Quantum Artificial Intelligence Is Closer Than You Think (2024)

FAQs

How close are we to quantum artificial intelligence? ›

While some experiments have been conducted using quantum computing to enhance machine learning (ML) algorithms, these efforts are still in the initial trial stages of development and are not developed enough to be effective for world-world use cases.

Quantum AI, on the other hand, leverages quantum computers, which use qubits (quantum bits). Qubits can exist in multiple states simultaneously, enabling them to perform parallel computations and potentially solve problems exponentially faster than classical computers.

The current field of quantum computers isn't quite ready for prime time: McKinsey has estimated that 5,000 quantum computers will be operational by 2030 but that the hardware and software necessary for handling the most complex problems won't be available until 2035 or later.

So far, the research on quantum artificial intelligence has given us the building blocks to achieve quantum advantage to solve problems in combinatorial optimization, soft computing, deep learning, and machine learning much faster than traditional classical computing.

Quantum AI is not a legitimate app for crypto trading; it is widely considered a scam.

By combining them, we create new and powerful capabilities. For instance, quantum AI can train neural networks for image and voice recognition using large datasets in a fraction of the time it would take for classical AI, leading to more accurate predictions and better performance.

In his recent TED talk, Hartmut Neven, founder of Google Quantum AI, dived into the world of quantum computing, revealing how this exciting technology transcends traditional computing.

It's a field that melds the transformative potential of quantum computing with the ingenuity of artificial intelligence (AI) to pave the way for groundbreaking advancements in machine learning algorithms, neural networks, and large language models (LLMs).

The abrupt shutdown of NASA's quantum computing project was triggered by an unforeseen incident during a routine test. During the analysis of a complex simulation, the quantum computer demonstrated unprecedented computational power, solving a previously intractable problem.

Challenges of Quantum Computing. Despite remarkable advances, quantum computing still faces many technological hurdles that limit its applications, scalability, and reliability for the time being. Due to their fragility, qubit interconnection, decoherence, and external noise, quantum systems are prone to errors.

What country is closest to quantum computing? ›

In recent times, China has gained the advantage in terms of quantum research. Although some in scientific and political circles dismiss China's recent progress, there is growing concern over China's quantum domination. The US is especially worried about recent news of China's quantum computing developments.

"AI is a sophisticated software layer that emulates the very capabilities of human intelligence, while quantum computing is assembling the very building blocks of the universe to create a computing substrate," he explains. "We're pushing computing both into the realm of the mind and the realm of the sub-atomic."

Quantum AI could solve problems considered impossible today

Simulating complex systems, such as chemical reactions or protein structures, also seems possible thanks to quantum AI. Other promising application fields include quantum machine learning, quantum simulations, and new materials development.

“AI methods are currently limited by the abilities of classical computers to process complex data. Quantum computing can potentially enhance AI's capabilities by removing the limitations of data size, complexity, and the speed of problem solving.”

In a 2022 Expert Survey on Progress in AI (2022 ESPAI), 50% of the respondents believed that high-level machine intelligence could exist by 2059. Sam Altman, CEO of OpenAI, believes that AGI will possibly be built in the “reasonably close-ish future”.

In all cases, the majority of participants expected AI singularity before 2060. In the 2022 Expert Survey on Progress in AI, conducted with 738 experts who published at the 2021 NIPS and ICML conferences, AI experts estimate that there's a 50% chance that high-level machine intelligence will occur until 2059.

Kurzweil believes that the singularity will occur by approximately 2045. His predictions differ from Vinge's in that he predicts a gradual ascent to the singularity, rather than Vinge's rapidly self-improving superhuman intelligence.