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Try it. You might be missing out! One of the benefits of getting all your trousers from a tailor made to your size is you never have to waste time trying on trousers, or waste time ordering-returning items.

Aren’t books massively outweighed by the crawled internet corpus?

I would doubt that because books are probably weighed as higher quality and more trustworthy than random Reddit posts

Especially if it's unsupervised training


Which phone and which software?

Samsung S24 Ultra with the stock dialer. I use DW Contacts to manage my address books, but stick with the stock dialer specifically for the recording feature. I understand this is CSC dependent.

I was curious enough to fact check this. The statue does look like two horses wrestling or even mounting two men, but here’s what the city’s tourism website says about it:

[the famous sculptor Toma Rosandić] named this composition of bronze horses and their tamers “Black horses at play, and with them great heroes”, saying that the horses represent strength, and men tame and control that strength.


I wasn't trying to imply that my interpretation of the art is the correct one.

It's just what I think of every time I see those statues.


It’s a valid interpretation. Fact checking may be the wrong word choice and if it wasn’t clear your story passed the fact check: there are indeed two statues, just like you described (with some margin for interpretation). I was just curious to see this postmodern sounding piece of art and it turned out to be a pair of fairly traditional bronze statues.

Counterpoint: Try to use an LLM for even the most coarse of visual similarity tasks for something that’s extremely abundant in the corpus.

For instance, say you are a woman with a lookalike celebrity, someone who is a very close match in hair colour, facial structure, skin tone and body proportions. You would like to browse outfits worn by other celebrities (presumably put together by professional stylists) that look exactly like her. You ask an LLM to list celebrities that look like celebrity X, to then look up outfit inspiration.

No matter how long the list, no matter how detailed the prompt in the features that must be matched, no matter how many rounds you do, the results will be completely unusable, because broad language dominates more specific language in the corpus.

The LLM cannot adequately model these facets, because language is in practice too imprecise, as currently used by people.

To dissect just one such facet, the LLM response will list dozens of people who may share a broad category (red hair), with complete disregard to the exact shade of red, whether or not the hair is dyed and whether or not it is indeed natural hair or a wig.

The number of listicles clustering these actresses together as redheads will dominate anything with more specific qualifiers, like ’strawberry blonde’ (which in general counts as red hair), ’undyed hair’ (which in fact tends to increase the proportion of dyed hair results, because that’s how linguistic vector similarity works sometimes) and ’natural’ (which again seems to translate into ’the most natural looking unnatural’, because that’s how language tends to be used).


Ed Sheeran seems to have gone from objectively awful to subjectively passable. There is a clip of him on british TV host Graham Norton’ show playing a recording of some pretty terrible singing.

https://www.google.com/search?q=ed+sheeran+graham+norton+bad...


Shouldn't there be many examples though?

There's so many examples of famous fat people that got skinny. I really struggle with this idea that it's all just muscle / muscle control to sing well under the lack of examples.


What kind of tools would you need to dump the ram of a locked macbook with disc encryption on? Seems like a pretty advanced microsoldering job. Facilities, equipment and skill requirements would limit this to extremely high profile investigations surely?


The author of the blog made his name and fortune founding Hashicorp, makers of Vagrant and Terraform among other things. Having done all that in his twenties he retired as the CTO and reappeared after a short hiatus with a new open source terminal, Ghostty.


I think you are right in placing emphasis on delegation.

There’s been a hypothesis floating around that I find appealing. Seemingly you can identify two distinct groups of experienced engineers. Manager, delegator, or team lead style senior engineers are broadly pro-AI. The craftsman, wizard, artist, IC style senior engineers are broadly anti-AI.

But coming back to architects, or most professional services and academia to be honest, I do think the term vibe architect as you define it is exactly how the industry works. An underclass of underpaid interns and juniors do the work, hoping to climb higher and position themselves towards the top of the ponzi-like pyramid scheme.


What’s your voice interface setup like? Local inference or cloud service?


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