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AI is sucking up energy at an alarming rate. Gartner predicts that AI could consume up to 3.5% of global electricity by 2030. But what if quantum computing could change that? Peter Chapman of IonQ, will break down how quantum tech could reduce the power needed to fuel AI’s explosive growth and why it’s the next big thing in computing.Newsletter: Sign up for our free daily newsletter)**More on this Episode: **Episode Page)**Join the discussion: **Ask Jordan Peter questions on AI and energy)Upcoming Episodes: Check out the upcoming Everyday AI Livestream lineup)Website: YourEverydayAI.com)Email The Show: [email protected])**Connect with Jordan on **LinkedIn)**Topics Covered in This Episode:1. Quantum Computing in AI2. Barriers to Adopting Quantum Computing3. Mechanics of Quantum Computing4. Quantum Computing’s Role in Energy Efficiency5. Quantum Computing's Future RoleTimestamps:**01:45 Daily AI news05:00 About Petter and IonQ06:24 Quantum computers needed for complex problem solving.09:11 Quantum cubits: electrons exist as probabilities everywhere.12:53 Quantum computing at cusp, future applications unknown.15:42 Quantum can address generative AI's energy demands.18:48 Quantum power surpasses universal atoms; AI potential.21:38 Exploring quantum processors for LLM efficiency improvement.27:08 Reduce energy demand to address climate change.29:20 Quantum excels in chemistry, optimization, AI tasks.31:26 Is human intelligence inherently quantum and efficient?**Keywords:**Peter Chapman, Quantum computing, classical systems, transistors, quantum processor, AI, large language models, Prime Prompt Polished Chat GPT, efficient prompting, Quantum Processing Units, linear algebra, barriers to adoption, theoretical perceptions, cloud services, energy savings, environmental impact, nuclear power, data centers, energy demands, power plants, optimization problems, CPUs, GPUs, QPUs, drug discovery, artificial intelligence, qubits, parallelization, classical bits, 64-qubit chip.
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