B-Con

It's almost as if we're building something that... mimics intelligence.

The US has proved it can do horizontal scaling, as the majority of adults gets a college degree.

The horizontal capacity is ineffectively used by having many degree mills and low-value degrees, but if we re-tooled the knowledge sets we could raise the bar.

Not OP but I've tried using all the major frontier models to find niche items in a field that I collect. The models get confused and hallucinate items that sounds complete reasonable, but don't actually exist. Usually it's an amalgamation of several real products.

My prompt is akin to "recommend <item type> with <niche criteria>". The first 3-ish results are about right, and then 7 of the next 10 are hallucinations and the LLM clearly can't throw up its hands and say "I got nothing".

I'm sure this is a hard problem because of a) how many items there are, b) how much overlap there is between product names, descriptions, manufacturers, different versions of the same product, etc, so keeping them distinct in the model's memory is probably hard, and even worse if it is dynamically fetching and summarizing content then it will be very easy to conflate different items, and c) LLMs are known for not working well on the edge cases with few examples.

I read Google's business incentive as "in it to not lose". AI is a new consumer endpoint and Google currently captures a lot of the endpoints.

> I think HN skews coding agent focused

100% this. Coding agents are an interesting test ground, but the people who care about them are a fairly small bubble.

I think they carry some of the overall AI weight because of the "what if you can vibe code your entire business" moonshot, but that's still orders of magnitude away and who knows if today's coding agents will actually be a stepping stone to that. If we ever get there it will likely be with entirely new domain languages.

I've learned this applies to a lot of life. Being a good manager, tech lead, consultant, etc, advisor, parent, friend, etc, is sometimes just half being a good therapist and helping them regulate.

I've watched a lot of "not officially financial advice" finance videos on YouTube (the solid people, not grifters), and while the financial theory side is interesting, when they talk about pragmatic investing and patterns of client behavior they have dealt with professionally, a large part of it is emotion management. Convincing clients to stick with a solid plan even when this month is abnormally bad, or avoid going all-in on the latest hotness, etc.

Go seems like a pragmatic fit, even though it was obviously not designed for LLMs and nor is it purely functional.

I review a lot of Go code, which means I review a lot of LLM Go code. Even though the human vs LLM authorship distinction has strong signals, Go's simple nature seems like a useful constraint on how LLMs can express themselves.

I think one of the key differences is that math is abstract whereas CS is relatively concrete.

CS examples are often easy to picture and understand the motivation for. You can use tools to visualize or play around with them and test them.

Math gets abstract so fast you have to spend a week of research to even understand the problem statement. The the motivations themselves can be completely unclear until you have a lot of context.

I majored in math (B.S.) and upper level math is completely foreign to me.

A human reader for a popular product is generally a paid actor who reads the script nearly verbatim, not a domain expert, so it has no bearing on the technical quality of the script.

I can see them as a shared fate for a couple reasons:

* the obvious one is Elon - both valuations are largely propped up on belief in Elon. Whenever he falters, his companies that are speculation-based (all of them) will take a hit

* Elon pitched SpaceX as an AI company. Tesla needs better AI because they keep sending signals that they won't be at L5 anytime soon, and Tesla's valuation is still very speculative[0]at least in part due to the race to L5 autonomy. i.e. Tesla will need better AI , and SpaceX is that natural fit (on paper, at least, I'm not sure SpaceX has any useful AI for any use case, let alone self-driving).

[0] Tesla's PE ratio of is still 30x massively out of line with it's actual earnings and ~30x the American automotive industry.

Same.

And since I won with an age, company, and title that is literally me right now... Well, I'm not exactly sure what to do with it information but some internalization is in order.

I'm simply impressed they're releasing at all. This has to be literally the worst 6 month time window in the last 20+ years to launch a new computing device at scale and have to build the vendor contracts and inventory from zero.

Yeah, I imagine Linux support would be more like a supported Linux distro rather than generic Linux support. Something like SteamOS but with kernel anti-cheat and secure boot from the start.

Big question is whether they can make craching the anti-cheat it hard/unpredictable enough that the publishers will trust it. If the publishers release such a platform and someone releases a live distro that can crack it with 3 mouse clicks, that's a lot of wasted effort.

I have no idea how effective the Windows anti-cheat is, but I imagine that Linux tooling in general is going to make it harder to lock a user out of controlling their own machine.

Even though I balked at the Steam Deck prices on the recent inventory restock, as they were up ~30% presumably due to the same hardware shortages, I got one anyway. Prices won't drop anytime soon and if any for-profit organization has earned my loyalty, its Valve.

When I used it I was somewhat incredulous that I could simply exit Steam mode have an actual Linux desktop environment, where I could literally do what I wanted. It was my computer, a proper general purpose computing machine, and it was (willingly* in my control. No sneaky root needed.

People want to do X, so the metric is how much X can be done.

Everyone is over-complicating the explanation. The answer for "why are we fixating on this bad metric" is almost always the same pattern.

Broad audiences need simple metrics to talk about. If the metric itself requires nuance, it's hard to communicate and hard to reason about. It's easier to push the need for nuance from understanding the metric itself down the road to where the metric is applied, which allows everyone to ignore it in immediate conversation.

They added $80 out of a $4.5T market cap, which means redistributing ~1.67% of value from shares outstanding to the new shares.

So being down 1.7% is literally exactly what you'd expect.

I'm with you.

Australia calls December "summer". If climate patterns changed and shifted our weather patterns by a month, we'd shift our season vernacular to match.

Seasons refer to the climate we experience. They're a human experience, not calendar slot.

> I've had to spend week and a half battling Gmail daily email account limits sending batches of 500 emails just to notify people in her address book, receiving hundreds of responses. Her memorial was attended by hundreds of people.

I love this story, because I had the same experience. When my dad passed, I had the same 500 email limitation, and had to send out multiple waves of emails through Gmail. He was loved by so many people!

Yawing seems like it must be adventurous, the contagious part not so much.

Even the mention of a yawn can trigger it.

Perhaps we are almost always in a state of needing a yawn, but the trigger is seldom met, and seeing or hearing about it is enough to make our brain go "oh yeah I forgot about that".

Perhaps yawning is actually underdeveloped and an ideal human would yawn at regular intervals without any prompting.

I know this guy from his videos over the years on hiking topics, like how to safely purify water with the minimum fuel and how to pack calorie efficient food.

His videos are incredibly well researched, very in-depth, and absolutely zero fluff. Very much feels like his cycle is to get intrigued by a topic, spend a year deep diving into everything that's published, extrapolate what he can from there, then summarize it in a 1 hr video.

Any time an app has bizarre functionality gap on iOS, I assume it's because of Apple's anti-consumer bullshit app restrictions.

No idea if that's actually what's going on, but Apple thinks of their devices as appliances and hates when apps offer pro-customer features.

I used to have that strip on a t-shirt as a teen.

So if the top 10% is $2m net worth, then what's the 1%? Are we supposed to mentally extrapolate?

I hate when only part of the criteria are provided. Arrives like this need a table. If they don't have it, it calls into question whether they should be writing the article.

This is exactly what I've said for a decade.

When people talk about the 1% they almost always mean the 0.1%>

Preserving more than one lineage and providing a cohesive family name isn't practically easy, and society did not go that direction, and that likely isn't a coincidence.

Discarding names doesn't preserve lineage. If you need a book to trace the names, then the point of using a name for lineage has failed.

> The traditional approach is for women to keep their maternal name and discard their paternal name on marriage while men do the opposite

It sounds like this scheme is "men keep one name lineage, women keep another".

Which, IMO, has the practical drawback of not identifying the current family unit. Lineage was important, but so was gathering all folks together into a household. When taxes, religious ceremony, etc. occurred, there was one household name on the roster responsible. This was particularly important in societies where men held certain rights for the household.

What societies?

Keyword being "practically". Just because there is an alternative doesn't mean society will adjust.

And hyphenation isn't a solution, it only works for one generation.

It hails from when family lines were important, and you can practically only have one line reflected in a name. Unsurprisingly, most societies considered the male's name to be the dominate lineage of interest, although that doesn't hold true 100% of the time.

For me, I despise having different abstractions get crossed.

I expect my media app, ie. YouTube, to know what I watch from the media app. YouTube knows about YouTube.

My operating system, ie. Roku, should not know about what's happening inside a given app. ie. Roku does not know about YouTube.

When they start crossing layers, that greatly upsets me.

I have a theory: They realized the right approach is to focus purely on the yes/no of what you choose to consume, rather than trying to optimize the consumption experience itself.

Remember how YouTube and Netflix used to let you rate things on 1-5 stars? That disappeared in favor of a simple up/down vote.

Most services are driven by two metrics: consumption time and paid subscriptions. How much you enjoy consuming something does not directly impact those metrics. The providers realized the real goal is to find the minimum possibly thing you will consume and then serve you everything above that line.

Trying to find the closest match possible was actually the wrong goal, it pushed you to rank things and set standards for yourself. The best thing for them was for you to focus on simple binary decisions rather than curating the best experience.

They are better off having you begrudgingly consume 3 things rather than excited consuming 2.

The algorithmic suggestion model is to find the cutoff line of what you're willing to consume and then surface everything above that line ranked on how likely you are to actually push the consume button, rather than on how much you'll enjoy it. The majority of which (due to the nature of a bell curve) is barely above that line.

See last week's thread on why more parents homeschool.

I just rebuilt my PC and setup Steam on Linux. It was fairly smooth.

I've dual-booted Arch and Windows for about 16 years. I always kept Windows around for gaming, and the occasional "doesn't support Linux" workflow.

For a few years where I didn't game I found myself almost exclusively in Linux. But then I spent the last 5-6 years stuck between the two as my PC use for daily tasks dwindled, I stopped working on side projects, and I started gaming a bit more.

I hated trying to split my time between them. Most of what I used a PC for was the browser, so I could just stay in Windows most of the time. I wanted to use Linux, but rebooting to use a web browser just didn't make sense. As a result I would accidentally go 2-3 months without ever booting Arch. As a result, I had a couple of major updates that didn't go smoothly.

I wanted to use Linux, though. I like having a customized WM, I like having so many useful tools at my disposal, etc. I just like using Linux, in spite of the occasional technical complexity.

In the last couple months I rebuilt my PC and a major requirement was that I get set up to game in Linux as much as possible. I even bought an AMD card to ensure smooth driver support.

I'm so incredibly thankful that Steam has made gaming not just possible, but relatively simple. Installation was simple. My single-player games seem well supported so far. And most importantly, Steam has made it obvious they're committed to this line of support, so this isn't some hero effort that will bit rot in a couple years.

I still have to reboot to play competitive games, due to their anti-cheat requirements, but that's less of a problem, I'll take what I can get.