Deploying Large Language Models (LLMs) into real-world applications goes beyond simple model training. The process involves multiple phases, such as data preparation, model fine-tuning, deployment, and continuous performance monitoring. These stages demand seamless...
In the artificial intelligence sphere, Google has introduced Gemini AI, its latest generative AI platform. Google Gemini platform, emerging from Google’s AI research divisions, DeepMind and Google Research, manifests in three distinct versions: Gemini Ultra: The...
Imagine a supercomputer’s power in your smartphone, making complex tasks simple. This is now possible with Google’s Gemini Nano. This technology brings the power of advanced AI, previously only in larger models like Gemini Ultra and Pro, into a smaller,...
The landscape of Natural Language Processing has shifted dramatically with the introduction of large language models (LLM) like OpenAI’s GPT series and Google’s Transformer-based models. These LLM applications aren’t just incremental improvements but...
Retrieval Augmented Generation (RAG) and Large Language Models (LLMs) like GPT variants both play distinct yet interrelated roles in advancing machine learning applications. Initiated as separate entities—RAG for enhancing data sourcing and LLMs for linguistic...
PEFT (Parameter Efficient Fine Tuning) – This term can make anyone curious, and today we will discuss everything about PEFT in this blog. In the ever-evolving sphere of Natural Language Processing (NLP), a seismic shift has occurred. With the introduction of...
