lukol

"money-losingest" -> AI already brings in billions and many AI companies could become profitable in little time if they'd stop R&D and simply keep selling what they already have.

yes, it's risky and investment-heavy but it's not a bottomless pit with no path to break even. there are many other recent technologies - NFTs? data centers in space? - that would be a better fit for this label.

This "new math" might be a recombination of things that we already know - or an obvious pattern that emerges if you take a look at things from a far enough distance - or something that can be brute-forced into existence. All things LLMs are perfectly capable of.

In the end, creativity has always been a combination of chance and the application of known patterns in new contexts.

Maybe I'm missing the point here - but how is this connected?

#1: You do not want randomness. You may believe you do until the Titanic crashes into your front yard and your significant vanishes into thin air. You want quite a lot of predictability, up to a degree where it might not even matter if things at the lowest level of existence are not perfectly deterministic.

#2: What's so bad about thinking about life as an exciting rollercoaster ride? The tracks are laid but the ride is still fun.

But remember, don't (super)determine and drive

opens coat Hey kid, wanna try some superdeterminism?

Couldn't agree more. Simple REST APIs often do the job as well. MCP felt like a vibe-coded fever dream from the start.

Don't disagree but being the social animals we are, images and videos will never not be important. Things will always feel better when I can connect it with a friendly face.

Next up: Executive AI takes over from AI executive

Anybody else experiencing severe decline in Claude output quality since the introduction of "skills"?

Like Claude not being able to generate simple markdown text anymore and instead almost jumping into writing a script to produce a file of type X or Y - and then usually failing at that?

Claude to the rescue: This is an interactive data story from The Pudding about research showing that talking to strangers makes us feel better, despite our expectations.

The piece follows conversations from a study of nearly 1,700 video calls between strangers with different backgrounds (age, race, politics, etc.). While people predicted they'd have negative experiences talking to strangers, the vast majority actually felt better by the end of their 30-minute conversations - regardless of how different they were from each other.The story argues that we've lost "bridging social capital" (connections with people unlike us) and explores how this contributes to declining social trust.

It ends with a personal reflection on helping a bleeding teenager on the subway, suggesting that despite our fears, most people will help strangers when needed - and that these connections are crucial for tackling big societal challenges.

It looks nice and I really want to engage with the page further but since my time is limited today and I'll have forgotten about this by tomorrow: What's the tl;dr?

How do you deal with specific wording that needs to be used in certain languages (often required for legal topics) or specific brand-related messages that need to be in place without any modifications? Does a developer still have the ability to manually translate certain strings?

Congrats on the launch! How does your PDF to text feature compare to services like LlamaParse and 2markdown.com? Especially in terms of layout and image understanding. And for a privacy focused service, it would be great if your privacy policy would contain text :) Is the service hosted in the EU?

I wonder if a well trained rat can beat an AI in terms of prediction quality per energy spent.

"Buy a bunch of H200s and build a SMR next to the data center? Nah, just take these rats and feed them for 3 years."

Last time Google made a big Gemini announcement, OpenAI owned them by dropping the Sora preview shortly after.

This feels like a bit of a comeback as Veo 2 (subjectively) appears to be a step up from what Sora is currently able to achieve.

So by the time the 12 year old has met ~20 people, there is a 50/50 chance that amongst those 20, there’s a birthday pair.

If you randomly choose the ~20 people from the global population then yes, this will be the case (especially after a number of rounds). And yes, I'm aware this is also the definition of the paradox.

But if you choose the people from your vicinity (i.e the people you are actually likely to meet), the chances will vary based on your individual parameters (which defines the number and quality of the sample size).

Took a brief look at the Wikipedia article: https://en.wikipedia.org/wiki/Birthday_problem

Thanks, I was not aware of this classification. I primarily tend to think of paradoxes as "self-contradictory statements" but you just expanded my definition.

While the math is clear, I'm a bit annoyed by the label "paradox" as the whole setup is too simplistic and reductionistic.

The actual chance of being in the same room with someone who shares your birthday needs to include other factors like your socioeconomic background, the cultural environment you are in, your present location, and certain historical facts.

Without having done the math, I'm fairly certain that a member of the baby boomer generation in New York has a higher chance of meeting their birthday sibling than a 12-year-old in a rural part of Australia.

https://xkcd.com/538/

While I will not argue the basic premise, I believe such comparisons always miss a crucial point: Humans, in contrast to almost all other animals, are able to reflect and learn. We can ask ourselves "What if?" better than anything else.

While an AI that's magnitudes smarter than humankind is likely to arise at some point - smarter in a way that will be hard / impossible for us to comprehend - dealing with a species that is able to evolve itself in a self-guided way will be very different than dealing with a colony of instinct-driven ants.

I believe future game engines will be state machines with deterministic algorithms that can be reproduced at any time. However, rendering said state into visual / auditory / etc. experiences will be taken over by AI models.

This will also allow players to easily customize what they experience without changing the core game loop.

Thanks for sharing this acquisition in such detail! How many potential targets did you evaluate to what degree before settling on Pixel? Trying to understand the total duration/effort from "I want to acquire something" to "acquisition completed".

This. Scrum is just a way of operationalizing the basic principles behind the Agile Manifesto while putting them in a way that can be communicated and understood outside of dev/product organizations. No Scrum Master/Agile Coach/Product Owner, etc. worth his/her salt will tell you to slavishly stick to every piece of Scrum as long as you get the basics (see the manifesto) right.

It is, however, a somewhat useful tool for helping you get this running in the first place (especially in organizations where there is a lot of chaos to begin with, i.e., upper management regularly changing the product scope and release timeline based on the color of their coffees, etc.).

Thanks for sharing your thoughts! I published a blog entry that describes our solution to this exact problem yesterday. We call it "Generation Augmented Retrieval (GAR)", please find the details here: https://blog.luk.sh/rag-vs-gar

Thanks! We've implemented a progress indicator, skeleton loaders, and object streaming using the Vercel AI SDK (see here: https://sdk.vercel.ai/docs/ai-sdk-core/generating-structured...). Especially the latter ensures that users start receiving content right away.