Latest news with #HartmutNeven
Yahoo
07-05-2025
- Yahoo
What's More Advanced Than AI? Quantum AI Is the Next Leap Forward
Our daily workflows and routine tasks have been infiltrated by artificial intelligence, whether or not you've noticed it. Things like Gemini's integration across Google products work in the background, giving you suggestions. You might even be engaging more directly with chatbots and image generators like OpenAI's ChatGPT and Dall-E. And looming in the near future are more sophisticated virtual assistants. As if AI itself weren't futuristic enough, there's a new leap forward on the horizon: quantum AI. It's a fusion of artificial intelligence with unconventional and still largely experimental quantum computing into a super-fast, highly efficient technology. Quantum computers will be the muscles, while AI will be the brains. "My colleagues sometimes ask me why I left the burgeoning field of AI to focus on quantum computing," Hartmut Neven, founder of Google's Quantum AI lab, wrote in a December blog post introducing the Willow quantum chip. "My answer is that both will prove to be the most transformational technologies of our time, but advanced AI will significantly benefit from access to quantum computing." Here's a quick breakdown of the basics to help you better understand quantum AI. AI vs. generative AI Artificial intelligence is a technology that mimics human decision-making and problem-solving. It's software that can recognize patterns, learn from data and even "understand" language enough to interact with us, via chatbots, to recommend movies or to identify faces or things in photos. One powerful type of AI is generative AI, which goes beyond simple data analysis or predictions. Gen AI models create new content like text, images and sounds based on their training data. Think ChatGPT, Dall-E, Midjourney, Gemini, Claude and Adobe Firefly, to name a few. AI Atlas These tools are powered by large language models trained on tons of data, allowing them to produce realistic outputs. But behind the scenes, even the most advanced AI is still limited by classical computing, the kind that happens in Windows and Mac computers, in the servers that populate data centers and even in supercomputers. But there's only so far that binary operations will get you. And that's where quantum computing could change the game. What is quantum computing? Classical and quantum computing differ in several ways, one of which is processing. Classical computing uses linear processing (step-by-step calculations), while quantum uses parallel processing (simultaneous calculations). Another difference is in the basic processing units they use. Classical computers use bits as the smallest data unit (either a 0 or a 1). Quantum computers use quantum bits, aka qubits, based on the laws of quantum mechanics. Qubits can represent both 0 and 1 simultaneously thanks to a phenomenon called superposition. Another property that quantum computers can leverage is entanglement. It's where two qubits are linked so that the state of one immediately influences the state of the other, no matter the distance. Superposition and entanglement allow quantum computers to solve complex problems much faster than traditional computers. Where classical computing can take weeks or even years to solve some problems, quantum computing reduces the timeframe for achievement to merely hours. So why aren't they mainstream? Quantum computers, running on purpose-built quantum chips, are incredibly delicate and must be kept at amazingly low temperatures to work properly. They're massive and not yet practical for everyday use. Still, companies like Intel, Google, IBM, and Microsoft are heavily invested in quantum computing, and the race is on to make it viable. While most companies don't have the funds or specialized teams to support their own quantum computers, cloud-based quantum computing services like and Google's Quantum AI could be options. Is quantum AI realistic? While the potential is enormous, the main criticism of quantum AI right now is that there's a lot of hype but not a lot of realistic applications. Quantum AI faces challenges like hardware instability and a need for specialized algorithms. However, improvements in error correction and qubit stability are making it more reliable. AI Atlas Current quantum computers, like IBM's Quantum System Two and Google's quantum machinery, can handle some calculations but aren't yet ready to run large-scale AI models. Additionally, quantum computing requires highly controlled environments, so scaling up for widespread use will be a big challenge. That's why most experts believe we're likely years away from fully realized quantum AI. As Lawrence Gasman, president of LDG Tech Advisors, wrote for Forbes at the start of 2024: "It is early days for quantum AI, and for many organizations, quantum AI right now might be overkill." Quantum AI in the future Quantum AI is still in the early trial stages but is a promising technology. Right now, AI models are limited by the power of classical computers, especially when processing big datasets or running complex simulations. Quantum computing could provide the necessary boost AI needs to process large, complex datasets at ultrafast speeds. Although the future real-world applications are somewhat speculative, we can assume certain fields would benefit the most from this technological breakthrough, including financial trading, natural language processing, image and speech recognition, health care diagnostics, robotics, drug discovery, supply chain logistics, cybersecurity through quantum-resistant cryptography and traffic management for autonomous vehicles. Here are some other ways that quantum computing could enhance AI:
Express Tribune
05-02-2025
- Business
- Express Tribune
Google plans to launch quantum computing applications within five years
Listen to article Google aims to release commercial quantum computing applications within five years, Google's head of quantum told Reuters on Wednesday, in a challenge to Nvidia's predictions of a 20-year wait. "We're optimistic that within five years we'll see real-world applications that are possible only on quantum computers," founder and lead of Google Quantum AI Hartmut Neven said in a statement. Real-world applications Google has discussed are related to materials science - applications such as building superior batteries for electric cars - creating new drugs and potentially new energy alternatives. Google's prediction arrives amid wider uncertainty about when such a breakthrough will occur. Predictions from investors and experts range from several years to at least two decades. For decades, scientists have been discussing quantum computing, which promises to deliver machines that are thousands of times more powerful than traditional computers. Traditional computers process information one number at a time, whereas quantum computers use "qubits" that can represent several numbers at once. Governments and businesses have kept a close eye on quantum computing's potential to disrupt modern cybersecurity and other fields such as finance and healthcare. Quantum computing resembles artificial intelligence in some ways. AI before ChatGPT's launch in 2022 was understood mostly by scientists. Scientists had been quietly producing breakthroughs to accelerate the field but there was no firm understanding of when AI would be commercially useful. Two decades out Nvidia's Jensen Huang has said that quantum computing is much farther away than five years. At an analyst event at the CES trade show in Las Vegas in January, Huang predicted practical uses for quantum computers are about 20 years away. "If you kind of said 15 years... that'd probably be on the early side," Huang said, "If you said 30, it's probably on the late side. But if you picked 20, I think a whole bunch of us would believe it. Huang's comments ripped about $8 billion in market value from a handful of quantum computing stocks. The sector was given a boost in December when Google announced it had cracked a key challenge in the field with its new chips. Google has been working on its quantum computing program since 2012 and has designed and built several quantum chips. By using quantum processors, Google said it had managed to solve a computing problem in minutes that would take a classical computer more time than the history of the universe. Google's quantum computing scientists announced another step on the path to real world applications within five years on Wednesday. In a paper published in the scientific journal Nature, the scientists said they had discovered a new approach to quantum simulation, which is a step on the path to achieving Google's objective.
Yahoo
05-02-2025
- Business
- Yahoo
Google Bets on Quantum Computing, Aims for Commercial Use in Five Years
Google (NASDAQ:GOOGL)(NASDAQ:GOOG) is pushing to bring commercial quantum computing applications to market within the next five years, according to Hartmut Neven, head of Google Quantum AI. The company is focusing on materials science, drug discovery, and new energy alternatives, areas where quantum computing could make a real-world impact. Warning! GuruFocus has detected 3 Warning Signs with NVDA. Quantum computing has been in development for decades, with its potential to revolutionize cybersecurity, finance, and healthcare by solving complex problems exponentially faster than traditional computers. Governments and businesses are keeping a close eye on its progress. Not everyone is convinced it will happen soon. Nvidia (NASDAQ:NVDA) CEO Jensen Huang recently predicted that practical quantum computing is still 20 years away, leading to a sell-off in quantum stocks. Still, Google's latest breakthroughs in quantum simulation suggest it's making steady progress, reinforcing its goal of bringing quantum computing into real-world applications much sooner than skeptics expect. This article first appeared on GuruFocus. Sign in to access your portfolio
Yahoo
05-02-2025
- Business
- Yahoo
Google Bets on Quantum Computing, Aims for Commercial Use in Five Years
Google (NASDAQ:GOOGL)(NASDAQ:GOOG) is pushing to bring commercial quantum computing applications to market within the next five years, according to Hartmut Neven, head of Google Quantum AI. The company is focusing on materials science, drug discovery, and new energy alternatives, areas where quantum computing could make a real-world impact. Warning! GuruFocus has detected 3 Warning Signs with NVDA. Quantum computing has been in development for decades, with its potential to revolutionize cybersecurity, finance, and healthcare by solving complex problems exponentially faster than traditional computers. Governments and businesses are keeping a close eye on its progress. Not everyone is convinced it will happen soon. Nvidia (NASDAQ:NVDA) CEO Jensen Huang recently predicted that practical quantum computing is still 20 years away, leading to a sell-off in quantum stocks. Still, Google's latest breakthroughs in quantum simulation suggest it's making steady progress, reinforcing its goal of bringing quantum computing into real-world applications much sooner than skeptics expect. This article first appeared on GuruFocus.
Reuters
05-02-2025
- Business
- Reuters
Google says commercial quantum computing applications arriving within five years
SAN FRANCISCO, Feb 5 (Reuters) - Google (GOOGL.O), opens new tab aims to release commercial quantum computing applications within five years, Google's head of quantum told Reuters on Wednesday, in a challenge to Nvidia's (NVDA.O), opens new tab predictions of a 20-year wait. "We're optimistic that within five years we'll see real-world applications that are possible only on quantum computers," founder and lead of Google Quantum AI Hartmut Neven said in a statement. Real-world applications Google has discussed are related to materials science - applications such as building superior batteries for electric cars - creating new drugs and potentially new energy alternatives. Google's prediction arrives amid wider uncertainty about when such a breakthrough will occur. Predictions from investors and experts range from several years to at least two decades. For decades, scientists have been discussing quantum computing, which promises to deliver machines that are thousands of times more powerful than traditional computers. Traditional computers process information one number at a time, whereas quantum computers use "qubits" that can represent several numbers at once. Governments and businesses have kept a close eye on quantum computing's potential to disrupt modern cybersecurity and other fields such as finance and healthcare. Quantum computing resembles artificial intelligence in some ways. AI before ChatGPT's launch in 2022 was understood mostly by scientists. Scientists had been quietly producing breakthroughs to accelerate the field but there was no firm understanding of when AI would be commercially useful. TWO DECADES OUT Nvidia's Jensen Huang has said that quantum computing is much farther away than five years. At an analyst event at the CES trade show in Las Vegas in January, Huang predicted practical uses for quantum computers are about 20 years away. "If you kind of said 15 years... that'd probably be on the early side," Huang said, "If you said 30, it's probably on the late side. But if you picked 20, I think a whole bunch of us would believe it." Huang's comments ripped about $8 billion in market value from a handful of quantum computing stocks. The sector was given a boost in December when Google announced it had cracked a key challenge in the field with its new chips. Google has been working on its quantum computing program since 2012 and has designed and built several quantum chips. By using quantum processors, Google said it had managed to solve a computing problem in minutes that would take a classical computer more time than the history of the universe. Google's quantum computing scientists announced another step on the path to real world applications within five years on Wednesday. In a paper published in the scientific journal Nature, the scientists said they had discovered a new approach to quantum simulation, which is a step on the path to achieving Google's objective.
