172 karma · joined September 19, 2019
Application was picking and showing a single random word from "hello world my name is hrgiger" then showing a greeen light, when I see green light, i think about the word and blink, headset was able to detect blinks as well so app was creating training data using blink time - xxx millis. So I created few thousands training data with 6 class using this and trained with my half-ass nn implementation and used generated weights to predict same way via mobile. Never achieved higher than 40%, tried all mixed waves, raw data, different windows of time series. Yet still it was a fun project to mess with, still I try to tune this nn implementation. If they achieve a practical solution I would use subtitles for the full length training. Simple netflix browser plugin might do the trick,but I am not sure if there will be a single AI algo that would understand everyones different data.
Here is a comparison with other frameworks, from 2018: https://arxiv.org/pdf/2002.02806.pdf
>"We are happy to report that the Rosetta molecular modeling suite was recently used to accurately predict the atomic-scale structure of an important coronavirus protein weeks before it could be measured in the lab. Knowledge gained from studying this viral protein is now being used to guide the design of novel vaccines and antiviral drugs."
[0] https://www.youtube.com/watch?v=gGvlNo3nMfw
For me most interesting upcoming changes are
JEP: 352: Non_Volatile Mapped Byte Buffers, JEP 345: NUMA-Aware Memory Allocation for G1 and JEP 370: Foreign-Memory Access API (Incubator). Especially FMA api [1] examples seems most promising but shipped with panama and I am not sure about the maturity yet: https://github.com/zakgof/java-native-benchmark
I wonder how GraalVM stands in this picture that beside of being polyglot, it has AOT and auto vectorization futures and I dont know if those are already/will be shipped also with openJDK
[0] https://jaxenter.com/java-14-update-news-163585.html [1] https://openjdk.java.net/jeps/370
$taskset --cpu-list 8 ./costofthread avg: 11000~
$taskset --cpu-list 8,11 ./costofthread avg: 33000~
$./costofthread avg: 60000~
Another post mentioned 2x4k screens so I thought creating load might delay expected events so I set up gpu to lowest:
"echo low > /sys/class/drm/card0/device/power_dpm_force_performance_level"
Then opened 2 drm and lot of youtube videos with new tabs and keep refreshing reddit, after a minute or two got black boxes
specs here: https://pastebin.com/JXE2HFUu
EDIT: Nope its not it turns out marvel has black theme, sorry misleading comment, move along
https://github.com/golang/go/issues/35112
https://github.com/golang/proposal/blob/master/design/35112-...
Attackers might be trying to steal your information from www.noudaldenhoven.nl (for example, passwords, messages, or credit cards). Learn more NET::ERR_CERT_AUTHORITY_INVALID
from:digicert:
TLS Certificate is not trusted The certificate is not signed by a trusted authority (checking against Mozilla's root store). If you bought the certificate from a trusted authority, you probably just need to install one or more Intermediate certificates. Contact your certificate provider for assistance doing this for your server platform.
Beside of that http works and isnt room 3 only closed once and never opened or am I missing something
Here are some supporting implementations: https://github.com/AOMediaCodec/av1-avif/wiki#demuxers--play...
If you want to check how it looks like on supported browser: https://kagami.github.io/avif.js/
I was also digging around and as OP mentioned found it interesting topic.
https://www.ioccc.org/2019/burton/prog.c
It is the Burton entry from The International Obfuscated C Code Contest, but seems like only handling ascii
https://www.ioccc.org/years-spoiler.html
Limits:
"Requires the C locale and ASCII character set. Input should be less than ten million octets to avoid this problem."