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- 🤖⚛️ Chemical Accuracy from Quantum Algorithms, Deep Learning Boom, and Open-Source AI for Defense
🤖⚛️ Chemical Accuracy from Quantum Algorithms, Deep Learning Boom, and Open-Source AI for Defense
A Newsletter for Computing Geeks, Entrepreneurs, and STEM Graduates
Benjamin Wolba
November 10, 2024
In partnership with
Qunova Computing: Shaping the Future of Quantum Chemistry on Commercial Quantum Computers
Quantum computing holds remarkable potential for revolutionizing fields like chemistry, materials discovery, and drug development.
However, the challenge is each computational step and measurement introduces errors that quickly accumulate, impacting the accuracy of results. How can one develop smarter quantum algorithms that produce valuable results for quantum chemistry while leveraging the capabilities of today’s quantum hardware?
Qunova Computing was founded in 2021 by Kevin (June-Koo) Rhee, a professor at the Korea Advanced Institute of Science and Technology (KAIST), who has been researching quantum algorithms for a long time.
He and his team have developed a quantum algorithm that can solve quantum chemistry problems 1,000 times more efficiently with chemical accuracy—the accuracy level needed to predict chemical behaviors reliably:
Future of Computing News
Funding News
Learn more about Quanscient from our first interview and deep-dive into Quanscient.allsolve
Good Reads
By Rodolfo Rosini: “At this point there is a future where Gemini (or whatever DeepMind are going to call their new AI agents) becomes an indispensable partner for the everyday life of a billion of consumers, and this generates so much economic activity that not only makes up for the lost ad losses, but also outstrips it.”
“It wasn’t just that building such a large dataset was a massive logistical challenge. People doubted the machine learning algorithms of the day would benefit from such a vast collection of images.”
“If Large Language Models (LLMs) are the printing press of the Generative AI age, then what’s next? What will be the AI equivalent of the telephone, the internet, the smartphone?”
“Federated Learning is often misunderstood as a privacy technology. In this post we explain how to reap the benefits of FL for training AI models at scale, while preserving privacy.”
“Rapid advances in applying artificial intelligence to simulations in physics and chemistry have some people questioning whether we will even need quantum computers at all.”
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