full transcript

From the Ted Talk by Janine Benyus: Biomimicry's surprising lessons from nature's engineers

Unscramble the Blue Letters


Now, in a gorup with so many IT people, I do have to mention what I'm not going to talk about, and that is that your field is one that has learned an emuroons amount from living things, on the software side. So there's computers that protect themselves, like an imunme system, and we're learning from gene ratgieloun and biological development. And we're learning from neural nets, genetic alogrhimts, evolutionary computing. That's on the software side. But what's interesting to me is that we haven't looked at this, as much. I mean, these machines are really not very high tech in my eiatsmiotn in the sense that there's dozens and donezs of carcinogens in the water in Silicon vllaey. So the hardware is not at all up to snuff in terms of what life would call a success. So what can we learn about making — not just computers, but everything? The plane you came in, cars, the seats that you're sitting on. How do we redesign the world that we make, the human-made wlord? More imtorptnlay, what should we ask in the next 10 years? And there's a lot of cool technologies out there that life has.

Open Cloze


Now, in a _____ with so many IT people, I do have to mention what I'm not going to talk about, and that is that your field is one that has learned an ________ amount from living things, on the software side. So there's computers that protect themselves, like an ______ system, and we're learning from gene __________ and biological development. And we're learning from neural nets, genetic __________, evolutionary computing. That's on the software side. But what's interesting to me is that we haven't looked at this, as much. I mean, these machines are really not very high tech in my __________ in the sense that there's dozens and ______ of carcinogens in the water in Silicon ______. So the hardware is not at all up to snuff in terms of what life would call a success. So what can we learn about making — not just computers, but everything? The plane you came in, cars, the seats that you're sitting on. How do we redesign the world that we make, the human-made _____? More ___________, what should we ask in the next 10 years? And there's a lot of cool technologies out there that life has.

Solution


  1. estimation
  2. enormous
  3. importantly
  4. world
  5. regulation
  6. dozens
  7. valley
  8. algorithms
  9. immune
  10. group

Original Text


Now, in a group with so many IT people, I do have to mention what I'm not going to talk about, and that is that your field is one that has learned an enormous amount from living things, on the software side. So there's computers that protect themselves, like an immune system, and we're learning from gene regulation and biological development. And we're learning from neural nets, genetic algorithms, evolutionary computing. That's on the software side. But what's interesting to me is that we haven't looked at this, as much. I mean, these machines are really not very high tech in my estimation in the sense that there's dozens and dozens of carcinogens in the water in Silicon Valley. So the hardware is not at all up to snuff in terms of what life would call a success. So what can we learn about making — not just computers, but everything? The plane you came in, cars, the seats that you're sitting on. How do we redesign the world that we make, the human-made world? More importantly, what should we ask in the next 10 years? And there's a lot of cool technologies out there that life has.

Frequently Occurring Word Combinations


ngrams of length 2

collocation frequency
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room temperature 2
fiber optics 2
fuel cell 2
increase efficiency 2
pulling water 2
large neuron 2
growing fertility 2


Important Words


  1. algorithms
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