🔬 Direction 1 closure on JAMES — when the hypothesis fails but the data turns "7-tier monotonic natural-stop gradient"
The article discusses findings from an experiment involving JAMES and the Gemma 4 challenge. It highlights the unexpected results of a hypothesis regarding dynamic token budgets and the performance of various cognitive stages. Key insights include a natural-stop gradient and the need for a second axis in cognitive mechanisms.
- ▪The hypothesis regarding dynamic token budgets was proven incorrect, revealing that the cap was a ceiling rather than a floor.
- ▪A 7-tier monotonic natural-stop gradient was identified, indicating a consistent performance across different workload tiers.
- ▪The cognitive stage 'verify' produced limited unique responses, suggesting a need for further refinement in cognitive mechanisms.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3926644) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Hashevolution Posted on May 25 🔬 Direction 1 closure on JAMES — when the hypothesis fails but the data turns "7-tier monotonic natural-stop gradient" #rag #gemma #gemmachallenge #llm Gemma 4 Challenge: Write about Gemma 4 Submission G Two weeks ago I shipped core/reasoning/budget.py to test whether per-call dynamic token budgets could cut JAMES's reasoning cost by 60-80% on gemma4:e4b. Built as an experiment: A/B sweep, raw JSON, env-flag default-OFF. The hypothesis flipped.
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