Archives for BERT Model - Page 3
Recently, Google Research introduced a new sparse attention mechanism that improves performance on a multitude of tasks that require long contexts known as BigBird. The researchers took inspiration from the graph sparsification methods. They understood where the proof for the expressiveness of Transformers breaks down when full-attention is relaxed to form the proposed attention pattern.…
The post What Is Google’s Recently Launched BigBird appeared first on Analytics India Magazine.
Recently, researchers from DeepMind, UC Berkeley and the University of Oxford introduced a knowledge distillation strategy for injecting syntactic biases into BERT pre-training in order to benchmark natural language understanding. Bidirectional Encoder Representation from Transformers or BERT is one of the most popular neural network-based techniques for natural language processing (NLP) while pre-training. At the…
The post How Syntactic Biases Help BERT To Achieve Better Language Understanding appeared first on Analytics India Magazine.
With the advent of transformer-based machine translation models, researchers have been successful in implementing state-of-the-art performance in natural language processing (NLP). In 2018, Google open-sourced its groundbreaking state-of-the-art technique for NLP pre-training called Bidirectional Encoder Representations from Transformers, or BERT. With the help of this model, one can train their state-of-the-art NLP model in a…
The post BERT Is So Popular That Google Have To Release A Website To Collate All Developments appeared first on Analytics India Magazine.
When OpenAI released its GPT model, it had 1.5 billion parameters and made it the biggest model back then. It was soon eclipsed by NVIDIA’s Megatron, which had 8 billion parameters. Last month Microsoft released the world’s largest language model Turing NLG that has 17 billion parameters. In terms of hardware, any model with more…
The post Are Larger Models Better For Compression appeared first on Analytics India Magazine.
The ability of natural language in machines, so far, has been elusive. However, the last couple of years, at least since the advent of Google’s BERT model, there has been tremendous innovation in this space. With NVIDIA and Microsoft releasing mega models with tens of millions of parameters, it is safe to say that we…
The post Top 8 Baselines For NLP Models appeared first on Analytics India Magazine.
Over these few years, large pre-trained models such as BERT, ELMo, XLNet, among others, have brought significant improvements on almost every natural language processing (NLP) tasks in organisations. Microsoft has been doing a lot of research around natural language processing (NLP) and natural language understanding (NLU) for a few years now. The Natural Language Processing…
The post Microsoft Introduces First Bimodal Pre-Trained Model for Natural Language Generation appeared first on Analytics India Magazine.
Natural Language Processing (NLP) is one of the most diversified domains in emerging tech. Last year, search engine giant Google open-sourced a technique known as Bi-directional Encoder Representations from Transformers (BERT) for NLP pre-training. This model helped the researchers to train a number of state-of-the-art models in about 30 minutes on a single Cloud TPU,…
The post Google’s NLP-Powered Pretraining Method ALBERT Is Leaner & Meaner appeared first on Analytics India Magazine.
Computer and human interaction are one of the crucial reasons for the rapid evolution of emerging technologies. In this domain, artificial intelligence and natural language processing (NLP) is helping to bridge the gap between all these tasks. There has been considerable research into systems that mine images or other visual backgrounds and are able to…
The post Meet ViLBERT, The Task-Agnostic Model Inspired From BERT For Vision Grounding appeared first on Analytics India Magazine.