I’m a cofounder of a startup in the US. Two of us are here on green cards, but our third cofounder is based in Switzerland. He has a PhD from a top university, previously founded a company, and has raised over $30M in the past.
At what stage would it be possible for us to bring him to the US on a visa? Would it be:
- As soon as we incorporate a C Corp?
- After raising funding?
- Once we have revenue?
Are there any specific visa pathways (O-1, L-1, E-2, etc.) that would be most relevant for him, given his background?
This should be an easy O-1 and you should kick off that process after you have incorporated the company (and done a few other easy company-related things).
I went to the most prestigious high school in France. The top 2 students in my maths class shared one thing in common: they would study the curriculum the summer before.
I did it one summer, and while I was nowhere near as good as them - something magical happened: even though I hadn't understood all the concepts, my ability to understand the concepts during the class went way up. It was easier to follow what the teacher was saying since no concept was totally new to my mind.
This is why teachers told us to read the material the night before, because then you have a skeleton to work with and it’s not completely new to you. It did help, but I didn’t always do it :)
I went to math high school which was the most prestigious one in Russia at the time. Most of math class graduates would go to study math at the uni, and for the first year would be far ahead of their coursemates — but then would be hit by the sudden need to actually study the material and prepare for the exams like a wall of bricks.
I did a Software Engineering Maths module at Oxford, having barely touched maths in several years. Working through the curriculum first was incredibly useful, because in the lectures everything just melded together, and my brain was already primed
To me less boring. I used to struggle to understand new concepts as they were presented. That year though, I was able to follow what the teacher was saying "live", ask interesting questions to deepen my knowledge.
It'd be what you made it. I went back for a CS degree long after having coded for years and there were certainly things I would have had to sit around and wait for others to catch up on if I let it. But instead I always pushed myself to build much more sophisticated versions of the basic things we were learning and I also tutored, which is where it really becomes not boring, because you get to see how other people learn things in different ways, which broadens your own perspective, as well.
So basically I'm just trying to say it's up to you to make things not boring
It was like that with physics for me in high school. At ages 11-13 we learnt a bunch of stuff, which nobody except I paid any attention to, and then we had to do it all again, exactly the same stuff, for ages 14-15 to prepare for GCSEs. I was horribly bored, but at one point I was lucky enough that the teacher just gave me A-level and then early uni stuff to figure out, so that kept me busy. then first year of uni was horribly boring again, which led me to be over-confident, and didn't do much work in second year, but thankfully I managed to pick up the slack in 3rd and 4th year of uni.
There are good reasons any company Google's size should devote resources to operations research. Google is really good at the research aspects, and has used the outputs to -- in some cases dramatically -- improve its own supply chain operations.
They're claiming we can see both, because the number of people sheltered per unit of land will have increased.
While I see this as plausible in some cases, I also think it's sweeping a big error constant into "housing affordability" if we're saying that the kind of housing "affordable" to one generation is of a different kind than was realistic for the preceding generation. If your parents could afford a single family home with a yard and you can afford an apartment in a building put up where someone's single family home used to be ... surely we can agree that actual housing affordability meaningfully decreased?
I work in Big Tech. Whenever we open positions both in the Bay and in NYC, we are flooded with applications to NYC with a lot less in the Bay. A good chunk of these come from people in the Bay wanting to move out.
I've been in the Bay for a few years now. I've noticed that a lot of people I talk to don't really like it here. They like their job and the paycheck but they would move out in a heartbeat if they could. As opposed to all the folks I know who live in NYC, most of them really enjoy it.
I wonder if that has something to do with it ["it" being the article]
If you spend all your time working the Bay Area sucks. But if you enjoy the outdoors and can find a healthy work life balance, it’s amazing. Where else can you go skiing and surfing in the same day?
This has been my experience as well, although I’ve started hearing folks complain about wanting a slightly slower pace of life after living in NYC for a couple of years. Especially those who moved out of the Bay.
It won't be worth looking into, because there's nothing they (devv.ai) can do, short of trying some automated self-improvement loop a la devin where the AI writes code, evaluates the code, fixes issues as they arise... Still not worth, it's not their core business.
You're just hitting a limit of the LLMs, they won't give you bug-free code, specially not from the first time, specially not complex ones like galloping timsort.
This might be an unfair statement but it really feels like all of these blogs don't know why. They copy/paste each other (you often seem the same errors in multiple notebooks/blogs) and I have a feeling no one really deeply understands what they're doing.
Found my answer for why thanks to the issues in latest dolphin fine-tune. They do these types of fine tunes mainly to reduce refusal rates and increase intelligence. They did the knee-jerk rerun of the same old data this time, as I suspected, just for lols to see where open-source is at.
Spoiler alert, fine-tunes won't be better until the data quality is better than meta's instruction fine-tune. Give it some weeks.
Why does [doplin-l3-8B] perform substantially worse in some tests?
One additional problem with people who write breathless tutorials about doing things with AI is that they are more likely than average to have been written with ChatGPT. Which, given the knowledge cutoff for most models, is not where I'd personally turn for data on recent technical developments, but is par for the course for the kind of low-effort copy-paste bloggers doing it for attention.
This particular one seems to be from someone who is documenting their learning process, which is a valuable contribution but, obviously, not a source of great authority on the how's and why's.
I would argue that a core benefit of using Substack, beyond the easiness to write, publish, send emails, is trust for payments. I would be more reluctant at putting my credit card info in a random self hosted blog vs an established company's like Substack.
I think Stripe handles Apple Pay (edit: also Google Play, per another commenter). I'm sure there are others. I'd think that Stripe, Apple Pay, and PayPal (speaking of "dark patterns") would get you about 90% of the way there.
That may still be too high a bar for non-technical people, though.
If you wrap it into a “hosted blog” service, it could make a lot of money. You won’t get commissions on the payments without being a “platform,” but that’d be your differentiator. It wouldn’t be a VC style billion dollar business but it could make multiple $100k per year revenue. And you could scale price by number of subscribers (like newsletter providers already do) rather than percentage of payments.
That’s the case now. But a product could provide the hosting and setup for the writers. It might not attract the same VC-level returns as the platform play of Substack, but it could be profitable and steal writers from them (especially writers who already have their own form of distribution and discoverability).
I’m a cofounder of a startup in the US. Two of us are here on green cards, but our third cofounder is based in Switzerland. He has a PhD from a top university, previously founded a company, and has raised over $30M in the past.
At what stage would it be possible for us to bring him to the US on a visa? Would it be:
- As soon as we incorporate a C Corp?
- After raising funding?
- Once we have revenue?
Are there any specific visa pathways (O-1, L-1, E-2, etc.) that would be most relevant for him, given his background?
Appreciate any guidance on this!