Brainchip Holdin - BCHPY STOCK NEWS

BrainChip Holdings (ASX: BRN, OTCQX: BRCHF) has released a new episode of its 'This is Our Mission' podcast featuring Srini Vasan, president and CEO of Quantum Ventura Inc. The episode focuses on cybersecurity's future and promising technologies for data protection.

Vasan, a member of the MIT Technology Review Global Panel, brings expertise in AI/ML, cognitive computing, blockchain, cybersecurity, and quantum computing. He currently works on large-scale data analytics projects with various U.S. entities including the SEC, public school systems, and healthcare systems.

The podcast, hosted by BrainChip CMO Steve Brightfield, discusses cybersecurity vulnerabilities and data privacy. BrainChip's Akida platform is highlighted as an event-based compute solution for edge AI applications, including robotics, drones, and automotive systems.

BrainChip Holdings announced the integration of its Akida™ processor into Quantum Ventura's CyberNeuro-RT (CNRT) cybersecurity protection technology. The solution, developed in partnership with Lockheed Martin's MFC Division and Pennsylvania State University, is partially funded by the U.S. Department of Energy.

The integration leverages BrainChip's neuromorphic processing for on-chip learning in network-specific attack detection. Akida's key advantages include its small form factor and significantly lower power consumption compared to GPUs, making it suitable for internet-connected devices that traditionally remain unprotected.

The Akida processor can detect malware, attack signatures, and malicious activity by learning normal network traffic patterns. Its ability to learn on-device without cloud retraining allows quick adaptation to emerging threats. The technology operates in micro-watt to milli-watt power budgets, making it ideal for battery-operated or fan-less embedded edge devices.

BrainChip Holdings (ASX: BRN, OTCQX: BRCHF) has announced the release of its Akida™ neural networking processor in the M.2 form factor. This new implementation enables low-cost, high-speed, and low-power AI processing at the edge, operating on approximately 1 watt of power.

The AKD1000 processor, available in B+M Key and E Key configurations of the M.2 2260 form factor, can be integrated into various devices including Raspberry PI and Edge AI box enclosures. The technology supports incremental learning and high-speed inference for applications where space and power are , such as industrial facilities, factory service centers, and network access devices.

The product is currently available for industry evaluation, development, and proof of concept, with pricing starting at $249. The IP is also available for licensing and integration into System-on-Chips (SoCs).

BrainChip Holdings has announced a partnership ecosystem for its Akida Edge AI Box, a compact AI computing platform powered by the Akida AKD1000 IC. The device, developed with VVDN Technologies, features embedded Linux, Ethernet, Bluetooth, and USB interfaces.

Key partners and applications include:

• Edge Impulse for AI model training and development
• BeEmotion for gesture recognition
• AI Labs for climate change solutions
• DeGirum for model evaluation
• Quantum Ventura for cybersecurity solutions
• Vedya Labs for computer vision analysis

The Akida Edge AI Box utilizes dual Akida processors for on-chip learning independent of the cloud, offering enhanced application security and faster learning capabilities. The system is designed for deployment across various sectors including healthcare, retail, automotive, and aviation, providing cost-effective AI processing at the edge.

BrainChip Holdings (ASX: BRN, OTCQX: BRCHF) announced that Frontgrade Gaisler has licensed its Akida™ IP for integration into space-grade AI acceleration systems. The agreement enables AI chip deployment in space, with Akida selected for its real-time data processing capabilities, resiliency, and low power consumption. The European Space Agency (ESA) has been leading efforts in neuromorphic computing deployment, recognizing its advantages over FPGA and GPU technology for edge deployments under space constraints. Frontgrade Gaisler, known for deploying space-grade microprocessors throughout the solar system, will incorporate BrainChip's neuromorphic AI to enhance space-borne computers with improved power efficiency while maintaining compatibility with existing Convolutional Neural Networks.

BrainChip Holdings has been awarded a $1.8M development contract from Air Force Research Laboratory (AFRL) for neuromorphic radar signaling processing technologies. The contract follows a successful demonstration of radar processing algorithms running on BrainChip's Akida™ neuromorphic hardware.

The project aims to validate sophisticated radar processing solutions in size, weight, power, and cost (SWaP-C) constrained platforms, including threat detection, air defense, and guidance systems. The technology will be implemented in various mobile platforms such as drones, robots, aircraft, and satellites.

BrainChip's Akida processor offers ultra-low power consumption for edge computing applications, making it ideal for military and spacecraft applications where power efficiency is crucial.

BrainChip Holdings has introduced the Akida™ Pico, the lowest power acceleration co-processor for AI applications. This innovation enables the creation of compact, ultra-low power, portable, and intelligent devices for various applications including wearables, healthcare, IoT, and defense. Key features of Akida Pico include:

- Ultra-low power standalone NPU core (<1mW)
- Support for power islands for minimal standby power
- Industry-standard development environment
- Very small logic die area
- Configurable data buffer and model parameter memory

The Akida Pico is built on the Akida2 event-based computing platform and can operate on less than a single milliwatt, making it suitable for battery-powered devices. It uses BrainChip's exclusive MetaTF™ software for compiling and optimizing specific Temporal-Enabled Neural Networks (TENNs).

BrainChip Holdings (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY) has released a technical paper introducing aTENNuate, a lightweight deep state-space autoencoder algorithm for raw audio denoising, super resolution, and de-quantization optimized for edge computing. This advancement expands BrainChip's leadership in neuromorphic event-based computing.

aTENNuate belongs to the class of state space-based networks called Temporal Neural Networks (TENNs). It can capture long-range temporal relationships in speech signals, useful for global speech patterns, noise profiles, and potentially semantic contexts. This technology complements BrainChip's Akida IP, an event-based neural processor that offers lower power consumption compared to conventional neural network accelerators.

BrainChip's event-based AI technology is expected to impact various markets, including wearable products (earbuds, hearing aids, watches, glasses) and AIoT devices in smart homes, offices, factories, and cities.

BrainChip Holdings (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY) highlights the advantages of event-based AI computing for radar and lidar systems. This technology offers performance improvements over conventional signal processing algorithms, addressing key detection and tracking challenges. Event-based AI is particularly efficient for processing point cloud solutions and working with sequential or continuous data streams.

Key benefits include:

• Rapid, accurate response to environmental changes
• Power efficiency, computing only when events occur
• Better data management, focusing on relevant data
• Adaptability to various system sizes and scopes