LLMs

MLOps: Machine Learning Life Cycle

MLOps Lifecycle strings model and software development together in an unified machine learning life cycle for CI/CD/CT of ML products.

ChatGPT Alternatives That Deserve Your Attention

Several Large Language Models are emerging: Google Bard/LaMDA, Meta’s LLaMA, Amazon’s Multimodal-CoT, HuggingFace’s Bloom, and open-source ChatLLaMA.

Who Cares if Big Data Is Dead!

What really matters is the quality of the data, the data literacy at the organization, and the motives behind using data analytics.

The Rise of ChatGPT: Separating Hype from Reality

ChatGPT is part of OpenAI’s GPT-3 family of large language models. It is immensely powerful but can confidently hallucinate too. Here is what ChatGPT can and can’t do.

Machine Learning and MLOps Tools on Google Cloud

Data and Machine Learning services on Google Cloud Platform (GCP) for end-to-end machine learning product lifecycle.

MLOps: All-in-One Platform vs Piecemeal Tools

Should you choose an all-in-one MLOps platform from your cloud provider or cobble together a solution from piecemeal tools?

SQL Renaissance

SQL is dead. Long live SQL. Why SQL is thriving even after 48 years. Resources to learn and master SQL.

Which Data Pipeline Orchestration Tool Is Right For You?

With diverse data sources, multi-cloud, and data mesh scenarios becoming increasingly common, a misfit data pipeline orchestration tool can multiply your woes.

Chasm of AI Security Between Research and Products

AI research continues to amaze us, but are those safe to use in products and services? Concerns about AI aligning with human goals have become real.

What Are Data, Machine Learning, and MLOps Pipelines?

Data pipelines transport data to the warehouse/lake. Machine Learning pipelines transform data before training/inference. MLOps pipelines automate ML workflows.