232 : Why most predictions go wrong ? #bitcoin #agenticAI #flyingCars - to name a few
From Deep Dive with Gemini by @shutosha
May 5, 2026 · 35 min
About this episode
The episode explores why predictions often fail by analyzing the complex interplay of past and future forces on the present.
Research #OrthogonalPresent the core concept that the "Now" is not a point on a simple linear timeline, but a high-dimensional coordinate where millions of trajectories from the past and future converge. Because multiple forces act on this single point, they create a resultant reality that is orthogonal to the vectors that created it, making the present inherently unknowable in real-time. #TemporalPhysics This refers to the analytical framework explaining why visionary and open-ended predictions consistently fail to materialize on schedule . It highlights that properly analyzing our timeline requires acknowledging both the "pull" of the future and the heavy, immovable reality of the past. #PastVector This symbolizes the massive momentum or "freight train" of realized history moving toward the future. Forecasting models frequently fail because they ignore this powerful inertia—such as 100 years of urban zoning, organizational culture, or 500 years of financial history—which heavily constrains current motion. #FutureVector This stands for the pull of potentiality moving toward the past . It embodies the trajectory of what could happen, driven by human…
People in this episode
Host: @shutosha
Topics covered
- predictions
- temporal physics
- forecasting models
- urban zoning
- technological breakthroughs
Keywords
- predictions
- temporal physics
- Bitcoin
- forecasting
- urban zoning
- technological breakthroughs
Mentioned in this episode
Organizations: Bitcoin, agenticAI, flyingCars, OrthogonalPresent, TemporalPhysics, PastVector, FutureVector, DoubleConeModel
Books & works: Deep Dive with Gemini
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