Four short links: 15 June 2015

Streams at Scale, Molecular Programming, Formal Verification, and Deep Learning's Flaws

  1. Twitter Heron: Stream Processing at Scale (Paper a Day) — very readable summary of Apache Storm’s failings, and Heron’s improvements.
  2. Molecular Programming Projectaims to develop computer science principles for programming information-bearing molecules like DNA and RNA to create artificial biomolecular programs of similar complexity. Our long-term vision is to establish molecular programming as a subdiscipline of computer science — one that will enable a yet-to-be imagined array of applications from chemical circuitry for interacting with biological molecules to nanoscale computing and molecular robotics.
  3. The Software Analysis Workbenchprovides the ability to formally verify properties of code written in C, Java, and Cryptol. It leverages automated SAT and SMT solvers to make this process as automated as possible, and provides a scripting language, called SAW Script, to enable verification to scale up to more complex systems. “Non-commercial” license.
  4. What’s Wrong with Deep Learning? (PDF in Google Drive) — What’s missing from deep learning? 1. Theory; 2. Reasoning, structured prediction; 3. Memory, short-term/working/episodic memory; 4. Unsupervised learning that actually works. … and then ways to get those things. Caution: math ahead.
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