Part 8 is out, posted by @greg_corrado & @ymatias on behalf of many, covering our work on AI and ML for healthcare-related applications, including medical imaging, ML in mobile healthcare settings, & the use of generative models like LLMs.
@jeffdean
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Quantum Computing Scalability Expands Problem-Solving Potential
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As this is scaled up, it has the potential to significantly broaden the range of problems to which quantum computers can be applied. Imagine a traditional computer that could only run computations of 20 computation steps, versus one that could run arbitrary length programs.
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Scaling quantum error correction for longer computations
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With further scaling, the error rates on "logical" qubits can hopefully be driven down sufficiently that we can run arbitrary-length quantum computations on a quantum computer, instead of ones with a limited number of steps.
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Physical Qubits Combined Into Noise-Resistant Logical Qubits
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What this work shows is that it is possible to group together many physical qubits and use all of their states to make a "logical" qubit, whose state is significantly less noisy (see the discussion in the blog post on surface codes, phase-flip errors and bit-flip errors).
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Physical Qubits Noise Limits Quantum Computation Steps
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The reason this is important is that single physical qubits are noisy, and on a computation running on physical qubits, this probability of noise accumulates over time, and therefore you are limited to running programs that are no more than a modest handful of computation steps.
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Google Quantum AI Achieves Logical Qubit Error Correction Breakthrough
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Our @GoogleQuantumAI team has made an important step towards development of a large-scale quantum computer: building a prototype logical qubit & showing that quantum error correction makes that logical qubit better as it gets bigger. Congrats to the team! https://
ai.googleblog.com/2023/02/suppre
ssing-quantum-errors-by-scaling.html
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Part 7: Quantum Computing Advances in Natural Sciences Research
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Part 7 is out, posted by @johnplattml on behalf of many, covering advances in our work on various problems in the natural sciences, including neurobiology, biochemistry, and the application of quantum computing to problems in physics.
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Robots Learn Natural Language Communication and Real-World Skills
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Part 6 in the series is out, discussing our work in robotics, especially allowing robots & humans to communicate naturally via language, apply common sense knowledge in real-world situations & increasing the number of low-level skills robots can perform.
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Part 5: Scalable Algorithms, Privacy, and Causal Inference
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Part 5 in the series is out, posted by @Mirrokhni on behalf of many, covering advances in:
· Scalable algorithms (esp. for graphs and clustering)
· Privacy and federated learning
· Market algorithms & causal inference
· Algorithmic foundations and theory