gerad

You need to pay for Gemini to access it. In my experience, it's not worth it. So much potential in the experience, but the AI isn't good enough.

I'm curious about the OpenAI alternative, but am not willing to pay $200/month.

It seems like a really easy way to overfit your model to your data, even while using LLMs.

> Meanwhile our oauth flow is still a tortured, unloved, twisted writhing mass of pain and suffering that prints bug reports like CVS receipts.

Wow, this line is a keeper. This whole comment is so insightful. Reminds me of how awesome HN can be sometimes.

I guess that'd explain the big bang nicely. It does make it the "outer universe" disappointingly unobservable though.

Blame stress

I learned this in the Cal Academy of Sciences the other day! Apparently we’re about halfway through a region of less interstellar activity.

https://en.m.wikipedia.org/wiki/Local_Bubble

Not to mention the cost.

Also, if you have kids then you check out tons of books at a time.

I don't understand why you need to wait to the end to checkout. It should happen via mobile app while you add things to the cart. At the end scan a qr code to pay or something when you leave.

Well not if you cut it with an appropriate amount of chloride and sodium.

I never understood this. Cows make protein from eating grass. I assume that we can do much of the same.

I read the GP as it’s easier to have the single infrastructure team implement it than have every single product team add support in their service.

I mean most app servers abstract away https on the server level and most dev is done unencrypted. So this seems reasonable.

The intuitive way for me to understand the Monte Hall problem is to pretended there are 1000 doors. You pick 1. There’s a 1 in 1000 chance you get it right. The host then opens 998 doors that don’t have the prize. Do you keep your original or do you switch? Are the odds 50:50?

VUSXX - 5.29%

I’ve made my own starter a couple times. It’s really no big deal. Takes a couple weeks of waiting but maybe an hour of total time over that two weeks.

It’s a false analogy. Baseball has way more variance than the other sports.

If we’re in a simulation and that simulation is advanced enough for our ancestors to build a simulation of the simulation - at what point does the recursion break down?

Africa?

> The problem is that, only after the interaction does the metrologist learn which input would have been optimal.

I read it as:

- Today, I need to predict tomorrow’s weather.

- Yesterday I made some measurements of the (temperature, pressure, etc) conditions that I need for today’s prediction.

- Yesterday it was impossible to know what measurements I’d optimally need to take for today’s forecast.

- Today, I can (quantumly, probabilisticly) go back in time and make sure I have the optimal set of measurements for today’s prediction.

- I can’t change anything that happened between yesterday and today, but I now have better information I can use to change tomorrow.

I’ve found that it’s not the setup but the maintenance that’s hard with these sort of solutions for others.

But we do call it red (and white) wine.

I’ve been self medicating with podcasts to solve this exact issue for 5-6 years. I’d advise trying to wean yourself off it before it goes on too long. I now have tinnitus from the earbuds in my ears at night.

Would you rather be paid upfront or in arrears? Simply the timing of the payments is a really big financial incentive to have tiered-pricing - which is why you see it so often in the wild.

It’s possible to use optimistic locking and versioning to ensure that things haven’t changed underneath you unexpectedly.

I just got back from the Netherlands, which is an interesting contrast. They use probably the same amount of space as a six lane stroad in some places, but instead of being entirely for cars, it looks like this:

- 1 or 2 car lanes (each way)

- a tram line (one each way on each side of the street, or in the middle)

- a separated, 2 way bike lane on either side of the street

- a separated (from the bike lane) sidewalk

- a canal

As you can imagine, this takes up a lot of space. Despite this, things feel much more walkable. The reason? No enormous parking lots around every store. Parking is generally almost entirely done at P+R parking lots outside of town, then taking public transit in.

For LLMs and generative AI we’re likely at the start of the curve. Things take longer than you expect in the short-term and less time than you expect in the long-term.

After this hype cycle ends, things will probably bump along slowly for a decade or so, then suddenly you’ll look up and they’ll be everywhere, and you’ll wonder “when did that happen?”

At least that’s the way it felt for other technologies to me. Internet, Bluetooth, cell phones, etc.

I usually throw it in a garment bag with the wash. Then take it out before it goes in the dryer.

Yeah, but the value they provide IMO (or promise to, it’s only promised in the readme, not shown) is the observability.

Creating one of these event driven systems is somewhat trivial. Node has event emitter built in for example.

Being able to monitor, debug, scale it and ensure it’s robust to failure is much harder.

In that respect it sounds kinda like tray.io. [1]

1: https://youtu.be/g_2HNv8HZcA

I run in wool socks [1] all the time. Wool is moisture wicking too [2].

1: https://www.smartwool.com/shop/mens-running-socks

2: https://www.rei.com/learn/expert-advice/what-does-moisture-w...