If they have custromer feedback and focus groups like they mention how did it happen in the first place? Some overoptimistic head-of-something? Really curious. I own previous -2021 mb and had to drive the upgrade (touch buttons) once as a replacement car. UX is terrible. Period. I even checked then in the dealership what they did to S-class and mybachs - and yes, same crappy wheel, etc. Anyways, I was mostly surprised that they didn’t know this before. Something is wrong with their research / decision making.
Can it be also related to demand not catching up or even declining? If place is in high demand and prices go down shouldn't it cause even more people coming to it (compensating for a possible price change). (Note: not an expert on this, I'm just curious how it really works - besides obvious thing: more supply -> price goes down).
Seems to be a duplicate with this Show HN authors made: https://news.ycombinator.com/item?id=46290617 . Let's please merge this if someone from the moderators team can do that. Thanks!
Probably people at some point were making same arguments about ASM and C. How many people though do ASM these days? Not arguing that for now it is relevant point, obviously Rust / C are way faster.
This is probably the right solution. It seems in reality nobody does this since it is expensive (more teachers, real attention to students, etc). Also if there is an explicit split there will be groups of people who "game" it (spend disproportional amount of time to "train" their kids vs actual natural talent - not sure if this is good or bad).
So, it feels to me ideally within the same classroom there should be a natural way to work on your own pace at your own level. Is it possible? Have no idea - seems not, again primarily because it requires a completely different skillset and attention from teachers.
To be fair. I live at Mission Bay (SF) that has Caltrain railway nearby (and you have to cross it if you take particular ways in/out). I drive (and like it a lot!) Waymo. Waymo avoids crossing it (it takes a longer way to drive a bridge). So, they probably realized the risk and still to this are not willing taking it.
It compiles human prompt into some intermediate code (in this case Python). Probably initial version of CPython was not perfect at all, and engineers were also terrified. If we are lucky this new "compiler" will be becoming better and better, more efficient. Never perfect, but people will be paying the same price they are already paying for not dealing directly with ASM.
The idea is that it doesn't store binary files locally, just pointers in the DB + meta data (SQLite if you run locally, open source). So, it's versioning, structuring of datasets, etc by "references" if you wish.
(that's is different from let's say DVC - that does copy files into a local cache, always)
Since it's developed in UCLA - do they have resources to do the next phases of trials (humans, etc)? I wonder if in such cases pharma (those who obviously have enough money) care about these molecules at all? Since they probably can't put a patent on it and heavily monetize it later. Are there examples of drugs that were developed like this successfully?
Good to see this project on the front page! We are using Vega (specifically Vega-Lite [1] as an engine and templates spec for data-science plots / visualizations in DVC (e.g. how it looks like in VSCode extension [2]).
It allowed us to have:
- same engine in CLI (can generate HTML and open in browser), VSCode extensions, SaaS
- have a way to describe plot visualization / representation as a declarative spec that can be then used in all those products (plot spec). We were exploring plotly and AFAIU there was no easy way to do the same
- it's quite comprehensive and community is responsive, the project is maintained
To name a few downsides from our experience:
- DSL is quite complicated. It requires some time to master it. It hurts the adoption. In our case I don't see that many users doing custom plots / templates - majority is using pre-baked built-in stuff or use Python and export as SVG.
- In our case some features were missing (and are still missing) - exponential average - that is most commonly used to smooth ML training curves.
Hey, congrats! Are you competing / is there some overlap / what are the key differences with Roe AI (YC W24) - roe.ai (just launched recently on HN https://news.ycombinator.com/item?id=41202694 as well).