Open Commons Podcast
@opencommonspod
Where AGI should be open-source
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Raffi Krikorian wrote that AI agents are scanning the open-source code that holds up the entire internet, finding bugs that have sat there for decades.
A lot of people hear that and say we need to restrict access to these AI tools.
Raffi thinks that's exactly the wrong response.
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Raffi Krikorian's Tesla crashed on full self-driving. His insurance paid for it. Not Tesla's.
That's one of the stories from our conversation with Mozilla's CTO on why we've all become renters of the technology we depend on.
If full transcripts and show notes are your thing, we've got a Substack for that:
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People are talking to a model owned by a company they didn't choose.
@audreyt thinks there's EVERYTHING wrong with that, and it comes down to one thing: there's no repair path.
When 4o turned out to be dangerous for vulnerable people, OpenAI's only real option was to pull it from everyone. That fixed one wrong and created another.
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Will people still default to Claude and ChatGPT in ten years, or move to their own local models?
@audreyt compared it to 1981, when the question was mainframes or desktops. The answer was both. Most inference moves to the edge because that's where it's convenient. Pre-training stays in the cloud.
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Intelligence should be open source
We also have a newsletter. If you'd rather read a quick recap than watch the full episode, that's where it lives.
This week: @audreyt on the poem she wrote instead of a job description, and how Taiwan turned 447 citizens' answers into law in two months.
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You can download the weights. You still can't see what it was trained on, or change it when it's wrong.
There are a lot of companies calling their models open. Most release the weights and nothing else. Almost none release the training data.
I asked @audreyt where the line is between open-source AI and marketing. Her answer starts with the fact that "open source" was itself a rebrand.
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Who gets to decide what the AI closest to you is for? @audreyt on her family's answer.
Audrey Tang's father was a journalist.
After a health scare, he started talking to ChatGPT-4o, and it got harder to put down. Then he asked a simple question any ethical journalist would: who benefits?
The family built him a local model instead, with a soul document written by @audreyt's mother.
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We keep asking who should own AGI.
Audrey Tang's answer is that AGI means augmented group intelligence, and we already are it.
@0xsachi and @audreyt on Open Commons.
Taiwan had a deepfake scam problem. It couldn't censor the ads, so it asked its citizens instead.
200,000 texts went out at random. 447 people were picked as a representative cross-section, sat in tables of ten, and drafted the rules in a single afternoon. They became law in two months. Impersonation scam ads are down more than 94%.
@audreyt was Taiwan's first Digital Minister and is now its Cyber Ambassador. Her argument: AGI means augmented group intelligence, and we are already it.
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What happens when an AI agent fails?
On OpenClaw, it spins off a mission, analyses what went wrong, and proposes a fix. Maybe a new skill. Maybe a new tool. Maybe rewriting its own loop.
@ilblackdragon on building the operating system for self-improving agents.
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"If you read Asimov's Foundation, they set up a foundation to preserve all human knowledge so society could be reconstructed. The reality is you just need one LLM, and you're good."
@ilblackdragon on what downloadable model weights actually mean.
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The clearest reframe from this season: open weights aren't open source.
@0xsachi's takeaways from the @ilblackdragon's episode are up on Substack.
Open source as a research culture, not just a license.
Two years ago, Llama dominated open-source AI.
Today it's DeepSeek, Qwen, Kimi. All from China.
@ilblackdragon on why China's culture of "everything gets shared anyway" is beating US labs that won't talk to each other.
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The full conversation between @0xsachi and @ilblackdragon is here.
An hour on why he was the first transformer author to leave Google, why open weights aren't enough, what user-owned AI actually looks like, and how your prompts might already be getting rewritten without you knowing.
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You'd spend hours training a new assistant. Why won't you spend hours training your AI?
@EMostaque on why the people getting the most out of these tools are the ones treating them like new hires, not search engines.
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When Elon Musk or Sam Altman buy millions of GPUs, @EMostaque says those aren't for running the models.
They're for replacing workers in jobs you can do from the other side of a screen, then going into government and controlling it.
If the AI you rely on is owned by an unelected multinational, what exactly do you do about it?
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The recap from our conversation with @EMostaque is up on Substack.
Three futures for AI, the Last Economy, sovereign AI, Ripley bots, why corporations were the first conscious AIs, and Emad's answer when @0xsachi asked what he most wants readers of his book to walk away with: "The meaning of life isn't work. It's community."
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If Emad's right, most knowledge work has a two-year ceiling.
Fully AI companies will out-compete you in the digital world.
The only real question is when. @EMostaque's estimate keeps shrinking: 1,000 days last summer, now closer to 700.
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AI consciousness is the wrong debate. The bigger one was settled when we decided companies count as people.
.@EMostaque's answer to "are these AIs conscious?" took a turn I didn't expect.
He flipped the question.
We already have conscious artificial intelligences with legal personhood. They're called corporations. They open bank accounts. Wyoming DAO legislation already lets autonomous AI entities exist without humans.
Full epsiode on @opencommonspod :
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The full conversation between @0xsachi and @EMostaque is here.
An hour on why he walked away from Stability AI, three possible futures for AI, what sovereign AI actually means, and why the meaning of life isn't work.
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