Intel announced that it has made some breakthrough advancements with its neuromorphic processors. The second-generation Loihi chip, known as Loihi 2, will be up to 10 times faster at processing algorithms and applications, the chipmaker stated, while still fitting on the tip of your pinky finger.
Advancements such as a pre-production Intel 4 process and the use of extreme ultraviolet lithography, or EUV, allowed the company to pack the chip with 15 times greater resource density, which means that Loihi 2 squeezes in up to 1 million neurons per chip. Through neuromorphic silicon, Intel hopes to defy the limits of Moore’s Law that constrains processors today.
The company’s work in neuromorphic research had led to advancements like a smell-o-vision chip in the first-generation Loihi. Neuromorphic computing is based on neuroscience and how the human brain functions, and it’s aimed at delivering speed and efficiency in learning across a number of applications.
“Neuromorphic computing represents a fundamental rethinking of computer architecture at the transistor level, inspired by the form and function of the brain’s biological neural networks,” Intel explained. “Despite many decades of progress in computing, biological neural circuits remain unrivaled in their ability to intelligently process, respond to, and learn from real-world data at microwatt power levels and millisecond response times.”
The new chip is a product of three years of research at the Intel Neuromorphic Research Community. It features self-learning capabilities, new neuron models, and asynchronous spike-based communication. Like the malleable human brain, Intel hopes that compared to traditional chip architectures, Loihi will deliver greater efficiency and faster processing speeds while consuming far less power. In early demos, the company claimed that Loihi consumes less than 1 watt of power, which is significantly less than traditional CPU and GPU solutions. The new processor comes with a 2x gain on synaptic density over the original and its neuron cores are about half the size of the prior generation.
Intel predicts that neuromorphic computing can be used for search engines, robotics, and solving complex problems. The neural networks powered by Loihi 2 can be used for faster deep learning training, and Intel claimed that early testing showed that Loihi 2 delivered 60x fewer ops per inference compared to the original Loihi. Loihi 2 comes with 8x the number of neurons, with up to 80x better synaptic utilization, in a 1.9x smaller size than Loihi 1.
“Investigators at Los Alamos National Laboratory have been using the Loihi neuromorphic platform to investigate the trade-offs between quantum and neuromorphic computing, as well as implementing learning processes on-chip,” said Dr. Gerd J. Kunde, staff scientist at Los Alamos National Laboratory, in a press release ahead.
“This research has shown some exciting equivalences between spiking neural networks and quantum annealing approaches for solving hard optimization problems,” Kunde added. “We have also demonstrated that the backpropagation algorithm, a foundational building block for training neural networks, and previously believed not to be implementable on neuromorphic architectures, can be realized efficiently on Loihi. Our team is excited to continue this research with the second-generation Loihi 2 chip.”
Along with the architectural upgrade powering Loihi 2, Intel also announced the Lava software framework. Designed as an open and modular framework, Lava will allow developers and researchers to build on each other’s progress to arrive at a common set of tools, methods, and libraries, Intel said, noting that Lava will run on heterogenous architectures across conventional and neuromorphic processors. This makes it ideal for work in A.I. and robotics.
In addition to the robotic nose, early applications of Loihi and neuro-based silicon like Loihi include gesture recognition and learning, robotic arm control, and scene understanding. Autonomous cars could be a natural progression of this research, and Intel counts Ford among the 150 partners for Loihi.
Acer’s Predator Atlas 8 finally has a US release date and price, several months after the company first showed off the handheld in May. The highlight is the Intel Arc G3 Extreme chip inside, which has been adopted by only a couple of other consoles besides the Atlas 8. This version will go on sale exclusively at Best Buy on November 1 for $1,299.99.
Acer originally said the Atlas 8 would arrive in North America in October, but left pricing open at the time. The launch came amid the ongoing DRAM crunch, which has made memory more expensive across the PC industry and complicated pricing for hardware makers.
Google DeepMind's AI world model Genie 4 can now build interactive worlds that you can explore and reshape as they run. It also generates ambient sounds, music, and dialogue that respond to your actions.
The new world model builds on Genie 3 with improved realism, more natural human movement, and better simulations of real-world physics. It could eventually help with everything from game development to training robots.
Apple has an incredible talent for making me admire its products while simultaneously questioning what on earth it's thinking with the pricing. This isn't even something as bizarre as a monitor stand, but the audacity for starting a new laptop lineup from $2,000 doesn't surprise me.
The newly announced 14-inch MacBook Pro with M6 is just the latest to showcase this. The funny thing is, I already know that it's going to be a reliable workstation. You get a powerful new 2nm M6 processor, a gorgeous Liquid Retina XDR display, and up to 24 hours of battery life. We were impressed by the M5 MacBook Air, so the high-end M6 powered MacBook Pro definitely won't let us down.