This is amazing. While it might seem like llms are “taking away math jobs”, my perspective is that it will allow mathematicians to be much more productive.
One way to think about research is that the space of unknowns is absolutely enormous. Researchers are human and they can only focus on discovering a small part of it. There just aren’t enough people doing research! LLMs will make the existing people a lot more productive, but the space is still huuuuuge!
If you have more than a 100 linux machines you certainly need someone who knows linux to support them. You can either hire a team to do this or hire someone who will manage a support contract with suse/ubuntu/red hat etc.
I don’t believe this is true. There are plenty of roles that are happy to hire remotely. Sure, there is an in person requirement for many job listings but Ive found EMs/companies to be very flexible if they need to hire talent.
For people that can’t/dont want to move to the “hubs”, just know that there is absolutely still a career path. I will say though that you need to have above average communication skills and proactively build relationships during in person off-sites.
There absolutely are remote first roles in the US, but the competition is also extremely intense. The median SWE and HNer wouldn't make the cut.
It also requires a level of maturity, clear thinking, self-starterness, and independence that is hard to come by without a proven track record and experience.
My advice is for the median/average SWE and HNer, not for the truly exceptional.
Spending a 7-10 years in a hub and then going remote first is the best path because you build the network you need to get referrals to vouch for you as a remote-first hire well as the track record needed to go remote-first.
7-10 years is too much. 2-4 is around the range I would give.
Its also nothing new; new grads gravitated towards these hubs anyway. Previously, they would settle down in the burbs. Now they're migrating anywhere in the US.
Thunderbolt would presumably make it much more expensive, the spec has a ton of USB features that go from “optional” to “required” to be able to go into TBT alt mode, like supporting active cables
You’re thinking along similar lines as I am. The article talks about “visibility” in the end. This might be a document that is written. Or it could be a demo thats shared. Or a simple shout out in slack.
As engineers, we tend to keep away from the limelight and quietly get shit done and be happy with it. But professional growth and recognition requires visibility somehow. We need to be creative on how to achieve that.
I use Sequelize at work and have used drizzle for a few personal projects and I can say that I really like the following:
- Native TS integration
- The migrations system is wonderful
- The API is more intuitive, imo.
I think it comes down to personal preference to use any/none of these tools, but I liked it enough to donate some space cash to the project.
I don’t use this specific orm but orms in general are trying to solve a very hard problem and as such there are a lot of ways to mess it up. If you can be the least bad at it and create slightly less dumpster fires than everyone else that’s a huge thing
Does Anthropic have standing to sue to Government for libel? I don’t think the Government is allowed to arbitrarily designate a company a supply chain risk without good cause.
13%!!! This should be a code red level event for … the world? I … don’t understand how world leaders are just standing by? Smartphone growth/adoption has been the bedrock of a LOT of economic growth. I would have expected massive Government intervention to avoid this.
Where are the China hawks? The argument for protecting Taiwan was that without their chips the smartphone market would contract, right? Thats whats happening now?!
Hard disagree with this take. Mass adoption of any technology is almost always a good thing; the more people are looking at the sane problem, the more clever/elegant/innovative solutions come out of it.
Im also not sure if “vibe coding” did not have a phase where early adopters were mucking around? I saw the early versions of gpt much earlier than chatgpt and a lot of folks were using transformers for coding before claude.
One way to think about research is that the space of unknowns is absolutely enormous. Researchers are human and they can only focus on discovering a small part of it. There just aren’t enough people doing research! LLMs will make the existing people a lot more productive, but the space is still huuuuuge!
reply