Alliance Partner on a16z’s Shift: To Drive Crypto Talent to Build Cutting-Edge Technology

According to a Financial Times report, CalPERS, the largest U.S. public pension fund (California Public Employees' Retirement System), is adjusting its asset allocation: cutting direct holdings of the "Magnificent Seven" tech giants while increasing exposure to private equity to reduce concentration risk in public equity investments. Calculations from regulatory filings show CalPERS will slash its direct holdings of stocks in Apple, Microsoft, Alphabet, Amazon, Nvidia, Meta, and Tesla by 26% in the first half of 2026. The fund is instead diversifying its portfolio across hundreds of companies, cutting concentrated bets on a small number of top firms. Anton Orlich, CalPERS' deputy chief investment officer, confirmed this allocation shift in an interview. He noted that public equity market valuations are already elevated, and concentration in a handful of leading companies is pressuring relative returns. In contrast, private companies offer more attractive pricing, helping CalPERS buffer against potential downturns in public markets. This rebalancing took place ahead of the recent tech stock sell-off. This week, multiple tech giants released earnings reports, stoking market concerns over whether AI spending can translate into tangible returns. Microsoft, Amazon, and Alphabet are set to report results next week, leaving the tech sector facing further tests. As of June 30, CalPERS' assets under management reached $637.1 billion. Data released by the fund in July showed its preliminary net investment return for the past 12 months was 14.8%, with both public and private equity portfolios performing strongly.

Secretary for Financial Services and the Treasury of the Hong Kong Special Administrative Region, Hui Ching Yu, stated that Hong Kong’s tokenization development is transitioning from the "experimental phase" to the "implementation phase". Currently, Hong Kong hosts over 1,400 fintech enterprises, including 8 virtual banks, 4 virtual insurance companies, and 12 licensed virtual asset trading platforms, which have achieved notable results in advancing tokenization. Hui added that the Hong Kong Exchanges and Clearing (HKEX) is committed to launching a tokenized warehouse receipt financing pilot program next year. The project will partner with designated banks, utilizing distributed ledger technology, to facilitate the use of commodity warehouse receipts as collateral. Furthermore, HKEX is also developing a multi-asset tokenization platform that will include commodity warehouse receipts from approved warehouses.

According to Bitget's market data, South Korea's KOSPI index closed up 16.53 points on Friday, October 23, with a 0.3% gain, ending at 5550.3 points. SK Hynix closed 4.41% higher, while Samsung Electronics rose 0.46%.

Jackson.ll (@0xOar), developer of Binance Wallet’s web version, posted today, stating: “Agent ID is being used in various ways, but users should also carefully check risk warnings. Enabling developer mode for the Agent means you can sign unverified contract transactions... Potential risks need attention. You can close the mode immediately after minting, or wait for products from verified developers.” He Yi subsequently retweeted the post. Earlier reports indicated that multiple minting projects exclusive to Binance Agent Wallet have recently emerged in the market, with some requiring developer mode activation.

，据行情信息，A 股宇树科技 20CM 涨停，现报价 624 原，成交额超 40 亿元，本周累涨超 46%。

Beating AI News Brief: ZhenFund has launched "Ask AI" on its official website, enabling entrepreneurs to directly inquire about the firms ZhenFund has invested in, its recent focus sectors, and relevant events tailored to them. The setup is straightforward: ZhenFund has compiled public information including its investment team, portfolio companies, focus areas, startup events, and contact details into a bilingual (Chinese-English) `zhenfund.md` file. Clicking any AI entry point redirects users to one of four platforms—Kimi, ChatGPT, Claude, or DeepSeek—with a pre-filled prompt that instructs the model to first read the `zhenfund.md` file before answering the entrepreneur’s questions.