IEEE

FPGA Design and Implementation of BCH Encoders and Decoders Using Pipelined Architecture for High Throughput Applications

This paper presents the design and FPGA implementation of a high-throughput BCH (n,k) encoder and decoder using a fully pipelined architecture. Unlike conventional designs based on finite state ...
IEEE

A Siamese Encoder-Decoder Model with Attention for LLM Prompt Reconstruction

Abstract: Reconstructing prompts in text generation systems is a significant challenge in natural language processing (NLP). This study presents a novel Siamese encoder-decoder framework augmented ...
blockchain

NVIDIA Advances AI Infrastructure With Disaggregated LLM Inference on Kubernetes

NVIDIA details new Kubernetes deployment patterns for disaggregated LLM inference using Dynamo and Grove, promising better GPU utilization for AI workloads. NVIDIA has published detailed technical ...
Network World

Nvidia targets inference as AI’s next battleground with Groq 3 LPX

The company says its new architecture marks a shift from training-focused infrastructure to systems optimized for continuous, low-latency enterprise AI workloads. 2026 is predicted to be the year that ...
GitHub

sherpa_onnx_asr.py

encoder: str = None, # Path to the encoder model, used with transducer decoder: str = None, # Path to the decoder model, used with transducer joiner: str = None, # Path to the joiner model, used with ...
Business Wire

AWS and Cerebras Collaboration Aims to Set a New Standard for AI Inference Speed and Performance in the Cloud

Fastest inference coming soon: AWS and Cerebras are partnering to deliver the fastest AI inference available through Amazon Bedrock, launching in the next couple of months. Industry-leading speed and ...