AI Chess Bot Trained on 91 Million Lichess Games Mimics Human Play

A Carnegie Mellon University Ph.D. student, Yiming Zhang, has developed an AI-powered chess bot called Allie, trained on 91 million human chess games. Allie can adapt to different skill levels and play similarly to a human, contemplating critical positions and resigning when the game is unwinnable. Zhang believes training AI systems to think like humans can create better agents for therapy, education, and medicine.

Meta, the parent company of Facebook, has embarked on an ambitious journey to develop artificial superintelligence (ASI) by 2027. The company has allocated $66–72 billion in capital expenditures to build the infrastructure necessary for this endeavor [1]. This strategic shift, spearheaded by CEO Mark Zuckerberg, aims to position Meta as a key player in the global AI arms race.

Meta's strategy is centered around vertical integration and aggressive scaling. The acquisition of Scale AI for $14.3 billion has provided the company with a proprietary data-labeling engine, reducing reliance on third-party services and accelerating the training of multimodal models like Llama 4 [1]. Additionally, Meta is constructing Hyperion and Prometheus, two gigawatt-scale data centers designed to rival the computational power of competitors like Microsoft and Google. These projects, coupled with custom AI chips (e.g., MTIA series) and partnerships with over 200 academic institutions, underscore Meta's commitment to self-sufficiency in AI infrastructure [1].

The potential rewards of Meta's ASI strategy are substantial. Successful implementation could unlock 20–40% annual productivity gains across industries, from healthcare to governance. Early signs of ROI include a 12% boost in return on ad spend (ROAS) in Q1 2025, with Goldman Sachs projecting a 20–30% revenue increase by 2027 if AI-driven innovations scale effectively [1].

However, Meta's strategy is not without significant operational, technical, and ethical risks. The $66–72 billion 2025 capital expenditure represents a 30% year-over-year increase, straining the company's balance sheet. Reality Labs, the division overseeing AI and metaverse projects, has posted $60 billion in cumulative losses since 2021, including a $4.21 billion operating loss in Q1 2025 [1]. Early iterations of Llama 4 have faced technical flaws, raising questions about the feasibility of achieving AGI by 2027. Moreover, Meta's reliance on third-party AI chips and its recent $29 billion partnership for Hyperion highlight supply chain fragility [1].

Ethical and regulatory hurdles also pose significant challenges. The EU's AI Act could impose $5 billion in annual fines and reduce long-term growth by 5–10%, while Meta's recent €1.2 billion GDPR fine underscores its vulnerability in privacy-sensitive markets [1]. The societal implications of ASI, such as job displacement and opaque decision-making in governance, demand robust ethical guardrails, which Meta is still refining.

For investors, Meta's AI strategy presents a high-risk, high-reward scenario. The company's $1.77 trillion market cap and 33% net margin provide financial flexibility to absorb short-term losses, but the long-term success of its AI bets depends on overcoming technical flaws, navigating regulatory challenges, and monetizing ASI effectively [1].

In conclusion, Meta's shift to AI superintelligence is a calculated gamble with the potential to redefine the tech landscape. The company's investments in vertical integration, talent acquisitions, and infrastructure position it as a formidable contender. However, substantial operational, technical, and ethical risks must be carefully monitored. Investors should keep an eye on key milestones, such as the Q3 2025 performance of Llama 4 and the completion of Hyperion by 2027, to assess the viability of this high-stakes strategy.

References:
[1] https://www.ainvest.com/news/meta-strategic-shift-ai-superintelligence-era-creation-risky-bet-2508/