$Alphabet(GOOGL.US) just dropped a new tech called TurboQuant 🤯 — it cuts memory usage during AI inference down to one-sixth while actually boosting performance. The market’s knee-jerk reaction: does this mean we won’t need as many memory chips after all? 🤔

But stepping back, this feels more like short-term trading noise than a shift in the fundamentals. For one, the tech mainly optimizes inference-stage cache — it doesn’t directly reduce demand for training or core storage. And with AI still in explosive growth mode📈, compute and memory demand are expanding together. One compression algorithm isn’t going to cause a demand collapse💀

Personally, I see this kind of “tech shock” as more of a volatility driver than a trend-changer. In the memory space, sentiment rules the short term, but the medium-to-long term story still comes down to the AI demand curve. This looks more like a shakeout on negative news than a broken thesis🧹