wodenokoto

> What Windows calls ⏎ Enter, Mac calls ⏎ Return. However, Macs also have an ⌤ Enter, although only on a numeric keypad

Just looked down on my windows keyboard and yes, the return key (the one above the right shift key) says "enter". That did not use to be the case. The return key used to say return and the tall key next to 3 and the numpad used to be the only enter key.

When did that change in PC land? I remember reading nerdy articles about the difference between return and enter.

I had no idea!

I always thought the catalogue was a duckdb file. E.g, data lives in partitioned parquet files, but which parquet files are current or soft deleted, etc, etc, is managed in a duckdb data file.

However, looking at https://ducklake.select/, it seems the catalogue lives in PostgresSQL - so it is not really a ducklake, but a postgresslake.

The more you know.

The EULA you have to accept hints that they are afraid you are going to abuse it to remove synthID - e.g, set up and edit and check loop

The article claims 10.1 is a reference to a 101 keyboard by IBM.

I think it is worth mentioning that age and sex is encoded in the social security number.

There are exceptions where the encoded birth date will be wrong (like immigrants with unknown birth dates) or dates where there are more people than the 4 digits that encode checksum validation and gender can handle.

That’s for gnu implementation. For the BSD implementation author just links to the source code.

Barefoot is the Heineken or Budweiser of wine.

So that sorta explains everything- price, taste, reach.

Tesla has managed to alienate the entire left wing while not enticing the right wing.

I’m having a really hard time understanding this. I don’t work on Postgres so cut me some slack.

Apparently both timestamp and timestamptz saves 8 bit integer that represents a datetime in a similar fashion as Unix epoch.

Neither of them stores a timezone or an offset.

So what are they?

I travel with my dual esim iPhone and the dual esim doesn't disappear.

So how are you solving the example in the article where they join on timestamps? Read both tables from the DB into the application?

Off the top of my head it's 3 things it advertises:

- By not being a optimised for chat, it can deliver confidence for answer and not for how an answer should be phrased

- Speed. It can take seconds for OpenAI to compile schemas, jev can respond before openAI has even begun thinking

- Token efficiency and price. I think its the output token they don't even charge for because they are negligible, and the tokens they do charge for are at a fraction of a comparable model.

If you are using structured output, I think those 3 together is a really big deal.

>But their example is classification but that would also be possible and faster with a classic BERT model.

I believe the things you can classify with ChatGPT without any tuning or training is way beyond what BERT can do.

> a $20 million state grant paid for both the research and the infrastructure.

Weimer described the project as a “proof of concept” that generates just 1.7 megawatts of energy, a tiny fraction of the 56 megawatts that they generate with a solar farm in the desert.

But the canal site hosts more than just panels. Bales said they “have instruments out there to measure temperature, relative humidity, wind speed, incoming radiation, outgoing radiation, and a prototype instrument to measure evaporation directly.”

It’s not that simple. It’s a research projects that does more than just solar.

So you need to ask “how much of the grant went into the solar-cover”, and set that up against the value produced (water evaporation, water quality, electricity, etc).

What you did is set the price of the entire research project up against one of its output.

What’s the deal with dual eSIM disappearing in Hong Kong?

Just collect common bi- and trigrams and a naive bayesian classifier.

> Spymarks just seem like another word for https://en.wikipedia.org/…

Stop using links instead of words. Your comment is literally unreadable without going on to other websites.

It's a game design document.

My guess is it is kinda like a first draft that some higher ups approve and budgets and then dialogue and game development and puzzle testing can begin.

I’m having a very hard time telling the blur of the trees apart between the iPhone 18 picture and the iPhone 17 picture of the same subject also posted in the article available here: https://www.dxomark.com/wp-content/uploads/2026/09/PoleHDR_D...

I know people use chat bots differently and I get that companies see value in personalization, but to me it is extremely valuable that I can start a chat without context.

When researching a topic a chatbot can be quite sensitive to certain wording and those can end up steering definitions. Two context free chats on the same topic can go in very different ways depending on how you word things, but when using the notebook feature in Gemini, where every chat becomes part of the context you completely lose the ability to discover if a topic is vaguely defined or have many definitions.

Shouldn’t we expect the LLM model in this case to already be trained on the test and train dataset?

I’m more worried that the query planner requires more compute than the query.

It seems absolutely crazy to me to expect an LLM to code a solution to a problem while also not expecting it to be able to adhere to a grammar.

They still do, to the best of my knowledge, although they have started incorporation reddit discussion too.

She’ll probably do that on her next 3 week trip.

I think it is overall a well written and engaging article on a topic I knew nothing about.

However, about half way through the author writes

> The only place on the whole island where the two worlds nearly collide is the Markham valley […]

Author then goes into a bit of detail on that place before giving two reasons why he believes “that”. Two reasons I cannot for the life of me parse

> The reason why I believe that, despite the minimal trade that existed, the highlands were functionally cut off, is that when the Europeans occupied New Guinea, they themselves did not ever speak of or show knowledge of the highlanders. Similarly, when the highlanders first encountered Australians, they had no concept of the coastal people, or where the shells came from, or any further concept of the broader world.

So the reason the highlanders world nearly collided with the coastal dwellers at Markham Valley is because the Europeans didn’t meet the highlanders when they occupied the island?

The other reason is to do with genetics, which I find equally detached from the core subject of those paragraphs.

An article named “This is how we do modern frequentist statistics” is an excerpt from a book called “Bayesian workflows”

Where is the article explaining that?

Anyway, great article, thanks for sharing.

And what about the rest of the world?

While I agree that dating apps encourage superficial engagement and that the app provider goal is to have you use the app, while the users goals are essentially "getting off the app", the main downfall of dating apps are fake profile and profiles promoting paid services (paid dating, paid sex, paid whatever)

I think it is a great premise and I feel the same way to. Is today like yesterday, because then I should bring a jacket, etc.

Shouldn't that hit nonfiction and fiction equally?