replit employee here. the team who built this is very small (less than a dozen, including non-eng roles for the go to market), and went from idea to general availability in 8 weeks
iirc the team managed to bring it to a lever an order of magnitude lower than off-the-shelf models
I think it's also a bit scary, because 8 weeks is very little time for testing, tuning, and validation of something as opaque as a machine learning model. If it worked right the first time, that's great. But there is still a lot of inherent uncertainty in ML projects. Decision makers need to take that uncertainty into account when planning.
That, or, the 8 weeks only covers the final training runs and the implementation/deployment, and doesn't include time spent developing and tuning proof-of-concept prototype models.
https://intuitiveexplanations.com/tech/replit/
Looks like this CEO isn't of good character after all. He looks almost like a jerk when looking at the end of the story. Even in his last email he tried to get his (obviously wrong) point. He never apologized for the things that mattered most, only tried to extinguish the social media fire all in all.
Also he doesn't look very smart, imho:
Big LOL here! The abstract things are the simplest, yeah! That's why progress in something like math or theoretical physics is made by the dumbest people, in contrast to something like sociology where you need genius level of intelligence to come up with some new ideas. Sure, sure.
But that's of course not everything this dude got completely backwards.
Would explain why replit is the most useless of all the online IDEs: It has no direction, no true value proposition. It's not a good cloud coding environment. It never was a good code snippet playground (actually one of the worsts). Now they even require accounts, so the quick code snippet aspect is also gone. Also they badly positioned in the education space…
Of course I wish them luck!
But I guess they have no chance against something like Gitpod, Github, or OpenShift codespaces, which are light-years ahead.
OK, maybe the exit-strategy is "just" to be visible enough that at some point they get bought by one of the above. (Which doesn't look like the most ethical thing to do ;-)).
I feel like, if there's ANYTHING we have learned in the past decade or two it's that people who defend a company tend to be doing so for the wrong reasons. See Sony or Microsoft, or Apple or Android, etc. Defending a company is just weird.
I look at replit as a tool, run by people. The tool might be cool, but the CEO made a bad decision and now I judge the product on that CEOs actions. There's no definitive time frame or action that just magically makes it better.
But in general, I'll stop thinking about the stupid actions of the CEO when my brain stops reminding me "Oh, no matter how cool this is, the actions of the CEO were incredibly poor." When will that be? No idea, but maybe sometime down the road he does enough good things that I will suddenly stop and think "cool, looking back, he's done enough good that I can probably forget about the poor decision he made and start looking at this again, because he's proven he isn't that one stupid action."
Goodwill is earned, it's not simply given. It's often hard won, but incredibly easy to lose.
Google => when will they cancel this?
Meta => metaverse what a joke
Etc...
We do it every day, whether we realize it or not. As a people we should support the companies that do good, and we should be aware of the companies doing bad. There's room for grey in there, it's not a one size fits all. But if you aren't aware of the bad then you aren't informed in your decision making.
If it bothers you, sorry. But I see it as a pro. I had a really bad experience with Remarkable, every time it comes up, I point out my experience so that others who might be making their own decision can use my experience in their decision making. When a company performs poorly. I guess by the metric you've provided above, this would be a low effort comment by your definition.
To me (programmer in Sweden) the largest single team I've been on was 14 people and that was _very_ large (indeed the largest in the tech department). We actually broke ourselves up into two more informal groups since we thought that was a more manageable team size.
can i get a clarification - when it says "in-browser" i hear "on-device" as in it doesnt call back to replit to get the predictions. i assume that's inaccurate?
for cost/compute purposes i'm wondering how small models have to get in order to run "truly in browser"