debut: 2/16/17
38,480 runs
If you have a problem with attention span ..this is not for you.
Look for shorter comments on other threads ...Thanks Sarge
Look for shorter comments on other threads ...Thanks Sarge
An Explanation of AI and Quantum Computing.
This blog provides a fascinating picture of the current state of classical AI, its deterministic nature, and the potential paradigm shift quantum computing could bring to the field.
Hoping these explanations bring clarity and depth to the pseudonyms on this site that keep referring to AI
AI as we know it today is bound by the principles of basic computing. Numerous flaws
At its core, AI relies on binary logic: sequences of zeros and ones processed through sophisticated algorithms.
These algorithms are deterministic, meaning they behave predictably, following predefined rules set by their developers.
No matter how advanced AI appears, whether it's performing natural language processing, generating art, or diagnosing diseases, it operates strictly within the confines of its programming.
While machine learning models like neural networks can "learn" patterns from data, the learning process itself is still guided by human-defined objectives and constraints.
Modern artificial intelligence is constrained by the rules of classical computing.
It has no capacity for independent thought or deviation from its programming.
Its intelligence, no matter how impressive, is ultimately constrained by the limitations of classical computing hardware and software architectures.
The deterministic nature of classical AI ensures reliability and predictability, but it also caps its potential at what its programmers can envision and implement.
Quantum Computing: A New Frontier
Quantum computing, on the other hand, introduces a completely different set of principles that defy the binary logic of classical computers.
In such systems, bits exist as either 0 or 1. In quantum systems, qubits exploit the phenomenon of superposition, allowing them to exist as 0, 1, or any combination of these states simultaneously.
This is akin to processing multiple scenarios at once, exponentially increasing computational power and enabling parallelism on an unprecedented scale.
Additionally, quantum entanglement allows qubits to be interdependent in ways that classical bits cannot, further amplifying computational possibilities.
In the context of AI, this means quantum computing could potentially enable AI systems to process vast amounts of information and explore a near-infinite number of possibilities simultaneously.
This capability could lead to emergent behaviours—outcomes that are not explicitly programmed but arise from the AI’s ability to process complex, interconnected data in novel ways.
The Implications: From Determinism to Emergence
The phrase "But quantum can" hints at a transformative leap.
Quantum computing could, in theory, allow AI systems to break free from the deterministic mold of classical computing.
By leveraging quantum phenomena, AI might move beyond rigid programming into realms of emergent behavior.
This raises profound questions:
Could quantum-powered AI develop forms of "decision-making" that are inherently unpredictable?
Could it exhibit creativity or problem-solving abilities that appear autonomous, even though they are still rooted in physics and mathematics?
However, it’s important to temper this vision with the current limitations of quantum computing.
As noted, scaling qubits remains a significant challenge due to issues like decoherence, where quantum states are lost due to interactions with the environment.
Error rates are another major hurdle—quantum systems are inherently prone to errors, necessitating complex error correction mechanisms that add layers of computational burden.
These barriers mean that while quantum computing holds immense promise, practical, large-scale quantum AI remains a distant goal.
This excerpt also touches on the role of cloud ( now Fog) computing in facilitating innovation.
By integrating disparate systems and simulating them together, cloud technologies have enabled breakthroughs in both classical and quantum computing.
This synergy allows researchers to model quantum systems, develop error-correction algorithms, and optimize quantum architectures—all crucial steps toward unlocking the full potential of quantum-powered AI.
The juxtaposition of classical AI and quantum AI underscores a potential shift in how we approach intelligence and computation.
While classical AI is remarkable in its achievements, it remains fundamentally constrained by its deterministic foundations.
Quantum computing could upend this paradigm, introducing a new era of AI that is less predictable, more autonomous, and possibly capable of emergent behaviours.
However, the path to this future is fraught with technical challenges, and the societal implications of such advancements demand careful consideration.
The story of AI and quantum computing is still unfolding, and it’s one of the most exciting frontiers of science and technology.
Whether quantum AI will truly "break free" or simply extend the boundaries of what is possible within deterministic systems remains an open question—one that will likely shape the next era of human civilization.
..Sarge
My Notes from a university forum I attended.
- edited -
Crabs in the barrel.
