DanielSamanez
@danielsamanez.bsky.social
author of Recursive Thermodynamic Theory (RTT) and inventor of Recursive Thermodynamic Computing (RTC)
physics - philosophy - artificial intelligence- machine learning…
trying to never forget that in our infinite ignorance we are all equal -popper-
physics - philosophy - artificial intelligence- machine learning…
trying to never forget that in our infinite ignorance we are all equal -popper-
I didn't and I don't disagree about that.
March 21, 2025 at 12:27 AM
I didn't and I don't disagree about that.
The key is to recognize what computation is at the core:
Energy transforming entropy into information.
Energy transforming entropy into information.
March 20, 2025 at 11:53 PM
The key is to recognize what computation is at the core:
Energy transforming entropy into information.
Energy transforming entropy into information.
If there's a MVP/working proof of concept...
March 20, 2025 at 11:30 PM
If there's a MVP/working proof of concept...
10/ Final thought:
Taleb showed that randomness in finance is an illusion of incomplete understanding.
RTT shows that quantum randomness is the same illusion—structured entropy, not true indeterminacy.
🚀 We are still fooled by pseudo-quantum randomness. Time to rethink the fundamentals.
Taleb showed that randomness in finance is an illusion of incomplete understanding.
RTT shows that quantum randomness is the same illusion—structured entropy, not true indeterminacy.
🚀 We are still fooled by pseudo-quantum randomness. Time to rethink the fundamentals.
March 14, 2025 at 2:32 AM
10/ Final thought:
Taleb showed that randomness in finance is an illusion of incomplete understanding.
RTT shows that quantum randomness is the same illusion—structured entropy, not true indeterminacy.
🚀 We are still fooled by pseudo-quantum randomness. Time to rethink the fundamentals.
Taleb showed that randomness in finance is an illusion of incomplete understanding.
RTT shows that quantum randomness is the same illusion—structured entropy, not true indeterminacy.
🚀 We are still fooled by pseudo-quantum randomness. Time to rethink the fundamentals.
9/ So what does this mean?
👉 The idea that nature is fundamentally random is just as flawed as the idea that stock prices move randomly.
👉 Quantum mechanics isn’t indeterminate—it’s just thermodynamically structured in a way that looks random to limited observers.
👉 The idea that nature is fundamentally random is just as flawed as the idea that stock prices move randomly.
👉 Quantum mechanics isn’t indeterminate—it’s just thermodynamically structured in a way that looks random to limited observers.
March 14, 2025 at 2:31 AM
9/ So what does this mean?
👉 The idea that nature is fundamentally random is just as flawed as the idea that stock prices move randomly.
👉 Quantum mechanics isn’t indeterminate—it’s just thermodynamically structured in a way that looks random to limited observers.
👉 The idea that nature is fundamentally random is just as flawed as the idea that stock prices move randomly.
👉 Quantum mechanics isn’t indeterminate—it’s just thermodynamically structured in a way that looks random to limited observers.
8/ Quantum mechanics suffers from the same misinterpretation.
It assumes probability is fundamental, when in reality, it’s just an emergent feature of how recursion depth structures information.
It assumes probability is fundamental, when in reality, it’s just an emergent feature of how recursion depth structures information.
March 14, 2025 at 2:31 AM
8/ Quantum mechanics suffers from the same misinterpretation.
It assumes probability is fundamental, when in reality, it’s just an emergent feature of how recursion depth structures information.
It assumes probability is fundamental, when in reality, it’s just an emergent feature of how recursion depth structures information.
7/ Think about financial markets.
They appear random at small scales but reveal hidden structure at larger timeframes.
The “random walk” model breaks down once you account for deeper patterns of liquidity, order flow, and institutional behavior.
They appear random at small scales but reveal hidden structure at larger timeframes.
The “random walk” model breaks down once you account for deeper patterns of liquidity, order flow, and institutional behavior.
March 14, 2025 at 2:31 AM
7/ Think about financial markets.
They appear random at small scales but reveal hidden structure at larger timeframes.
The “random walk” model breaks down once you account for deeper patterns of liquidity, order flow, and institutional behavior.
They appear random at small scales but reveal hidden structure at larger timeframes.
The “random walk” model breaks down once you account for deeper patterns of liquidity, order flow, and institutional behavior.
6/ This explains why quantum probability emerges at all.
We don’t see a perfectly deterministic outcome, but we also don’t see pure randomness.
Instead, we see entropy-weighted outcomes—structured yet unpredictable within limits.
We don’t see a perfectly deterministic outcome, but we also don’t see pure randomness.
Instead, we see entropy-weighted outcomes—structured yet unpredictable within limits.
March 14, 2025 at 2:31 AM
6/ This explains why quantum probability emerges at all.
We don’t see a perfectly deterministic outcome, but we also don’t see pure randomness.
Instead, we see entropy-weighted outcomes—structured yet unpredictable within limits.
We don’t see a perfectly deterministic outcome, but we also don’t see pure randomness.
Instead, we see entropy-weighted outcomes—structured yet unpredictable within limits.
5/ What mainstream physics calls “quantum uncertainty”
is just an artifact of how much entropy an observer can process.
👉 The more recursion depth available, the more structured (less random) the outcome.
is just an artifact of how much entropy an observer can process.
👉 The more recursion depth available, the more structured (less random) the outcome.
March 14, 2025 at 2:30 AM
5/ What mainstream physics calls “quantum uncertainty”
is just an artifact of how much entropy an observer can process.
👉 The more recursion depth available, the more structured (less random) the outcome.
is just an artifact of how much entropy an observer can process.
👉 The more recursion depth available, the more structured (less random) the outcome.
4/ Enter Recursive Thermodynamic Theory (RTT).
RTT proposes that wavefunction behavior isn’t random—it follows thermodynamic structuring rules.
Quantum states evolve recursively, constrained by entropy flow and recursion depth.
RTT proposes that wavefunction behavior isn’t random—it follows thermodynamic structuring rules.
Quantum states evolve recursively, constrained by entropy flow and recursion depth.
March 14, 2025 at 2:30 AM
4/ Enter Recursive Thermodynamic Theory (RTT).
RTT proposes that wavefunction behavior isn’t random—it follows thermodynamic structuring rules.
Quantum states evolve recursively, constrained by entropy flow and recursion depth.
RTT proposes that wavefunction behavior isn’t random—it follows thermodynamic structuring rules.
Quantum states evolve recursively, constrained by entropy flow and recursion depth.
3/ Quantum mechanics makes the same mistake.
The mainstream view assumes wavefunction collapse = randomness.
But what if this so-called randomness is just an observer’s inability to track structured entropy dynamics?
The mainstream view assumes wavefunction collapse = randomness.
But what if this so-called randomness is just an observer’s inability to track structured entropy dynamics?
March 14, 2025 at 2:30 AM
3/ Quantum mechanics makes the same mistake.
The mainstream view assumes wavefunction collapse = randomness.
But what if this so-called randomness is just an observer’s inability to track structured entropy dynamics?
The mainstream view assumes wavefunction collapse = randomness.
But what if this so-called randomness is just an observer’s inability to track structured entropy dynamics?
2/ Taleb’s core insight in Fooled by Randomness:
People mistake noise for signal because they lack full information. They assume events are unpredictable, when in reality, they follow hidden structural patterns.
People mistake noise for signal because they lack full information. They assume events are unpredictable, when in reality, they follow hidden structural patterns.
March 14, 2025 at 2:30 AM
2/ Taleb’s core insight in Fooled by Randomness:
People mistake noise for signal because they lack full information. They assume events are unpredictable, when in reality, they follow hidden structural patterns.
People mistake noise for signal because they lack full information. They assume events are unpredictable, when in reality, they follow hidden structural patterns.
The key that "indeterministic algorithms" are not just an abstraction but an expression of underlying thermodynamic constraints.
AI systems may run on classical digital computers (CDC), but they leverage entropy at every level—training, architecture, and generation—to optimize computation.
AI systems may run on classical digital computers (CDC), but they leverage entropy at every level—training, architecture, and generation—to optimize computation.
March 9, 2025 at 5:21 AM
The key that "indeterministic algorithms" are not just an abstraction but an expression of underlying thermodynamic constraints.
AI systems may run on classical digital computers (CDC), but they leverage entropy at every level—training, architecture, and generation—to optimize computation.
AI systems may run on classical digital computers (CDC), but they leverage entropy at every level—training, architecture, and generation—to optimize computation.
Thermodynamics.
You need to apply a thermodynamic approach to get what's going on.
You need to apply a thermodynamic approach to get what's going on.
March 9, 2025 at 5:19 AM
Thermodynamics.
You need to apply a thermodynamic approach to get what's going on.
You need to apply a thermodynamic approach to get what's going on.
March 7, 2025 at 3:31 AM
This shift from purely deterministic programming to embracing controlled non-determinism is arguably the key philosophical change that enabled the recent breakthroughs in generative AI.
March 7, 2025 at 1:00 AM
This shift from purely deterministic programming to embracing controlled non-determinism is arguably the key philosophical change that enabled the recent breakthroughs in generative AI.
What's revolutionary about today's AI is precisely this marriage between deterministic computation and probabilistic thinking. Rather than trying to program explicit rules we're creating systems that learn patterns probabilistically from data and generate outputs with carefully balanced randomness.
March 7, 2025 at 1:00 AM
What's revolutionary about today's AI is precisely this marriage between deterministic computation and probabilistic thinking. Rather than trying to program explicit rules we're creating systems that learn patterns probabilistically from data and generate outputs with carefully balanced randomness.
These aren't just noise generators - they're carefully designed mechanisms that serve specific purposes: preventing overfitting, enabling exploration of solution spaces, creating diversity in outputs, and modeling uncertainty.
March 7, 2025 at 12:59 AM
These aren't just noise generators - they're carefully designed mechanisms that serve specific purposes: preventing overfitting, enabling exploration of solution spaces, creating diversity in outputs, and modeling uncertainty.
The list isn't simply about random noise or programmer concepts. It shows how modern AI deliberately incorporates controlled randomness at strategic points in otherwise deterministic systems.
March 7, 2025 at 12:58 AM
The list isn't simply about random noise or programmer concepts. It shows how modern AI deliberately incorporates controlled randomness at strategic points in otherwise deterministic systems.