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It may seem like a long time since the world of natural language processing (NLP) was transformed by the seminal “Attention is All You Need” paper by Vaswani et al., but in fact that was less than 3 years ago. The relative recency of the introduction of transformer architectures and the ubiquity with which they have upended language tasks speaks to the rapid rate of progress in machine learning and artificial intelligence. There’s no better time than now to gain a deep understanding of the inner workings of transformer architectures, especially with transformer models making big inroads into diverse new applications like predicting chemical reactions and reinforcement learning.
Whether you’re an old hand or you’re only paying attention to transformer style architecture for the first time, this article should offer something for you. First, we’ll dive deep into the fundamental concepts used to build the original 2017 Transformer. Then we’ll touch on some of the developments implemented in subsequent transformer models. Where appropriate we’ll point out some limitations and how modern models inheriting ideas from the original Transformer are trying to overcome various shortcomings or improve performance.
Transformers are the current state-of-the-art type of model for dealing with sequences. Perhaps the most prominent application of these models is in text processing tasks, and the most prominent of these is machine translation. In fact, transformers and their conceptual progeny have infiltrated just about every benchmark leaderboard in natural language processing (NLP), from question answering to grammar correction. In many ways transformer architectures are undergoing a surge in development similar to what we saw with convolutional neural networks following the 2012 ImageNet competition, for better and for worse.
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In this article, see how to transform advertisement and graphic design industries through AI.
The term artificial intelligence is an umbrella term that covers a wide range of machines that learn through the data that we feed them with to perform certain cognitive tasks just like humans.
Because of their outstanding abilities, the use of artificial intelligence powered machines is growing exponentially. These machines possess the ability to read and understand text, hear sounds and understand them, see and identify images and even move flawlessly around obstacles just like humans.
From Gmail’s smart compose, which recommends what to type next, to **Facebook **recommending who to tag by detecting the faces in the photos, to **Siri **being able to understand voice commands and creating responses, all are using the power of AI.
Considering these examples, we can say that AI has transformed the methods and ways of working across the world and the surprising fact is that it is still evolving. To understand how AI is helping in transforming organizations, some recent trends in AI have been discussed in detail further.
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iBrandox is a top-notch agency for advertising company in Delhi. A primary role of an advertising agency is the creation of an advertising and marketing plan specific to your business, product, and brand. A firm engaged in providing services of advertisement for clients to create awareness and market for them is known as an advertising agency.
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