I make a lot of stuff using similar techniques to this guy[1]. Adding a mesh mid-print adds a good bit of structural integrity for thing pieces, and comes in handy for accessories like earrings and necklaces. Also fun to play with negative space when you start using optically interesting materials like iridescent or metallic meshes.
“Gender projects” change cultural norms, and don’t have ongoing variable costs. They just need to be funded long enough for the effects to be percolated throughout the community and become sticky.
Education projects require ongoing variable costs such as teachers, books, resources, etc. Even if the results are effective in the short term, once funding dries up for the variable costs the community can’t sustain the ongoing investment and as the parent says, all you have left are the fixed cost artifacts like schoolhouses but no funding to sustain the variable costs necessary to utilize it as a schoolhouse.
Yea, when I worked at Dominos we were charging like $2.50 for a 20 oz coke and $3.50 for a 2 liter.
Since the same 2 liter was like $1 at the grocery store, I thought we were gouging costumers and making bank on them, and figured the manager was being dramatic whenever inventory counts were off by a few.
Turned out we had a really raw deal with Coke, and were only charging like 25-50¢ more than we bought from for. And we were also required to order them from the distributor, to prevent us from stocking the cooler with cheaper ones from the grocery store.
That hasn’t stopped Tesla before. They have a track record of treating automotive-grade quality standards as optional when doing electronics sourcing[1].
As the article notes, Tesla conveniently “fixed” their thermals and durability issue that caused by inventing a feature called cabin overheat protection and marketing it as for people/animals overheating and not for the non-automotive-spec electronics in the cabin.
If you can’t bring auto quality electronics to the car, just change the car so it avoids standard auto thermal conditions ¯\_(ツ)_/¯
You can control the notifications – just go into the Managed Shared List section, and there's an area to control notifications when adding (on by default) and when completing (off by default) items.
That used to be the same mix my household used. I’d suggest giving the Reminders app a try as a drop in replacement for Notes. There’s a really handy list template in the Reminders app called Groceries. It’ll auto-group items you add to the list into categories so it’s easier to sweep through the store in one go and not have to double back repeatedly for things you overlooked further down the list.
No idea why it’s tucked into the Reminders app instead of Notes, but it’s been really handy since stumbling on it and a QoL improvement in my household over a generic Apple Notes list.
Even if it feels oddly out of place there and more appropriate for Notes, kudos to whomever on the Reminders app team advocated for and shoehorned in that featureset.
Regexes occasionally get called "black magic", and there is is an inverse of Clarke's Third Law: Any sufficiently advanced magic is indistinguishable from technology.
I think you meant “any sufficiently commoditized magic is indistinguishable from technology”, or “any sufficiently analyzed magic is indistinguishable from science.”
I am still waiting for an LLM trained to focus on effin' regexes and their variants like sed, somebody please do a page with ads for this and you will have a nice little side income and warm fuzzy feeling on top of it.
Natural language -> fully working one, I don't mean some email validators but way more complex stuff. Although, I've recently had a case which was too much even for regexes in any form or spec, then sort of grammar-based parser needed to be done from scratch.
Take a look at Tapo or Kasa devices (both TP-Link products).
I recently got a few to try out, and expressly chose them because they do motion and sound detection on device and also support microSD for local recording.
I've only had them a few weeks so can't speak to any slow-showing pain points, but so far both the video doorbell[1] and two inexpensive cameras I purchased[2][3] to test out have been awesome.
I set up an automation so they record continuously when I leave and when home to record on detection only (motion for all three and sound for the Kasa camera) to try to be economical on wearing out the SD cards. But for me personally knowing I'll likely have those go out on me and need replaced was an ok trade off for the convenience, and probably a wash financially because everything I wanted happens locally whereas I kept seeing them gated behind a subscription plan when looking at other options.
There's also an option in the app to enable them to speak stream locally to a NAS or NVR via RTSP if you want to do that with them. So I can eventually set that up for more reliability when the eventual SD burnout occurs, and scratch my tinkering itch with things like streaming it to Frigate and testing it out vs the native detection features, without any actual presasure to need to since it all just works as is.
The doorbell is what I was originally needing the continuous local recording and on-device object detection for. The two cameras were bonuses I threw in to grab a few of their inexpensive models to try out while I was at it. And so far for about $100 in total I've been impressed. Key word being so far – they're still recent enough I might be in my honeymoon phase with them and just don't know it yet.
Yeah the $30 2k camera you linked seems good, but I worry about local card storage, because if someone steals the camera you have no evidence who did it!
I wish the camera could stream to Frigate/whatever but stream empty delta frames when nothing is detected.
I don't think tabular data of any sort is a particularly good fit for LLMs at the moment. What are you trying to do with it?
If you want to answer questions like "how many students does Everglade High School have?" and you have a spreadsheet of schools where one of the columns is "number of students" I guess you could feed that into an LLM, but it doesn't feel like a great tool for the job.
I'd instead use systems like ChatGPT Code Interpreter where the LLM gets to load up that data programatically and answer questions by running code against it. Text-to-SQL systems could work well for that too.
For me personally, a lot of times it's for table augmentation purposes. Appending additional columns to a dataset, such as a cleaned/standardized version of another field, extracting a value from another field, or appending categorization attributes (sometimes pre-seeded and sometimes just giving it general direction).
Or sometimes I'll manually curate a field like that, and then ask it to generate an Excel function that can be used to produce as similar a result as possible for automated categorization in the future.
So in most cases I both want to provide it with tabular data, and also want tabular data back out. In general I've gotten decent results for these sorts of use cases, but when it falls down it's almost always addressable by tinkering with the formatting related instructions – sometimes by tweaking the input and sometimes by tweaking the instructions for the desired output.
Give it the data as separate columns. For each cell give it the row index and the data.
That way it's just working with lists but can easily key that eg all this data is in row 3, etc. Tell it to correlate data by the first value in the pair like that.
> I say "decent" because most of the available training data for Pandas does things in a naive way.
They're around the level of the median user, which is pretty bad as pandas is a big and complicated API with many different approaches available (as is base R, in case people think I'm just hating on pandas).
I've seen enough examples of an LLM misinterpreting a column or row - resulting in returning the incorrect answer to a question because it was off by one in one of the directions - that I'm nervous about trusting them for this.
JSON objects are different - there the key/value relationship is closer in the set of tokens which usually makes it more reliable.
yeah... so, you want to two step it. Parse the table into something structured, then answer the question. For a lot of LLM "problems", it's about the same as teaching a kid a multi-step problem in math - if you try to do it in one step, you are going to have a hard time .
The only reason I'm not immediately answering is because I need to check whether it's a trade secret. We do our own thing that I haven't seen anywhere else and works super well. Sorry for being mysterious, I'll try to get an OK to share.
The flap created for LASIK (and LASIK-like surgeries, such as SMILE or LASEK) heals, but doesn't have the structural integrity that occurs when the epithelium has to fully regrow like for PRK. So that flap becomes a semi-permanent weakness that can be dislocated down the road and cause problems.
In general PRK is still considered the safest laser surgery option, but trades off the long-term risk of the epitheium flap for a much longer initial post-op recovery time. With PRK you have to be careful that there's no hazing as the epithelium regrows, but once it's regrown it's as good as it ever was. So for folks with a high risk of future eye injuries, PRK tends to be preferred (or required, in some instances like the special forces).
[1] https://thangs.com/designer/kaizen3dprints