Fuck off with classifying persons and putting yourself in predefined drawer.
Let people be people no matter what age, believes or sexual orientation.
Fuck off with classifying persons and putting yourself in predefined drawer.
Let people be people no matter what age, believes or sexual orientation.
Classifying aviation-related posts on Hacker News with SLMs
https://www.skysight.inc/blog/hacker-news-aviation
#HackerNews #Classifying #aviation-related #posts #on #Hacker #News #with #SLMs #aviation #machinelearning #hackernews #SLMs #technology
An analysis of 40+ million Hacker News posts reveals that 0.62% are aviation-related, with the percentage steadily increasing over time. Using small language models, we classified 10.7B tokens of content to discover aviation's surprising popularity among technologists.
(19/N) Let's now turn to the third question of the #ThreatModelingManifesto:
3. What are you going to do about it?
It pays to first establish a few contraints for what you can do, in theory, by #classifying your #assets. Again, for an individual human being, opposed to organizations or companies, it's nearly impossible to impose principles like #ZeroTrust or #NeedToKnow on personal relationships, the closer they get.
So, avoid recycling terms from popular, but less intuitive schemes: Fanciful intelligence labels like “top secret”, “confidential”, or “unclassified” do not tell you what goes into the respective box, and how to handle access to it.
Add another column to your assets spreadsheet, label it "Classification", and pick a more human-centered approach for its values, like:
Let's briefly go through these suggestions:
For Your Eyes Only (FYEO)
Assets that are only accessible to, and controlled by nobody but you, because they need to be resilient, even in the face of the closest of your close people misbehaving. Preferably, these assets are kept publicly undetectable and unknown. When you are gone, these assets will be gone, too. FYEO does not make a good default class, though.
Start of this thread:
https://mastodon.de/@tuxwise/113503228291818865
(1/N) With more challenging times ahead, the #4Ds will become more important, too: ✋ **Defend** your boundaries: know what matters to you, and properly safeguard it – instead of being an alert-driven option tinkerer. 🪪 **Define** yourself: use multiple identities that focus on a single purpose each – instead of having everything you do, have and think linked back directly to you. 👑 **Decide** like a sovereign: get to know your needs, and what meets them best – instead of sacrificing them to the interests of others. 🌐 **Dwell** the space: seek community, practice solidarity and citizenship – instead of being beaten a little later than others, in a glorious bunker. In the future, I'll post a few ideas and suggestions based on the 4Ds. BTW, I have dropped the adjective "#digital" from my vocabulary. There is no more separate "digital sphere" or "cyberspace" that wasn't part of our everyday lives. #privacy #security #anonymity
The approach they used for #classifying the poems' function in the narrative were interesting, using #LLMs. Performance is pretty bad so far. Keli took up the call for #openness about #failure from a session this morning and showed that the different models are bad in different ways, which allowed the team (and us) to learn something about the models. I think that's great and valuable!
'Principled Out-of-Distribution Detection via Multiple Testing', by Akshayaa Magesh, Venugopal V. Veeravalli, Anirban Roy, Susmit Jha.
http://jmlr.org/papers/v24/23-0838.html
#detecting #distribution #classifying
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods
Tiago Salvador, Kilian FATRAS, Ioannis Mitliagkas, Adam M Oberman
Action editor: Mingsheng Long.