fresh bytes
Subscribe Now

Scientists now know how your brain differentiates faces

Researchers at Caltech have taken a huge step in figuring out how the brain processes faces. In a study published this week in Cell, the team found that the brain only needs around 200 neurons to differentiate faces from each other.

To figure this out, scientists first showed monkeys a set of pictures and recorded which face cells — neurons that specifically respond to faces — fired and which didn’t. What they found was that single cells weren’t responding to single faces. Instead, each cell was encoding a vector, or one direction in facial space, which means that a single neuron may respond only to a certain distance between a person’s eyes or a dimple on the left side of the mouth.

Continue reading at Engadget

Leave a Reply

featured blogs
Mar 3, 2021
In grade school, we had timed math quizzes. With a sheet full of problems and the timer set, the goal was to answer as many as possible. The key to speed is TONS of practice and, honestly, memorization '€“ knowing the problems so well that the answer comes to mind at first ...
Mar 3, 2021
The recent 34th International Conference on VLSI Design , also known as VLSID , was a virtual event, of course. But it is India-based and the conference ran on India time. The theme for this year was... [[ Click on the title to access the full blog on the Cadence Community s...
Feb 26, 2021
OMG! Three 32-bit processor cores each running at 300 MHz, each with its own floating-point unit (FPU), and each with more memory than you than throw a stick at!...
Feb 25, 2021
Learn how ASIL-certified EDA tools help automotive designers create safe, secure, and reliable Advanced Driver Assistance Systems (ADAS) for smart vehicles. The post Upping the Safety Game Plan for Automotive SoCs appeared first on From Silicon To Software....

featured paper

Increase the flexibility of your precision analog designs leveraging a low-cost MSP430™ MCU

Sponsored by Texas Instruments

There are many ways to address performance requirements while reducing the overall cost of your design. People often use dedicated integrated circuits to address specific functions, but this approach can cause variations in cost, complexity, and ease of use. There is another way to unlock the full potential of your design. Read more to see how a programmable MCU provides additional functionality and flexibility that is not typically available with conventional approaches.

Click here to read the paper

featured chalk talk

Cutting the AI Power Cord: Technology to Enable True Edge Inference

Sponsored by Mouser Electronics and Maxim Integrated

Artificial intelligence and machine learning are exciting buzzwords in the world of electronic engineering today. But in order for artificial intelligence or machine learning to get into mainstream edge devices, we need to enable true edge inference. In this episode of Chalk Talk, Amelia Dalton chats with Kris Ardis from Maxim Integrated about the MAX78000 family of microcontrollers and how this new microcontroller family can help solve our AI inference challenges with low power, low latency, and a built-in neural network accelerator. 

Click here for more information about Maxim Integrated MAX78000 Ultra-Low-Power Arm Cortex-M4 Processor