Barclays_Global_Portfolio_Manager_s_Digest_Striking_a_Balance

This document is intended for institutional investors and is not subject to all of theindependence and disclosure standards applicable to debt research reports prepared for retailinvestors under U.S. FINRA Rule 2242. Barclays trades the securities covered in this report for itsown account and on a discretionary basis on behalf of certain clients. Such trading interestsmay be contrary to the recommendations offered in this report.Barclays Capital Inc. and/or one of its affiliates does and seeks to do business with companiescovered in its research reports. As a result, investors should be aware that the firm may have aconflict of interest that could affect the objectivity of this report. Investors should consider thisreport as only a single factor in making their investment decision.* This individual is a member of the Product Management Group and is not a Research AnalystAll research referenced herein has been previously published. You can view the full reports,including analyst certifications and other required disclosures, by clicking the hyperlinks in thispublication or by going to our Research portal on Barclays Live.FOR ANALYST CERTIFICATION(S) PLEASE SEE PAGE 31.FOR IMPORTANT EQUITY RESEARCH DISCLOSURES, PLEASE SEE PAGE 31.FOR IMPORTANT FIXED INCOME RESEARCH DISCLOSURES, PLEASE SEE PAGE 32.Global Portfolio Manager's DigestStriking a BalanceWe provide context and perspective on research across regionsand asset classes, this week highlighting our thoughts on whatcould turn sentiment positive on the "AI trade"; adjusting ourcall following the Fed's decision to cut rates by 50bp; and whatthe Fed's move means for Asia markets.• What's Next for the "AI Trade": The bull case around AI boils down to a simple concept: ifscaling laws hold and frontier model performance continues to improve at great leaps overcoming generations, then end-user products in consumer and enterprise will similarlyimprove greatly in terms of functionality and accuracy and adoption will increase. To thatend, we see GPT-5’s upcoming release as a potential catalyst to get things going again. Ifsuccessful, sentiment could shift greatly, AI hyperscaler capex would need to ramp further,and all this investment will likely end up being another expensive moat for mega-cap tech.Further, we think that another recent breakthrough around test-time-compute could usher ina new sub-category of frontier AI lab innovation around finding a more optimal mix of trainingand inference compute, which could dramatically reduce the capex needs of the overallindustry, but it's too early to tell. An alternative view, and much more bearish take, is thatscaling laws don’t hold up, the foundation models stop improving, and the capex wave stops.In this scenario, GPT-5 would likely be introduced in late 2024 or early 2025 to great fanfare,only to see the same kind of experimental enterprise AI workloads running on top of it but nokiller apps or broad-based consumer/enterprise adoption.• The Fed's Recalibrat