Last updated: 27th Jan, 2024 Training an AI / Machine Learning model as sophisticated as the one used by ChatGPT…
AI-ready data usually refers to data that has been prepared in such a way that it can be effectively used…
Last updated: 23rd Jan, 2024 Can innovation be taught and learned methodically? Can there be an innovation playbook using which,…
Last updated: 23rd Jan, 2024 Two NLP concepts that are fundamental to large language models (LLMs) are transfer learning and…
In the rapidly evolving landscape of software development, the integration of artificial intelligence (AI) and generative AI (Gen AI) is…
Last updated: 21st Jan, 2024 Machine Learning (ML) models are designed to make predictions or decisions based on data. However,…
The Transformer model architecture, introduced by Vaswani et al. in 2017, is a deep learning model that has revolutionized the…
As data scientists and MLOps Engineers, you must have come across the challenges related to managing GPU requirements for training…
A pre-trained or foundation model is further trained (or fine-tuned) with instructions datasets to help them learn about your specific…
Training large language models (LLMs) like GPT-4 requires the use of distributed computing patterns as there is a need to…
Are you fascinated by the power of deep learning large language models that can generate creative writing, answer complex questions,…
In this blog, we will learn about a comprehensive framework for the deployment of generative AI applications, breaking down the…
NLP has been around for decades, but it has recently seen an explosion in popularity due to pre-trained models (PTMs),…
Have you been wondering what sets apart two of the most prominent transformer-based machine learning models in the field of…
At the heart of NLP lies a fundamental element: the corpus. A corpus, in NLP, is not just a collection…
In the field of AI / machine learning, the encoder-decoder architecture is a widely-used framework for developing neural networks that…