phn

Sure, let's assume that is true now (I don't know and not on me to check really), but if half of consumption disappears, where will the earners earn from to continue that cycle? What if people stop paying their mortgages? Textbook recession where everyone is affected.

"Capital investments" are not a magic money source if the economy is tanked.

If all jobs are taken away for the sake of robot driven productivity, who will consume the products and services being offered that result in profit?!

(EDIT: I am not against AI at all, just trying to understand where this all leads)

So, determinism is the core of the issue for you?

I'm sorry but you can compare them in the sense that they're just computer programs that can be useful to you.

On the new moon, when the moon is between the earth and the sun, the light reflects back towards the sun, so you don't see it i.e. the moon is dark.

As for the full moon, the earth and sun are on the same side of the moon, so the sun is lighting the moon "from behind you" and you can see that.

I do understand the "invisible side effects" side. I do try to be conservative in what I do in signal listeners.

I do what I must in the atomic context, and trigger celery tasks for everything else.

The only part I don't really agree with, is the avoidance of app separation and signals. It's one of the cleanest ways to decouple your modules and keep some level of sanity in a medium-sized codebase. It comes down to deciding what parts really need to depend on others and be very explicit about that.

I generally end up with a few core apps with the main data objects that a lot of other "parallel" ones depend on, a bit "star shaped". And then a few "aggregator" apps that cover functionality that needs to work across multiple of these domains. I see it all as an extension of how you think about your data model.

Computer use itself is evolving as CLIs and APIs are important again to enable AI use. We'll certainly converge at a happy medium, CLIs, APIs and text for AI, and maybe some form of dynamic interface that the AI builds/adapts on the spot for the exact task you want to execute, on the environment you're at. And of course, good ol' purpose built tools/UIs as we do today, when it makes sense.

Would you be able to share a bit about your workflow? Have been meaning to try AI gen for game models, and would love to know how people are tackling this.

I think part of the issue is that these retailers are also customers of meta/google on the side of purchasing ads, and as a merchant you're highly encouraged to send as much data on your events as you can, or your conversion tracking can be "less accurate"and your campaigns are less efficient.

So it's less about "we're sending the data to $megacorp" and more about "I want the most bang for buck on my own campaigns" when the decision is made.

Using a different email certainly helps, though!

EDIT: highly encouraged by meta et. al! Whether this is a legitimate request to improve results or pure self-interest on the part of meta I don't know!

The issue is, even with all the browser protections, you still create an account anywhere or buy something an input your name/email address/shipping address, your "hashed data" immediately gets sent to meta/google as a conversion with "this guy bought a cat toy", and you start getting ads for cat related stuff everywhere.

They don't even need to "track" you properly for this stuff to work and it seems there's no way to escape it.

A fascinating thing for me after reading this is: how can it be that the "circuit input" is compatible with its output to the point where the performance improves? The training process never saw this particular connection just like it didn't see layer 60 output into layer 3 or whatever.

Great read, makes you wonder what else is encoded in these models that might be useful!

A good example of this is Rust. Rust is by default memory safe when compared to say, C, at the expense of you having to be deliberate in managing memory. With LLMs this equation changes significantly because that harder/more verbose code is being written by the LLM, so it won't slow you down nearly as much. Even better, the LLM can interact with the compiler if something is not exactly as it should.

On a different but related note, it's almost the same as pairing django or rails with an LLM. The framework allows you to trust that things like authentication and a passable code organization are being correctly handled.

Very small suggestion: Can you make the entries actual links/anchor tags so that it is possible to copy link, middle-click to open in a new tab, and so on?

You can look at it both ways.

Using the database as a queue, you no longer need to setup transaction triggers to fire your tasks, you can have atomic guarantees that the data and the task were created successfully, or nothing was created.

I think the problem starts with the name. I've been coding with LLMs for the past few months but most of it is far from "vibed", I am constantly reviewing the output and guiding it in the right direction, it's more like a turbo charged code editor than a "junior developer", imo.

Have you tried Roo Code in "Orchestrator" mode? I find it generally "chews" the tasks I give it to then spoon feed into sub-tasks in "Code" (or others) mode, leaving less room to stray from very focused "bite-sized" changes.

I do need to steer it sometimes, but since it doesn't change a lot at a time, I can usually guide the agent and stop the disaster before it spreads.

A big caveat is I haven't tried heavy front-end stuff with it, more django stuff, and I'm pretty happy with the output.

And a great way to pick up the guitar every day is to have it ready to go at all times. Keep it outside the bag/case and at arms reach.

If you're visiting Shinjuku, nearby there's a narrow street called Omoide Yokocho. Just take in the vibe and choose a yakitori spot to grab a bite and drink your poison of choice (tea/beer/sake). I would recommend going at night/dinner time.

Speaking of Shinjuku and videogames, if you've ever played any yakuza/like a dragon game, you owe it to yourself to go to Kabukicho and its big red gate.

In any case, whatever you choose to visit in Tokyo, it will be really nice, and a lot of it will still be waiting when you eventually come back.

Cheers!

The worst so far, and the best when compared to all of your remaining days.

I think Elden Ring (and the souls genre in general) IS designed with the assumption players have access to the internet to search for stuff if they want.

The game will still provide quite a challenge even if you know where you need to go and get weapons/items/etc. The bosses won't defeat themselves even if you know the overall strategy to use.

I think of it as kind of a self-regulated difficulty system, if you want to go in blind you are still free to do so.

I'm not a scientist by any means, but I imagine even accurate opaque models can be useful in moving the knowledge forward. For example, they can allow you to accurately simulate reality, making experiments faster and cheaper to execute.

Employees have been feeding sensitive data to online translators in the same way.

Not to say it isn't a problem, but it's not an AI/chatGPT specific one.

Can you elaborate on why you think that?

IMO, their scripting language is pretty accessible to anyone with a bit of experience with programming and has nice syntactic sugar to integrate with the engine.

For sure, I'm not saying it'd be better or worse. It's just hard to imagine a world without Chrome.

Imagine how different the world would be if Google really went with the "enhanced version" of Firefox instead if building Chrome.

Does anyone know how this compares with centrifugo?

Fully cross-platform for the usual suspects on desktop, mobile and web.

If you want to publish on consoles you need to pay someone who ported the engine to the console you want to target (or port the engine yourself). The code can't be open source because of licensing issues.

From: https://docs.godotengine.org/en/stable/tutorials/platform/co...

If someone could challenge my layman understanding:

Isn't the information still there, inside the black hole, but just not retrievable from the outside?

I mostly agree with other commenters, but I really must hard disagree with point 5.

Proper abstraction is the one thing you need to get right, and django makes it so easy to make clean separate modules work together using a shared base and way of working (user model, groups, permissions, urls, signals, etc.).

One day you'll need to use your payments logic to sell something else, embrace it.

While point #1 is of course valid, it is most useful for new code, or code with significant resources behind it to optimise it for lambda.

For people with an established codebase, not wanting to go all in on lambda/serverless, or wanting to use existing frameworks, the trade-off might be worth it.