Training a foundation LLM from scratch costs millions and requires internet-scale data — which is why most enterprises don't bother. Sapient thinks it has a cheaper path. To overcome this brute-force ...
Right off the bat, let’s give a shout out to the mathematician propeller-heads who create the transformations that make it possible to do all kinds of high performance computing to simulate, model, ...
Abstract: The autoregressive (AR) models, such as attention-based encoder-decoder models and RNN-Transducer, have achieved great success in speech recognition. They predict the output sequence ...
Abstract: Recently, end-to-end models have been widely used in automatic speech recognition (ASR) systems. Two of the most representative approaches are connectionist temporal classification (CTC) and ...
Deploying DFlash block diffusion on NVIDIA hardware accelerates autoregressive LLMs during latency-sensitive inference. Autoregressive large language models generate tokens sequentially. This ...
Researchers from Renmin University and Bytedance have released iLLaDA, an 8B language model that works differently from ChatGPT. It matches Qwen2.5 at the base level but falls behind after fine-tuning ...
The boffins on Google’s DeepMind team unveiled an experimental new language model this week that uses techniques originally developed for AI image generators to boost text output performance by as ...
The main novelty seems to be an extra layer of indirection with the prior network (whether it is an autoregressive transformer or a diffusion network), which predicts an image embedding based on the ...
Synthesizing realistic audio, images, and videos using algorithms has always been essential in Signal Processing, Computer Graphics, and Computer Vision. When using pre-artificial intelligence (AI) ...
DeepSeek speculative decoding framework DSpark went live June 27 on V4-Flash and V4-Pro, reporting up to 85 percent faster ...
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