July 14, 2025 News
Meta Considers Abandoning Open-Source AI Strategy for Closed Superintelligence Models
Meta's new Superintelligence Lab is reportedly discussing a pivot away from open-source AI models like the delayed Behemoth model toward closed-source development. This potential shift would mark a major philosophical change for Meta, which has championed open-source AI as a differentiator from competitors like OpenAI. The company faces pressure to monetize its massive AI investments while competing with rivals in the commercialization of AI technology.
Skynet Chance (+0.04%): Consolidation toward closed AI models reduces transparency and external oversight, potentially increasing risks of uncontrolled development. However, the impact is moderate as other open-source efforts continue and Meta hasn't definitively committed to this change.
Skynet Date (-1 days): Meta's focus on superintelligence development and willingness to invest heavily in AGI research suggests continued acceleration of advanced AI capabilities. The competitive pressure to commercialize could drive faster development cycles.
AGI Progress (+0.03%): The establishment of a dedicated Superintelligence Lab and Meta's explicit focus on developing AGI represents significant organizational commitment to AGI research. The company's massive investments in talent acquisition and infrastructure indicate serious progress toward AGI goals.
AGI Date (-1 days): Meta's substantial financial commitments including nine-figure salaries for top researchers and new data centers suggest accelerated development timelines. The competitive pressure with OpenAI, Anthropic, and Google DeepMind is likely driving faster AGI development cycles.
Meta Announces Massive 5GW Hyperion AI Data Center to Compete in AI Race
Meta is building a massive 5GW AI data center called Hyperion, with a footprint covering most of Manhattan, to compete with OpenAI and Google in the AI race. The company also plans to bring a 1GW super cluster called Prometheus online in 2026, significantly expanding its computational capacity for training frontier AI models. These data centers will consume enormous amounts of energy and water, potentially impacting local communities.
Skynet Chance (+0.04%): Massive computational scaling enables training of more powerful AI models, potentially increasing capabilities that could lead to alignment challenges. However, this is primarily about competitive positioning rather than fundamental safety breakthroughs or failures.
Skynet Date (-1 days): The enormous computational resources will accelerate AI model development and training cycles, potentially speeding up the timeline for advanced AI capabilities. Multiple companies racing with massive compute could compress development timelines.
AGI Progress (+0.03%): The 5GW computational capacity represents a significant scaling of resources available for training frontier AI models, which is crucial for AGI development. This level of compute could enable training of much larger and more capable models.
AGI Date (-1 days): The massive computational infrastructure coming online by 2026 will likely accelerate AGI development timelines by enabling faster experimentation and training of larger models. The competitive race dynamic with other tech giants further compresses development schedules.