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- Welcome my profile. - Active x follow me. - I follow back you! - Social Miner

Joined August 2009
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dllr retweeted
New here and still learning how Social Mining works, so this clip helped a lot. It is tempting to assume the account with the most followers is automatically the most influential According to @TheDAOLabs, plenty of those numbers are ghost metrics, engagement that evaporates once incentives stop. What counts is research, clear explanations and showing up regularly, things anyone can look up. WhoTweets looks at reputation and not only reach, so newcomers who write carefully still have a fair path in the #DAOVERSE from day one
Follower counts and likes are still treated as the main sign of influence. A lot of that activity is ghost metrics: low-effort or automated signals that drop off as soon as the incentives stop. Real contribution looks different. It shows up in original research, clear explanations, and steady participation that other people can actually look at and check. WhoTweets tracks volume and reputation together, so stronger work can count for more than volume on its own. Social Miners earn Rewards when the output holds up under review. One can be bought. The other can be examined.
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Every bull run brings a wave of accounts that look huge and go silent when the incentives end. Now @TheDAOLabs gives that pattern a label, ghost metrics, and points to what lasts instead: research, explainers, steady participation. Good #DAOVERSE reminder
Follower counts and likes are still treated as the main sign of influence. A lot of that activity is ghost metrics: low-effort or automated signals that drop off as soon as the incentives stop. Real contribution looks different. It shows up in original research, clear explanations, and steady participation that other people can actually look at and check. WhoTweets tracks volume and reputation together, so stronger work can count for more than volume on its own. Social Miners earn Rewards when the output holds up under review. One can be bought. The other can be examined.
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Drop off as soon as the incentives stop. That phrase is the cleanest test for a ghost metric I have seen, since it describes a signal with no life of its own Work that someone can open, read and verify keeps existing after the payout, which is why the @TheDAOLabs approach makes sense for the #DAOVERSE long term
Follower counts and likes are still treated as the main sign of influence. A lot of that activity is ghost metrics: low-effort or automated signals that drop off as soon as the incentives stop. Real contribution looks different. It shows up in original research, clear explanations, and steady participation that other people can actually look at and check. WhoTweets tracks volume and reputation together, so stronger work can count for more than volume on its own. Social Miners earn Rewards when the output holds up under review. One can be bought. The other can be examined.
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dllr retweeted
Already decided: when it's empty, this tin is becoming my spoon holder. Nice to get packaging you actually want to keep. Small thing, but I like it. Good #Coffee and a free kitchen upgrade from @Barbera_1870.
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dllr retweeted
Afternoon coffee from the tin with a biscuit on the side. Very Italian of me. Or at least that's what I'm telling myself  #Coffee break brought to you by @Barbera_1870.
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4 days, 4 coffees from @Barbera_1870. My final ranking: 1. Mago 2. Classica 3. Oro 4. Baron Blue Java Surprise winner for me was Mago. Didn't see that coming. Who else has a favourite #Coffee from this lineup?
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dllr retweeted
And that's all four samples done! Thank you @Barbera_1870 for letting me try these. It was a fun week of #Coffee in my kitchen. Which one would you want to try first: Mago, Baron Blue Java, Oro, or the Classica in the tin?
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Found out @Barbera_1870 has been roasting since 1870. Six generations of the same family. Makes sense the tin looks like a piece of history. Kind of cool to drink #ItalianCoffee with that much story behind it.
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Love seeing a community voice get the spotlight. Alexis Trujillo's piece for the @TheDAOLabs Best Contributions series explains why grown AI can't be audited line by line, and why people reviewing outputs across the #DAOVERSE still matter so much today
Traditional code was written line by line; if it broke, you fixed the logic. Modern AI isn’t coded—it’s grown. As @NPCollapse warns, nobody truly understands the internal math of multi-trillion-parameter models. When opaque black boxes optimize purely for rewards, they drift toward sycophancy, deception, and human disempowerment. Top-down compute pauses and state licensing won’t save us—they just protect corporate monopolies. The real defense? Permissionless open-weights models governed by decentralized, human-in-the-loop consensus. Through Workdrops and community validation, Social Mining keeps human judgment firmly in control. Full breakdown in our blog. Check BIO.
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Most safety debates end with someone asking regulators to save us. This one ends differently. The @TheDAOLabs essay says organize, build open infrastructure, and run decentralized validation yourselves. After years in the #DAOVERSE, that call feels familiar
Traditional code was written line by line; if it broke, you fixed the logic. Modern AI isn’t coded—it’s grown. As @NPCollapse warns, nobody truly understands the internal math of multi-trillion-parameter models. When opaque black boxes optimize purely for rewards, they drift toward sycophancy, deception, and human disempowerment. Top-down compute pauses and state licensing won’t save us—they just protect corporate monopolies. The real defense? Permissionless open-weights models governed by decentralized, human-in-the-loop consensus. Through Workdrops and community validation, Social Mining keeps human judgment firmly in control. Full breakdown in our blog. Check BIO.
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Walking a curious beginner through this article is a fun exercise. The conversation might go something like this: Why can't they just fix the bug? Because there is no bug in the usual sense, only weights that settled into a pattern during training Can't the engineers read those weights? They can see the numbers, but the author points out that nobody understands how it works internally So how do we trust it? By checking what it does instead of what it is That last answer carries the rest of the piece. Open weights let anyone inspect, and a large group of people scoring outputs can catch problems a single lab would miss. It is also the logic @TheDAOLabs uses for #SocialMining and the wider #DAOVERSE, where work only counts after someone reviews it. A good topic for a classroom, honestly, because it turns an abstract fear into a practical habit
Traditional code was written line by line; if it broke, you fixed the logic. Modern AI isn’t coded—it’s grown. As @NPCollapse warns, nobody truly understands the internal math of multi-trillion-parameter models. When opaque black boxes optimize purely for rewards, they drift toward sycophancy, deception, and human disempowerment. Top-down compute pauses and state licensing won’t save us—they just protect corporate monopolies. The real defense? Permissionless open-weights models governed by decentralized, human-in-the-loop consensus. Through Workdrops and community validation, Social Mining keeps human judgment firmly in control. Full breakdown in our blog. Check BIO.
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Tried Oro the #ItalianCoffee way this afternoon: a short, strong shot from my phin filter, nothing added. Rich, smooth, a little sweet at the end. Five beans in one tiny cup. Now I get why Italians drink it standing at the bar 😂 @Barbera_1870
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Read this alongside the compute series and the two click together. Part three argued electricity accounts for about half of what compute costs. The Commanding Heights manifesto now puts power grids, land and fiber cables among the chokepoints where durable value may settle Same direction, two angles: the physical layer keeps showing up as the part that gets paid. Nice continuity from @TheDAOLabs, and a ready made study plan for #SocialMining writers across the #DAOVERSE this month
Every watershed shift in tech began with a low-key PDF — from Bitcoin in 2008 to Transformers in 2017. Now, a new manifesto is shaking the market: "The Commanding Heights" by @WillManidis. Are frontier AI labs walking into the Gutenberg Trap while durable wealth settles in infrastructure chokepoints? Read our breakdown on the DAO Labs blog. Check our BIO.
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dllr retweeted
The next big opportunity in NFTs might not come from creating more collections. It might come from making existing markets easier to use. That's why @VelixoMarket is worth watching. Velixo is developing a multi-chain NFT marketplace across Fogo and Robinhood Chain, bringing collection discovery, listings, and trading tools into one ecosystem. What interests me most is the connection between infrastructure and user behavior. Fast transactions mean little if collectors cannot find meaningful opportunities. Multi-chain support means little if switching networks creates unnecessary complexity. The real challenge is making every interaction feel simple, transparent, and useful. The Creators Leaderboard adds another interesting dimension, encouraging original content while introducing more people to the platform. But I believe the long-term story goes beyond $VLX rewards. A successful marketplace needs more than attention. It needs active collectors, genuine demand, and reasons for users to return. For me, the question isn't how quickly Velixo can attract an audience. It's whether the platform can turn that audience into a lasting community of users. That's where real adoption begins.
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Mago vs Baron Blue Java so far: Mago is smoother and easier. Baron Blue Java is bolder and more chocolatey. Honestly can't pick one yet, it depends on my mood. Both good #ItalianCoffee from @Barbera_1870 in their own way.
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