November 6, 2025 News
Laude Institute Launches Slingshots Grant Program to Accelerate AI Research and Evaluation
The Laude Institute announced its first Slingshots grants program, providing fifteen AI research projects with funding, compute resources, and engineering support. The initial cohort focuses heavily on AI evaluation challenges, including projects like Terminal Bench, ARC-AGI, and new benchmarks for code optimization and white-collar AI agents.
Skynet Chance (-0.03%): Investment in rigorous AI evaluation and benchmarking infrastructure strengthens our ability to assess AI capabilities and limitations, contributing marginally to safer AI development. The focus on third-party, non-company-specific benchmarks helps maintain transparency and reduces risks of unmonitored capability advances.
Skynet Date (+0 days): Enhanced evaluation frameworks may slow deployment of inadequately tested AI systems by establishing higher standards for capability assessment. However, the impact on timeline is modest as this is primarily infrastructure building rather than direct safety intervention.
AGI Progress (+0.02%): The program accelerates AI research by providing compute and resources typically unavailable in academic settings, with projects targeting key AGI-relevant challenges like code optimization and general reasoning (ARC-AGI). Better evaluation tools also help identify and address capability gaps more effectively.
AGI Date (+0 days): By removing resource constraints for promising AI research projects and focusing on capability evaluation that drives progress, the program modestly accelerates the pace of AI development. The emphasis on benchmarking helps researchers identify and pursue productive research directions more efficiently.
OpenAI Announces $20B Annual Revenue and $1.4 Trillion Infrastructure Commitments Over 8 Years
OpenAI CEO Sam Altman revealed the company expects to reach $20 billion in annualized revenue by year-end and grow to hundreds of billions by 2030, with approximately $1.4 trillion in data center commitments over the next eight years. Altman outlined expansion plans including enterprise offerings, consumer devices, robotics, scientific discovery applications, and potentially becoming an AI cloud computing provider. The massive infrastructure investment signals OpenAI's commitment to scaling compute capacity significantly.
Skynet Chance (+0.05%): The massive scale of infrastructure investment ($1.4 trillion) and rapid capability expansion into robotics, devices, and autonomous systems significantly increases potential attack surfaces and deployment of powerful AI in physical domains. The sheer concentration of compute resources in one organization also increases risks from single points of control failure.
Skynet Date (-1 days): The unprecedented $1.4 trillion infrastructure commitment represents a dramatic acceleration in compute availability for frontier AI development, potentially compressing timelines significantly. Expansion into robotics and autonomous physical systems could accelerate the transition from digital-only AI to AI with real-world actuators.
AGI Progress (+0.04%): The $1.4 trillion infrastructure commitment represents one of the largest resource allocations in AI history, directly addressing the primary bottleneck to AGI development: compute availability. OpenAI's expansion into diverse domains (robotics, scientific discovery, enterprise) suggests confidence in near-term breakthrough capabilities.
AGI Date (-1 days): This massive compute infrastructure investment dramatically accelerates the timeline by removing resource constraints that typically limit experimental scale. The 8-year timeline with hundreds of billions in projected 2030 revenue suggests OpenAI expects transformative capabilities within this decade, likely implying AGI arrival before 2033.
Inception Raises $50M to Develop Faster Diffusion-Based AI Models for Code Generation
Inception, a startup led by Stanford professor Stefano Ermon, has raised $50 million in seed funding to develop diffusion-based AI models for code and text generation. Unlike autoregressive models like GPT, Inception's approach uses iterative refinement similar to image generation systems, claiming to achieve over 1,000 tokens per second with lower latency and compute costs. The company has released its Mercury model for software development, already integrated into several development tools.
Skynet Chance (+0.01%): More efficient AI architectures could enable wider deployment and accessibility of powerful AI systems, slightly increasing proliferation risks. However, the focus on efficiency rather than raw capability growth presents minimal direct control challenges.
Skynet Date (+0 days): The development of more efficient AI architectures that reduce compute requirements could accelerate deployment timelines for advanced systems. The reported 1,000+ tokens per second throughput suggests faster iteration cycles for AI development.
AGI Progress (+0.02%): This represents meaningful architectural innovation that addresses key bottlenecks in AI systems (latency and compute efficiency), demonstrating alternative pathways to capability scaling. The ability to process operations in parallel rather than sequentially could enable handling more complex reasoning tasks.
AGI Date (+0 days): Diffusion-based approaches offering significantly better efficiency and parallelization could accelerate AGI timelines by making larger-scale experiments more economically feasible. The substantial funding and high-profile backing suggest this approach will receive serious resources for rapid development.