May 20, 2026 News
OpenAI's Reasoning Model Disproves 80-Year-Old Erdős Conjecture in Geometry
OpenAI claims its new general-purpose reasoning model has autonomously produced an original mathematical proof disproving a famous unsolved conjecture in geometry first posed by Paul Erdős in 1946. This follows a previous false claim seven months ago where OpenAI mistakenly announced GPT-5 had solved Erdős problems, only to discover it had found existing solutions. The current claim is supported by verification from prominent mathematicians including Noga Alon, Melanie Wood, and Thomas Bloom, marking what OpenAI calls the first time AI has autonomously solved a prominent open problem in mathematics.
Skynet Chance (+0.04%): Autonomous complex reasoning and novel problem-solving in mathematics demonstrates AI systems can now perform sophisticated intellectual tasks independently, potentially increasing capability for unexpected behaviors. However, mathematical reasoning is still a narrow domain and doesn't directly relate to goal misalignment or control challenges.
Skynet Date (-1 days): The demonstration of long-chain autonomous reasoning capabilities suggests faster-than-expected progress in AI systems that can independently solve complex problems. This acceleration in reasoning capabilities could shorten timelines to advanced AI systems that might pose control challenges.
AGI Progress (+0.04%): Successfully solving a prominent 80-year-old mathematical problem autonomously using a general-purpose reasoning model represents significant progress toward AGI's requirement for abstract reasoning, creativity, and intellectual generalization. The ability to discover novel solutions across fields suggests meaningful advancement in core AGI capabilities beyond narrow pattern matching.
AGI Date (-1 days): The breakthrough demonstrates that general-purpose reasoning models are advancing faster than anticipated, achieving autonomous novel research contributions sooner than expected. This suggests acceleration in the timeline toward AGI as systems demonstrate intellectual capabilities previously thought to require human-level general intelligence.
IrisGo Develops Proactive AI Desktop Agent with Andrew Ng Backing
IrisGo, backed by Andrew Ng's AI Fund with $2.8 million in seed funding, is developing a desktop AI companion that learns user workflows and automates them proactively. The system, founded by former Apple Siri engineer Jeffrey Lai, uses on-device processing for privacy while targeting knowledge workers with automation of repetitive business tasks. The company has launched beta versions for macOS and Windows and secured a preinstallation deal with Acer.
Skynet Chance (+0.01%): The development of proactive AI agents that can anticipate and act on user needs without explicit prompting represents a small step toward more autonomous AI systems, though the limited scope to desktop tasks and hybrid architecture with user authorization controls mitigate immediate concern. The on-device processing and user authorization requirements suggest some attention to control mechanisms.
Skynet Date (+0 days): The focus on building commercially viable proactive agents that operate with some autonomy suggests incremental progress in AI agency capabilities, though the narrow application domain and privacy-focused design represent only modest acceleration. The system's hybrid architecture requiring user authorization for complex tasks moderates the timeline impact.
AGI Progress (+0.01%): The development of proactive AI agents that can learn workflows from observation and automate tasks represents meaningful progress in learning from demonstration and autonomous planning capabilities relevant to AGI. However, the limited scope to desktop automation and reliance on existing models for complex reasoning indicates this is an application-layer advancement rather than fundamental capability breakthrough.
AGI Date (+0 days): The commercial deployment of learning-based proactive agents with backing from major players like Nvidia, Google, and Andrew Ng signals growing investment and infrastructure for autonomous AI systems, modestly accelerating the timeline. The preinstallation deals with device manufacturers like Acer could rapidly scale deployment of agentic AI capabilities to mainstream users.
OpenAI Plans September IPO Following Dismissal of Musk Lawsuit
OpenAI is reportedly preparing for an initial public offering as early as September 2026, working with Goldman Sachs and Morgan Stanley on the process. The move comes immediately after a lawsuit from co-founder Elon Musk against OpenAI was dismissed. The IPO is expected to be a major event in tech finance, potentially competing with SpaceX's own public offering plans.
Skynet Chance (+0.01%): An IPO creates stronger public market pressures for rapid revenue growth and quarterly results, which could incentivize faster deployment of powerful AI systems with less emphasis on safety considerations. However, public scrutiny and regulatory oversight may also increase accountability.
Skynet Date (+0 days): Market pressure from public investors typically accelerates product development and deployment timelines to meet growth expectations. The financial incentives of being publicly traded could marginally speed up the release of advanced AI capabilities.
AGI Progress (+0.01%): Going public provides OpenAI with significantly enhanced access to capital markets for scaling compute infrastructure and research operations. The additional funding resources and financial flexibility from an IPO directly support the massive investments required for AGI development.
AGI Date (+0 days): The influx of capital from a successful IPO will likely accelerate OpenAI's research and development efforts by removing funding constraints. Greater financial resources enable faster scaling of compute, talent acquisition, and parallel research initiatives that could advance AGI timelines.