clhodapp

It's not supposed to be about superior and inferior, it's supposed to be about bigger and smaller.

Fable kind of screwed that up, though.

Needing fine-tuning for the use-case completely changes the product category

Personally, I think it's more that text diffusion is not the ideal driver of an agentic work loop than that text diffusion is a total dead end. I am still hoping to see how it does on authoring and editing with further scaling and optimization. I think the push for AGI has put a bit too much focus on the idea of one general model doing everything.

Honestly, it's an addressable market versus development cost question... How many clients will you lose if you support OIDC but not SAML? Does the delta justify carrying a SAML implementation? If so, do it. But the post is still correct that SAML is a fractal of bad design either way. And it's good to say this openly, and to run this calculus each time you are considering a new SAML implementation.

I can see how it might require an explicit state machine (keep a mutable state number and switch over the inlined bodies of what could be functions), but I'm not seeing how it could require `goto`.

Are there more-complex relationships that might require it?

No algorithm requires tail-call elimination in a general-purpose language with imperative mutability. It's just another way to express iteration.

There has stopped being a formal procedural consequence for OpenAI leaders to declaring AGI, there is a clear (small) business benefit to doing so, and the capabilities of all the frontier models are impressive. So why not declare AGI? It's not like anyone can prove it's not...

Don't be surprised to see other (or even the same) people declaring AGI again and again, as it becomes the best time to do so for different parties.

It seems to support USB4 with what they call "stock firmware". They haven't clarified what that means, but my assumption has been that it's a binary blob made by the manufacturer of their microcontroller that doesn't support all of their fancy debugging features (thus actually turning my into an Aliexpress special eGPU dock with a high quality buck converter).

It feels apparent to me that LLMs don't do what is colloquially thought of as thinking.

What is less apparent is that humans do.

Yup. You basically just need something for probability to push off of

Seems like they are closer to scratch than reasoning... Generating some scratch to draw from helps make it easier to compute the real answer.

Hrm, but the insistence is more "NAT should not be a practical requirement in a pure IPv6 network", not "No NAT ever for any reason".

NAT-based compatibility strategies are widely deployed in the real world (most cell carriers and Google's IPv6-mostly corporate network use NAT to allow communication with the IPv4 world from IPv6 only devices).

IPv8 is just a reactionary response to IPv6 not being "IPv4 with larger addresses" like people who know IPv4 well would prefer.

There would be no reason to adopt it if IPv6 were adopted.

That's not a fix. A fix would be undoing the change and making it opt-in.

I'm incubating my experience over on Linux

Consumers would buy bread with sawdust and then, upon learning about it, expect the sawdust to come out and the price to stay the same

They will monitor and if "too many" people are still doing normal software installs (I refuse to call it "sideloading" when that properly refers to pushing software from a different device over a debug connection), they'll raise the annoyance barrier higher.

Marketing types have started subbing in "Operating System" for "Platform" lately. And, because it feels bold and fresh to them, they often name whole product an "OS" when they do this in order to make anyone who talks about the product re-sell the pitch for them.

Yup. Adopting a month-old Postgres release is quite aggressive. It's much more prudent to start considering adoption after it's had six to twelve months of battle testing.

Adopting a month-old AI model version for new development is the default industry expectation right now. Adopting a six month old model is a recipe for having to migrate to a new one almost immediately, when it hits EOL.

That's fine, but it should still have the same technical availability level

That's another problem Google have: they won't stand behind their products until they are outdated.

That can work in the B2C space but it's horrible in B2B.

Sounds delightfully like something the Chongqing Punk would say

Models don't even agree with themselves in terms of returning identical results

It frankly doesn't matter how much human effort went into finding the vulnerability, it just matters if it exists, how severe it is, and how easy it is to exploit.

It sure is suspicious that both Anthropic (adaptive thinking) and OpenAI (Avoid generic brevity instructions) both seem to be suggesting that the best way to improve outcomes is to entirely leave it to them to decide how many tokens get used.

I mean, it's true that it would be ideal of this stuff did just get figured out optimally behind the API, but there is definitely an incentive on their side to burn more tokens.

The backfiring is baked in, if you think about it: This program is going to die in just a few days, while Sony is going to continue selling physical games for years.

Something I haven't been able to figure out.... How are you supposed to actually get an API key to use quota from your subscription? The terms of service still forbid using OAuth authentication and the API keys from the console indicate that you need to pre-load your account with funds when you try to use them.

While the gist of what you say is true, it is hard to get very good at treating them as instruments when they keep getting replaced with new, ostensibly-better versions every few months. But those new versions are not strictly better. They are mostly-better while actually having different strengths and weaknesses.

It's hard to decide when to use the best tool for a job you are aware of to ensure throughput and when to spend time experimenting with a new tool to learn what it's good at.

I believe this is an attempt to try out a possible answer to the problem of "If AI makes it non-viable for individual companies to pay junior devs, there will be no junior devs". The posited theory: Maybe the AI companies pay them off what is effectively a tax on the industry as a whole (that they can extract because every company has no choice but to pay their fees). It's pretty dystopian so I hope this isn't the future, but... maybe worth trying as an experiment?

So, the author gave the model single sentence prompts like "Balatro, but for the game of coin flips" plus generic encouragement like "make it better" three times ended up with netlify-hostable web games each time? That is hard for me to believe.

It's likely that at least some amount of additional context was provided to the model to enable it to reliably create the desired form factor. This introduces the caveat that the author probably views some amount of context as being trivial / beneath the level of mentioning. But then the question becomes where they draw the line.