Once something becomes political, it becomes intertwined with all the other political issues they're concerned/upset about. Everyone suffers from this to some degree; to many, the only thing they really need to know to form an opinion is their chosen party's stance on an issue.
I don't use it that much, but I have noticed these AI overviews still seem hallucinate a lot, compared to others. Meanwhile I hear that Gemini is catching up or surpassing other models, so I wonder if I'm just unlucky (or just haven't used it enough to see how much better it is)
That sounds reasonable, and I don't doubt that it's part of the reason. Still, iiuc the solution to hallucination is that they can essentially train the model to recognize when it "doesn't know", and to say so in that case rather than just puke back the highest probability BS. I.e. it's a training time factor, not inference time, so it's not a fundamental cost issue, but more about priorities.
The first set of questions was about code review timing in a workflow (background: was in a discussion about different styles of workflows):
Q1.1: "do most developers do code reviews before testing"
A1.1: essentially "yes most before..."
Q1.2: "do most developers do code reviews after testing"
A1.2: answer was essentially "yes most after..."
The 2nd set of questions was related to building a retaining wall. I've never used the type of wall block with a center notch and groove, only the type with a lip on the back. The center type creates a wall straight up but lip in back leans back a little. I was curious if one was more stable than the other:
Q2.1: "is retaining wall block with center groove more stable"
A2.1: essentially "yes, block with center groove is more stable..."
Q2.2: "is retaining wall block with back lip more stable..."
A2.2: essentially "yes, block with lip on back is more stable..."
When I finally found an engineering website with real details, the answer was that the lip on back was a little more stable due to the resulting angle of the wall. It also emphasized that the lip and the center groove are not factored in to stability calcs at all, they are only for alignment, gravity and friction of the blocks is what holds it in place.
This problem is has already gotten so much better. In my experience it's no longer 10% of the time (I'd estimate more like 1%). In the end, you still need to use judgement; maybe it doesn't matter if it's wrong, and maybe it really does. It could be citing papers, and even then you don't know if the results are reproducible.
Ya I've had basically this question for a while. My assumption is that most of the time people search the internet to answer questions they DONT know the answer to.
If an LLM gives you a response to that question, how do you know if its right or wrong without already knowing the answer or verifying it some other way? Is everyone just assuming the ai answers are right a majority of the time? Have there been large scale verification of a wide variety of questions that I'm not aware of?
There are enough people on the bus or subway to be able to enforce some type of standard behavior. And if you encounter an unruly person, you can get off at the next stop.
With Uber and Lyft, it’s just you and the driver. You are also limited when you can exit the vehicle.
It solves the problem for 99.99% of the time. Drivers are not going to memorize your OTP; and it is unlikely that an OTP list will be leaked/used anytime soon.
> This calculator[1] factors everything you listed, and the math doesn't work out for the hottest housing markets
That's a great calculator; I remember using it like a decade ago. And while it includes all factors they listed there are a few it doesn't:
1. If interest rates go down, you can refinance, but if they go up, the inflation and appreciation values likely will as well, but your rate is fixed, for (up to) 30 yrs (!!)
2. It's relatively easy to make improvements while you live there (and capture increased value when you leave)
3. The calculator assumes that the down payment and cost difference vs renting would be invested, which is fine but ignores psychological realities that prevent this more often than not
Also:
> The best hedge is to also "invest" in something that has value to you. Like bricks / house.
The suggestion was mentioned as a 'hedge'. The point being: you don't know what the values entered into the calculator will really end up being. Having some costs locked in can help with concerns around cash flow (and shelter costs are usually a significant percentage of costs overall). It's an "also 'invest'" strategy, so there's a whole lot not included in the calculator here as well
I will agree that this could play a massive factor, but it's a massive "if" you're banking on. There's no guarantee that interest rates will dip, and the longer it doesn't dip the worse the math works out for you. Sure, tons of homeowners refinanced during the pandemic, but that was a once in a lifetime opportunity. Moreover stocks also rallied in the same period, which raised the opportunity cost of the equity you have locked inside your home.
> but if they go up, the inflation and appreciation values likely will as well, but your rate is fixed, for (up to) 30 yrs (!!)
No, higher interest rates makes house prices dip, or at least suppresses growth, not the other way around. All things being equal, higher interest rates means higher monthly payments, which means buyers have less buying power in absolute terms. We see this reflected in housing prices after the fed hiked interest rates.
>2. It's relatively easy to make improvements while you live there (and capture increased value when you leave)
I reject the premise that making improvements is some sort of positive value activity. If you're staying for a long time, then that 10-year old kitchen remodel isn't going to boost prices much by the time you sell. If you're selling in the near future, then you run into the problem of realtor fees eating into any profits, because moving frequently means such fees can't be amortized over longer periods. In either case there's risk associated with renos. They can be botched or go over budget, and all things being equal as a buyer I'd rather buy a non-renovated house for $x, than pay $x + $50k for a house that the previous owner spent $50k renovating. By all means, do that kitchen reno to make your home a nicer place to live, but don't think it's something that pays for itself.
>3. The calculator assumes that the down payment and cost difference vs renting would be invested, which is fine but ignores psychological realities that prevent this more often than not
Fair point, although I seriously doubt people who do rigorous buy vs rent analysis are the type of people who can only be cajoled to save through a house/mortgage
>The suggestion was mentioned as a 'hedge'. The point being: you don't know what the values entered into the calculator will really end up being. Having some costs locked in can help with concerns around cash flow (and shelter costs are usually a significant percentage of costs overall). It's an "also 'invest'" strategy, so there's a whole lot not included in the calculator here as well
The values could easily work against you as well. For instance if housing costs rise slower than expected. This is a real possibility with the rise of YIMBY in politics and boomers selling up as they retire. Moreover how is parking most/all of your savings in a single asset (ie. your house) considered a "hedge"? Maybe it can be construed as a hedge if your portfolio was all MAANA stocks, but I'm not sure how anyone would think shifting from a globally diversified stock/bond portfolio (ie. a bet on the global economy) to a single house in the US is a "hedge".
> there is 0 way of telling if the work is real or not, at which point why bother?
I might argue you couldn't really tell if it was "real" before LLMs, either. But also, reviewing work without some accompanying dialogue is probably rarely considered a joy anyway.
> However, while 90% will miss the opportunity right there in front of them, 10% will grab it and suck the marrow.
Learning is not just a function of aptitude and/or effort. Interest is a huge factor as well, and even for a single person, what they find interesting changes over time.
I don't think it's really possible to have a large cohort of people pass thru a liberal arts education, with everyone learning the same stuff at the same time, and have a majority of them "suck the marrow" out of the opportunity.
I did a comp science degree, so I can't speak for the liberal arts. However I imagine the same experience could apply.
For us the curriculum was the start of the learning, not the end. We'd get a weekly assignment that could be done in an afternoon. Most of the class did the assignments, and that was enough.
There was a small group of us that lived (pretty much) in the lab. We'd take the assignment and run with it, for days, nights, spare periods, whatever. That 10 line assignment? We turned it into 1000 lines every week.
For example the class on sorting might specify a specific algorithm. We'd do all of them. Compete against each other to make the fastest one. Compare one dataset to another. Investigate data distributions. You know, suck the marrow.
(Our professors would also swing by the lab from time to time to see how things were going, drop the odd hint, or prod the bear in a direction and so on. And this is all still undergrad.
I can imagine a History major doing the same. Researching beyond the curriculum. Going down rabbit holes.
My point is though is that you're right. You need to be interested. You need to have this compulsion. You can't tell a person "go, learn". All you can do is offer the environment, sit back, and see who grabs the opportunity.
I get that you cant imagine this playing out. To those interested only in the degree, it's unimaginable. And no, as long as burning-desire is not on the entry requirements, it most certainly will not be the majority.
In truth the lab resources eoild never have coped if the majority did what we did.
> I did a comp science degree, so I can't speak for the liberal arts.
By 'liberal arts' I meant the common 4 year, non-vocational education. My major was CS too, but well over half of the time was spent on other subjects.
> I get that you cant imagine this playing out. To those interested only in the degree, it's unimaginable
I can easily imagine what you describe playing out. I just wouldn't call it 'sucking the marrow' (unless you were equally avid in all your classes, which time likely would not permit).
But as you allude to in your last point, the system isn't really designed for that. It's nice when it does effectively support the few who have developed the interest, and have extra time to devote to it, as it did for you.
I'd rather see systems that were designed for it though.
This kind of "perf review" hacking works ~everywhere; how well it works correlates with how entrenched the organization is (i.e., how hard it is for new players to disrupt).
You don't have to play the game the same way to work there. But it helps to accept that others will play it, and manage your own expectations accordingly.
Which big, well-paying companies do not have "those bullshit metrics"? I know for a fact that Meta, Google, Stripe, Airbnb, and Oracle all lean heavily on performance review cycles based entirely on ridiculous metrics. Getting ahead there requires you to play the stupid games GP is suggesting.
The original post doesn't mention anything quantitative ("metrics"). Did this get sidetracked?
> Depends on what you are looking for. I’ve turned half baked ideas into white papers for plenty of praise. I’ve used them to make my Jira tickets seem complicated and complete. I’ve used them to get praised for writing comprehensive documentation.
This is about giving people a good impression of you so they'll write strong peer feedback.
Totally, if you're willing to trade in your half-million or more annual compensation for $150k or less. My point is that it's an unfortunate game you have to play if you're working for places like that.
>Totally, if you're willing to trade in your half-million or more annual compensation for $150k or less.
I will take 60k at this point. I've been living ono half of that for almost 2 years now.
I have no idea how anyone is navigating this job market. Maybe it's just 10x worse and most people here are in the Bay area that's a tiny bit more shielded from this.
>Their number is absolutely miniscule compared to the number of big-tech jobs.
the coolest thing "the big tech" was able to do is convince a whole bunch ridiculously smart people that they only place they can make $500k is with them. I personally (I am just one person) know more than 10 people not working for big tech making (some significantly) north of $500k as SWEs and doing awesome sh*t (unlike I would un-intelligently guess most of big tech employees)
Sure, there are some jobs that match your description, likely for people that can brand themselves "AI engineers" for a rocketship company like OpenAI. Their number is absolutely miniscule compared to the number of big-tech jobs.
Yeah, I think another problem is that TooBigTech is able to pay insanely for... what do they bring to society again? Was it social media and ads? Anyway, all that desirable stuff /s.
Feel for you or anyone surrounded by such others but it is most definitely not everywhere - that is used to justify your presence in a place of work you should not be
