Not to mention they will need to research how to make their models faster and cheaper to run in order to fit some margin within what people are actually willing to pay.

Are there any indications that this will be possible? Consumer hardware will continue getting better but I can't see 512GB RAM in a MacBook Pro any time soon. I'm hoping linear attention techniques plus MoE will make breakthroughs in size/compression and throughput.

> but I can't see 512GB RAM in a MacBook Pro any time soon

Could totally see this being a comment from a forum in like 1994 but swap out GB for MB and MacBook Pro to whatever the popular consumer pc was at the time

Yeah but the price of RAM wasn't increasing at that point.

Well, we're probably not going to be running frontier models anytime soon, but I think the general assumption is smaller models will continue to improve until they're sufficiently good frontier models aren't needed.

There's potentially also augmentation through tools, harnesses and RAG to help boost how well they work without tons of parameters.

There will be a 1024GB unified memory MacBook Pro.

Not at a price that your average consumer can afford for a long, long time

Certainly not any time soon, but I have faith it'll happen one day.

In the last ten years laptop memory footprints have, what, doubled at the low end? Smallest MacBook Pro in 2016 was 8GB, smallest is 16GB today? Max I think has gone up 8x meanwhile, 16 to 128?

I wonder if there's a bit of a chicken-and-egg issue where there wasn't much that demanded 10x the RAM, so there wasn't much pressure to develop more or increase production to support it at consumer prices.

There's wayyyyyyy more demand for memory generally now, so assuming it's not a demand bubble that pops rapidly, I'd expect the new normal to end up at a much higher baseline. 512GB would be 4x greater than today's max, so even with the relatively slow last 10 years development pace, give it five years max?

The problem is that the situation in the RAM market might just... not go away. It's locked in for the next couple of years unless the AI market goes pop. Which it might! But if it doesn't, there's no particular reason to think that the incentives for cornering the market like OpenAI have would go away.

We might see that new normal in five years or so. We will see a new normal sooner than that if there's a run on AI because of the sudden availability of DRR fab capacity, but also we'll probably see the level of local models freeze at whatever state they've got to at that point. But an equally likely outcome is that any new DDR capacity that comes online is just immediately absorbed by frontier AI, and consumer devices stay at "just good enough" for a decade.

The new Macbook Neo is 8GB. I think that if we are lucky, the huge RAM demand right now means new factory buildouts which eventually means more supply and prices go back down, and capacity begins to go up. This level of demand was just not anticipated by anyone.

Sure, and OpenAI, Anthropic, Grokkk are totally self-made and profitable.

Well, the level of tech is at least on a whole different level at those companies than whatever cohere is doing.

I find Mistral Medium 3.5 with OpenCode is perfectly fine if you're willing to talk to it in a more fine-grained way about actual code. For me that's fine because even with huge frontier models I don't like trying to vibe prompt like a product manager.

maybe we need regulations for such things... maybe stricter gun^Wdisrupting tech laws could limit the abuse...

Well, the technology is also pretty shit.

We should pivot the culture to one that is pro-liberal arts again. These people know how to read and write better than STEMs in general.

CS as the only path to programming was always too narrow, and often people with a broader education are better at creative solutions. With AI-assisted programming I'd argue they have an even clearer advantage now.

I’ve always noticed that truly excellent programmers with strong lexical instincts also tend to be formidable with their native language. Not necessarily verbose, but capable of clear and structured writing.

I’d even go so far as to argue that if someone has poor writing skills in their native language, they’re probably not a very good programmer.

> These people know how to read and write better than STEMs in general

That is completely untrue. Efficient, creative writing is a skill that can be learned by anyone by following a handful of rules.

In theory, it isn't that difficult, in practice writing _accessible_ text takes a lot of practice and feedback. Letting go of your own biases towards base levels (curse of knowledge) is something that already trips most people and what people find really difficult to overcome.

Which is why the statement you are responding to is often more true than you might realize. Because these people have had a lot more practice in that specific area. Although not all of them, that would be a generalization in itself.

I help run a writer's symposium, and let me tell you it's really hard to write a good novel.

We get editors all the time talking about things they commonly see done badly in submissions.

Slush pile readers (the people reading unsolicited submitted manuscripts) have so many war stories about awful writing.

The books you see on the shelves are less than 1% of what's created and even then there are ones that get through that are bad.

Now we have amazon inundated with AI generated books that are just incoherent.

And that is creative writing that strives only to be entertaining. Tech writing tries to teach you how to do something, which is much harder.

I like watching maker videos, and even the ones trying to explain how they are doing something always skip over important steps.

I have a liberal arts degree and I don't want to do technical writing. It's so much harder than dev work and it's utterly mind numbing.

I've never had a problem working https://pgtap.org/ into CI.

I know the article title says "integration tests" but when a lot of functionality is done inside PostgreSQL then you can cover a lot of the test pyramid with unit tests directly in the DB as well.

The test database orchestration from the article pairs really well with pgTAP for isolation.

Kind of a tangent but I'm really interested in why statements like:

> if you have carbon-based life forms, you will have water and CO2.

..can lead to statements like:

> it is just way more likely than any other form

I totally agree on the observation, but what is fascinating to me is why a deductive statement can be considered to indicate likelihood in probability. It seems there is a bit of abductive reasoning going on behind the scenes which neither the deductive logic or inductive probability can really capture on their own.

I don't see that particular statement "leading" to the second statement. You quoted very selectively and didn't quote the part that is the reason why I believe carbon-based to be much more likely, i.e. the fact that silicon is such a bad candidate and that no other molecule allows complex chemistry. Maybe that helps with your fascination. Obviously I skipped all the actual arguments, but they are easy to find by the interested reader in standard literature.

There's a third kind, which is when unscrupulous business managers or politicians use it to make decisions that they would not be capable of auditing for a rationale when otherwise required to know why such a decision was made.

It's more of an ethics and compliance issue with the cost of BS and plausible deniability going to zero. As usual, it's what humans do with technology that has good or bad consequences. The tech itself is fairly close to neutral as long as training data wasn't chosen specifically to contain illegal substance or by way of copyright infringement (which isn't even the tech, it's the product).