Distributed algorithms
Sources:
Lex Fridman has discussed distributed algorithms with several experts across different podcast episodes.
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Delegation Chains and Lumps:
- Po-Shen Loh explained the concept of delegation chains in distributed algorithms. When each agent is responsible for a group, larger lumps are more likely to become bottlenecks. Adjustments like prioritizing the smallest lump can distribute sizes more evenly, which can relate to representative decision-making processes in networking systems 1.
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Elegant Algorithm for Distributed Problems:
- Po-Shen Loh shared an elegant algorithm for solving delegation in a distributed way. Initially, everyone is their own representative, and at each step, they decide whether to delegate or stay. This decentralized approach helps handle limited bandwidth efficiently 2.
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Neural Networks and Distributed Algorithms:
- Lex Fridman discussed with Cal Newport the complexities of neural networks and how they resemble distributed algorithms. They conversed about the interpretation challenges due to the dynamic and highly connected nature of these systems 3.
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Fragile Lower Bounds:
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Verifying Computation in Distributed Systems:
- Charles Hoskinson highlighted the importance of verifiable computation in distributed networks. By generating proofs of correct computation, tasks can be securely outsourced to untrusted servers, while the blockchain verifies the proofs 6.
These discussions reveal various facets of handling distributed algorithms, from balancing network loads to verifying computations and addressing theoretical bounds.
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