BRAINCHIP HOLDINGS LTD WKN: A14Z7W ISIN: AU000000BRN8 Kürzel: BRN Forum: Aktien Thema: Hauptdiskussion

Link:https://www.tinyml.org/event/asia-2023/

Nandan Nayampally auf der tinyML Asia 2023 Solutions and Applications Brainchip’s Specialized Akida Architecture for Low Power Edge Inference with HW Spatiotemporal Acceleration and On-chip Learning Nandan NAYAMPALLY, CMO, Brainchip Brainchip’s Innovative Akida v2.0 Architecture Event-based, neuromorphic processing Extremely efficient computation only processes and communicates on events resulting in minimal latency and power consumption. Hardware accelerates event domain convolutions, temporal convolutions, and vision transformers while consuming very low power for battery-operated devices. At-memory compute Low-latency and low-power computation via parallel execution of events propagating through a mesh-connected array of Neural Processing Units (NPUs) each with a dedicated SRAM memory. Quantized parameters and activations Supports 8, 4, 2, 1-bit parameters and activations on layer-by-layer basis for model implementations tailored for optimum accuracy versus size, power, and latency. Accelerates Traditional AI models The MetaTF software stack quantizes and converts models in Keras/TensorFlow and Pytorch/ONNX to Akida event-driven models. Fully-digital Implementation Portable across process technology with standard synthesis design flow. Plus Novel Architectural Features below … Select Architectural Highlights Temporal Event-based Neural Networks (TENNs) Radically reduces number of parameters and operations by an order of magnitude or more for spatiotemporal computations with 2D streaming input such as video and 1D streaming input such as raw audio. Easily trained with back propagation like a CNN and inferences like a RNN. Extracts 2D spatial and temporal 1D kernels for 3D input and extracts temporal 1D kernels for 1D input. Vision Transformers (ViTs) Multi-head attention included in hardware implementation of Transformer Encoder block with configurations from 2 to 12 nodes. A two-node configuration at 800 MHz executes TinyViT at 30 fps (224x224x3). On-device learning Brainchip’s patented algorithm for homeostatic Spike Time Dependent Plasticity (STDP) enables on-device learning. AI applications can implement incremental learning so that models can adapt to changes in the field. On-device learning can add new classes to a model while leveraging features learned in its original, off-line training. Model Development Methodologies No-code Model Development and Deployment with Edge Impulse Users with limited AI expertise can develop and deploy optimized Akida models. Build-Your-Own-Model with Brainchip’s MetaTF Experienced AI users can build and optimize custom Akida models. Results Video Benchmarks Audio and Medical Vital Signs Benchmarks Image Benchmarks

Nominiert für ... MANUFACTURING TECH DISRUPTOR OF THE YEAR BrainChip Ltd. https://globalbusinesstechawards.com/2023-shortlist/

Der Kurs hat jetzt wieder das Niveau von August 2020 das zeigt uns wie stabil der Kurs ist 😂 alleine durch die Inflation hat man ca 6% Gewinn erwirtschaftet, Glückwunsch an alle investierten. Der Chips geht seinen Weg 😂😂✌️🍻

https://www.iot-now.com/2023/09/08/135571-brainchip-tata-elxsi-to-provide-intelligent-ultralow-power-solutions/

The mis-understanding between Artificial Intelligence and Machine Learning. https://www.linkedin.com/pulse/mis-understanding-between-artificial-intelligence-fran%C3%A7ois

Im Augenblick hilft hier nur noch künstliche Intelligenz https://itdigest.com/hardware-and-networks/brainchip-showcases-foundation-for-next-generation-ai-solutions-at-ai-hardware-edge-ai-summit/

https://de.pons.com/verbtabellen/deutsch/vergessen

Qualcomm CEO says AI may breathe new life into smartphones: 'It could create a new upgrade cycle' https://www-cnbc-com.cdn.ampproject.org/c/s/www.cnbc.com/amp/2023/09/06/qualcomm-ceo-ai-may-breathe-new-life-into-smartphones.html

Vergisst auch noch super chips