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Dillon Cower
@dcower
Software Engineer . Before: on WebRTC, Duo, spatial audio, ambisonics, VR media. 🐘: @dcower@mastodon.gamedev.place 🎸🎸🎹πŸ₯: ratan.band
Seattle, WAdcower.comJoined June 2012

Dillon Cower’s Tweets

Following our recent expansion of 24x7 rider-only operations across all of SF and in downtown PHX, we’re forging ahead with advancing capabilities for future scope, e.g., freeways. Exciting road ahead! Here’s a snippet from my recent ride from our South Bay HQ to the SF office:
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Expanded our rider-only (no human driver) 24x7 operations to all of SF and doubled the downtown PHX area including airport. Proud and inspired by what the team accomplished this year, leveraging some mind-blowing AI/ML advances. More exciting milestones ahead… onward!
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Today we’re proud to announce: ➑️ We’re the first AV company to launch a commercial service to an airport ➑️ We just doubled our #DTPHX territory in a matter of weeks ➑️ We’re now rider-only 24/7 in all of #SF We’re leading the way forward. blog.waymo.com/2022/12/wheels
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This clip is from one of my rider-only (fully autonomous) rides in San Francisco. Excited for SF residents to experience this. It's really remarkable how well it works. Sign up and try it for yourself!
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Receiving the @californiapuc driverless pilot permit means we can now bring this rider-only experience to San Francisco residents. 24/7; no human driver. Download the Waymo One app and join the waitlist to ride with us! bit.ly/3G8EdhO
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Over the next six months, those in the Bellevue, Washington area may see our fifth-generation #WaymoDriver as we conduct a variety of tests that will help us deepen our understanding of weather as we expand our Driver’s capabilities. πŸ€–πŸš˜πŸŒ§οΈ
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Introducing LocoProp, a new framework that reconceives a neural network as a modular composition of layersβ€”each of which is trained with its own weight regularizer, target output and loss functionβ€”yielding both high performance and efficiency. Read more β†’ goo.gle/3bdKOhA
Similar to backpropagation, LocoProp applies a forward pass to compute the activations of each neural network layer. In the backward pass, LocoProp sets per neuron "targets" for each layer. Finally, LocoProp splits model training into independent problems across layers where several local updates can be applied to each layer's weights in parallel.
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Alright, fine: it's getting enough traction that I think I need to address this paper as a certified Grumpy Linguist in NLP. (I generally try to avoid peer reviewing students in public but at this point it's definitely *already* very public, so πŸ€·β€β™€οΈ.)
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DALLE-2 has a secret language. "Apoploe vesrreaitais" means birds. "Contarra ccetnxniams luryca tanniounons" means bugs or pests. The prompt: "Apoploe vesrreaitais eating Contarra ccetnxniams luryca tanniounons" gives images of birds eating bugs. A thread (1/n)🧡
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1/3 At #ICRA2022, nine Waymo research papers were accepted, including one named Symphony that was nominated as an Outstanding Learning Paper. Symphony is a powerful new approach to learning from demonstration that enables realistic and diverse simulations for testing autonomous
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