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Blackstone's launch of Blackstone Real Estate Income Trust (BREIT) in 2017 aimed to democratize access to the lucrative world of commercial real estate investment, traditionally reserved for large institutions and wealthy individuals. The promise of an “all-weather strategy” combined with a 4% annual dividend in a low-interest environment fueled BREIT's rapid growth. The fund has generated over $5 billion in fees for Blackstone since inception and today manages about $114 billion in assets (~8% of the firm’s entire fee-earning assets). Since its inception, the fund claims it has delivered an annualized net return of 10.5%— almost double the return of a comparable index of publicly traded REITs. However, recent scrutiny has cast doubt on the fund's strong performance amidst the downturn in the commercial real estate market following the pandemic. Critics argue that BREIT's returns are based on Blackstone's internal and potentially inflated valuations rather than real market conditions. These concerns are amplified by the fact that BREIT does not disclose crucial assumptions behind its NAV calculations to investors or regulators, and because these calculations are both unaudited and unregulated by the SEC. Chilton Capital Management, which invests in public REITs, concluded last April that BREIT “was overstating the value of its NAV by more than 55%”. But Blackstone argues that “it is unfair to compare BREIT” to publicly traded funds, highlighting that the fund’s portfolio is focused on top-performing asset classes such as data centers, logistics, and student housing, with minimal exposure to struggling urban office buildings. In any case, if BREIT's assets are indeed overvalued, investors may have been overpaying hundreds of millions of dollars in management and performance fees. Beyond concerns stemming from inflated valuation, there has been an even more worrisome revelation about the fund’s dividends not being fully sustained by operational cash flows. Not being able to cover a promised dividend can be seen as a Ponzi-like warning, because it means the money has to come from selling off assets, borrowing money, or attracting new investors — which BREIT acknowledges in its disclosures. This reality was put to the test recently in 2022, after a crash in the commercial real estate market led to a flood of redemptions in the fund, forcing the need for Blackstone to raise additional outside capital to meet those requests. And things might get worse. If market recovery continues to lag, it will be harder for BREIT to claim it is the exception. But so far, the BREIT saga has raised an important issue. Private equity firms like Blackstone have only recently begun catering to retail investors, with the fund serving as a litmus test for the entire industry. Will these structures with a mismatch between the liquidity of underlying assets and redemption terms stand the test of time? We are closer to finding out.

Yann LeCun, Meta's AI chief, has expressed skepticism about large language models (LLMs) like ChatGPT achieving human-like reasoning and planning. He has openly criticized LLMs for having a limited understanding of logic, lack of persistent memory, and inability to plan hierarchically, arguing that they can only respond accurately to prompts “if trained with the right data”. As such, LeCun is focusing his efforts on developing a new generation of AI systems aimed at achieving "superintelligence," which he believes could take around ten years to realize. Meta has been investing heavily in LLM development to compete with tech giants like OpenAI and Google. Despite this, LeCun's team at the Fundamental AI Research (Fair) lab is pursuing an approach known as "world modeling," aiming to equip AI with common sense and a human-like understanding of the world. This approach involves training AI by mimicking human learning processes, such as “feeding systems with hours of video and deliberately leaving out frames”, with the goal of “getting the AI to predict what will happen next. In a way, resembling how children learn from “passively observing the world around them”. While LeCun's vision is ambitious, it faces skepticism and significant challenges. Critics argue that teaching AI common sense and causality is highly complex and has not yet proven effective. There has also been some internal tension in Meta, with some insiders attributing the company's late entry into the generative AI space to an overly academic culture within Fair. Despite these challenges, LeCun remains a key adviser to Zuckerberg, emphasizing that achieving artificial general intelligence is a scientific challenge rather than merely a technological or product design issue. Common sense has long been a persistent challenge for AI. As the AI development landscape grows increasingly competitive, the success of LeCun's ambitious vision could potentially give Meta a significant edge. Most importantly, it could redefine the future of AI as a whole.