BrainChip at CES2025

BrainChip is distinguished by its brain-inspired neuromorphic AI technology that enables hyper-efficient, small footprint neural net acceleration for complex problems. What sets BrainChip apart is that it provides fully-digital, portable AI IP technology, that can be integrated on-chip with close proximity to sensors, providing real-time, intelligent and secure response minimizing the need for cloud intervention.

This unique approach optimizes constrained resources like memory, maximizes performance, and minimizes power consumption, enabling radically, innovative solutions for a range of industries, from space and healthcare to automotive and security.

The differentiation versus competition is extended with it’s ability to learn on-device – which allows each BrainChip equipped device to be customized in secure manner. Additionally, with the rapid migration of Generative AI and Large Language Models (LLMs) and Multi-modal applications, BrainChip’s TENNs (Temporal Event Based Neural Nets) can deliver 100x compression and performance gain without compromising accuracy which it forsees as a disruptive force to streamline the migration to Hybrid Edge AI computing.

The company’s emphasis on delivering AI at the edge, combined with a suite of revolutionary products like the AkidaTM IP and Edge AI Box, showcases BrainChip‘s commitment to proliferating efficient, cost-effective AI in tangible and impactful ways.

This year, we brought even more exciting demos and
insights, featuring our Akida platform.

Here’s what we demonstrated:

LLMs + RAG Demo

How we’re advancing large language models (LLMs) with Retrieval-Augmented Generation (RAG) for smarter, real-time AI applications.

Anomaly Detection Demo

Our latest anomaly detection solution running on Raspberry Pi 5. This versatile demo targets multiple verticals, including Industrial IoT, manufacturing, healthcare (wearable devices), cybersecurity, fraud detection, and more.

Building ML Models with
Edge Impulse

Hands-on demos with Edge Impulse, demonstrating how easy it is to build and deploy custom machine learning models directly on the Akida platform.

CES Podcast

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