The next 36 months will be WILD

Quick Overview

The convergence toward Artificial General Intelligence (AGI) is estimated around the 2027-2028 window, driven by compounding advancements in compute scaling, capital expenditure, and algorithmic efficiency, leading to recursive self-improvement (RSI) and an acceleration loop where models become economically substitutable before achieving consciousness, as detailed by figures like Dario Amodei and Sam Altman.

Key Points: The '2027 Convergence' estimates AGI/ASI arrival between 2027 and 2028, based on the convergence of compute scaling, capital expenditure, and algorithmic efficiency trends. Key AI pioneers like Dario Amodei (Anthropic) and Sam Altman (OpenAI) contribute to this consensus, with Anthropic suggesting AI matching Nobel-level capability in a datacenter. The AI development timeline shows NVIDIA (Jensen Huang) projecting competitive ability by 2029, while OpenAI (Sam Altman) projects AGI by 2027-2028, defining 'The Collapse Window'. The acceleration loop of Recursive Self-Improvement (RSI) involves five steps: Algorithmic Research, Data Generation & Curation, Writing/Implementation, Training Models, and Evaluating New Models. Empirical scaling laws suggest task duration is accelerating exponentially, moving from minutes of coherence for chatbots to multi-week autonomous projects for researchers by 2026. The core constraint is the massive 500 TWh AI power demand (around 12% of US 4000 TWh total), necessitating rapid infrastructure upgrades like solar, natural gas, and nuclear SMRs. The 'Invisible Displacement' is characterized by a vanishing job ladder, where entry-level roles drop by 13% in AI-exposed roles due to hiring freezes, creating 'ghost jobs' that are never filled.

Context: This presentation focuses on projecting the timeline for Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI), referencing predictions from leading figures like Dario Amodei and Sam Altman, and introduces concepts like the '2027 Convergence' and the 'Industrial Siege' dynamic driving relentless competition. The speaker utilizes charts to illustrate the exponential growth in AI capabilities (Task Horizon) and the looming energy constraint, ultimately framing the current employment situation as Solow's Paradox 2.0 where productivity rises but job creation stalls.