Thanks for the heads up! App error it seems, tried to clean it up.

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Absolutely, but also the attorney from Devil’s Attorney

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Interesting points, maybe a book I’ll have to give a read to. I’ve long thought that information overload on its own leads to a kind of subjective compression and that we’re seeing the consequences of this, plus late stage capitalism.

Basically, if we only know about 100 people and 10 events and 20 things, we have much more capacity to form nuanced opinions, like a vector with lots of values. We don’t just have an opinion about the person, our opinion toward them is the sum of opinions about what we know about them and how those relate to us.

Without enough information, you think in very concrete ways. You don’t build up much nuance, and you have clear, at least self-evident logic for your opinions that you can point at.

Hit a sweet spot, and you can form nuanced opinions based on varied experiences.

Hit too much, and now you have to compress the nuances to make room for more coarse comparisons. Now you aren’t looking at the many nuances and merits, you’re abstracting things. Necessary simulacrum.

I’ve wondered if this is where we’ve seen so much social regression, or at least being public about it. There are so many things to care about, to know, to attend to, that the only way to approach it is to apply a compression, and everyone’s worldview is their compression algorithm. What features does a person classify on?

I feel like we just aren’t equipped to handle the global information age yet, and we need specific ways of being to handle it. It really is a brand new thing for our species.

Do we need to see enough of the world to learn the nuances, then transition to tighter community focus? Do we need strong family ties early with lower outside influence, then melting pot? Are there times in our development when social bubbling is more ideal or more harmful than otherwise? I’m really curious.

Anecdotally, I feel like I benefitted a lot from tight-knit, largely anonymous online communities growing up. Learning from groups of people from all over the world of different ages and beliefs, engaging in shared hobbies and learning about different ways of life, but eventually the neurons aren’t as flexible for breadth and depth becomes the drive.

Oh yeah, the 365 version is terrible. And post of the time, it could have been a Python Gradio interface or similar simple implementation without having to fight so much to make basic things work. Most of what I want Excel to do it just isn’t efficient enough for; particularly with lets and lambdas, it’s gotten quite powerful as a programming paradigm where you can visualize and manipulate your data spatially in a kind of Logo / NetLogo style way which is really interesting, but the second you reference a few thousand cells a few times even a solid CPU starts screaming.

I use Excel for a decent number of tasks and can do some magic with it, but only ever really for work where it’s easier to share a weird Excel sheet than it is to pass around a Python script (which given I teach Python, isn’t actually as often as most people experience).

But what about those of us in R1C1 mode using lambdas to do recursive cell operations across data pulled from multiple sheets? Am I anywhere near the kinda of Eldritch horrors discussed? I’ve also written indirect references based on Sheet name to populate filters from web scraped tables. I just don’t know how deep the pit goes at this point.

From Lisa Explains it All to becoming a computer science professor I feel this in my bones.

C could just be a blank and you have to bit blit the arrow on yourself.

I don’t know why, but I still can’t open a core file without going I’m in. I don’t do QA, though, and so tinkering with final breath of my program frozen in time maintains some novelty.

My two cents, after years of Markdown (and md to PDF solutions) and LaTeX and a full two years of trying to commit to bashing my head against Word for work purposes, I’m really enjoying Typst. It didn’t take long to convert my themes, having docs I can import which are basically just variables to share across documents in a folder has been really helpful. Haven’t gone too deep into it but I’m excited to give it a deeper test run over the next little bit.

Lots of immediate hate for AI, but I’m all for local AI if they keep that direction. Small models are getting really impressive, and if they have smaller, fine-tuned, specific-purpose AI over the “general purpose” LLMs, they’d be much more efficient at their jobs. I’ve been rocking local LLMs for a while and they’ve been great as a small compliment to language processing tasks in my coding.

Good text-to-speech, page summarization, contextual content blocking, translation, bias/sentiment detection, click bait detection, article re-titling, I’m sure there’s many great use cases. And purely speculation,but many traditional non-llm techniques might be able to included here that were overlooked because nobody cared about AI features, that could be super lightweight and still helpful.

If it goes fully remote AI, it loses a lot of privacy cred, and positions itself really similarly to where everyone else is. From a financial perspective, bandwagoning on AI in the browser but “we won’t send your data anywhere” seems like a trendy, but potentially helpful and effective way to bring in a demographic interested in it without sacrificing principles.

But there’s a lot of speculation in this comment. Mozilla’s done a lot for FOSS, and I get they need monetization outside of Google, but hopefully it doesn’t lead things astray too hard.

Yeah, this is the approach people are trying to take more now, the problem is generally amount of that data needed and verifying it’s high quality in the first place, but these systems are positive feedback loops both in training and in use. If you train on higher quality code, it will write higher quality code, but be less able to handle edge cases or potentially complete code in a salient way that wasn’t at the same quality bar or style as the training code.

On the use side, if you provide higher quality code as input when prompting, it is more likely to predict higher quality code because it’s continuing what was written. Using standard approaches, documenting, just generally following good practice with code before sending it to the LLM will majorly improve results.

Yeah, I knew freelance folks who provided long term support with such complicated setups. The base daily rate plus hourly with a monthly retainer and weekly on call fees. Wild.

Or, hourly = extremely high paid contract work.