Mercedes EQE, page-53

You do realise that thread discusses HW yeah?

Or you not really understand the diff between HW & SW?

Hmmm....wonder if BRN has a SW, algo based IP available for ML?

https://www.newelectronics.co.uk/content/news/edge-impulse-releases-support-for-brainchip-akida-neuromorphic-ip/

Edge Impulse enables developers to build enterprise-grade ML algorithms, trained on real sensor data, in a low to no code environment. These trained algorithms can be quantised, optimised and converted to Spiking Neural Networks (SNN), which are compatible and can be deployed with BrainChip Akida devices.

This capability is available for new and existing Edge Impulse projects by using the BrainChip MetaTF model deployment block integrated on the platform. This deployment block enables free-tier developers and enterprise developer users to create and validate neuromorphic models for real-world use-cases and deploy on BrainChip Akida development kits.

A reference project targeting image classification is publicly available as an Edge Impulse public project, giving experts a head-start with developing algorithms for the next generation of neuromorphic computing.

Machine Learning experts will be able to create Akida-compatible models using the Edge Impulse expert mode within the learning block and using the BrainChip MetaTF model deployment block to use Tensorflow based models and quantise them to complete or mixed low-precision bits, from 1 to 4 bits. It also allows the implementation of quantisation-aware training to help retain the performance.

In addition, the optimised model can be converted to Akida-based SNN networks and experts will be able to download them to deploy on BrainChip Akida development kits. Users will also be able to see performance metrics, Akida model summary, and configuration data.

“We’re delighted to support BrainChip’s proliferation of their Akida technology,” said Jan Jongboom, CTO at Edge Impulse. “The combination of BrainChip’s advanced technology and Edge Impulse’s industry-leading developer experience gives users an easy and seamless way for deploying ML at the edge using efficient and essential SNNs algorithms that helps the advancement of solving real-world problems of all types.”

Edge Impulse is widely used to rapidly develop, deploy, and maintain ML algorithms where security, low-power, and remote deployment needs require intelligence at the edge. BrainChip’s Akida IP promises to massively increase the processing capability and efficiency of such applications.

Edge Impulse has started to integrate BrainChip’s MetaTF Software Development Environment so that those new to ML and Akida can more easily incorporate the benefits of the technology in their projects.

Here's a task for you as you always keen throwing questions at everyone else.

Go do some research and use the checklist to find totally comparable tech.

Plenty of similar products out there, which is normal in any industry, and will fit for certain use cases but not all are created or function equally.

The Akida chip includes several key features that differentiate it from other neural network processors and deep learning accelerators. These are:

• Event-based computing leveraging inherent data and activation sparsity

• Fully configurable neural processing cores, supporting convolutional, separable-convolutional, pooling and fully connected layers

• Incremental learning after off-line training

• On-chip few-shot training

• Configurable number of NPUs

• Programmable data to event converter

• Event-based NPU engines running on a single clock

• Configurable on-chip SRAM memory

• Runs full neural networks in hardware

• On chip communication via mesh network

• On chip learning in event domain

• Process technology independent platform

• Network size customizable to application needs

• IP deliverables include: RTL, dev tools, test suites and documentation