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reacted to AbstractPhil's post with 🔥 7 minutes ago
Massive AlephLM success. The task collective is producing powerful MOE shared knowledge adapters. A serious success and a massive first step towards the next stage. The current family collective results are present here; https://huggingface.co/AbstractPhil/geolip-aleph-qwen/blob/main/exp009_family/results/results.json
This is akin to a stackable non-intrusive lora that enables increased shared collective behavior.
This includes the three mentioned json tasks, a math task, a tinystories task, and a diffusion task for cifar10. Each adapter anchored to the knowledge within model that already exists while enhancing the knowledge through anchored lookup systems and decision-driven hierarchical access trees.
All tasks activate independently upon manual override, all tasks handle direct shared knowledge when left to greedy decoding, each task issued multiple tests alongside to determine fidelity and accuracy throughout the process.
The results show the gating is more than willing to hop from sector to sector, using alternating weight shifts from the cooperative anchored systems - even systems never trained for the tasks contributing to the accuracy of the results for other tasks due to the lookup accuracy to the heuristic chains, never having seen the tasks before. Each structure is independently trained and the collective cooperates together through a dense activation network.
Full writeup and article https://huggingface.co/blog/AbstractPhil/aleph-autoregression-differentiation-ft2.Organizations
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Imagine saving over 40% of your tokens and time on debugging... Now, what if I told you there's a tool that captures the "hidden patterns" of your AI agent and automatically corrects them in the background without any intervention from you? 🤯🚀
The ai-rule-learning-mcp tool
Works automatically in the background of every session with the agent (such as Cloud Code, Cline, Aider, or others).
https://lnkd.in/dw9bAbqy
It detects recurring errors and lapses and instantly corrects the AI's behavior.
The result?
Perfect consistency and real improvement across sessions because the tool automatically injects the correct approach into its memory. 🧠
Why do you need it now?
Professionals use this tool to manage agent behavior in the background, while most developers still waste time and tokens rewriting instructions and correcting the same silly mistakes every time they open a new session because the AI forgets the context.
As long as you can't monitor what's learning in the background, you'll keep spending tokens and wasting hours digging through the same problems. 💸
It's fully automated; you don't need to see or modify the patterns yourself.
Install it in one step:
pip install ai-rule-learning-mcp
⚡ It's completely free, and installation takes only 30 seconds.
The tool detects past patterns and automatically injects strict instructions to prevent repeating mistakes and establish the correct working method, whether at the beginning or in the middle of a session. 🎯 Save your effort and tokens now and let the tool automatically manage the AI agent's behavior.
For discussion and support, join our Discord: https://lnkd.in/dvHMS6Hd
👇 What's the most common pattern your agent makes that you wish the tool would fix?
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