“LLM decoding is bottlenecked for large batches and long contexts by loading the key-value (KV) cache from high-bandwidth memory, which inflates per-token latency, while the sequential nature of ...

Recently, my colleagues and I published a study on decoding language from brain recordings made using functional MRI. Brain decoders are being developed to help restore communication to people who ...

Object recognition is a key function in both human and machine vision. While brain decoding of seen and imagined objects has been achieved, the prediction is limited to training examples. We present a ...

In the rapidly evolving world of technology and digital communication, a new method known as speculative decoding is enhancing the way we interact with machines. This technique is making a notable ...

A neural interface framework integrating L2 regularization with attention supervision paradigms achieves 96.87% classification accuracy in EEG signal decoding, while an innovative generative AI ...

While lots of excellent software packages are available for decoding, they’re coded in higher-level languages suitable for CPUs and aren’t necessarily going to behave deterministically. FPGAs are a ...

A recent paper from Friedrich-Alexander University benchmarks energy consumption and compression efficiency for six video codecs across software and hardware decoders. While the study uses VP9 as a ...