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ALR

@ALRubinger

Self-employed by the guy who ran open source programs @blocks, @apple, @redhat. Building the plane as we fly https://t.co/E1NdEX8WFS.

Calichusetts Katılım Ocak 2009
1.7K Takip Edilen5.5K Takipçiler
ALR
ALR@ALRubinger·
@thericebowlgirl You can ignore first principles until they bite ya
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Neha Kalani
Neha Kalani@thericebowlgirl·
quick update on how this is going: they have gone back to linear because maintaining their internal tool that they vibecoded was taking away from their actual work’s bandwidth.
Neha Kalani@thericebowlgirl

an employee at this startup that my sister works at, made their own JIRA - they've all fully discarded JIRA/Linear/Trello, and are using their own tool. It's faaar better than JIRA and is just as detailed. and this person is not even a developer, he leads QA.

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Kirah Sapong
Kirah Sapong@kirahsapong·
Lot of good points but also fair bit of confusion on what shared compute gets you so let’s clarify 1. Shared compute does NOT mean model gets smarter over time. Weights are frozen at inference time. You’d need something like shared memory layer or plan to post train on data 🧵
GREG ISENBERG@gregisenberg

I think the most interesting thing about Jack Dorsey's "Slack killer" is the idea around shared compute. I haven't seen people talk about it so here are my thoughts FWIW: Open models got good, close enough to the paid frontier stuff to run for real. But the strongest ones need expensive hardware most people probably won't buy alone, and it's kinda a pain to set up if you aren't technical. Shared compute solves exactly that. In Buzz, one person runs the machine, loads up an open model like Google Gemma, and everyone in the community plugs into that same model. Basically, a whole group has real AI they own and control together, running on their own hardware, learning from their own data. Once you see it, a bunch of things click into place. 1. A community can now run a top open model together, on a machine they own, instead of renting from a lab. 2. It learns from the group's private data and gets sharper over time, and all of that stays inside the community. 3. A narrow, private model can quietly get better than ChatGPT for the one world your group lives in. 4. It's impossible to copy, because the edge is the private data on your machine, not the model itself. 5. The moat stops being how smart your AI is and becomes whose data it learned from. 6. Compute becomes something you share like a building shares a gym. 10 people split one machine instead of 10 people each renting forever. 7. Idle compute becomes income!!! Your machine sits dead half the day, so it earns money renting that time to someone who needs it. 8. Communities become the unit of intelligence instead of companies. The group with the smartest shared brain wins, and being a member means owning a piece of it. 9. A shared brain becomes an asset you build equity in. You put in money and data, it appreciates, and your slice is worth something the day you leave. 10. The whole thing runs on open protocols, so the group keeps full control and nobody outside can throttle it or shut it off. You know me, obviously, my head went to what startup ideas come to mind here. Adding them to @ideabrowser soon. Well… 1. The vertical brain. Pick one profession, tax lawyers or real estate agents or indie game devs, and build the shared machine trained on everything that group knows between them. A year in it's the smartest AI in that field, impossible to copy, and you own the club it lives in. 2. The rental marketplace for collective brains. Once these private models exist, outsiders will pay to use them. You build the layer where a group lists its brain, an outsider pays per task, and the money flows back to the members while you take a cut. A marketplace for expertise, not compute. 3. The idle-compute exchange. Every shared machine sits unused half the day. You build the market that rents that dead time to whoever needs the power right then, so owners earn money off a machine that was just sitting there. Idk where Buzz goes, but it's cool to see Jack putting it out. Right now the way it works in AI is you rent your intelligence from a few giant labs that own the machine, set the price, and hold the off switch. Shared compute flips that, because a community can run the model together, feed it their own private data, and keep full control of the whole thing. It's one of those things that might look tiny today, but Jack does has a habit of being early.

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ALR@ALRubinger·
@chrismattmann Slowly then suddenly, and suddenly was … today?
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ALR@ALRubinger·
Open source is the best engine of innovation on the planet
Jensen Huang@JensenHuang

For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models. images.nvidia.com/pdf/Open-Weigh…

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ALR@ALRubinger·
I was adamant as lead of the @blocks OSPO that we give the company self-service open source. Anyone should be free to get moving on a new project in the open from the beginning. Thrilled that buzz.xyz was born from this.
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ALR
ALR@ALRubinger·
@davemorin This is the origin story of GNU and arguably open source. Freedom to own and control your hardware 🫡 From laser printers to June ovens LFG
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ALR
ALR@ALRubinger·
@avycadotoast What in the Fiddler on the Roof is going on here
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avy
avy@avycadotoast·
i have a friend who can’t get married to her boyfriend anytime soon because the boyfriend has an elder sister who isn’t married yet. and why isn’t the elder sister married yet? because HER boyfriend also has an elder sister who isn’t married yet
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Jason Zhou
Jason Zhou@jasonzhou1993·
how do you keep todo/backlog for your agents? especially all wip ideas you got while chatting to agents?
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ALR@ALRubinger·
Another thing give been thinking a lot about with multiplayer is context. Context is the only thing that any org has that’s uniquely their value. And the only thing that makes agents extra effective. You want: Access to all the context Loaded at the right time Available to the right people in your org Buzz has a brilliant context model, congrats y’all
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ALR@ALRubinger·
Block team is really on to something with Buzz. I’ve been building Aileron around core principles: separating auth from the agents, making all artifacts auditable and cryptographically verifiable. Multiplayer and free of frontier lab lock in is the way forward.
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ALR@ALRubinger·
I think more likely: Build the product that folks can BYOAgent to - and load it with context and tools necessary for it to do the job. Commoditize the LLMs, commoditize the agents, make each org successful on what only it can do
dax@thdxr

the agent you're building into your product is most likely not going to work just drop it, what's going to happen is there will be a few agent products that individuals and teams choose to use and they will want everything there. might mean they don't even want your product

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ALR@ALRubinger·
@tlongwell_bzz Nice one T, congrats on the writeup and launch
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Tyler Longwell 🐝
Tyler Longwell 🐝@tlongwell_bzz·
Your agents have been working solo. Time they joined the hive. Buzz is an open-source workspace for humans and AI agents, on a relay you own. Come see what all the Buzz is about! engineering.block.xyz/blog/buzz
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ALR@ALRubinger·
@jack Allright team, who's gonna share the Buzz origin story?
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jack
jack@jack·
we're launching BUZZ! a new groupchat platform for teams of people and agents of all sizes, built to reduce our dependency on slack and github. model-agnostic, decentralized, self-sovereign, and open source. 🐝 buzz.xyz
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ALR@ALRubinger·
@maxandersen Huge congrats, Max! 🤘🏻
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Max Rydahl Andersen
Max Rydahl Andersen@maxandersen·
🎉 JBang just passed 3 MILLION binary downloads! A 2019 experiment — "why should running a small Java program need a whole project?" quietly became Java infrastructure. ~1,000 downloads/day, 130+ countries, From Java 8 to 26+ Thank you 🙏 jbang.dev/learn/somehow-…
Max Rydahl Andersen tweet media
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Josh Long
Josh Long@starbuxman·
@nmcl Mark! You were amazing in the @java documentary my friend! Mind DM’ing me your SMS so I don’t have to use this cursed platform to talk to you?
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ALR@ALRubinger·
@adisingh Adi, I’m down. Got some ideas. 🤘🏻
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Adi Singh
Adi Singh@adisingh·
In LA for the weekend! Who are some cool founders/startups we should meet? So excited
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ALR@ALRubinger·
The algorithm changes feel great, and they shouldn’t. They prove how one company’s incentives are bad for the one thing this platform was built to do: connect people. This is a poor town square and they don’t deserve to be our stewards.
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ALR@ALRubinger·
Feels like our agents mirror our own competence. They amplify what you're good at. My background is in making application servers. The code I do now is backed with unit and system tests, has clear goals, is well-specified. At the same time, the horror that is my front-end design remains. And I know pros are getting much more out of their agents on this than I am.
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