Here are some predictions for quantum in 2024:

Quantum supremacy 

The D-Wave CEO predicts that the industry will achieve a proven, defensible quantum supremacy result in 2024. 

Quantum computing 

UKTN predicts that quantum computing will become an increasingly tangible and accessible technology, emerging in enterprise environments

Quantum technologies 

Venture capitalists predict that 2024 will be a critical year for quantum technologies. 

AI and quantum computing 

Floriane de Maupeou, investor at French VC Serena, expects that the convergence between AI and quantum computing will increase in 2024

Quantum technology focus 

2024 will see an increased focus on quantum technology among business schools and entrepreneurship programs. 

Quantum ready cryptography 

Organizations must start planning and testing to adopt NIST’s new PQC algorithms in 2024

Satellite and space security 

Satellite and space security is becoming increasingly important in 2024. 

Quantum computing can improve research and development, supply-chain optimization, and production

The Dawn of Quantum PracticalityHowever, in 2024 we should see of a glimpse of achieving the spirit of that term. In other words, expect a few companies and research institutions to perform everyday computational tasks using quantum computers with a performance better than classical.

Quantum computing has the potential to transform many sectors by solving problems that are currently unsolvable for classical computers. These problems include cryptography, machine learning, optimization, drug discovery, and climate modeling. 

Here are some predictions for quantum computing: 

• Quantum supremacy Some experts predict that practical quantum computers will be available within the next decade, while others believe it could take 20–30 years or more. 
• Quantum computing market According to Yahoo Finance, the global quantum computing market is projected to reach $4,456 million by 2030, growing at a CAGR of 24.2% during the forecast period of 2023–2030. 
• IBM IBM is nearly finished building a 1,121 qubit quantum computer and aims to have a QC with up to 100,000 qubits in 2026. By 2030, they aim to have over 1 million qubits. 
• Quantum computing field In 2024, the quantum computing field is expected to transition from physical qubits to error-corrected logical qubits and see increased global collaboration in quantum research

Quantum computing is growing rapidly, with a compound annual growth rate (CAGR) of 32.1% between 2023 and 2030. The global quantum computing market is expected to grow from $928.8 million in 2023 to $6.5 billion by 2030

Quantum computing is becoming increasingly important for industries such as finance and healthcare. It offers increased speed, accuracy, and reliability for computing tasks. As a result, more and more companies are investing in this technology

According to a 2022 LinkedIn report, quantum computers could generate nearly a trillion dollars in annual revenue by 2050. A 2020 Boston Consulting Group (BCG) report estimates that productivity gains from quantum computing could lead to $450 billion to $850 billion in annual operating income by 2050. A 2022 Statista study suggests that quantum computing could create $450 billion to $850 billion in value in the next 15 to 30 years

By 2050, quantum computers are expected to achieve speeds of 1,000,000 to 10,000,000 qubit/s and perform approximate calculations

According to LinkedIn, quantum machine learning (QML) is the futurebecause it has many potential benefits when combined with machine learning

Quantum computing can provide better results faster, and its ability to calculate solutions simultaneously has huge potential for AI and ML. However, quantum computers are still a long way from being used in everyday life. McKinsey and Company predicts that only 2,000 to 5,000 quantum computers will be operational by 2030, and those capable of handling the most complex problems may not exist until 2035 or later.

Quantum computing can speed up machine learning in several ways: 

• Parallel calculations: Quantum computers can perform calculations in parallel, which is a significant factor in their speed. 
• Higher dimensional spaces: Quantum computers can operate in higher dimensional spaces. 
• Superposition: Quantum computers can evaluate multiple possibilities simultaneously. 
• Non-classical models: Quantum models can tap into non-classical probabilistic models. 
• Complex data sets: Quantum computing machine learning models can efficiently factor and classify complex yet condensed data sets. 
• Computational capabilities: Quantum computers have the computational capabilities to manage machine learning algorithms that are too strenuous for classical computers. 

Quantum machine learning, also called quantum-enhanced machine learning, uses the information processing power of quantum technologies to enhance and speed up the work performed by a machine learning model

According to a Quora user, AI is better than quantum computing because it can solve real-world problems and run on a common PC. Quantum computing, on the other hand, can only solve a few problems, has little practical use, and is expensive to run. 

Here are some other differences between AI and quantum computing: 

• Benefits: AI can help with productivity, decision-making, and complex problem-solving. It can also strengthen the economy, manage repetitive tasks, and help with disaster management. Quantum computing can lead to 100% efficient fuel cells, advances in drug discovery, and personalized medicine. 
• Complexity: Quantum computers can handle complex optimization problems that traditional computers cannot. Quantum computers are also good at solving certain types of problems faster and more efficiently than traditional computers. 
• Cost: According to a Quora user, quantum computing is expensive to run. 
• Accessibility: AI can run on a common PC. 
• Real-world application: AI can solve thousands of real-world problems.

Here are some differences between AI and Quantum AI: 

• Complexity AI’s complexity and IT infrastructure can be a challenge for organizations. Quantum AI complexity theory is a subfield of computational complexity theory that studies the difficulty of computational problems. 
• Benefits Quantum AI can offer benefits like:
• Applications Quantum AI can be used for:

The quantum-powered AI organizationQuantum simulations in healthcare have the potential to speed up drug discovery and analysis using quantum optimization techniques. In addition, quantum AI can benefit areas such as cybersecurity and finance by handling high-dimensional data

(Full article source google)

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