Will AI Eat Quantum Computing’s Lunch

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Google vs AI Rivals — As it prepares to defend against the DOJ’s antitrust case remedies proposal, Google subpoenas OpenAI, Perplexity and Microsoft, seeking financial, user, and licensing data.

Grid AI Boost — The Energy Department committed $30M to fund AI projects designed to free up a backlog of renewable energy waiting to connect to the grid.

AI Czar — Trump has proposed a potential White House AI czar role to coordinate federal AI regulation & use, bypassing Senate confirmation for fast implementation.

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Black Forest Labs — xAI's four-month-old image generation partner is in talks to raise a $200M round led by Andreessen Horowitz that may fetch a $1B+ valuation.

xAI — Elon Musk’s AI startup reportedly plans to release a standalone AI chatbot and Language Model app to compete with OpenAI’s ChatGPT as early as December.

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THE HOTTEST THING IN TECH
Will AI Eat Quantum Computing’s Lunch

The buzz and funding around quantum computing has intensified this year, fueled by tangible advancements attracting investors, governments, and industries. IBM’s CEO, Arvind Krishna, projected the development of a 4,000+ qubit quantum computer by 2025, a significant leap. That increased capacity could transform various industries, including cryptography, drug discovery, and AI, offering solutions to currently unsolvable problems. The AI boom is synergistic, but is it also a threat to the sector? 

AI Driving Quantum Computing Funding 

2024 has seen a massive surge in quantum computing funding with startups attracting over $1.5B in venture funding across 50 deals. This nearly doubles the $785M raised in 2023 and surpasses the previous high of nearly $963M in 2022.This growth trajectory fuels optimism that quantum computing is progressing towards practical applications. While quantum computing holds potential across diverse sectors, its connection to the booming AI sector is likely contributing to this boom. 

The superior processing power of Quantum computing could significantly accelerate AI development by offering a potential solution to the vast computational demands and energy consumption of Gen AI. Additionally, studies suggest it could be 100x more energy efficient than supercomputers for comparable calculations, potentially mitigating AI's energy burden.

Big Tech Stakes a Claim 

Established tech giants are heavily investing in quantum computing, spurred by its potential to reshape industries.

IBM is a pioneer in quantum computing. Significant milestones include the development of a 1,121-qubit chip called IBM Quantum Condor and its open-source Qiskit framework fosters collaboration and innovation. However, concerns remain about the company’s valuation relative to its anticipated growth.

Google is actively researching in the field, collaborating with NVIDIA this month to enhance quantum device design using simulations on the Eos supercomputer. Their focus is mitigating limitations of quantum hardware through large-scale simulations.

Microsoft is focusing on neutral atom quantum computing. It also achieved a breakthrough this month by entangling 24 logical qubits using this tech. It now plans to release a commercial quantum computer with over 1,000 physical qubits by 2025. Its research also explores quantum error correction and qubit virtualization.

Startups To Watch

Just this week, PsiQuantum announced a game changing approach aiming to develop a large-scale, fault-tolerant photonic quantum computer by 2027. Its silicon-based photonic tech offers advantages in scalability and speed and the company has raised over $1B, including from the US and Australian governments, indicating strong confidence in its vision.

Earlier this year, Quantinuum raised $300M to focus on trapped ion quantum computing, known for its high fidelity and long coherence times. Quantinuum also emphasizes quantum networking, a potentially lucrative sector with projected market value of $38 billion by 2040.

Another startup, Riverlane, specializing in quantum error correction tech landed a $75M Series C round in 2024. Their focus is crucial for developing stable and reliable quantum computers capable of complex computations.

Other notable startups include Xanadu, Quandela, and ORCA Computing.

Is AI a Potential Risk Factor?

Recent AI advancements have raised questions about whether quantum computers will be essential in the long run. AI's simulation and deep learning capacity is being applied effectively to simulate physics and chemistry, encroaching on quantum computing's perceived strengths. Companies like Meta are leveraging neural network-based methods for modeling materials with strong quantum properties.

AI-based approaches using classical hardware are significantly cheaper and often faster than current quantum methods, particularly for weakly correlated systems. This cost advantage, coupled with rapid advancements in AI model development, poses a challenge to the economic viability of quantum computing for certain applications. Limiting factors include only a modest speed advantage over classical algorithms and the bottleneck of transferring large datasets in and out of quantum computers. 

Collaboration or Competition?

Some experts believe AI won’t entirely replace quantum computers, particularly for simulating strongly correlated systems. But, others express concerns about the significant valuations in the field given AI's rapid progress. Ultimately, the relationship between AI and quantum computing might be characterized by both collaboration and competition. While some experts believe the technologies will complement each other in a hybrid approach, others view them as competing forces. The future likely holds a complex interplay between these two technologies, with their respective roles in specific applications yet to be fully determined.

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