nour e
9.8K posts
nour e
@neldien_
currently tinkering @shotwellst yc p26 breakfast is still the most important meal of the day | prev: @roblox @mergedev @cal @tarjimly @spitrapbits
Katılım Aralık 2011
830 Takip Edilen992 Takipçiler
too much hot tubbing yall aint serious about natalmaxxing 😪
will (in sf rn)@ItsWillHenry
SF right now: - No one does Zoom. every meeting is a walk, a coffee, or somehow a hot tub. - 10 people under 22 have each raised $5M+. - Every conversation is peptides, space, or AI. sometimes all three in the same hot tub. - YC dropped a project list. 400 people pivoted within 48 hours. - Amazing weather tho
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nour e retweetledi
No one is more indignant when falsely accused of theft than a habitual thief.
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A company reached out with 30,000 workers they are collecting egocentric data on from factory workers. The workers are wearing headsets during their shifts.
Comment below and DM me if you want to be connected.
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Chronicle Labs (@chroniclelabs_) is building a staging environment for enterprise AI agents. Like trading teams backtest algorithms before deploying capital, Chronicle helps teams replay production events in sandboxes to backtest agents before real-world deployment.
Congrats on the launch, @sir_aymansaleh and @donutsandloops!
ycombinator.com/launches/QFn-c…
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nour e retweetledi
Meet Anoria.
The first wearable that reads your emotions so you can enhance your EQ.
Welcome to the EQ era.
RT + comment "EQ" to receive an invitation to pre-order.
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Ship robots, not demos
✅ SF Bay Area
✅ Broader California
⌛️USA
Coming soon to a home / hotel / laundromat near you
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@davidmarcus @messenger @Meta M was legendary. @zuhayeer and I used it in college, and we were always curious: when we asked it to draw something was it just someone on the otherwise drawing the image???
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11 years ago, I was running @messenger at @Meta, acquired wit.ai, and tried to build an AI-augmented assistant called M alongside what was then FAIR (Facebook AI Research). At the time LLMs weren’t a thing, human-in-the-loop supervised learning couldn’t scale. Demand was insane, though. People loved it. In the last few weeks, I brought M back for myself with @openclaw and it’s magical. Today’s random example below. More about this later this week…
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I've left OpenAI and the Codex team to build Blackstar: A new hardware company building the future of human-computer interaction.
We believe that software is solved. Building apps is now easy, but the next meaningful improvement in human-AI communication requires changing the OS & hardware. That's why we're building a new device entirely.
I'm also excited to announce our $12m seed round led by @AbstractVC, with participation from @naval, @SVAngel, @chapterone, and Timeless, among other amazing angels who've supported us from the old Alex days.
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Our newest model, π0.7, has some interesting emergent capabilities: it can control a new robot to fold shirts for which we had no shirt folding data, figure out how to use an appliance with language-based coaching, and perform a wide range of dexterous tasks all in one model!
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nour e retweetledi
Introducing Operator, our newest industrial AI robot built to work, not demo.
Operator handles your warehouse's most repetitive tasks: packing, sorting, and kitting. Up to 24 hours a day, with flexibility and consistency that allows businesses to scale quickly.
This is what we've been building. ↓ [1/4]
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this is some weirdo energy - why’re you freaking out about your friends making it
Samuel Spitz@samuel_spitz
Everyone I know in SF who’s not at OpenAI/Anthropic is freaking out about how their friends are about to make $5-50M with these IPOs
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we've launched 100+ spectacular connectors + we’re launching several every week, but we’re taking a more methodical approach to building each.
I broke down our team’s process here: hubs.li/Q046y7YM0
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now that it's been 2 weeks, what have you liked most about auto-memory? what's not working?
if you have specific stories of when it went well or poorly, we would love to hear!
Thariq@trq212
We've rolled out a new auto-memory feature. Claude now remembers what it learns across sessions — your project context, debugging patterns, preferred approaches — and recalls it later without you having to write anything down.
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