"It's just about having more compute." Wait, is that really all there is to AI? As Richard Sutton's 'bitter lesson' sinks in for more AI researchers, a debate has stirred that considers a potentially more subtle relationship between advancements in AI based on ever-more-clever algorithms and massively scaled computational power.
Combining PyTorch and Google's cloud-based Colab notebook environment can be a good solution for building neural networks with free access to GPUs. This article demonstrates how to do just that.
Even though transformers for NLP were introduced only a few years ago, they have delivered major impacts to a variety of fields from reinforcement learning to chemistry. Now is the time to better understand the inner workings of transformer architectures to give you the intuition you need to effectively work with these powerful tools.
GPT-3 is the largest natural language processing (NLP) transformer released to date, eclipsing the previous record, Microsoft Research’s Turing-NLG at 17B parameters, by about 10 times. This has resulted in an explosion of demos: some good, some bad, all interesting.
Signal Processing is a branch of electrical engineering that models and analyzes data representations of physical events. It is at the core of the digital world. And now, signal processing is starting to make some waves in deep learning.
Recurrent Neural Networks can be used for a number of ways such as detecting the next word/letter, forecasting financial asset prices in a temporal space, action modeling in sports, music composition, image generation, and more.
Get a handle on how deep learning is affecting the finance industry, and identify resources to further this understanding and increase your knowledge of the various aspects.
Natural language processing has made incredible advances through advanced techniques in deep learning. Learn about these powerful models, and find how close (or far away) these approaches are to human-level understanding.
Building Neural Networks with PyTorch in Google Colab
Autograd: The Best Machine Learning Library You’re Not Using?