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👉 Start Your Free ScanThis one loop was a patentable invention.
def uncertainty_guided_cache_invalidation(query, E, cache):
"""ML-guided selective invalidation using uncertainty/drift"""
drift = cosine_sim(E[query], cache.E).std() # semantic drift (uncertainty)
thresh = base_thresh * (1 + cache.staleness(query)) # adapt to recency/frequency
if drift > thresh:
keys = cache.semantic_neighbors(query, radius=drift) # target related entries only
return cache.invalidate(keys, decay=drift) # selective, proportional purge
return cache.get(query)
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