Anything less than the most possible is a detriment to their workflow. Anyway, the takeaway I have from Lyft, and my first motivation here is that there is no such thing as over-provisioning or too much compute in a deep learning engineer's mind. I'm happy to talk about that experience in the comments because I have a lot of fond memories from my time there. Something I thought was a solved problem was very much not, and ultimately resulted in my team and others building a 5,000 watt monster of server (+ power distribution, + thermals, + chassis, etc etc) that took up an entire rear row of seating.
Don't get me wrong, there were a multitude of other difficult technical challenges to solve outside of the deep learning ones that were gating, but I had underestimated just how not-ready the CNNs for object detection and classification were. Forget testing silicon with the potential to reduce power requirements by 10x, I was lucky to get a willing ear to hear my case for changing a flag in the TensorFlow runtime to perform inference at FP16 instead of FP32. Instead, the only requirement that mattered org-wide was: "Don't do anything that slows down the perception team". At Lyft L5 I thought I would be applying specialized inference accelerators (Habana, Groq, Graphcore, etc.) into the vehicle compute system. It's one thing to nod along when reading Knuth write "premature optimization is the root of all evil" it's another to experience it firsthand. The disappointment was pretty brutal when I realized just how wrong I was.
I saw my role as coming in to product-ize, to take what was close to the finish line and get it over it.
Here was a project that that would save lives, that would improve the human condition, that was all ready to go. So, flashback to 2018, and I'm a hardware engineer focusing on the compute system at Lyft's autonomous vehicle (AV) program, Level5 (L5). See, while I'm genuinely interested in hearing from the community what you think as this is the culmination of a lot of effort from a lot of people across so many different fields (seriously, the number of folks across manufacturing, engineering, design, logistics, and marketing who have had to work together to launch this is nuts), I really just want to tie the larger motivations for Tensorbook as a product back to a personal narrative to explain why I'm so proud. I want to share with you all something we've been working on for a while at Lambda: the Razer x Lambda Tensorbook: But before I tell you about it, I want to make this all about me, because I built this for me. Show HN: Razer x Lambda Tensorbook Hi all, long time lurker, first time poster.
If you need more information on her, feel free to send in another ask! So she has always supported space endeavours, and is the biggest sponsor and donor of the DSED.īasically, feel free to just use her name if there are some inventions that wouldn't normally make sense, because I would too. She's interested in space exploration because well, why not! No one really knows her actual motivations in developing tech, whether it’s for Earth or for space exploration, but she is vocal on media about expanding human reach. So not only she is a businessperson, she's also very smart and has created innovative technology like the protective dome around Japan, the universal translator the world uses, and the combadges of the crew. Charming and humorous, she's heavily inspired by Tony Stark's character in the Marvel Cinematic Universe, Asami Sato (cough) in Legend of Korra, and James Halliday in Ready Player One. She comes from old money-and by old, meaning from the 2000s-and for decades, her family has always been in the technology business (think Microsoft or heck, Stark Industries) and has owned Sato Industries, the leading and biggest tech conglomerate in the world based in Japan. Instead of Eleanor Ashford, her name is now Riko Sato. If I’m wrong though, current applicants are always welcome to revise and resend their apps, just inform us that it is a revision! After a quick Ctrl+F in our inbox, no one has used her yet for their app, so it's safe to change her name. Could you elaborate a bit on eleanor ashford? who is she, why is she interested in space exploration, where does her money come from, that sort of thing? Thanks for asking and giving us the chance to elaborate on her! I actually forgot to change her name, as it was only meant to be a placeholder, so apologies for the neglect.