Crypto Highlights: Top 3 Gainers and Losers on CoinMarketCap Today

Morgan Stanley believes that the recent sell-off in the semiconductor sector has been excessive, and that market panic rather than fundamentals is the biggest risk. Driven by demand for AI infrastructure, downstream orders continue to accelerate, with semiconductor supply remaining the core bottleneck. LPS constraints actually make growth more stable. The sector may fluctuate within a range in the short term and is currently near the bottom; prospects for the computing power and storage subsectors are favorable.

Joseph Lupton from the JP Morgan Global Economic Research Team pointed out in a research report on November 10 that recent improvements in labor productivity have been driven more by capital deepening and increased intensity of factor utilization. The broad efficiency gains from AI, resulting from process reconstruction, data integration, and organizational adjustments, will still take time to materialize. This means orders for chips, servers, and electrical equipment may grow first, but continuous investment returns for computing power operators and end users may not arrive at the same pace.

Goldman Sachs believes that the AI investment cycle is currently in the "trough of disillusionment," but this is not the first time. The core contradiction lies in the fact that the business models of new cloud computing providers are highly dependent on end-user returns from AI spending, while currently "there are basically zero companies that can attribute profits to AI." Social Capital founder Palihapitiya has clearly defined an 18-month key window, during which the market will decide which AI business models are sustainable and which are not.