Thought Leadership - TrueFoundry Blog

TrueFoundry Blog

Thought Leadership

A collection of 6 posts

Is AI Workload Bloating Up Your Cloud Bill?

Thought Leadership

Is AI Workload Bloating Up Your Cloud Bill?

We firmly believe that every company will be a Machine Learning (ML) company in the coming few years. As organizations embrace ML, one of the significant challenges they face is managing the associated cloud costs. Running AI/ML workloads in the cloud can quickly become expensive, but with careful planning

LLMOps CoE: The next frontier in the MLOps Landscape

LLMOps CoE: The next frontier in the MLOps Landscape

In this blog, we will explore the importance of LLMOps and how it tackles the challenges associated with LLMs, such as iteration, prompt management and testing complexities. We also go a step further and suggest how you can get started on your LLMOps journey. Large language models (LLMs) have caused

Thought Leadership

The $360K question about Large Language Models Economics

The purpose of this article is to educate the reader about how Large Language Models (LLM) pricing works. This is motivated by our conversations with multiple companies using LLMs commercially. We realized in these conversations that LLM economics is often misunderstood, leaving a huge scope for optimization. Do you realize

Prompt Engineering

Prompt Engineering: Learning to Interact with LLMs

The emergence of ChatGPT / OpenAI and other Large Language Models (LLMs) has revolutionized the world and is one of the most significant technological advancements of the past decade. With the help of AI, we can now automate numerous day-to-day tasks that were once mundane and time-consuming. However, to fully leverage

Evaluating Production Readiness and Technical Debt of ML Systems

Thought Leadership

Evaluating Production Readiness and Technical Debt of ML Systems

Machine learning (ML) is revolutionising various industries and applications, ranging from healthcare and finance to self-driving cars and fraud detection. However, deploying ML systems in production environments is challenging due to various factors, such as technical debt and the lack of production readiness. Technical debt is an ongoing concern for

Learn about various LLM applications in this age

Thought Leadership

LLMs, LLMs Everywhere: Exploring their applications!

The advent of extremely large language models, such as ChatGPT (with 20 billion parameters) and GPT-3 (with 175 billion parameters), has revolutionized the field of natural language processing. These models are trained on vast amounts of data and exhibit remarkable performance in text understanding and generation. Thanks to their ability