lecture · HACKER NEWS RECOMMENDATION
Deep Dive into LLMs like ChatGPT
Andrej Karpathy · 10 HN recommenders · 8 recommendation months
Recommended by 10 Hacker News commenters across 8 months (2025–2026).
SignalTube analysis
Among 6 other lecture videos tagged LLMs & generative AI, the mean is 4.2 distinct HN recommenders. This video has 10 distinct HN recommenders, about 2.4× that mean. Recommendations span 8 distinct months, longer than the peer average of 3.7 months. This is a data-derived comparison, not a human review or quality rating.
56% of its 18 labeled comments are marked as recommendations or strong recommendations. HN mention years are 2025–2026; those years describe discussion history, not upload date. Its verified runtime is 211 minutes 24 seconds. YouTube lists its publication date as 2025-02-05.
- Channel / speaker
- Andrej Karpathy
- Verified runtime
- 3h 31m 24s
- YouTube upload date
- 2025-02-05
- Hacker News mention years
- 2025–2026
SAME TOPIC AND FORMAT
Compare with related videos
The comparison cohort uses other lecture videos in LLMs & generative AI. “Shared recommenders” counts HN users who recommended both videos in the source graph.
| Video | HN recommenders | Recommendation months | Positive label share | Shared recommenders | Runtime | Upload date |
|---|---|---|---|---|---|---|
| Deep Dive into LLMs like ChatGPTCurrent video | 10 | 8 | 56% | — | 3h 31m 24s | 2025-02-05 |
| Sparks of AGI: early experiments with GPT-4lecture · Sebastien Bubeck | 7 | 4 | 35% | No recorded overlap | 48m 32s | 2023-04-06 |
| Let's build the GPT Tokenizerlecture · Andrej Karpathy | 5 | 5 | 63% | No recorded overlap | 133m 35s | 2024-02-20 |
| LSTM is dead. Long Live Transformers!lecture · Seattle Applied Deep Learning | 4 | 4 | 80% | No recorded overlap | 28m 48s | 2019-12-03 |
THREE SOURCE-BASED CONTEXT POINTS
Why Hacker News recommends it
Each note combines the dataset’s stance label and short rationale; comment bodies are not reproduced. Open the HN source for the original discussion.
The archive classifies this as a contextual reference in “Show HN: How LLMs Work – Interactive visual guide based on Karpathy's lecture”. Its short rationale: Source for the 44 TB training data figure.
The archive classifies this as a strong recommendation in “Microgpt”. Its short rationale: Worthwhile even with basic LLM understanding.
The archive classifies this as a strong recommendation in “Ask HN: What would you recommend a vibe coder learn about how all this works?”. Its short rationale: General intro making sense of the tech without heavy math.