Looking at only what you presented, it seems like Endothermic/Homeothermic share a lot of overlap (hot blooded) and Ectothermic/Poikilothermic share a lot of overlap (cold blooded)?
I think endo/ecto are mechanisms and homeo/poikilo are results. They mostly match up (why spend all that energy generating body heat if you're not going to use it to maintain a constant maximally-biochemically-effective temperature?) but not 100%. An ectothermic-homeothermic animal would have to put more effort into using the environment to maintain a constant body temperature. Google says there are some lizards in that category.
We offer a no data retention option for all teams. If a business wants to try us out for free I’m happy to set something up.
We also offer our application self-hosted/on-premise/cloud-premise. We have single-tenant (separate data) options as well. These options have a higher deployment cost so they may not make sense for teams under 10.
It would be sort of workable on my country. Where it would be something like:
> dot snabela dot at punktum at
“Snabela” (maybe its snabel-a or snabel a) means “trunk a” trunk as in an elephant’s trunk.
Punktum is just the Danish word for period.
Now I’m really regretting not getting a domain to utilise this fact, as I’ll only ever say my email out loud within my own country, and it would be hilarious to have a way that’s just as messed up as the authors. I guess it’s not too late.
I look back at the leopard to snow leopard upgrade with incredible fondness. 2 years worth of work. "Zero new features": improved performance, better cpu + memory usage.
Probably the only stuff people Hacker News care for.
Yeah, me too. I was just randomly giving a Macbook Pro for work once, and it had Snow Leopard on it. I didn't know anything about OSX or why versions were named after animals.
I definitely that I liked each subsequent version less.
I remember my mom taking my White iBook G3 to the repair store and them upgrading me from Panther to Leopard in 2010. Completely blew my mind and I'm still in love with the UI.
Migrated from Auth0 to Firebase because it was 2 orders of magnitude cheaper.
After explaining that we didn't need any fancy features, just OIDC+SAML sign-in they proposed a number that was a little over $1/user/month ($30,000 a year for 2500 seats). This was after multiple rounds of back-and-forth, sitting through custom decks and sales pitches around "you aren't paying for SSO, you are paying for an increase in conversion and revenue".
Firebase is self serve for ... $0.015/user/month (or $450/year for the same 2500 seats)
Instead of pure code try seeing it as a book. If I read a book with a lot of spelling/grammar errors, a story that goes nowhere, characters that aren't interesting to me, plots that make no sense, etc..., then I'd tend to think of it as a not well written. Same with code, if variable names are obscure, function names don't match what they actually do, needless abstractions, nonexistent documentation, no tests, etc..., then I'd tend to think of it as a not well written project. Those aren't the only things I look for, but that's a start for me.
One could also argue, "why does it matter how it's written, it's not a book and it does what I need to do so that's fine." If it works and you don't have to do anything, great. If you have to troubleshoot it because it broke, then hopefully the code is structured in a way that lends itself to debugging. Otherwise, you might end up having a bad time.
For myself I'd say the lodash repo is well written. Would you agree/disagree?
My impression from when I read a big chunk of the React codebase to confirm some suspicions about how they'd implemented hooks ("wait, if that's how these behave, does that mean they... no, surely they didn't... well, yep, that's exactly what they did") was that it had more layers of abstraction than would be ideal and was a bit under-commented, but not awful.
I've been considering a Garmin InReach Mini, its roughly $350 for the device and roughly $300 for a satellite subscription for 2 years. This iPhone ... is quite compelling in the face of that.
Assuming you use case is to press an emergency button which shares your location with a dispatcher and nothing else which this seems to be for now. You apparently can’t text family to say you’re running late etc.
My read of the marketing materials is that it supports the "Find My" feature which you can use to share locations with friends/family?
This is really a killer feature for me as an outdoor enthusiast who hangs out in places with no reception every other weekend. I'm also a weight weenie and really care about how heavy the stuff I carry is. I'm going to keep an eye on how well this works in the field for sure.
I've been considering a Garmin InReach Mini, its roughly $350 for the device and $300 for a satellite subscription for 2 years.
If the satellite messing works well, this phone just added $650 worth of value for me on top of a regular iPhone. Basically, it doesn't matter how much a continued subscription will cost after year two. I'd be completely happy to buy a new phone in two years just for this one feature.
Good thing, what the hell does that mean? Good for what purpose?
Obviously they don't deny it because it's true, that's not my point. My point is that even being true, their first concern could be their customers, but it's not because they're scumbags.
I'm on the team at Sapling Intelligence, a deep-learning AI Writing Assistant. A lot of privacy and security conscious folks don't like the idea of a keylogger, so we have self-hosted/on-premise/cloud-premise options for businesses. We have a list of available offerings here: https://sapling.ai/comparison/onprem. Sapling deployments can also be configured for no data retention, sacrificing some model customization.
Cost-wise, it doesn't make sense for individuals to host a neural-network based grammar checker, though some of the rule-based options may work. There's a future where if we can maintain some sort of Moore's law scaling we will be able to run these language models on individual computers as opposed to the cloud.
> Cost-wise, it doesn't make sense for individuals to host a neural-network based grammar checker
Why?
We already do the same in the photography world in the form of apps like Topaz Labs' denoise/sharpen/gigapixel, as well as video enhance. Why would I care how many gigs of disk space and even a GPU might be required for an NN grammar checker if it literally makes back the money by improving the writing that influences my career? Hell, I can expense what is needed to run this if the payoff to my company is "the quality of work is better, and more secure".
Well, I think you'd first have to know the resource requirements, and it's reasonable that so few people would be willing/capable of running it that it doesn't make much business sense to focus on that as an option.
I'm not an expert and would appreciate being corrected if I'm wrong, but I'm under the impression using a neural network after it has been trained typically requires relatively little computation and data. It's training it that takes the big compute and requires lots of data.
I think many services like Grammarly would be perfectly possible to implement without sending your data off device. There are just massive incentives not to.
Not really, that's an assumption based on a misunderstanding about how NN actually work.
While the training (e.g. the part necessary in order to even have a product) is incredibly resource intensive, and will yield a model that's typically hundreds of megabytes, actually applying the resultant model to new data takes milliseconds at most for plain text analysis.
