polynoamial
@polynoamial
Past bets that played out
These are the clearest thesis calls with observable outcomes, linked back to the original videos.
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
What this channel is watching now
Recent mentions show where this author is concentrating attention right now.
Latest videos and market context
Recent source posts from this author. Create an account to inspect the complete persisted research trail.
@wtgowers I can believable that GPT-5.5 Pro solves it with steering and/or scaffolding + tons of test-time compute. T...
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
@yoavgo @littmath I feel like this is a complicated point so I want to put together a longer post explaining my views.
The source contains no substantive market, macro, sector, or company-specific claims—only an intent to write a longer post later.
@yoavgo @littmath Can you clarify the question?
The source contains only a request to clarify a question and provides no market, macro, company, sector, or ticker-relevant information.
@yoavgo @littmath It's hard to draw a line... we're talking about log scale, so at some point it becomes completely u...
Commentary suggests that future frontier models (e.g., “GPT-5.5 Pro”) could require dramatically higher inference/training cost ("1000x"), implying AI compute intensity may rise nonlinearly and become economically unrealistic without steering/optimization. This is a qualitative, speculative point with no concrete company/news catalyst.
Proof-backed call history
These are recent thesis calls tied to original source content where available.
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
Post speculates that future frontier models (e.g., “GPT-5.5 Pro”) could achieve previously hard results via better steering/scaffolding and much more test-time compute, implying the “intelligence vs test-time compute (TTC)” curve shifts left (tasks become easier/cheaper to solve). Tradable implication: rising demand for inference/test-time compute and associated AI infrastructure (GPUs, networking, memory, foundry capacity, data centers/cloud).
About this channel
Channel bio, source link, and public-market context from YouTube.
@polynoamial
Most recognized assets
Unlock the full track record
Create an account to inspect the complete author history, trust-weighted rankings, and persisted research across authors, theses, and assets.