ERNIE 2.0 is an AI language model proficient in understanding both English and Chinese languages.
Through a series of evolutions and improvements from Ernie 1.0, this language has shown remarkable capabilities, outperforming competitors including Google’s BERT and XLNet in numerous benchmarks that measure language comprehension.
Understanding abilities
- Superior performance in Natural Language Inference and Semantic Similarity
- Advanced proficiency in Sentiment Analysis
Technical groundwork
- Utilizes Transformer architecture
- Trained on extensive BookCorpus dataset
Model structure
ERNIE 2.0 is designed with a multi-layer Transformer architecture. At its core are foundational elements of the Transformer encoder, reminiscent of BERT’s mechanisms. This language understanding model differentiates itself by incorporating a continuum of pre-training methodologies.
The model incorporates several components:
- A [CLS] token at the beginning of input sequences.
- [SEP] tokens to delineate separate input segments.
- Unique task-specific embeddings provide context (‘Task ID’) for the input, allowing the model to differentiate and adapt to a range of pre-training objectives.
Enhancements in ERNIE 2.0
- Integration of a Continual Pre-training Framework
- Incorporation of Multitask Learning
- Innovative use of Self-Supervised Signals for training without human-labeled data
Examples of pretraining tasks
- Capital letter predictions to identify proper nouns
- Sentence relationship determinations
- Expanded semantic understandings
Multitasking approach
- Execution of various pretraining objectives simultaneously
Goals and milestones
- ERNIE’s continual updates aim to refine the model’s Language Representation and Processing
Strategic updates
- Continual Learning: Building and updating ERNIE with unsupervised pre-training tasks
- Multi-Layer Transformer: Enhancing contextual embeddings and language representations
The unveiling of ERNIE 2.0 is part of Baidu Research’s broader initiative to forward AI and autonomous technologies.
The company’s Apollo project has recently reached a milestone of over one million miles of navigation in Chinese urban landscapes. This venture, along with collaborations like the Intel Nervana Neural Network project, positions Baidu at the forefront of AI development.
The Duer conversational platform emphasizes Baidu’s commitment to expanding AI accessibility, now integrating voice command functionality in hundreds of millions of devices.
