[HN Gopher] Show HN: Razer x Lambda Tensorbook
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Show HN: Razer x Lambda Tensorbook
Hi all, long time lurker, first time poster. I want to share with
you all something we've been working on for a while at Lambda: the
Razer x Lambda Tensorbook:
https://www.youtube.com/watch?v=wMh6Dhq7P_Q But before I tell you
about it, I want to make this all about me, because I built this
for me. 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. So, flashback to 2018, and
I'm a hardware engineer focusing on the compute system at Lyft's
autonomous vehicle (AV) program, Level5 (L5). Here was a project
that that would save lives, that would improve the human condition,
that was all ready to go. I saw my role as coming in to product-
ize, to take what was close to the finish line and get it over it.
The disappointment was pretty brutal when I realized just how wrong
I was. 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. At Lyft L5 I thought I would be applying
specialized inference accelerators (Habana, Groq, Graphcore, etc.)
into the vehicle compute system. Instead, the only requirement that
mattered org-wide was: "Don't do anything that slows down the
perception team". 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. 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. 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. I'm happy to talk about that experience in the comments
because I have a lot of fond memories from my time there. 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. Anything less than the most
possible is a detriment to their workflow. I still truly believe
AVs will save lives; so by extension, enabling deep learning
engineers enables AVs enables improvement to the human condition.
Transitive property, :thumbsup: So moving on, my following role in
industry was characterized by working closely with the least
technical people I have ever had the opportunity to work with in my
life. And I mean opportunity genuinely, because doing so gave me so
much perspective on the things that you and I here probably take
for granted. (How do we know that Ctrl+Alt+T will open a terminal?
Why does `touch` make a file? How do I quit vim?) So, the takeaway
from that experience, and motivation #2 for me is that computers
can be so unaccessible in surprising ways. I have a deep respect
and appreciation for Linux, and I want others to see things the
same way, so anything I can do to make easier the process of "self-
serving" or "bootstrapping" to my level of understanding, is
something worth doing to me. So, with those two personal
motivations outlined, I present to you, for your consideration, the
Razer x Lambda Tensorbook. A laptop with a no-compromise approach
to speeds-and-feeds and shipping with OEM support for Ubuntu.
sincerely, Vinay. Product Marketing @ Lambda
Author : vimeh
Score : 23 points
Date : 2022-04-12 18:42 UTC (4 hours ago)
| daviddever23box wrote:
| Tell us about the choice of Razer Blade 15 (2021) as the platform
| (or, as we refer to it, CH570).
| ganoushoreilly wrote:
| https://lambdalabs.com/blog/lambda-teams-up-with-razer-to-la...
|
| Here's a link with more info for anyone else curious.
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