December 17, 2024

By Andrés Escobar

From zero to NeRF: what to expect data-wise on a NeRF project

In this follow-up to our initial exploration of NeRF (Neural Radiance Fields), we’ll dive deeper into the essential aspects of data preparation and management for utilizing this innovative technology. Additionally, we’ll highlight a selection of practical tools that can aid you in your NeRF journey, enabling you to better understand and apply its capabilities. Recap … Continued

Pandas & Polars: is it time to migrate? definitely maybe đŸ€”

Where are we? đŸ—ș If you are a data scientist, machine learning engineer, or otherwise involved in a data-driven project, it is highly likely that you have used pandas to clean, sanitize, filter, and prepare the data to be used as input for your chosen methods, models, or algorithms. In this early step, which usually … Continued

Deploying Llama2 with NVIDIA Triton Inference Server

  Intro NVIDIA Triton Inference Server is an open-source inference serving software that enables model deployment standardization in a fast and scalable manner, on both CPU and GPU. It provides developers the freedom to choose the right framework for their projects without impacting production deployment. It also helps developers deliver high-performance inference across cloud, on-premise, … Continued

Enhancing Llama2 Conversations with NeMo Guardrails: A Practical Guide

Intro NeMo Guardrails is an open-source toolkit developed by NVIDIA for seamlessly incorporating customizable guardrails to LLM-based conversational systems. It allows users to control the output of an Large Language Model (LLM), for instance avoiding political topics, following a predefined conversation flow, validating output content, etc. Inspired by SelfCheckGPT, NeMo heavily relies on the utilization … Continued

Real-Time Video Processing: deploying applications into the cloud

How does Amazon Go charge you without the need for a physical checkout? Is it possible to detect failures in manufactured products just by analyzing a camera’s recording? Can we develop an application that supervises cultivated fields to detect pests and optimizes irrigation?  The answer to all these questions lies in the field of machine … Continued

Building a Reliable Data Foundation: Data Quality for LLMs

Achieving substantial value with large language models (LLMs) can be challenging without a scalable data foundation. Data points are collected from multiple sources and defined in multiple different ways. This could cause them to be in opposite directions and lack consistency. Lack of proper entity documentation and a strong data quality strategy boils down to … Continued

Guiding LLM Behavior: The Art of Prompt Engineering

Large Language Models (LLMs) have revolutionized the field of artificial intelligence and natural language processing. These powerful models possess an incredible ability to generate human-like text and perform a wide range of language-related tasks. However, to truly unleash their power and achieve specific goals, careful and strategic prompt engineering is essential. By crafting well-designed instructions, … Continued

Making the Right Changes: Using A/B Testing to Optimize Your Product

Introduction Are you a business owner or an IT professional? If so, you’re likely always on the hunt for ways to enhance your product, service, or algorithm. Changes can be risky, especially in productive environments. It’s hard to predict whether they will benefit your business. This is where A/B testing becomes valuable. A/B testing is … Continued

Reinforcement learning: AI meets Pavlov’s dog

Introduction Ever heard of Pavlov’s dog? In 1897 Ivan Pavlov, a russian physiologist, published his findings on conditioned behavior, that demonstrated how dogs could be conditioned to associate an unconditioned stimulus (food) with a neutral stimulus (bell), leading to a conditioned response (salivation) triggered by the bell alone.  The idea behind this experiment is that … Continued

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