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It's pointless to listen to health advice from anyone who used performance enhancing drugs. The improvements for him came from the drugs

It's going to follow the path that the internet took. At the beginning of the internet, most pages were created by individuals. Even company web sites were normally created by a small team. You could trust the information. Then the ad networks started along with SEO and content marketing.

Right now you can relatively trust LLM results but then people will find a way to manipulate the output and ads will get inserted and trust will be lost.

True, there may be complications if you travel to Japan from a 3rd country. It might be something they are aware of. I imagine most trips are directly from the other country of citizenship/residence.

I've wondering if a potential leading indicator for AGI could be a large drop off in open positions from a frontier lab.

Let's see, throughout US history at times it's been: British, Irish, Italians, Mexicans, Hispanics, Blacks, Japanese, Chinese, Vietnamese, Jews, Muslims, Russians, Venezuelans, Cubans, Haitians...

I lived in Japan and know many people in this situation. Most people just never tell the government and keep both. There's no proactive outreach by the government for these cases and it's ok unless you happen to mess up and produce your foreign passport when entering Japan instead of your Japanese passport. It's a "don't ask, don't tell situation".

There was a lawyer, originally from Japan, living in the US who did try to force clarity on this issue and sued the Japanese government. Unfortunately she lost so the status quo remains. https://www.asahi.com/ajw/articles/15077494

I agree with you but we've seen that many people will just blame the immigrants. It's easier to blame change that you can visibly see rather than change that is forced to happen due to abstract demographic trends. No one has a good solution for this. If immigration gets too high, citizens will vote for parties that support anti-immigrant policies to bring it back in line.

Doesn't it mostly stem from demographics? Developed countries are experiencing lower natural population growth so some have tried to make that up with immigration. Our economy and centralized fiscal policies generally assume a growing population. Without that, there's little that can be done. Automation can be used to increase productivity but that also faces a backlash from people worried about their jobs. People will blame the problems on politicians but the problem is beyond them.

They allow it until the kids are 19. Then they are supposed to make a decision about which one they want to keep.

The guy had a failed startup and somehow leveraged that into the situation today.

You shouldn't always optimize for the long term. You should optimize for the reality of the environment that you're in. In large, public companies, that usually means looking ahead normally 1-2 quarters unless there are exceptional projects with leadership buy-in.

Unless you're working on the absolute cutting-edge, you don't need every member of the team to be at the top of their game. It's happened many times in sports that a team full of too many superstars underachieves.

Look at the President and the US government. This is society now.

It's attacking civilians that's controversial.

This sounds a lot like what some lazy people will say "I could be a doctor/astronaut/millionaire/movie star. I just don't want to"

Also, the one person listed in the Organization Members works at Google as a Developer Advocate.

Unless you're hiring for rare roles that require niche skills, it's unlikely that you'll get people that are in overlapping networks. If you do, you might be encountering the problem where Company A has a bunch of people that used to work at Company B. Now Company A is just an "old boys club" from Company B and is biased towards their old colleagues.

If you ask for single referrals, how do you combat the problem of people just recommended people based on friendships and not actually work quality?

Imagine you have a coin-flipping tournament with a large number of people - perhaps even billions. 2 people face off in rounds and the winner advances. By the end someone will have won all their rounds. Is this person skilled or lucky?

I don't understand why tech companies are so reluctant to go back to in-person interviews. This used to be the norm before COVID and it would solve most of these issues. It's also ironic that the authors are from Microsoft/Amazon and Meta which have very structured interviews that tend to be about just hitting the right keywords during the interview itself. None of these places even really care about what you've done previously, for better or worse.

He's basically said as much directly. I think it was in his book that he would like to get back to research at some point in the future. If he had things his way, AI would still not be public and would be used for advancing science only. Then there'd be no competitive interests pulling them into consumer products.

R&D is hit or miss. And a lot will miss. It's really no different from the VC model where 90% of their startups will fail but the 10% that succeed will make up for the rest.

Pointing out a few examples that didn't go anywhere is a meaningless argument. You need to look at it holistically.

Why would you want to ruin morale for no reason?

I track my time even though I don't have clients. I find it helps me say "ok this next block is for this task" and it helps me keep focus.

If you're being treated poorly and it's causing you stress, leave.

It's going to take time to earn trust from peers and your manager to start getting more meatier work. If you're early career, I think 2 years is a good guideline. Many places hiring someone for their second job will expect you to be leaving your first job around 2-ish years. 2 years gives you the chance to take on larger projects and see the results of your work and get feedback about things you've pushed to production.

You probably shouldn't stay at your first job more than 3 or 4 years. The second job change is the hardest. It's when you realize that different companies do and value things differently. Staying too long at your first job will make it tougher to adjust. It's also good to get exposure to new ways of working while you're still agile enough to soak it up.

If you've left more than 2 or 3 jobs within 2 years it starts to look like a red flag.

Never waste the opportunity a good crisis presents

You can only tell which part of the S-Curve you're on in retrospect. It's not something you can tell while you're experiencing it. Both scenarios of AI maxing out or continuing to improve are both likely.

I think this is it. I'm a general software engineer and would like to switch to being in this field but something like this is just way over my head. It sounds like a great innovation but I'm lacking the domain knowledge to fully understand it. I've spent several months going through online courses to basically get to a Biology 101 understanding. Getting to the level of understanding something like this seems like it would be a multi-year effort and I don't really know what's the best way to proceed.

It's pretty easy to lose 5 pounds. You need a total caloric deficit of about 17500 kcal over a certain period of time. There are plenty of caloric counting apps that are a few dollars/per month. Why would this be worth $100?

You're saying though that it can be done in one week without eating any protein and somehow you'll maintain muscle mass from taking a supplement of acai berry. Most of that weight loss is going to be water weight and glycogen, not fat. It seems dubious. All weight loss plans basically end up being "eat less calories that your body uses". There's no way around that.

You say the meal plan is 1800 calories. If you have a petite woman doing this, her caloric outake may be around that. Consuming 1800 calories for her is not going to do anything.

> this is actually a great video overview of how LLM works and the tokenization part

Did you mean to link to the video? I would be interested.

I was expecting legit questions. These are just rude

That was a time when the latest arms technology could be obtained both by normal citizens and the government. Do you think that today an armed population could repel a determined federal government?