@kellogh@hachyderm.io
@kellogh@hachyderm.io avatar

kellogh

@kellogh@hachyderm.io

I'm a software engineer and sometimes manager. Currently #Raleigh but also #Seattle. Building ML platform for a healthcare startup. Previously, built an IoT platform for one of "those" companies.

Open source: dura, fossil, Jump-Location, Moq.AutoMock, others

Do I have other interests? No, but I do have kids and they have interests. I think that counts for something. I can braid hair and hunt unicorns!

I put the #rust in frustrate

He/Him

#metal #science #python

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kellogh, to random
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RFK, you seem angry, what’s eating at you?
https://infosec.exchange/

kellogh, to random
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are there mastodon clients that are scriptable?

i keep wishing for something good, like @ivory, but extremely customizable that lets me display toots differently, or filter in non-standard ways, or include links to resources that others might not find useful

mistersql, to random
@mistersql@mastodon.social avatar

Does anyone have the name for the process in IT where the friction involved in using a service is ratcheted up so high and so fast that everyone stops using it?

Like developer ghettos that take 15 minutes to just log into them via multiple jumpboxes to get to a machine with no internet access, chat/email apps that only work in incognito browser & the auth expires daily, air gapped machines at an office.

kellogh,
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@mistersql “shadow IT” is related, not quite the same

kellogh,
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@tribaal @mistersql i was thinking shadow IT is the outcome of this.

carnage4life, to random
@carnage4life@mas.to avatar

Last week, a Nigerian PM that I mentor mentioned layoffs happening at Microsoft in Nigeria but I didn’t expect them to shut down the entire development center and lay off everyone.

It’s not surprising given the layoffs across the industry but it is disappointing.

kellogh,
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@carnage4life i don’t understand, why is this not surprising? i would think they’d be expanding there

kellogh, to LLMs
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i used an analogy yesterday, that are basically system 1 (from Thinking Fast and Slow), and system 2 doesn’t exist but we can kinda fake it by forcing the LLM to have an internal dialog.

my understanding is that system 1 was more tuned to pattern matching and “gut reactions”, while system 2 is more analytical

i think it probably works pretty well, but curious what others think

kellogh,
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@Lobrien i would have written the same thing but you beat me to it

jeremydmiller, to random
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As an OSS maintainer, the best pull requests are fixes to problems you didn't even know existed

kellogh,
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@jeremydmiller that’s the majority of contributions i make these days to other people’s projects. i got stuck on something, looked at the code, the fix seemed pretty easy

kellogh, to ai
@kellogh@hachyderm.io avatar

Experiments and discussion of various UX approaches to displaying code generation suggestions

Personally, the big problems I have with are

  • “this change is crap, except this line here, give me just that”
  • changes that are poorly integrated into the file
  • the chat never has the right context, so conversations tend to be circular or unhelpful

https://austinhenley.com/blog/intellicode.html

kellogh, to random
@kellogh@hachyderm.io avatar

Left: what Trump thinks the Bible says
Right: what the Bible actually says

quote: 38 “You have heard that it was said, ‘Eye for eye, and tooth for tooth.’[a] 39 But I tell you, do not resist an evil person. If anyone slaps you on the right cheek, turn to them the other cheek also. 40 And if anyone wants to sue you and take your shirt, hand over your coat as well. 41 If anyone forces you to go one mile, go with them two miles. 42 Give to the one who asks you, and do not turn away from the one who wants to borrow from you.

unclepj, to random
@unclepj@zirk.us avatar

Ok, question. Why do we say Attorney at Law? Is there some other kind? Like Attorney at Having a Good Time or Attorney at Snowboarding?

May I suggest Attorney at Napping? That’s something I could get behind.

kellogh,
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@unclepj @futurebird attorney inlaw is what you call your wife’s divorce attorney

anthrocypher, to random
@anthrocypher@hachyderm.io avatar

For sometimes very good reasons, leaders right now are scared of dealing with extended constituencies. But they're also the only way to build something with outsized impact in an internet age.

I don't love VC-scale businesses for their own sake, but I do love the internet.

kellogh,
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@anthrocypher what’s an extended constituency?

kellogh,
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@anthrocypher oh! i like this way of thinking about it. especially the control angle. that’s powerful

w7voa, to random
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A major witness expected to take the stand today in NYC in Donald Trump's criminal trial: Stormy Daniels.

kellogh,
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@w7voa there’s video of this testimony, right? RIGHT??

kellogh, to stackoverflow
@kellogh@hachyderm.io avatar

i wonder what the thinking is, for to sell their data to

on the one hand, it feels a lot like the company is being stripped for parts. on the other, openai was probably doing it anyway, so now at least they get paid for it

either way, this seems like a new era

kellogh,
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@ChrisHunt yeah, it smells like leadership that’s unwilling to find another path. which makes sense, ever since the founders sold it, it’s been run by the MBA mindset

kellogh, to random
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Great paper! Also a great reminder that (artificial) neural networks are still quite useful for studying real brains, because they can help model and study questions like, “how did this phenomenon come to be?”
https://neuromatch.social/@dlevenstein/112395909323594371

norootcause, to random
@norootcause@hachyderm.io avatar

One of the most important skills is knowing where to direct your attention when you’re under load.

kellogh,
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@norootcause fwiw ADHD is the inability to do this

AnnemarieBridy, to random
@AnnemarieBridy@mastodon.social avatar

I’d be curious to know what effect, if any, this change has on a relatively large LLM’s likelihood of outputting strings of text that are memorized from training data sources.

Meta multi-token prediction makes LLMs up to 3X faster | VentureBeat https://venturebeat.com/ai/metas-new-multi-token-prediction-makes-ai-models-up-to-3x-faster/

kellogh,
@kellogh@hachyderm.io avatar

@AnnemarieBridy the way i understood the paper, it wouldn’t change much, but there’s a lot of variables, like the increased data efficiency also means there’s less training data to reference, but theoretically without increasing overfitting (quoting the source)

kellogh,
@kellogh@hachyderm.io avatar

@paninid @AnnemarieBridy are you serious?

kellogh,
@kellogh@hachyderm.io avatar

@paninid @AnnemarieBridy latency touches every part of every business case

  • environmental impact is less
  • cost is less
  • interactive apps see drastically better user experience
  • some applications weren’t possible but are enabled by lower latency

if you don’t understand the user experience impact, try using Groq at 500 tokens/s https://groq.com/

kellogh,
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@paninid @AnnemarieBridy Little’s Law is doing the work here — if you cut latency 1/3 and keep the amount of work the same, you also can cut the number of servers to 1/3

kellogh,
@kellogh@hachyderm.io avatar

@paninid @AnnemarieBridy i don’t think that’s a logical step you can make. the largeness gives it the “general” capabilities, where you don’t have to train it for a specific task. most enterprises are using LLMs via RAG, i.e. they have no need to train their own model. one of the benefits of LLMs in general is that model training is left to the people who are best at it, and everyone else just uses databases

deech, to random
@deech@mastodon.social avatar

I've moved to Raleigh,NC. I would love to connect/hangout/talk tech. If you're in the Triangle area hit me up!

kellogh,
@kellogh@hachyderm.io avatar

@deech oh hey! i’m in Raleigh too. Moved a couple years ago. Would love to catch up

kellogh, to rust
@kellogh@hachyderm.io avatar

ooo promising new framework. Check out the ad! 😂 https://youtu.be/YpHFthVa7nU?si=QCJHyg7_dEmBeGTu

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