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ac

AC is the abbreviation for Andre Cronje, a well-known developer in the decentralized finance (DeFi) field, famous for creating Yearn Finance. Yearn Finance is an automated yield aggregator that helps users optimize returns across different DeFi protocols. Cronje has significant influence in the DeFi community, and the projects he develops are often noted for their innovation and complexity. AC is also commonly used to refer to other projects and contributions that Cronje is involved in.
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first_img Goldman Sachs: AI-related companies account for approximately 40% of the market capitalization of the S&P 500

The AI wave is breaking the traditional asset diversification logic of pension and sovereign funds, with risks spreading from technology stocks to multiple areas such as private equity, corporate bonds, and infrastructure. Institutional investors are beginning to reassess the AI exposure of their entire portfolios.Goldman Sachs estimates that AI infrastructure-related companies account for about 40% of the total market capitalization of the S&P 500; Apollo data shows that this year, AI-related issuances have accounted for nearly half of the investment-grade bond issuance and 87% of venture capital funding. Monte Tarbox, Chief Investment Officer of the New York City Retirement System, recently rejected a fundraising request due to an overweight position in a private equity fund related to AI.Institutions currently face the challenge of lacking a unified standard for measuring AI exposure. The Los Angeles County Employees Retirement Association estimates that 8% to 19% of its holdings are related to AI; a survey by Invesco of 90 sovereign wealth funds shows that more than half list market concentration as the primary risk of AI investment. Some large institutions are beginning to adopt a holistic portfolio approach to track AI-related exposure and the correlations between assets, while some institutions are starting to use AI tools to monitor their own portfolios.

Goldman Sachs: Consumer-grade AI agents enter the platform layer with capital expenditures of $1.4 trillion in 2027

Goldman Sachs Research released a viewpoint on September 18, stating that AI is transitioning from the experimental phase to the implementation phase, with the rise of consumer-grade AI agents marking the emergence of the platform layer. At the Communacopia + Technology Conference held in San Francisco, most companies showcased cases from experimentation to implementation. Goldman Sachs expects that by 2027, capital expenditures for U.S. mega-cap companies will reach $1.4 trillion, exceeding Wall Street consensus.Goldman Sachs analyst Eric Sheridan stated that consumer-grade AI agents are shifting from conversational relationships to action-oriented tasks. If consumers overcome trust and security issues, they could execute complex tasks such as purchasing tickets and booking hotels. The monetization of such agents in the mass market will be similar to search, achieved through advertising and subscriptions. AI is evolving from the infrastructure layer to the platform layer and application layer, with declining token unit pricing and increased utility being key drivers of mass adoption.During the conference, concerns about AI risks became a major topic, but Goldman Sachs believes this will not slow down infrastructure construction, as demand for computing power still exceeds supply and most projects have already been contracted. Supply chain constraints such as memory chips, electricity, and land may pose resistance, but the capital expenditure cycle is expected to remain high through 2027.
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