@ryanzip

Co-founder @zipline, using fleets of robot airplanes to approximate teleportation

 San Francisco
zipline.com
Joined May 2013
  • Tweets1.1K
  • Following280
  • Followers10.3K
216Media
when Ziplines need maintenance, they fly themselves home. Increasingly, they fly home by hopping across our network of charging sites. Today in Houston:
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Ryan Oksenhorn retweeted
Brent Key✌️
@brentdavidkey
Sep 23
Replying to @ryanzip
@ryanzip amazing service as always 🙌🏼 I am taking advantage of the free delivery fee while I can👍🏼👍🏼
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and for good measure, we hit it with a second zap. bigger bang!
Ryan Oksenhorn
@ryanzip
Sep 23
Video results of zapping a zipline
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Video results of zapping a zipline
Ryan Oksenhorn
@ryanzip
Sep 22
the things you see on slack at this company. never a dull moment at zipline
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the scale in this video from last year still blows my mind, but what's even wilder is that since filming this we've changed the system to deliver from >50% higher than what you see here in our obsessive quest to be silent & invisible
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the things you see on slack at this company. never a dull moment at zipline
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It only took 30 years to notice this, but there is a glaring issue in the PokeRap s01e03
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how it started how its going
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More cool robotics demos today, but remember the Brittle Lesson: mechanical complexity is brittle in the real world. How many hours of real-world use will that hardware get before one of the 10k+ parts break?
Ryan Oksenhorn
@ryanzip
Sep 14
Robotics companies have all accepted The Bitter Lesson and we now see awesome demos, but most have no idea about The Brittle Lesson and boy are they in for a surprise when trying to productize.
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The Brittle Lesson is coming for many robotics companies that will soon need to move from flashy demo → reliable product
Ryan Oksenhorn
@ryanzip
Sep 14
Robotics companies have all accepted The Bitter Lesson and we now see awesome demos, but most have no idea about The Brittle Lesson and boy are they in for a surprise when trying to productize.
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Robotics companies have all accepted The Bitter Lesson and we now see awesome demos, but most have no idea about The Brittle Lesson and boy are they in for a surprise when trying to productize.
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Hardware is hard. Every sensor, every part, every degree of freedom is a burden. The more parts, the more failure points. That brittleness is the enemy, but this brittle lesson clearly hasn't been learned by most teams. Instead, you see them touting high DOF as a feat!
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A better heuristic for which robotics co's will succeed is: study how much work went into minimizing DOF, part count, and # of sensors.
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90th birthday cake, delivered.
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it's a beautiful day for flying
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Zipline's footprint in Africa is growing faster than at any point in our nearly ten years of operations. Exciting updates coming soon!
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You're not using enough AI and it is your fault when LA floods.
No Safe Words
@Cyber_Trailer
Sep 7
Los Angeles, CA (moments ago) Local resident of 30 years has never seen the LA river reach this level following a series of thunderstorms that swept through the region this afternoon.
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seeing these wild Astra blender examples is bringing back this thought: Astra actually hits orbital velocity. It can stay up in orbit seemingly indefinitely, without decaying on its task over time.
Ryan Oksenhorn
@ryanzip
Feb 5
Why things suddenly feel different after gradual progress: AI reached orbital velocity. There is no value in a velocity 1m/s slower than orbital. But once you gain 1m/s....
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.@zipline now flies in Sport Mode
Ryan Oksenhorn
@ryanzip
Sep 5
Replying to @ryanzip
Dynamic Flight Trajectories are like hyper-miling: realtime modelling of wind, airspeed, lift, and drag optimizes speed + altitude profile to minimize time, energy, and noise. Each Zipline refines its plan in flight as conditions change. We now climb while moving toward destination, descend to build airspeed, climb to slow down. We let gravity do more oft he hard work.
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