The following are the top three Natural Language Processing (NLP) advances:
1) Quantum Natural Language Processing (QNLP): There is a growing interest in the intersection of quantum computing and NLP. New quantum designs for basic tasks such as text encoding and models for language operations motivated by quantum theory are being explored. This includes advancements in word embeddings, sequential models, attention mechanisms, and grammatical parsing within the quantum framework.
2) Advancements in AI Processors and Chips: The computational power of NLP models has increased because of the improvements in AI chips. Such chips can process more parameters, allowing NLP systems to interpret more than 100 billion parameters.
3) Enhanced Data Availability and Quality: The growth in data availability, as well as with improvements in data labeling tools, has significantly enhanced the training data quality for NLP systems. This has therefore contributed to the expansion of the NLP market and the capabilities of NLP models.
