---
title: "The only AI glossary you’ll need this year"
slug: "the-only-ai-glossary-youll-need-this-year"
date: 2026-07-03
category: tech-pub
tags: []
language: en
sources_count: 1
featured: false
publisher: AInauten News
url: https://news.ainauten.com/en/story/the-only-ai-glossary-youll-need-this-year
---

# The only AI glossary you’ll need this year

**Published**: 2026-07-03 | **Category**: tech-pub | **Sources**: 1

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## TL;DR

- TechCrunch has updated its AI glossary as a living reference for terms that now show up constantly in product meetings, pitches, and AI coverage.

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## Summary

- TechCrunch has updated its AI glossary as a living reference for terms that now show up constantly in product meetings, pitches, and AI coverage.
- It explains core concepts such as AGI, LLMs, tokens, training, inference, fine-tuning, hallucinations, chain of thought, and reinforcement learning.
- Newer infrastructure terms like MCP, Mixture of Experts, memory cache, token throughput, coding agents, and RAMageddon show how AI now reaches into hardware, standards, and cost models.
- The piece is useful orientation, but it is still a glossary: it does not decide which terms are technically solid and which ones mainly work as industry jargon.

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## Why it matters

TechCrunch has updated its AI glossary as a living reference for terms that now show up constantly in product meetings, pitches, and AI coverage.

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## Key Points

- TechCrunch has updated its AI glossary as a living reference for terms that now show up constantly in product meetings, pitches, and AI coverage.
- It explains core concepts such as AGI, LLMs, tokens, training, inference, fine-tuning, hallucinations, chain of thought, and reinforcement learning.
- Newer infrastructure terms like MCP, Mixture of Experts, memory cache, token throughput, coding agents, and RAMageddon show how AI now reaches into hardware, standards, and cost models.
- The piece is useful orientation, but it is still a glossary: it does not decide which terms are technically solid and which ones mainly work as industry jargon.

---

## Nauti's Take

Good glossaries are almost infrastructure in 2026. Not because everyone needs to memorize every term, but because vague language hides weak decisions. The useful part here is that TechCrunch goes beyond model vocabulary and includes cost and systems terms like token throughput, memory cache, and RAMageddon. The blind spot: a glossary sorts meaning, not priority. In practice, the sharper question is which term actually changes how you work, buy, or build.

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## FAQ

**Q:** What is The only AI glossary you’ll need this year about?

**A:** - TechCrunch has updated its AI glossary as a living reference for terms that now show up constantly in product meetings, pitches, and AI coverage.

**Q:** Why does it matter?

**A:** TechCrunch has updated its AI glossary as a living reference for terms that now show up constantly in product meetings, pitches, and AI coverage.

**Q:** What are the key takeaways?

**A:** TechCrunch has updated its AI glossary as a living reference for terms that now show up constantly in product meetings, pitches, and AI coverage.. It explains core concepts such as AGI, LLMs, tokens, training, inference, fine-tuning, hallucinations, chain of thought, and reinforcement learning.. Newer infrastructure terms like MCP, Mixture of Experts, memory cache, token throughput, coding agents, and RAMageddon show how AI now reaches into hardware, standards, and cost models.

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## Related Topics

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## Sources

- [From LLMs to hallucinations, here’s a simple guide to common AI terms](https://techcrunch.com/2026/04/12/artificial-intelligence-definition-glossary-hallucinations-guide-to-common-ai-terms/) - TechCrunch AI

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## About This Article

This article is a synthesis of 1 sources, curated and summarized by AInauten News. We aggregate AI news from trusted sources and provide bilingual (German/English) coverage.

**Publisher**: [AInauten](https://www.ainauten.com) | **Site**: [news.ainauten.com](https://news.ainauten.com)

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*Last Updated: 2026-07-04*