Yo kidz! Remember to update/upgrade your #FreeBSD to latest 14.3 prior updating to 15.0. Otherwise you'll need to use /rescue dir to fetch base.txz of 15.0 and unpack libsys.so.7 to /lib manually.
You're welcome.
I profess #computerscience (#datamining, #knowledgediscovery, #machinelearning, #networkscience) at Amherst College. I like #oysters, #mountains (in any season), #sailing, and #theorems.
I am a #FreeBSD "enthusiastic power-user" (i.e., fanboy), and I used to be a src-committer and the developer of FreeSBIE.
| Home | https://matteo.rionda.to |
| Research Group | https://acdmammoths.github.io |
| ORCID | https://orcid.org/0000-0003-2523-4420 |
| GitHub | https://github.com/rionda |
Yo kidz! Remember to update/upgrade your #FreeBSD to latest 14.3 prior updating to 15.0. Otherwise you'll need to use /rescue dir to fetch base.txz of 15.0 and unpack libsys.so.7 to /lib manually.
You're welcome.
If you have even the slightest curiosity about optimising compilers and aren't already following @mattgodbolt's Advent of Compiler Optimisations, you absolutely should.
In the past few days I’ve seen talk about RAM prices shooting up due to demand from big datacenters.
Today I read that a historic brand like Crucial - I own plenty of their hardware, including SSDs - is dropping consumer products to focus on gear for those same datacenters.
The result (or maybe the intention?) is to push people away from self hosting, undermine the OwnYourData idea and make everyone depend on huge datacenters for life.
So much for owning your data.
So much for decentralisation.
Because taking down one giant datacenter is far easier than taking down thousands or millions of individual nodes.
Friends and colleagues, don’t trade your freedom for a bit of convenience. Once you give it away, getting it back is very hard.
Always Own Your Data.
Proud advisor moment: the CRA interviewed my former undergrad researcher and current PhD advisee Maryam Abuissa about their experience as a young researcher.
#undergraduate #undergradinthelab
https://cra.org/crn/2024/10/securing-machine-learning-with-sequestered-encryption-on-gpu-hardware/