Context compression finally works in production: new research cuts LLM input 16x without the accuracy hit

LCLMs compress LLM context before decode — 8.8x faster at 16x compression, beating every KV cache method tested. Open-sourced by NYU and Columbia.

AV2 promises 30% better compression than AV1 and costs nothing to use

The Alliance for Open Media (AOMedia) recently released version 1.0.0 of the AV2 specification and reference code. The ...
IEEE

Implementing the Fast Full-Wave Electromagnetic Forward Solver Using the Deep Convolutional Encoder-Decoder Architecture

Abstract: In this communication, a novel deep learning (DL)-based solver is proposed for the electromagnetic forward (EMF) process. It is based on the complex-valued deep convolutional neural networks ...
GitHub

combining-feedforward-feedback.rst

``` ```python # Adds a feedforward to the loop output before sending it to the motor motor.setVoltage(pid.calculate(encoder.getDistance(), setpoint) + feedforward) ``` Moreover, feedforward is a ...
GitHub

intro-and-chassis-speeds.rst

Odometry involves using sensors on the robot to create an estimate of the position of the robot on the field. In FRC, these sensors are typically several encoders (the exact number depends on the ...