AI research strategy

Jun 19

Open AI Research Faces Consolidation Into Proprietary Platforms

The economics of training large language models—requiring massive compute, data, and capital—concentrate power among a handful of companies (Anthropic, OpenAI, Google, Meta) who can afford the infrastructure, leaving smaller labs and academic teams dependent on renting API access under terms those companies control. This shift from open-source to closed access matters because the companies controlling foundational models also control what research questions get asked, what safety constraints get embedded, and who can compete in downstream applications. The open research movement's risk isn't losing altruism—it's losing the ability for anyone outside these walls to audit, modify, or contribute to the systems reshaping knowledge work and AI policy.

theme-ai ai model alignment ai safety AI research strategy

Jun 2

AI Labs Recruit Philosophy and Ethics Experts for Consciousness Research

Source: Financial Times (paywall)

Google DeepMind, Anthropic, and Meta are staffing up with psychologists, ethicists, and philosophers. The hiring pattern suggests these labs believe current or near-term AI systems could exhibit properties—sentience, suffering, moral status—that require specialized expertise to evaluate, rather than leaving assessments to engineers alone. Consciousness research is becoming a competitive necessity rather than a fringe academic pursuit, which will likely accelerate capability development and corporate hedging against regulatory or reputational liability.