Experts are nearing a quantum advantage, with unimaginable computational power that could unlock the true potential of machine-learning.
copyright by www.raconteur.net
Experts are nearing a quantum advantage, with unimaginable computational power that could unlock the true potential of machine-learning Machine-learning and quantum computing are two technologies that have incredible potential in their own right. Now researchers are bringing them together. The main goal is to achieve a so-called quantum advantage, where complex algorithms can be calculated significantly faster than with the best classical computer. This would be a game-changer in the field of AI.
Such a breakthrough could lead to new drug discoveries, advances in chemistry, as well as better data science, weather predictions and natural-language processing. “We could be as little as three years away from achieving a quantum advantage in AI if the largest players in the quantum computing space meet their goals,” says Ilyas Khan, chief executive of Cambridge Quantum Computing.
This comes after Google announced late last year that it had achieved “quantum supremacy”, claiming their quantum computer had cracked a problem that would take even the fastest conventional machine thousands of years to solve.
“Developing quantum machine-learning algorithms could allow us to solve complex problems much more quickly. To realise the full potential of quantum computing for AI, we need to increase the number of qubits that make up these systems,” says Dr Jay Gambetta, vice president of quantum computing at IBM Research.
Quantum devices exploit the strange properties of quantum physics and mechanics to speed up calculations . Classical computers store data in bits, as zeros or ones. Quantum computers use qubits, where data can exist in two different states simultaneously. This gives them more computational fire power. We’re talking up to a million times faster than some classical computers. And when you add a single qubit, you double the quantum computer’s processing power. “To meet Moore’s Law [the number of transistors on a computer chip is doubled
And when you add a single qubit, you double the quantum computer’s processing power. “To meet Moore’s Law [the number of transistors on a computer chip is doubled about every two years while the cost falls], you would need to add a single qubit every year,” says Peter Chapman, chief executive of IonQ.
“Our goal is to double the number of qubits every year. We expect quantum computers to be able to routinely solve problems that supercomputers cannot, within two years.”
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A focus on optimisation problems
Already industrial behemoths, such as IBM, Honeywell, Google, Microsoft and Amazon, are
. Their investments will have a major impact on accelerating developments.
“We expect algorithm development to accelerate considerably. The quantum community has recognised economic opportunities in solving complex optimisation problems that permeate many aspects of the business world. These range from ‘how do you assemble a Boeing 777 with millions of parts in the correct order?’ to challenges in resource distribution,” explains Dr David Awschalom, professor of quantum information at the University of Chicago.
read more – https://www.raconteur.net/technology/quantum-computing-ai
Experts are nearing a quantum advantage, with unimaginable computational power that could unlock the true potential of machine-learning.
copyright by www.raconteur.net
Such a breakthrough could lead to new drug discoveries, advances in chemistry, as well as better data science, weather predictions and natural-language processing. “We could be as little as three years away from achieving a quantum advantage in AI if the largest players in the quantum computing space meet their goals,” says Ilyas Khan, chief executive of Cambridge Quantum Computing.
This comes after Google announced late last year that it had achieved “quantum supremacy”, claiming their quantum computer had cracked a problem that would take even the fastest conventional machine thousands of years to solve.
“Developing quantum machine-learning algorithms could allow us to solve complex problems much more quickly. To realise the full potential of quantum computing for AI, we need to increase the number of qubits that make up these systems,” says Dr Jay Gambetta, vice president of quantum computing at IBM Research.
Quantum devices exploit the strange properties of quantum physics and mechanics to speed up calculations . Classical computers store data in bits, as zeros or ones. Quantum computers use qubits, where data can exist in two different states simultaneously. This gives them more computational fire power. We’re talking up to a million times faster than some classical computers. And when you add a single qubit, you double the quantum computer’s processing power. “To meet Moore’s Law [the number of transistors on a computer chip is doubled
And when you add a single qubit, you double the quantum computer’s processing power. “To meet Moore’s Law [the number of transistors on a computer chip is doubled about every two years while the cost falls], you would need to add a single qubit every year,” says Peter Chapman, chief executive of IonQ.
“Our goal is to double the number of qubits every year. We expect quantum computers to be able to routinely solve problems that supercomputers cannot, within two years.”
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
A focus on optimisation problems
Already industrial behemoths, such as IBM, Honeywell, Google, Microsoft and Amazon, are
. Their investments will have a major impact on accelerating developments.
“We expect algorithm development to accelerate considerably. The quantum community has recognised economic opportunities in solving complex optimisation problems that permeate many aspects of the business world. These range from ‘how do you assemble a Boeing 777 with millions of parts in the correct order?’ to challenges in resource distribution,” explains Dr David Awschalom, professor of quantum information at the University of Chicago.
read more – https://www.raconteur.net/technology/quantum-computing-ai
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