Row 31034

Row ID: 31034 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 31034 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Sweet ad hominem, _bro_. It speaks volumes about this sub and how much you all know about programming, development and AI. I've been doing Software Development for 25 years and use AI every day. I've studied AI and robotics in Uni. We (humans) are only neural networks. That's all we are no more no less. Once we can model that neural network well enough we will have human level consciousness. There is no soul. No god. No human essence. When we have a powerful enough neural net it will vastly surpass humanity full stop.

> Neural networks enjoy widespread success in both research and industry and, with the advent of quantum technology, it is a crucial challenge to design quantum neural networks for fully quantum learning tasks. Here we propose a truly quantum analogue of classical neurons, which form quantum feedforward neural networks capable of universal quantum computation. We describe the efficient training of these networks using the fidelity as a cost function, providing both classical and efficient quantum implementations. Our method allows for fast optimisation with reduced memory requirements: the number of qudits required scales with only the width, allowing deep-network optimisation. We benchmark our proposal for the quantum task of learning an unknown unitary and find remarkable generalisation behaviour and a striking robustness to noisy training data.

["Training deep quantum neural networks", Nature, Feb 20, 2020](https://www.nature.com/articles/s41467-020-14454-2)

["I lost my job to AI this week..."](https://www.youtube.com/watch?v=U2vq9LUbDGs)

FieldValue
text Sweet ad hominem, _bro_. It speaks volumes about this sub and how much you all know about programming, development and AI. I've been doing Software Development for 25 years and use AI every day. I've studied AI and robotics in Uni. We (humans) are only neural networks. That's all we are no more no less. Once we can model that neural network well enough we will have human level consciousness. There is no soul. No god. No human essence. When we have a powerful enough neural net it will vastly surp…
label r/economics
dataType comment
communityName r/Economics
datetime 2024-05-21
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Raw Record

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  "text": "Sweet ad hominem, _bro_. It speaks volumes about this sub and how much you all know about programming, development and AI. I've been doing Software Development for 25 years and use AI every day. I've studied AI and robotics in Uni. We (humans) are only neural networks. That's all we are no more no less. Once we can model that neural network well enough we will have human level consciousness. There is no soul. No god. No human essence. When we have a powerful enough neural net it will vastly surpass humanity full stop.\n\n> Neural networks enjoy widespread success in both research and industry and, with the advent of quantum technology, it is a crucial challenge to design quantum neural networks for fully quantum learning tasks. Here we propose a truly quantum analogue of classical neurons, which form quantum feedforward neural networks capable of universal quantum computation. We describe the efficient training of these networks using the fidelity as a cost function, providing both classical and efficient quantum implementations. Our method allows for fast optimisation with reduced memory requirements: the number of qudits required scales with only the width, allowing deep-network optimisation. We benchmark our proposal for the quantum task of learning an unknown unitary and find remarkable generalisation behaviour and a striking robustness to noisy training data.\n\n[\"Training deep quantum neural networks\", Nature, Feb 20, 2020](https://www.nature.com/articles/s41467-020-14454-2)\n\n[\"I lost my job to AI this week...\"](https://www.youtube.com/watch?v=U2vq9LUbDGs)",
  "label": "r/economics",
  "dataType": "comment",
  "communityName": "r/Economics",
  "datetime": "2024-05-21",
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