Why AI's Next Frontier Isn't More Hardware, but Smarter Algorithms

Google's TurboQuant represents a fundamental shift in tackling AI's memory bottleneck: instead of scaling hardware capacity, the algorithm compresses KV cache without sacrificing accuracy. This approach could reshape cost structures across the industry, from data centers to consumer devices, suggesting that algorithmic innovation—not hardware expansion—may be the key to solving memory constraints in large language models.