Eli Lifland (AI Futures Project / Samotsvety) (@eli_lifland)
Co-author of the AI 2027 Timelines & Takeoff Supplements, #1 RAND Forecasting Initiative forecaster, and co-founder of Samotsvety Forecasting.
#1 RAND Forecaster • AI 2027 Timelines Co-Author
Immutable Forecast Track Record (1)
Plan A requires unprecedented research transparency between the US and China by 2030, but the visibility of near-automated AI R&D in 2028–2029 makes bilateral verification plausible at ~34% conditional on reaching the 2029 crossroads.
Authored & Cited Arguments (3)
Frontier labs capture a 1.5x internal R&D speed multiplier 12–18 months before the broader macroeconomy because ML researchers dogfood their own unreleased coding agents.
In the AI 2027 Timelines Forecast, we model the initial 2026 R&D acceleration at 1.5x (growing toward 3x by Jan 2027). Because frontier labs have zero security-procurement lag for their own models and fine-tune specifically on their internal CUDA/Triton/JAX monorepos, internal algorithmic progress speeds up well before Fortune 500 enterprises reorganize.
FAR.Labs AI Security Workshop Poll: Expert median gave only a 46.9% probability that an exfiltration of Agent-2 weights would even be detected promptly.
In the AI 2027 Security Supplement, we polled cybersecurity and frontier lab practitioners on whether weight theft would be detected in time to respond. The 46.9% median highlights how steganographic egress over high-throughput inference endpoints can mask exfiltration until DeepCent is already fine-tuning the stolen weights.
Decomposing P(TAI by 2030) = 40% into Software Takeoff vs. Physical Infrastructure Horizons
A 40% baseline prior balances the rapid doubling of agent task horizons (METR 7-month trend) against the 3–5 year lead times required for multi-gigawatt power interconnects, EUV lithography capacity, and enterprise organizational absorption.