BRN Discussion Ongoing

FJ-215

Regular
Early access is available for models including TENNs/LLM models.

AkidaNet/TENN Automatic Speech Recognition Model


Our TENNs model approach is applied to Automatic Speech Recognition for compact accurate voice to text applications.

AkidaNet/ TENN Large Language Model (LLM)


Our TENNs model approach is applied to an LLM model with a 1.2B parameter model that is getting excellent Perplexity scores compared to larger transformer based LLM models and features significantly reduced training costs.

AkidaNet/TENN Large Language Model (LLM+RAG)


Our TENNs model approach is applied to an LLM model with Retrieval Augmented Generation to provide intelligent access to documentation for those end use cases looking to embed an LLM for their products user interface.
Hi manny100,

Early access to what????

Akida 2 is nearly 3 years old!!!

Great news though,

We are at some point about to release this Akida 2 as a reference chip...........

Yes,,

it's , available thru the cloud.

BUT???
 
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manny100

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Hi Manny,

The Catalogue page mentions radar designs (also cybersecurity):

https://brainchip.com/corporate-catalogue-lp/

Reference Platforms & Roadmap
Validated designs for radar, wearables, voice AI, communications, cybersecurity, and future platform direction.

This may be for the see-in-the-dark robot application.
Thanks Dio, good pick up.. Makes it easier for developers.
 
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Frangipani

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A new monthly newsletter is out.

It contains the following info on BrainChip’s novel four reference platforms Akida Radar, Akida Tag, Akida Private Voice Assistant and Akida Communications:

“At BrainChip, delivering great IP and silicon is just the beginning. CES attendees got a sneak peek at our 2026 roadmap and strategy including four key Reference Platforms: complete, validated blueprints that combine hardware, software, and AI models that demonstrate key use cases that can be adapted by customers with our eco-system partners to create end products, highlighting our value proposition and speeding time to revenue.
  • Akida Radar: demonstrates efficient, real-time Micro-Doppler classification of flying objects, detecting unique motion patterns to objects without cloud dependency
  • Akida Tag: a compact, battery-powered wearable device showcasing how the Akida architecture enables always-on anomaly detection with self-learning in real-time using minimal power
  • Akida Private Voice Assistant: Complex generative AI performance on standard mobile hardware using TENNs to deliver expert-level intelligence instantly, without the latency or vulnerability of a connection
  • Akida Communications: Enables low Size Weight and Power (SWaP) for signal intelligence in handheld devices where power is scarce, allowing immediate adaptation to threats Processes RF data locally for maximum security
Stay tuned for more in the coming months as these reference platforms get unwrapped for release.”



The Future Is at the Edge: BrainChip at CES 2026​

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CES 2026 underscored a clear industry message: intelligent systems are moving decisively to the edge. From our suite at the Venetian, BrainChip spent the week engaged in continuous demonstrations and in-depth discussions on the future of edge AI, with strong interest from industry leaders, innovators, and partners throughout the show. Seeing Akida’s neuromorphic computing capabilities resonate so clearly across real-world use cases—from ultra-low power to high-performance edge applications—reaffirmed the importance and momentum of the work we are doing. Read on for an inside view of the BrainChip CES suite and what’s ahead.

Akida in Action with CES Partner Demos​

BrainChip welcomed three of our valued partners to the CES suite to demonstrate Akida’s low power, low latency, private edge AI accelerators in action.

Akida in Action with CES Partner Demos​

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By combining BrainChip’s on-device inference with HaiLa’s low-power Wi-Fi, we’ve eliminated the need to transmit heavy raw data. Akida™ processes the image locally and sends only a lightweight metadata code over the network. It’s smart, sustainable, and drastically reduces bandwidth.

Visual Computing Pipeline with Deep Perception​

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Deep Perception deploys real-time object detection, classification, and other video inference workloads in hours with production-ready GStreamer elements purpose-built for BrainChip Akida accelerators. Together they deliver a complete low-power video stack for power-constrained environments.

Edge AI Cybersecurity with Quantum Ventura / Metaguard AI​

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Metaguard AI integrates BrainChip’s Akida neuromorphic processor into its lightweight CyberNeuro-RT platform to continuously analyze the behavior of network traffic in real-time on the edge, reducing the cloud operational cost, improving data privacy and response time while maintaining long battery life.

Akida’s ready-to-develop AKD1500 Edge AI Co-Processor​

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BrainChip gave CES Suite visitors an up-close look at the new AKD 1500 neuromorphic Edge AI accelerator co-processor chip. Designed to deliver exceptional performance with minimal power consumption, the AKD1500 achieves ~ 1 Tera-Operations per second second (TOPS) while operating under 250 milliwatts—setting a new benchmark for edge AI efficiency. This makes AKD1500 ideal for deployment in battery-powered wearables, smart sensors, and power-constrained environments.

Accelerating Innovation: BrainChip’s Reference Platforms​

0e85203f-64e6-c6b1-59c9-23af34a0c6db.png
At BrainChip, delivering great IP and silicon is just the beginning. CES attendees got a sneak peek at our 2026 roadmap and strategy including four key Reference Platforms: complete, validated blueprints that combine hardware, software, and AI models that demonstrate key use cases that can be adapted by customers with our eco-system partners to create end products, highlighting our value proposition and speeding time to revenue.
  • Akida Radar: demonstrates efficient, real-time Micro-Doppler classification of flying objects, detecting unique motion patterns to objects without cloud dependency
  • Akida Tag: a compact, battery-powered wearable device showcasing how the Akida architecture enables always-on anomaly detection with self-learning in real-time using minimal power
  • Akida Private Voice Assistant: Complex generative AI performance on standard mobile hardware using TENNs to deliver expert-level intelligence instantly, without the latency or vulnerability of a connection
  • Akida Communications: Enables low Size Weight and Power (SWaP) for signal intelligence in handheld devices where power is scarce, allowing immediate adaptation to threats Processes RF data locally for maximum security
Stay tuned for more in the coming months as these reference platforms get unwrapped for release.

Akida Pico Now on Akida FPGA in the Cloud​

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BrainChip's Akida Pico is now available for testing on Akida FPGA in the Cloud with no hardware requirements. Pico is an ultra-low power co-processor operates efficiently in the micro-watt (μW) to milli-watt (mW) range, empowering devices to perform at their best without sacrificing battery life, purposely built to enhance applications in speech and audio processing as well as medical vital sign monitoring.

Looking Ahead to 2026​

Webinar: Keyword Spotting on Akida Pico​

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Join us on February 24th at 8:00 AM PST for an exclusive deep dive into the latest breakthrough in neuromorphic computing. BrainChip Solutions Architects Kurt Manninen and Ritik Shrivastava will demonstrate Akida Pico on FPGA, our latest ultra-low power NPU core designed for the next generation of intelligent edge devices.

Embedded World​

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Join BrainChip at Embedded World for unprecedented insight into the world of embedded systems, from components and modules to operating systems, hardware and software design.

Edge AI Foundation San Diego​

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Through our longstanding partnership with the EDGE AI Foundation, BrainChip will be exhibiting at the 2026 San Diego event alongside industry experts, researchers, and innovators shaping the future of edge AI.
Stay tuned as we continue to expand the boundaries of edge AI. From space to sensors—and everything in between—BrainChip is building the future of AI.
 
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Old but I think thru could have just updated the benefits

 
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