1.	At the heart of FIITED is the utility-based approach to determine chunk significance. However, basing eviction decisions purely on utility scores might introduce biases. For instance, recent chunks might gain a temporary high utility, leading to potentially premature evictions of other valuable chunks.
2.	This approach does not consider the individual significance of dimensions within a chunk, leading to potential information loss.
3.	While the chunk address manager maintains a free address stack, this design assumes that the most recently evicted space is optimal for the next allocation. This might not always be the case, especially when considering the locality of data and frequent access patterns.
4.	The system heavily depends on the hash table to fetch and manage embeddings. This approach, while efficient in accessing chunks, might lead to hashing collisions even though the design ensures a low collision rate. Any collision, however rare, can introduce latency in access times or even potential overwrites.
5.	The methodology leans heavily on access frequency to decide on embedding significance. However, frequency doesn't always equate to importance. There could be rarely accessed but critically important embeddings, and the method might be prone to undervaluing them.
1. At the heart of FIITED is the utility-based approach to determine chunk significance. However, basing eviction decisions purely on utility scores might introduce biases. For instance, recent chunks might gain a temporary high utility, leading to potentially premature evictions of other valuable chunks.