Tag
large language models
Large language models are becoming a core layer of AI systems, shaping how teams train, evaluate, prompt, and deploy models. This topic covers model safety, explainability, inference cost, and the business deals that determine who gets access to compute and capability.
11 articles
Meta’s moderation shift shows where AI cuts costs
Meta’s move to AI moderation shows 4 ways large language models can replace human review and cut operating costs.
Meta is replacing moderators with AI to cut costs
Meta is shifting content moderation to large language models, with human review set to drop sharply as AI spending climbs.
LLMs work by predicting the next token
A clear guide to how LLMs are trained, tuned, and used, with 5 practical pieces of the model pipeline.
ChatGPT grew from chatbot to platform
ChatGPT has expanded from a 2022 chatbot into a multilingual app, search tool, and agent platform with hundreds of millions of users.
Why fine-tuning still beats prompt-only AI
Fine-tuning remains the best way to make foundation models reliable for specific tasks.
What large language models are, and how they work
Large language models turn huge text corpora into systems that generate, summarize, and reason with language.
AE-LLM aims to make LLMs more efficient
AE-LLM proposes adaptive efficiency optimization for large language models, but the provided source does not include benchmark details.
Google Plans $40B Bet on Anthropic
Alphabet may invest up to $40 billion in Anthropic, deepening a rival partnership as Google races to secure more AI capacity.
Mythos, Anthropic’s unreleased AI model, explained
Anthropic says Mythos is too dangerous to ship. Here’s what its 73% hacking score, 31-point math gain, and limited rollout mean.
LLMs plus knowledge graphs for ML explainability
A manufacturing XAI method uses a knowledge graph plus an LLM to turn ML results into clearer, more user-friendly explanations.
Prompt Engineering, Explained Without the Hype
Prompt engineering turns vague requests into usable AI outputs. AWS breaks down the methods, use cases, and tradeoffs behind better prompts.