Conversations With AI:
Exploring Intelligence, Context, and Purpose.
An Augmetrics® Blog Series
Welcome to Conversations With AI — a window into our evolving dialogue between humans and several of the leading LLM and AI models. At the heart of these conversations lies Augmetrics®, a novel compute platform purpose-built to reshape how knowledge is processed, delivered, and applied.
Our conversations explore technologies that address the most critical challenges in AI today: the need for efficient computation, contextual accuracy, and trustworthy, on-demand decision support. The dialogue centers on solving deeper issues of relevance, transparency, and sustainable resource use in AI.
These discussions illuminate the major conditions shaping AI’s future — from runaway compute costs and resource constraints, to black-box model opacity and the struggle to transition from search-era habits to truly intelligent systems. Along the way, where possible, we’ll share real-world use cases and achievements that demonstrate the impact and promise of these innovations.
Join us as we ask the hard questions, challenge assumptions, and chart new paths for AI — paths designed to serve both people and planet.
Latest Conversations
- Gaining – and Retaining – Knowledge in the Post-Search Engine Era
For decades, search engines have been the dominant gateway to knowledge…
- Post-Preprocessing: What It Means & Why It Matters
After raw data has been cleaned, normalized, and structured in the preprocessing…
- Self-Service Knowledge: What Changes in the Post-Search Era?
For decades, search engines have defined self-service knowledge, allowing…
Latest Blog Posts
Stay updated on the key aspects around AI and data-processing
Gaining – and Retaining – Knowledge in the Post-Search Engine Era
For decades, search engines have been the dominant gateway to knowledge…Read Article
Post-Preprocessing: What It Means & Why It Matters
After raw data has been cleaned, normalized, and structured in the preprocessing…Read Article
Self-Service Knowledge: What Changes in the Post-Search Era?
For decades, search engines have defined self-service knowledge, allowing…Read Article
How Do AI Model Changes Impact Your Personal AI Client’s Learning Gains?
Every time an AI model updates, it doesn’t just improve—it completely replaces…Read Article
Why Does Current AI Technology Discard Recent Model Learning?
Most people assume that AI models continuously build on past knowledge…Read Article
Does Data Sampling and De-Duplication in Pre-Processing Remove Important Context for LLMs?
Before an LLM (large language model) is trained, it undergoes a critical pre-processing stage where vast…Read Article
What Is an LLM’s Neural Network & How Is ‘Human Context’ Decided?
A large language model (LLM) is powered by a type of neural network, designed to process…Read Article
What is Forward/Backward Propagation & How Is The Correct Answer Decided Upon?
At the heart of AI model training are two key processes: forward propagation and backward…Read Article
The Big Picture: Where Model Training Fits in AI Development
The model training phase is just one part of a much larger AI development…Read Article
What Is Reinforcement Learning (RL), How Is It Used & How Effective Is It?
Reinforcement Learning (RL) is a machine learning approach where an AI agent learns by…Read Article
The Role of Synthetic Data
Despite the incredible size of the data used in model training, real-world datasets…Read Article
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