A Visual Guide to RNNs, CNNs, Transformers, and Calibration, with Hands-On Experiments on Accuracy and Efficiency
9 comments
Build a Large Language Model (From Scratch): https://sebastianraschka.com/llms-from-scratch/
Build a Reasoning Model (From Scratch): https://sebastianraschka.com/reasoning-from-scratch/
The way quite a lot of brains fell out, some unreflectively quoting how this could get us to AGI, system 1, “no hallucinating”, etc, while others ignored the breadth and new data vs existing classifiers and saw no possible upside, was revealing. The game demos were especially harmful, was told repeatedly that Jev must have near instant visual input support, as few to none of the flashy Doom, Minecraft, etc. showcases explained this was using game state.
Hype really is the worst aspect of this industry.
> Like ChatGPT in 2022 was exciting because it was a general-purpose chat model that could generate all kinds of texts, one of the reasons the tech community is excited about Jev is that it is the ChatGPT moment for classification, where it can cheaply classify all kinds of text inputs without having to fine-tune a custom classifier for each task.
We've been comparing strategies for classifying email and Jev is looking promising. I compared some strategies here: https://housecat.com/blog/classifying-email
Read the full thread on Hacker News →
Related stories
- Language Models for Text Classification: From Bag-of-Words to Jevmagazine.sebastianraschka.comHacker News · 1 points · 1 day ago
- Hacker News · 1 points · 9 days ago
- Hacker News · 1 points · 10 days ago
- Hacker News · 1 points · 5 days ago
- Hacker News · 3 points · 3 days ago
- Hacker News · 7 points · 11 days ago