persedes

I was looking into Herdr too, but could not bring myself to switch away from tmux yet (there are a couple of shortcuts that I have in my workflow, which I can't config in Herdr). What I ended up doing was to use the tmux agent sidebar, which, with mouse support, I think does a lot of the same things already.

I'm not in the space, but I'd think that the reputational damage alone is the more significant part here.

They're providing the training data for free too. I'd think there's mutual interest there.

100%. Looks like they're using pangram (hope they're getting that for free...) which also flags stuff like Grammarly. That one's an interesting gray zone to me that I've not thought off before. LLMs whales doing the heavy lifting is one thing, but small edit tools like grammarly that "improve" your phrasing are likely a massive algea like contributor to what is out there too.

It's 0x0000000000000000000....4, but no, just good ol' human failure (and a bunch of extra f-ups along the way)

Nice to see TissUse getting a shout out :)

  the FDA wanted data from organs-on-a-chip or some comparable alternative. 

This is the main takeaway from the article imho and great news! ~15 years ago those systems were were not very interesting for pharma companies (bayer used to have a campus a few s-bahn stops away) due to regulators requiring animal tests over those systems.

I think businesses are footing the majority of that bill right now due to regulatory requirements, but for individuals that price increase is def coming. Maybe I'm too pessimistic, but enjoy it while it lasts :')

Hah second the AI part. Started a home assistant setup years ago to setup water leak sensors with alerts to my phone, but didn't feel comfortable enough having home assistant accessible from the web, so besides writing brittle yaml files now also had to deal with open VPN etc etc and after major update my config files were incompatible and with kids just didn't get back to it.

However this week spent an hour with claude to migrate to tailscale, latest home assistant update, sensor setup and filtering for my rtl433 antenna, connected hue lights while we're at it, migrated to latest pihole version and put everything in git in one nice compose file with a step by step instruction on how everything was setup and which account sign ups were needed. I still checked every step and manually approved stuff, but the remote session feature made this easy to finish.

Trying to map this observation to code and appreciate them starting with very simple examples (that Astra screw-fixed into lean.) But in a simplified way this is close to promting the model to create a set with the members 1,2,1,5 and it correctly creates {1,2,5} in code. So The initial "proof" / instruction was wrong and it silently fixed that. ( Which is one of the failure modes they're describing)

Or just for the token usage. The rug pull is coming eventually

That's wishful thinking, I know, but would love a breakdown of those metrics into what actually goes into AI inference, training versus just TikTok / YouTube streaming, or just a Google search...To have some perspective. My hypothesis that prolonged video streaming might contribute similarly to AI usage? (But CDN etc might make that tricky to calculate...)