AI Technology & Industry Review
A research team presents a novel language-conditioned robot manipulation framework called Gen2Act, which achieves generalization to unseen tasks using publicly available web data, eliminating the need to collect specific robot data for every task.
In a recent new paper VALL-E 2: Neural Codec Language Models are Human Parity Zero-Shot Text to Speech Synthesizers, a Microsoft research team presents VALL-E 2, the latest advancement in neural codec language models. This innovation marks a milestone in zero-shot TTS synthesis by achieving human parity for the first time.
A pioneering research group introduces MovieChat, a novel framework tailored to accommodate extensive video durations exceeding 10,000 frames. This innovative system achieves unprecedented performance in deciphering prolonged video content.
In the new paper Learning Robust Real-Time Cultural Transmission Without Human Data, a DeepMind research team proposes a procedure for training artificially intelligent agents capable of flexible, high-recall, robust real-time cultural transmission from human co-players in a rich 3D physical simulation without using human data in the training pipeline.
A research team from the University of Hong Kong, Shanghai AI Lab, Huawei Noah’s Ark Lab and the University of Washington takes dataset generation methods via large-scale pretrained language models (PLMs) to the extreme with ZEROGEN, a flexible and efficient zero-shot learning framework via dataset generation.