GPT

Software / AppVerified via Wikidata

OpenAI's language model noted for strengths in math and reasoning alongside other models.

Mentioned in 45 videos

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Videos Mentioning GPT

AI in Healthcare: Why Hospitals Are Moving Cautiously Toward Consolidation with Bob Wachter, MD

AI in Healthcare: Why Hospitals Are Moving Cautiously Toward Consolidation with Bob Wachter, MD

Stanford Online

A large language model discussed for its capabilities in healthcare queries and potential use by patients and professionals.

The Stove Guy: Sam D'Amico Shows New AI Cooking Features on America's Most Powerful Stove at Impulse

The Stove Guy: Sam D'Amico Shows New AI Cooking Features on America's Most Powerful Stove at Impulse

Latent Space

Referred to in the context of avoiding being 'oneshotted' by advanced AI models, implying a need for the CEO to keep up with AI development.

⚡️ How to turn Documents into Knowledge: Graphs in Modern AI — Emil Eifrem, CEO Neo4J

⚡️ How to turn Documents into Knowledge: Graphs in Modern AI — Emil Eifrem, CEO Neo4J

Latent Space

A generative pre-trained transformer model, mentioned in the context of industry-wide shifts in AI performance.

Is AI Trending Up or Down in 2026? (Let’s Take a Closer Look)

Is AI Trending Up or Down in 2026? (Let’s Take a Closer Look)

Cal Newport

A family of large language models from OpenAI, mentioned as a source of expensive API calls that Open Claw users encountered.

Stanford CS547 HCI Seminar | Spring 2026 | Observing the User Experience in 2026

Stanford CS547 HCI Seminar | Spring 2026 | Observing the User Experience in 2026

Stanford Online

Mentioned as the tool used to create a chart about layoffs.

Tokenmaxxing: How Top Builders Use AI To Do The Work Of 400 Engineers

Tokenmaxxing: How Top Builders Use AI To Do The Work Of 400 Engineers

Y Combinator

An AI model that Gary Tan found to be less efficient in managing context compared to other models for his knowledge base.

Stanford CS153 Frontier Systems | Jensen Huang from NVIDIA on the Compute Behind Intelligence

Stanford CS153 Frontier Systems | Jensen Huang from NVIDIA on the Compute Behind Intelligence

Stanford Online

Mentioned as a key development that enabled AI to think and generate tokens, marking a significant shift in computing.

Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 10: Inference

Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 10: Inference

Stanford Online

A quantization technique that uses hashing information to quantize layer by layer and track error propagation, improving accuracy.

AI Dev 26 x SF | Amrita Venkatraman: 3rd Era of Software Development

AI Dev 26 x SF | Amrita Venkatraman: 3rd Era of Software Development

DeepLearningAI

Refers to early Generative Pre-trained Transformer models that made AI coding usable.

AI Dev 26 x SF | Andrew K.  Davies: Deterministic Memory: How to Build an AI That Cannot Lie

AI Dev 26 x SF | Andrew K. Davies: Deterministic Memory: How to Build an AI That Cannot Lie

DeepLearningAI

A large language model mentioned as an example of current AI platforms typically lacking persistent conversational memory.

Devin’s 80% Moment: Background Agents, 7x PRs, & End of Hand-Held Coding — Walden Yan & Cole Murray

Devin’s 80% Moment: Background Agents, 7x PRs, & End of Hand-Held Coding — Walden Yan & Cole Murray

Latent Space

Mentioned in comparison to Claude regarding early agent development and capabilities.

Full Episode: The AI Industrial Revolution

Full Episode: The AI Industrial Revolution

Naval

An AI model discussed in terms of its capability reflecting the user's skill level and the importance of sporadic feedback.

Scaling Past Informal AI - Carina Hong, Axiom Math

Scaling Past Informal AI - Carina Hong, Axiom Math

Latent Space

A large language model that found a proof to an unsolved Erdos problem, which was then verified by Axiom Math's competitor, Harmonic.

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Applications, Applied AI

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Applications, Applied AI

Stanford Online

A family of large language models developed by OpenAI, discussed in the context of why companies might choose to post-train open-source models rather than solely rely on frontier models like GPT-6.

The hidden pattern behind successful products | Mark Pincus (FarmVille, Words with Friends, & more)

The hidden pattern behind successful products | Mark Pincus (FarmVille, Words with Friends, & more)

Lenny's Podcast

An AI language model, used by Pincus as an example of a product with clear 'lightning in a bottle' signal, where its impact was immediately obvious, contrasting with B+ ideas.

Dave Baszucki on Roblox, Teen Entrepreneurs, and the Future of Play | Conversation with Tyler

Dave Baszucki on Roblox, Teen Entrepreneurs, and the Future of Play | Conversation with Tyler

Conversations with Tyler

Mentioned jokingly as a potential source for David Baszucki's knowledge of 'Mutiny on the Bounty'.

Building with Instruction-Tuned LLMs: A Step-by-Step Guide

Building with Instruction-Tuned LLMs: A Step-by-Step Guide

DeepLearningAI

The GPT lineage (GPT, GPT-2, GPT-3) is discussed as the foundation of LLMs, built on unsupervised pre-training. GPT-4 mentioned as a tool for synthetic data generation.

Zynga Founder: Consumer Is Not Investible Right Now - Thats Why You Should Build It

Zynga Founder: Consumer Is Not Investible Right Now - Thats Why You Should Build It

Y Combinator

Mentioned as a significant AI model, used to analyze book content and apply the 'proven better new' framework.

Why The AI Doomers Might Be Right - Robert Wright

Why The AI Doomers Might Be Right - Robert Wright

Chris Williamson

The 'T' in GPT stands for Transformers, a core architecture used in many large language models, including those discussed for AI advancement.

Stanford CS547 HCI Seminar | Spring 2026 | Toward Ontological Multiplicity in AI and Computing

Stanford CS547 HCI Seminar | Spring 2026 | Toward Ontological Multiplicity in AI and Computing

Stanford Online

A language model used by the speaker to generate images based on prompts. The speaker illustrates how altering prompts can lead to different, sometimes unexpected, visual outputs.

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Infrasctructure, Enterprise AI, SaaS

Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Infrasctructure, Enterprise AI, SaaS

Stanford Online

Mentioned as a leading proprietary model that users are eager to access, contrasting with the growing capabilities of open-source models.

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