I remember Sega Channel. In 6th grade, my friend had it. I didn't grow up with BBSes and had only learned about the Internet the year before (from the same friend), so the idea of downloading games was pretty wild. The service was way ahead of its time.
IIRC, it was $15/mo. There was a monthly or weekly rotation of games, including some pre-releases. I think at one point we played Vectorman when it was still new in stores or possibly just prior to its official launch.
Take-home pay is indeed higher in the bay but unless already had a family, that take-home pay is worthless in what is without a doubt the most socially dull major metro in the US.
I go on way more road trips and hikes than what San Francisco ever permitted. While SF has a few good hikes, it expensive to own a car (parking, insurance, break ins, ticketing).
Seattle has access to Canada, islands, mountains, snow skiing, and boating.
It's something else that I can't easily explain. I'm a remote SWE now, and I go to a local office I'm not assigned to. Just in that tech circle, I have way more friends at work here than I did in Silicon Valley, where I saw my team and department each day in-office. I was just as friendly and outgoing in both places, and similar place in my life (married).
There are a lot of good things about living in Silicon Valley, so it's a bit annoying when people take all that for granted. I do miss being able to bike everywhere I needed in Mountain View. But I was happier after we left.
The problems are roughly:
- Monoculture
- Generally risk-averse and cliquish population whose primary concern is (understandably) survival and accumulating the money needed to live a normal middle class life and are drawn to the “peaceful” atmosphere of the region (a word you’ll hear especially frequently)
- Terrible urban planning and poor density for socialization: sprawling suburbia, lifeless downtown cores, everyone is far away from each other and as a result of the grueling commutes, few are willing to spontaneously hang out after work
It’s a toxic mix that leads to a social death spiral.
The downtown areas of Mountain View, Cupertino, San Jose, Los Altos, Saratoga, and Palo Alto are pretty lively (sorry Sunnyvale). And most of America is suburbia, but people are still friendlier there.
Bullshit. Claude 3.5 Sonnet owns the competition according to the most useful benchmark: operating a robot body in the real world. No other model comes close.
This seems incorrect. I don't need Claude 3.5 Sonnet to operate a robot body for me, and don't know anyone else who does. And general-purpose robotics is not going to be the most efficient way to have robots do many tasks ever, and certainly not in the short term.
Of course not but the task requires excellent image understanding, large context window, a mix of structured and unstructured output, high level and spatial reasoning, and a conversational layer on top.
I find it’s predictive of relative performance in other tasks I use LLMs for. Claude is the best. The only shortcoming is its peculiar verbosity.
Definitely superior to anything OpenAI has and miles beyond the “open weights” alternatives like Llama.
The problem is that it also fails on fairly simple logic puzzles that ChatGPT can do just fine.
For example, even the new 3.5 Sonnet can't solve this reliably:
> Doom Slayer needs to teleport from Phobos to Deimos. He has his pet bunny, his pet cacodemon, and a UAC scientist who tagged along. The Doom Slayer can only teleport with one of them at a time. But if he leaves the bunny and the cacodemon together alone, the bunny will eat the cacodemon. And if he leaves the cacodemon and the scientist alone, the cacodemon will eat the scientist. How should the Doom Slayer get himself and all his companions safely to Deimos?
In fact, not only its solution is wrong, but it can't figure out why it's wrong on its own if you ask it to self-check.
In contrast, GPT-4o always consistently gives the correct response.
I'm working on robots. In the long run I'm interested in dexterous manipulation for industrial or commercial tasks (e.g., assembly of products) but given the big $$$ already deployed in this space, am wondering if I can find a simpler (and faster to build!) application.
Playing with 6-axis arms but also built RoBart for fun, controlled by Claude. Would love to connect with folks to ideate on the concept of a very cheap autonomous robot (maybe with some very limited manipulation ability for e.g. opening doors). I can think of an application in the health care space already.
Footage at my web site (which badly needs a redesign lol): http://trzy.org
No wonder there is rampant age discrimination in tech. Who wants to hire older workers who want to silo at home, avoid mentoring juniors, and force teams to have video calls when the rest of the team could have met in person?
Not the author of the OP link, but we don't find any gap between senior and junior candidates (a reasonable proxy for age) on remote preference in our data set. Every subcohort is somewhere in the high 30s to low 40s, all within a few percent and well within MOE for the size of those subgroups even if you treat the sample as completely independent (which of course it is not).
None of the small LLMs are good enough yet. You could certainly build a system around local VLMs but it would require much more task specific programming baked in.
I’m certainly interested in building a product (not entirely controlled by an LLM but I see lots of utility in building interfaces with them) but not really sure what this would be useful for. Looking into some spaces now but there has to be a clear ROI to get any sort of funding for robotics.
This comment only makes sense if you are assuming a significant majority of these places are "terrible", which is baffling to me, unless you are silently using your personal preferences to define "terrible" in the context of the larger conversation.
