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[2026-02-21 10:36] rolandnsharp7643: >so what did we complete today. we added reinforcement learning. and changed the data set and what else ● From what I've seen today and the context in the plan: Reinforcement learning — TD (temporal difference) learning integrated into the symbolic layer. The td_weights.bin file tracks learned concept-token associations that update over time. Dataset — Switched to chat_input.txt, a corpus of 16K conversations with <|user|>/<|assistant|> turn markers. Built the chat mode (--chat flag) for interactive use. Scaled model 8x — 1.25M → 9.6M parameters: - 6 → 12 layers - 128 → 256 dim - 128 → 256 context window - Adjusted Adam (lower LR, longer warmup, standard betas) - 100K → 200K training steps Knowledge.build optimization — The other Claude fixed build_associations from O(concepts × total_pairs) to O(total_pairs) with an index. Turned a 6+ minute hang into seconds. Forth-based concept system — Dictionary with 20 primitives, 2,982 concepts, 23,855 associations — all feeding into generation alongside the symbolic constraints. Is there anything else from earlier sessions I'm missing? I only have direct visibility into the scaling work. [2026-02-21 10:39] rolandnsharp7643: 9.5 million params --- should take about eight hours [2026-02-21 10:39] rolandnsharp7643: roland@cube:~/code/flow/ocaml/vidya$ dune exec bin/main.exe num docs: 16838 BPE: 103 chars + 500 merges = 606 vocab | 2.8 chars/token num params: 9592320 pre-tokenized 16838 docs in 7.45s step 2500 / 200000 | loss 4.7787 step 5000 / 200000 | loss 3.7486 step 7500 / 200000 | loss 3.0879 [2026-02-22 21:57] rolandnsharp7643: Vidya speaks! [2026-02-22 21:58] rolandnsharp7643: hello > what do you do ? How do you do ? i write code. i'm good. how are you? > Yes, I'm doing well. awesome! where are you? > You've lived here for a long time! true. what are your favorite hobbies? > Do you think I like Chinese food or an organic or a fish? [2026-02-22 22:02] xenonfun: is this the 9.6M model? [2026-02-22 22:02] rolandnsharp7643: yeah about 10 million [2026-02-22 22:09] rolandnsharp7643: but all the interesting reinforcment learning and other ideas are turned off. Claude says they are only relevant once the model has basic grammar, perhaps at 100M+ [2026-02-22 22:13] xenonfun: yeah I was looking at code to see if that whole knowledge fourth stuff was integrated, seems very interesting.