States’ Sandia National Laboratories found that Loihi is a good fit for high-performance computing applications, too, like tracking financial market movements, disease spread within a population, and data flows within social networks.
These use cases represent things that could eventually generate revenue for Intel, but when Uhlig was asked how Loihi could materialize as an actual product, he pointed to the PC and cloud examples.
For the PC example, Uhlig said Intel could feasibly use its neuromorphic chip technology as a building block for silicon in a client system — we’re thinking CPUs in this case. The purpose would be to perform common AI tasks like speech recognition or gesture recognition.
While the use of neuromorphic technology in a CPU would be new, there is precedent for Intel integrating specialized accelerator technologies in its processors. One of the more prominent examples for PCs is the Gaussian Neural Accelerator that was introduced in Intel’s 10th-generation Core processors to handle low-power tasks like real-time translation.
As for offering neurochips as a cloud service, Uhlig said Intel Labs is now in a better place organizationally where it can stand up such products in the future. That’s because Intel Labs was moved last year under the Software and Advanced Technology Group, which is led by Intel CTO Greg Lavender.
The new organizational structure is a benefit for Intel, Uhlig said, “because we’re able to take our innovation, particularly things that are software-oriented, and scale them through Greg’s organization,” which has the charter of identifying new software revenue opportunities, as The Register has recently reported.
When it comes to how Intel’s Loihi’s development could benefit the company in other ways, Uhlig said the chipmaker could take the design methodology used for neurochips, called asynchronous design, and apply it to the way other chips are made.
“What we can do is take that asynchronous design methodology and deploy it into other parts of Intel products and get additional efficiency,” he said. ®