# CAEL 0.4.1: a chat assistant with no neural network and no transformer

> Source: <https://discuss.huggingface.co/t/cael-0-4-1-a-chat-assistant-with-no-neural-network-and-no-transformer/191825#post_1>
> Published: 2026-11-14 00:22:35+00:00

Hi all. I’d like to share CAEL, a hobby project: a chat assistant built without any neural network. No transformer, no neural weights, no LLM behind the replies. It runs on a CPU in plain Python.

**How it works**

- Symbolic, count-based and cellular-automaton engines for reasoning and state.
- Exact skills for conversation: quantities, rates, clock times, syllogisms, schedules and changed values.
- Chat memory: it answers from what you said earlier in the conversation.
- Checked web answers: when it doesn’t know, it searches and answers only if a second independent source agrees.
- An index of about 285,000 human-written answers (Stack Exchange, OpenAssistant, databricks-dolly-15k) for open questions.

**Honest results**

- On the five Open SLM Leaderboard tests, run locally: 49.97% mean against SmolLM2-360M’s 58.86%. It is ahead on ArithMark-3 (69.5% vs 59.6%) and far behind on HellaSwag and PIQA. This is a local comparison and not a leaderboard entry, since CAEL uses offline Wikipedia and the ARC Corpus while answering.
- In blind chat rounds against Qwen3.5-0.8B (set to 1000 Elo), CAEL scores about 796. It does not match a small LLM at general chat. I judged these rounds myself, so treat them as a rough guide.

**Where it is weak:** open advice, how-to questions and creative writing. It often declines to answer where an LLM would say something plausible.

**Links**

It is source-available for non-commercial use, and it was built with AI assistance. I’d welcome feedback, especially ideas for non-neural approaches to open-ended chat.

*Edit: 0.4.1 is now published on Hugging Face; the link above replaces the earlier 0.4.0 model card link.*