
mark
2.6K posts

mark
@thisisnotmark_
AI/ML Research Lead @ NASA | Founder @ Mosaic Voice AAC. Views my own not my employer’s.
Katılım Şubat 2015
1.5K Takip Edilen545 Takipçiler
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will be presenting my paper “Life, Machine Learning, and the Search for Habitability: Predicting Biosignature Fluxes for the Habitable Worlds Observatory” tomorrow at #AAAI. if anyone at AAAI wants to meet for coffee let me know!
arxiv.org/abs/2601.12557
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If you’re seeing this… this is your sign.
Take the next giant leap in your future by applying for an internship, where students work on real NASA projects, build technical and professional skills, and learn directly from NASA mentors: go.nasa.gov/4tSQNdU

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anyone at OpenAI, PLEASE take the fallback hell and the code bloat the model produces as seriously as you probably are with UI/UX. it’s a real problem and it’s single handedly the biggest annoyance and time sink of working with codex today. it needs to know when to delete and remove stuff instead of always adding and adding and adding
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somebody should make a skill that runs daily that gets updated info about security vulnerabilities from a trusted source(s) to seed one’s agents so that it knows to avoid these
Ryan Carson@ryancarson
🚨 There's a major attack going on via npm right now. Do not install any packages right now. Talk to your agent ASAP and check if you're vulnerable or have been compromised. This is urgent ‼️
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I see things going this way but it is an increasingly scary prospect. when I do dip down into the code often times I see such dirty and hacky workarounds. but often they don’t actually hurt performance in that moment, just human readability and my propensity for writing clean code. but do I fight against that, or accept that this is how things are and let it do its thing, while only steering for functionality, system architecture, overall objective, instead of ALSO clean and aesthetically pleasing code?
François Chollet@fchollet
Agentic coding is a form of machine learning. Generated code is best treated as a blackbox artifact whose behavior and generalization should be managed via empirical evaluation, like with any ML model.
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I also love building iPhone apps with Codex
Thomas Ricouard@Dimillian
I also love building iPhone app with Codex too
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I think I’m converging on the same thing. I think there’s too much cognitive load reading every intermediate step between prompts, especially when you add iterating over the markdown plan in the first place. it becomes too much to read, and then you’re trying to manage several agents at once.
I like to sit at the prompting level until the feature is working superficially and then dig deep into the code and figure out how specifically I’d like it to refactor. I usually catch a few things that where I hate how the agent went about it. then I dig really deep once the PR is made.
if the feature isn’t working well after a few iterations though, I will step in because usually that’s when the agents start patching things in hacky workaround ways and then all hell breaks loose if you don’t cut that at the head
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@thisisnotmark_ good question. i found the middle ground works best - review at feature completion, not every prompt. the agent needs room to iterate but you catch issues before its too deep. i checkpoint more frequent on new components, less on refactors. what worked for you
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@thsottiaux did the 10x usage increase from the party or promotion get removed somehow? I noticed my rate limit got cut in half, and others have as well (see here: reddit.com/r/codex/commen…)
my account page also doesn't mention the temp 10x increase
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@AllanatrixQ you in DC? been wanting to start/attend an AI for Science meetup out here. there are probably at least like 8 of us here
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