GPT-4
OpenAI multimodal large language model
What podcasters actually say about GPT-4.
120 mentions, no marketing. Save them all to a pod and ask any question.
Common Themes
Videos Mentioning GPT-4
AI Dev 26 x SF | Ankit Mathur: The Coding Agent Multiverse of Madness
DeepLearningAI
An updated version that provided a large boost in developer productivity.
AI Dev 26 x SF | Amrita Venkatraman: 3rd Era of Software Development
DeepLearningAI
Used for writing plans due to its strength in strategizing and thinking. It's noted as being better for planning than Composer 2.
Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Enterprise Internal Knowledge
Stanford Online
Described as a significant step-change in model quality.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 15: Mid/Post-Training
Stanford Online
A model exhibiting strong instruction following capabilities, capable of 'oneshotting' complex prompts. It serves as a benchmark for which other models are compared against, even in reverse engineering efforts.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 14: Data
Stanford Online
Used by Microsoft in the '51' project to classify a subset of data based on the prompt 'determine educational value', generating target data for training a cheaper classifier.
Pyramid of Work and The Future of Enterprise Automation | The a16z Show
a16z Deep Dives
A large language model from OpenAI. It was too slow for Happy Robot's needs for negotiating rates, leading them to fine-tune other models.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 17: Alignment - Multimodality
Stanford Online
Used to synthesize training data for LLaVA by generating questions and conversations based on image captions and objects.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Guest Lecture: Dan Fu
Stanford Online
Mentioned as a reference point for the capabilities of current large language models.
Stanford CS153 Frontier Systems | Scale, AGI, and the Future of Everything
Stanford Online
A more advanced model developed by OpenAI, mentioned as being ready during the development of ChatGPT and a key component in making the chatbot much better.
Inside The AI Race: DeepMind, OpenAI, Anthropic, China, and The Race to Superintelligence
Tim Ferriss
A later version of ChatGPT that significantly reduced hallucination and added multimodal capabilities (video, audio, long context window, reasoning, agentic coding), demonstrating the rapid progression of AI models.
How To Read AI Research Papers Effectively
DeepLearningAI
A large language model mentioned as a benchmark and a tool for asking for paper recommendations.
Stanford CS547 HCI Seminar | Spring 2026 | Toward Ontological Multiplicity in AI and Computing
Stanford Online
A commercial LLM chatbot that, along with Bard, offered multiple perspectives on the definition of 'human' but shared a common underlying assumption of humans as biological individuals.
NEW: Alex Hormozi Answers Your Questions on Reddit
Alex Hormozi
Mentioned as a significant improvement in AI model development from GPT-3, with subsequent versions showing smaller gains.
Why the Next 10 Years May Add 50 to Your Lifespan | Dr. Derya Unutmaz
FoundMyFitness
An earlier AI model used for scanning literature to save research time, which is less advanced than current versions.
Why Physical AI Is the Next Platform Shift
Y Combinator
Encord deals with multiple petabytes of data, processing more data than was used to train GPT-4.
How Anthropic builds products like Claude Code before the AI models are ready | Dianne Penn
Lenny's Podcast
A competitor AI model mentioned for its early use in coding, setting a benchmark for Claude's development in that area.
Stanford CS229 Machine Learning | Spring 2026 | Lecture 12: Representation Learning
Stanford Online
Mentioned as an example of a large model (W0) that can be shared across multiple users when using techniques like LoRA.
Stanford CS329A Self-Improving AI Agents | Part 1 | Course Overview
Stanford Online
An estimated large language model with trillions of parameters, discussed in the context of exponential growth in model size.
Stanford CS329A Self-Improving AI Agents | Part 8 | Agentic Evaluations and Long Horizon Tasks
Stanford Online
A more recent model compared to GPT-2, capable of handling tasks for a few minutes with 50% success rate.
How Microsoft is Adapting to the AI Era
a16z Deep Dives
Cited as a major reason for the current excitement around AI, enabling users to perform a wide range of tasks.
AI Isn’t “Out of Control” — The AI Companies Are
Cal Newport
Mentioned as an example of an LLM whose capabilities in creating plausible text can involve impressive finite computations.
⏭️ Forward Deployed: Voice AI on what works in 2026
Latent Space
Mentioned as a potential model for cascaded pipelines, balancing speed and intelligence.
The Truth about OpenAI’s “Secret AI Civilizations”
Cal Newport
A previous iteration of OpenAI's language models where scaling up and longer training led to performance gains.
The Real Story Behind GPT-6’s “Stealth Thinking”
Cal Newport
A previous LLM model mentioned as a point of comparison for performance improvements and scaling.