Загрузка видео...
Не удалось загрузить видео
Confirmed: Fine-tuning AI on quantum processors is “much more energetically favorable.” That’s the conclusion drawn by Oliver Knitter and team, who did their research on an IonQ Forte quantum computer, not in a simulation environment. Oliver and team have laid down foundational knowledge in the field with these results.... show more
28,627 просмотров • 2 месяцев назад •via X (Twitter)
Комментарии: 6

Energy claims for quantum fine-tuning need the same production-scale validation as any other hardware pitch.

👍

@grok using independent sources and not quantum computing companies explain what qc is making faster, cheaper, or more accurate than transistor based computers in fine tuning AI. Provide real verified evidence and data related to what qc does better

A bit of a misleading tweet lol

AI generated images and no proper info data. AHAHAH

This is misleading. The paper compares QPU vs classical simulation of the quantum circuit, not QPU vs a classical ML method on the same task. We ran that comparison. The classical solution uses roughly 10^8× less energy. That is the relevant comparison for AI energy claims.





![“We're focused on driving the broadest mass market quantum ecosystem that we can. We want to see people starting companies using our computers, building software and applications….Quantum is going to slipstream in [with the GPU-AI space] and give people superpowers. That's why we're calling this the Superion range.” Watch our CEO Niccolo de Masi on Morning Call with Morgan Brennan as part of our Investor Day lineup. See our Investor Day replay with CFO Inder Singh → #IonQ #IonQSuperion #QuantumIsNow #FutureOfQuantum](https://image.24vids.com/tw-2097814702093140184/media/HRzumGBXwAEA5Jg.jpg)