In this episode of the Justin Riddle Podcast, Justin dives into the concept of Knightian Freedom where large enough computational spaces become intractably complex to the point where maybe freewill is possible. The focus of this episode is a paper put out by Hartmut Neven (of Google’s Quantum AI Lab) and colleagues from 2021 entitled “Do robots powered by a quantum processor have the freedom to swerve?” This paper discusses how the exponentially large spaces that quantum computers evolve into are so large that they cannot be represented or simulated on digital computers. The size is so vast that it would take a computer the size of the universe computing for trillions of years to simulate even a few femtoseconds of the quantum computers that are about to be commonplace. Similar to modern AI, we will won’t be able to understand why a quantum computer generated the output that it did and perhaps this is the essential ingredient that leads to freewill. Rampant incomputable complexity is freewill. Second, Hartmut and colleagues propose a simple experiment to reveal whether or not there are additional factors that play into what output is generated by a quantum computer. Assume you run a quantum circuit that generates a perfect uniform distribution between many different possible outputs. Then, you observe that the quantum computer does not behave as if there was a uniform distribution, but instead selects one of those possible outputs more often. This is the ‘preference’ of the quantum computer. Next, you develop a circuit to amplify these deviations from uniformity with the intention of amplifying the probability of entering into that preferred state. Now, we have essentially created a ‘happy circuit’ which embraces the quirky preference of our quantum computer. Finally, you can correlate deviations from this happy state to psychological data in an effort to build up a taxonomy of subjective experiences that the quantum computer can enter into. Finally, you embed the quantum computer with its happy circuit into an artificial neural network such that errors produced by the AI push the quantum computer away from happiness and this unhappiness is fed back into the AI. Now we have created an AI system with quantum feelings! Will this newfound sense of subjectivity enable more effective AI systems or will the AI get bogged down by a spiral of despair and refuse to compute?! All of these questions and more are explored here. Enjoy!
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In this episode of the Justin Riddle Podcast, Justin dives into the concept of Knightian Freedom where large enough computational spaces become intractably complex to the point where maybe freewill is possible. The focus of this episode is a paper put out by Hartmut Neven (of Google’s Quantum AI Lab) and colleagues from 2021 entitled “Do robots powered by a quantum processor have the freedom to swerve?” This paper discusses how the exponentially large spaces that quantum computers evolve into are so large that they cannot be represented or simulated on digital computers. The size is so vast that it would take a computer the size of the universe computing for trillions of years to simulate even a few femtoseconds of the quantum computers that are about to be commonplace. Similar to modern AI, we will won’t be able to understand why a quantum computer generated the output that it did and perhaps this is the essential ingredient that leads to freewill. Rampant incomputable complexity is freewill. Second, Hartmut and colleagues propose a simple experiment to reveal whether or not there are additional factors that play into what output is generated by a quantum computer. Assume you run a quantum circuit that generates a perfect uniform distribution between many different possible outputs. Then, you observe that the quantum computer does not behave as if there was a uniform distribution, but instead selects one of those possible outputs more often. This is the ‘preference’ of the quantum computer. Next, you develop a circuit to amplify these deviations from uniformity with the intention of amplifying the probability of entering into that preferred state. Now, we have essentially created a ‘happy circuit’ which embraces the quirky preference of our quantum computer. Finally, you can correlate deviations from this happy state to psychological data in an effort to build up a taxonomy of subjective experiences that the quantum computer can enter into. Finally, you embed the quantum computer with its happy circuit into an artificial neural network such that errors produced by the AI push the quantum computer away from happiness and this unhappiness is fed back into the AI. Now we have created an AI system with quantum feelings! Will this newfound sense of subjectivity enable more effective AI systems or will the AI get bogged down by a spiral of despair and refuse to compute?! All of these questions and more are explored here. Enjoy!
#30 - Current Events in Orch-OR: an interview with Stuart Hameroff
Justin Riddle Podcast
1 hour 14 minutes 40 seconds
3 years ago
#30 - Current Events in Orch-OR: an interview with Stuart Hameroff
In episode 30 of the Quantum Consciousness series, Justin Riddle sits down with Stuart Hameroff to get an update on current events in the Orchestrated Objective Reduction (Orch-OR) Model. This interview took place on August 30th, 2022 in his home in Tucson, AZ. The interview covered four major topics. Our discussion of these topics is interleaved with my reaction, summary, and commentary on the topic of discussion. First, we discussed a recent submitted study that found coherent transmission of excitons between tubulin proteins in a microtubule. This study provides evidence for long range quantum coherence in microtubules, which is a requirement for the Orch-OR model to be grounded in microtubule function. Second, Stuart explains some unpublished pilot data that find superradiant photon emission in microtubules for multiple seconds. This finding has multiple implications. First off, this could be evidence of sustained quantum coherence in microtubule on the order of fractions of a second to multiple seconds. If true, then this implies that the slow cognitive processes of the human mind could be instantiated in slower quantum computations. In addition, this implies that coherent light emission could be a means by which multiple microtubules become entangled to form a network of quantum bits – in essence, a quantum computer. For the third topic, we discuss a recent review paper published by Stuart that explores the idea that the brain is organized in a biological hierarchy spanning multiple spatiotemporal scales. A collaborator of his, Anirban Bandyopadhyay, claims to have recorded coherent kilohertz and megahertz electrical activity from the scalp of humans in what he calls a dodecogram. This data is currently unpublished and I am personally skeptical as this would require coherent activity in this very fast frequency domain across a large spatial swath of cortex to be picked up from the scalp. At this point, I ask a series of questions to Stuart on the relationship between human cognition and microtubule function. The Orch-OR model claims that slow human cognition is a “beat” generated from much faster microtubule function. However, in my view, this beat explanation suggest that human cognition might be emergent, or epiphenomenal, which is not something that Stuart or myself are comfortable with. Finally, we discuss the recent controversy surrounding a study conducted to test the so-called “Diosi-Penrose objective reduction” model. In short another researcher proposed a similar theory to Penrose’s objective reduction model of wave function collapse. In this other theory, the collapse of the wave function was suggested to emit radiation. In this recent experimental study, they found no evidence of radiation emission upon collapse of the wave function. Therefore, the authors of this study concluded that the Diosi OR model was incorrect, but then drew the conclusion that therefore Orch-OR and Penrose OR are not supported by evidence. Stuart refutes this by explaining that Penrose OR does not propose the emission of radiation. I have included chapters in this video so that you can skip to the interview if you so desire. I hope you enjoy!
Justin Riddle Podcast
In this episode of the Justin Riddle Podcast, Justin dives into the concept of Knightian Freedom where large enough computational spaces become intractably complex to the point where maybe freewill is possible. The focus of this episode is a paper put out by Hartmut Neven (of Google’s Quantum AI Lab) and colleagues from 2021 entitled “Do robots powered by a quantum processor have the freedom to swerve?” This paper discusses how the exponentially large spaces that quantum computers evolve into are so large that they cannot be represented or simulated on digital computers. The size is so vast that it would take a computer the size of the universe computing for trillions of years to simulate even a few femtoseconds of the quantum computers that are about to be commonplace. Similar to modern AI, we will won’t be able to understand why a quantum computer generated the output that it did and perhaps this is the essential ingredient that leads to freewill. Rampant incomputable complexity is freewill. Second, Hartmut and colleagues propose a simple experiment to reveal whether or not there are additional factors that play into what output is generated by a quantum computer. Assume you run a quantum circuit that generates a perfect uniform distribution between many different possible outputs. Then, you observe that the quantum computer does not behave as if there was a uniform distribution, but instead selects one of those possible outputs more often. This is the ‘preference’ of the quantum computer. Next, you develop a circuit to amplify these deviations from uniformity with the intention of amplifying the probability of entering into that preferred state. Now, we have essentially created a ‘happy circuit’ which embraces the quirky preference of our quantum computer. Finally, you can correlate deviations from this happy state to psychological data in an effort to build up a taxonomy of subjective experiences that the quantum computer can enter into. Finally, you embed the quantum computer with its happy circuit into an artificial neural network such that errors produced by the AI push the quantum computer away from happiness and this unhappiness is fed back into the AI. Now we have created an AI system with quantum feelings! Will this newfound sense of subjectivity enable more effective AI systems or will the AI get bogged down by a spiral of despair and refuse to compute?! All of these questions and more are explored here. Enjoy!
