There's also https://github.com/ankane/strong_migrations for Ruby

The checks/explanations are fairly simple and straightforward so it also makes a good reference regardless of whether you're using the library

I think you could automate this with 2 transactions

- connection A, lock timeout=0, acquire unwanted lock

- connection B, lock timeout=0, run migration

- collection A, rollback

Then connection B will fail if it tries to acquire an undesirable lock since it will conflict with A. You'd be adding a very small window when you're actually holding the undesirable lock, though

This is essentially how my tool discovers locks for a given arbitrary DDL statement.

Personally, a combination of low tech and semi scientific tests based on what you normally do (redo the same task you used an older model for with a newer one).

So far, Simon Willison's pelican bike "benchmark" is the only one I've found that shows Fable 5.1 beating Opus 5.5. My personal experience has been Opus is unusable on design work it's so terrible. Evaluating whether we should consolidate AWS DMS tasks (Postgres full load and change data capture) into fewer tasks with more tables, Opus 5.5 was factually wrong and needed correction roughly every other turn.

On a "help me find a sandbox solution for agents embedded in a web app to run untrusted code" research project it kept misrepresenting security boundaries and ended up recommending DuckDB which ironically specifically says it does not provide a strong security boundary in its own documentation. GPT 6 (can't remember if it was Sol or Astra) and Fable 5.1 both recommended FaaS like Cloudflare Workers and AWS Lambda which fit fairly well with the requirements.

I switched from Opus to Fable in the session going badly sideways and told it to "Review the previous conversation and come up with a correct comparison table and corrected recommendations grounded in objectivity supported by citations. Do research as necessary to understand the current ecosystem" and that was a full 180 back to coherency...

>What was hard there was to train the model head without ML expertise, and considerable amount of data

Which has become a lot easier the big, expensive general purpose LLMs

Some of the use cases seem interesting but a lot of them also seem like the "old" stuff can do it faster/cheaper

For the privacy use case, there's Stanford NER and wrappers around it. That is likely cheaper and faster than Jev (it'll run on CPU)

JSON or XML in with json schema for the response?

https://developers.openai.com/api/docs/guides/structured-out...

Not an ML guy so maybe missing something important here. It seems like many use cases could be covered by even dumber, simpler models created with the aide of general purpose LLMs.

Like, can't I just tell Claude or GPT to help me create a BERT or <insert old boring ML framework model> that's even cheaper and faster?

For instance, Frigate runs 4.6mb yolov9 image object detector on a $50 USB Coral stick. It takes like 1-2 watts of power, responds in 15ms, and is completely local. A pay-per-token cloud hosted not-really-an-LLM-but-probably-based-on-one that runs in 150+ ms still seems terribly inefficient.

Zigbee, Zwave, and Bluetooth (although a bit to a lesser extent) are easy mode of you want local only. They're not IP-based networks so no Internet access to begin with.

Bluetooth--local only but setup can be a bit trickier since they don't automatically form a mesh. You may need to configure relays if your existing devices have that capability or buy dedicated relays

My switches go up and down just like they always did. I can also toggle them from the app (ok so sometimes the switch is up and the thing is off but multi-way switches have been like that forever), track their on/off state, and use them as event sources to do other things.

There is a single magic switch that does "extra" stuff and that one's in the master bedroom. All of them except that one fail open and continue working like regular switches if Home Assistant is unavailable.

The livingroom has a Shelly dimmer that replaced an analogue dimmer and it also turns 2 lamps on and off.

The basement switch was wired to a single bulb and it triggers an event that powers all the smart bulbs in lamp holders spliced into arbitrary circuits on and off so all the basement lights work with the existing switch instead of just the 1 physically wired to it.

I think there's plenty of dumb things you can do with smart home tech but there's also tons of subtle and convenient enhancements as well. Phone alarm emits an event that opens the curtains and turns on a lamp is also a nice one.

Having a dashboard that shows whether (many) things are on or off and their power consumption is super handy. Dropping an Emporia circuit power monitor widget in the dashboard shows if the washer and dryer are running (a little bit of power, a lot of power, a lot of power + a little bit more power)

>I don't know if bragging about being AI-native is something any of us should be doing

Me neither but we now have a likert scale on our performance review for it...