The next AEC Hackathon will be held in San Francisco on February 23-25, 2018. Four challenges await: Best overall project; Best project that solves a big AEC (Architecture, Engineering, Construction) problem; Best hack from a past event and Best mashup project. Tickets are now online. Get your Hackathon hat on and head over to the event registration today! The Khronos Group is a proud supporting organization of AEC Hackathon.
The Khronos Group announces the release of a geometry compression extension to glTF 2.0 using Google Draco technology to significantly reduce the size of glTF models and scenes. The Khronos glTF Draco extension specification is accompanied by optimized, open source compression and decompression libraries on the Draco GitHub site to enable the rapid deployment of glTF compressed geometry into tools, engines, applications, and browsers everywhere.
The Khronos Neural Network Exchange Format, among other technologies, go a long way to enable highly optimized implementations of inference for systems trained on a range of systems. Explains Chris Rowen, CEO for Babblabs, "This is extremely valuable to opening up the path to exploit optimized high-volume inference engines in phones, cars, cameras and other IoT devices. This higher-level robust set of interfaces breaks the tyranny of instruction set compatibility as a standard for exchange and allows for greater levels of re-optimization as the inference execution hardware evolves over time." Read more on the Semiconductor Engineering blog.
Standards make life easier, and we depend on them for more than we might realize — from knowing exactly how to drive any car, to knowing how to get hot or cold water from a faucet. Balancing the need for a stable standard, while at the same time allowing technology advances to be rapidly exploited, is a big part of what Khronos does. There are two ways a Khronos standard can be extended: Vendor Extensions and Khronos Extensions. Read on to learn how both of these work within Khronos.
This podcast episode of “The Interview” with The Next Platform focuses on an effort to standardize key neural network features to make development and innovation easier and more productive. To explore this topic, The Next Platform was joined by Neil Trevett. Listen to the podcast and read the write up.