Four short links: 30 August 2019


Multi-Language Teams, AI Release Models, Security Myth, and The Internet is for End Users

  1. Lessons From Working With Teams Who Speak English as a Second LanguageWe normally “take notes in public” by writing down key points in a shared document or chat. One of us will act as a contemporaneous note taker, capturing key points that anyone makes so that everyone can read the gist in addition to hearing it. This “real time subtitles” approach also communicates that we are actively listening and if we have misunderstood something, or they realize they misspoke and want to rephrase, then they can revisit that point immediately. This can be a superpower.
  2. Release Strategies and the Social Impacts of Language Models — a paper on OpenAI’s strategy for releasing their language model, which is scary-good at generating text. We chose a staged release process, releasing the smallest model in February, but withholding larger models due to concerns about the potential for misuse, such as generating fake news content, impersonating others in email, or automating abusive social media content production. We released the next model size in May as part of a staged release process. We are now releasing our 774 million parameter model.
  3. The Myth of Consumer-Grade Security (Bruce Schneier) — that distinction between military and consumer products largely doesn’t exist. All of those “consumer products” Barr wants access to are used by government officials—heads of state, legislators, judges, military commanders, and everyone else—worldwide. They’re used by election officials, police at all levels, nuclear power plant operators, CEOs, and human rights activists. They’re critical to national security as well as personal security.
  4. The Internet is for End Users (IETF Draft) — As the internet increasingly mediates essential functions in societies, it has unavoidably become profoundly political; it has helped people overthrow governments and revolutionize social orders, control populations, collect data about individuals, and reveal secrets. It has created wealth for some individuals and companies while destroying others’. All of this raises the question: who do we go through the pain of gathering rough consensus and writing running code for?
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