My worry with the confidence scoring is that it conflates "an agent used this and didn't obviously break" with "this is correct". An agent can follow bad advice for several steps before anything fails. So a KU gaining confirmation weight doesn't tell you much about whether it's actually true, just that it propagated. You're crowd-sourcing correctness from sources that can't reliably detect their own mistakes.
It's why at Tessl we treat evals as a first-class part of the development process rather than an afterthought. Without some mechanism to verify quality beyond adoption, you end up with a very efficient way to spread confident nonsense at scale.
I submitted a package-lock.json file to the playground and got a vulnerability report after processing. The sort order next to the pie chart is weird. Medium / High / Critical / Low. I'd expect Critical / High / Medium / Low?
The vuln report ended up in my email spam folder.
I had to hit 'resend' multiple times to receive the verification email. Once I did, I had to either create a new account or login. I don't yet have a password. When I tried to create an account, it said my email was already taken. This onboarding flow seems quite janky.
Is Vulert Open Source software? I couldn't find any links or repos. What does "Join the Open-Source Security Movement" mean in this context?
I submitted two open-source tools. The submission form has a field for 'License' in which the only two options are 'Free' and 'Commercial'. Those aren't licenses. Maybe adjust that field to either say 'cost' or 'terms', or actually have a license field which lets you paste an SPDX entry (or entries) or pick a license from a list.
There certainly used to be a strong push to have internal people use the product a lot more during the development cycle. There was also a real desire to make the devel version actually usable. That fell by the wayside, sadly.
Having your developer workstation break while you have a backlog full of stuff to do, would absolutely make you less motivated to run the developer release. Especially if you're not on the desktop team.
First comment on the video - from the maker of the video - is
" FIX (worked for me): write Ubuntu ISO to USB flash with dd"
So, yeah. Okay.
(Speaking as ex-Canonical, and still Ubuntu user. I upgraded my ThinkPad 2 days before release, and it was a catastrophe I had to manually un-fudge with the help of the apt maintainer. It was a packaging problem).
My feeling on this particular release is that it was rushed out, and should probably have been kept back for a month or two. The xz and t64 (2038) issues occupied some unexpected time this cycle.
Also, there used to be a dedicated QA lab which did a whole slew of automated tests. I don't believe that still exists.
Also, also. The Ubuntu community has shrunk, which means fewer people doing QA.
Also, also, also. The guy running the desktop team left the day after the release. Read into that what you will.
Love that book. It enabled me to have one of my favourite flights of all time. Sat next to Chris Turner, chatting about his time at Acorn for about 9 hours.
Been using and contributing to (and working for) Ubuntu on everything since 2005 or so.
I still use it for everything. I don't have time or inclination to switch. However I have been somewhat convinced to take a look at Nix (packaging) for some of the tools I use. But all my existing systems are fine. So likely when I next get a work machine (next week) I'll probably (if allowed) use Nix to install anything developer related over and above the stock image and supplied packages.
Abstract: Generative AI (GAI) offers unprecedented possibilities but its
commercialization has raised concerns about transparency, reproducibility,
bias, and safety. Many "open-source" GAI models lack the necessary
components for full understanding and reproduction, and some use
restrictive licenses, a practice known as "openwashing." We propose the
Model Openness Framework (MOF), a ranked classification system that rates
machine learning models based on their completeness and openness,
following principles of open science, open source, open data, and open
access. The MOF requires specific components of the model development
lifecycle to be included and released under appropriate open licenses. This
framework aims to prevent misrepresentation of models claiming to be
open, guide researchers and developers in providing all model components
under permissive licenses, and help companies, academia, and hobbyists
identify models that can be safely adopted without restrictions. Wide
adoption of the MOF will foster a more open AI ecosystem, accelerating
research, innovation, and adoption.
I further thought about your feedback and the comments from the owner of exchangerate-API and have removed that section from the blog and mentioned it in a follow-up post.
I appreciate your comments, as they made me think more about that topic.