Viewing profile — bwasti
bwasti
HN member- Joined
- Fri, Mar 10, 2017, 8:26 AM UTC
- HN karma
- 336
- Public activity
- 115 items
- HN profile
- View on Hacker News ↗
About bwasti
No profile information was provided.
Recent public activity
-
comment
Comment #26268188
Mining Bitcoin can be done with pencil, paper and the ability to communicate with others also interested in Bitcoin.
-
comment
Comment #26251757
A popular post on r/wallstreetbets[1] summarizes Michael Burry’s thesis that CPI (consumer price index) is unaffected as long as inflation isn’t directly impacting consumers of the…
-
comment
Comment #25934049
I've posted this once before but I grabbed a domain name and preloaded a tutorial. Happy to remove if that's against the rules!
- story
- story
-
comment
Comment #25842763
The source can be found here: https://github.com/bwasti/mebm
- story
-
comment
Comment #25664828
> It can also handle nonlinear conversions such as Fahrenheit to Celsius huh?
- story
-
comment
Comment #25410243
You can just try the instructions with an off-the-shelf assembler. They're not supported.
-
comment
Comment #25410233
I've found the M1's 128bit instructions to be quite fast. My M1 MacBook Air can hit 90GFlops on a single core. My 2019 16" MacBook Pro is only 1.5 times faster at 135GFlops per cor…
- story
- story
- story
- story
-
comment
Comment #24712892
I believe problems solved by this tool generally disappear when using named tensors
-
comment
Comment #24082005
perhaps title "Sweatpants Forever: How the Fashion Industry Collapsed" for context?
-
comment
Comment #23467297
would a library like pybind (for C++ extensions) be compatible with the philosophy of this python implementation?
- story
- story
- story
-
comment
Comment #22616541
this can be done in browser with tensorflow.js + a pretrained mobilenet in a couple dozen lines of code example: https://jott.live/html/tfjsmobilenet code: https://jott.live/code/t…
- story
- story
-
comment
Comment #20856699
Note that this a layout trick and not an algorithmic one. An algorithmic speed up that is good for dense convolutions with small kernels is to use Winograd: https://arxiv.org/abs/1…