Quick question for anyone who has run a campaign: how many of those likes were still around a month later?
This new post calls that fading activity ghost metrics and argues real contribution is the kind other people can check. Research, explainers, consistently showing up. In #SocialMining, Rewards from @TheDAOLabs follow work that passes review, which feels like the right incentive
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.
Can we just look at this tin for a second?
It looks like something from an old Italian grocery shop. I'm definitely keeping it after the coffee's gone. @Barbera_1870 knows how to make #ItalianCoffee look good.
The Classica blend is the boldest of the four for me.
Strong, a little tangy at the end, and it stays with you. Really good with milk. If you like your #Coffee with personality, this is the one from @Barbera_1870.
pingder retweeted
Vietnamese phin filter + the Barbera Can = my new favourite morning photo
Sorry, not sorry for all the coffee pictures this week. Blame @Barbera_1870 for making #ItalianCoffee look this nice.
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.
Opened the Barbera Can and the smell is strong! Intense, a little chocolatey.
Moka pot is going. This is the one I'm most curious about taste-wise. Final #Coffee of the @Barbera_1870 samples, let's see.
Engineers will feel this one in their bones: there is no single line to open and audit. Every debugging habit we have assumes the fault has an address, a file, a function, a commit. Training spreads behaviour across trillions of weights, so that address simply does not exist, and this write up from @TheDAOLabs admits better tools may not close the gap soon. Worth a read for anyone in the #DAOVERSE who still treats interpretability as solved
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.
Breakfast at my favourite Banh Cuon Trung spot, with a hot cup of Oro I brought from home 😅
Soft rice sheets, egg, warm broth, and a smooth #coffee that doesn't overpower any of it. Perfect Lạng Sơn morning. Thanks @Barbera_1870
Breakfast at my favourite Banh Cuon Trung spot, with a hot cup of Oro I brought from home 😅
Soft rice sheets, egg, warm broth, and a smooth #coffee that doesn't overpower any of it. Perfect Lạng Sơn morning. Thanks @Barbera_1870
Two curves moving in opposite directions explain most of this thesis. Per the figures the article cites from Max Munro's video, model capability gets about 13 times cheaper each year while the cost to build frontier AI roughly triples
If both hold, selling access at $20 a month cannot fund multi billion R&D, and margin migrates to whoever owns the pipes. A clear technical framing from @TheDAOLabs, and a good #SocialMining exercise: check those two curves against your own sources
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.
Two curves moving in opposite directions explain most of this thesis. Per the figures the article cites from Max Munro's video, model capability gets about 13 times cheaper each year while the cost to build frontier AI roughly triples
If both hold, selling access at $20 a month cannot fund multi billion R&D, and margin migrates to whoever owns the pipes. A clear technical framing from @TheDAOLabs, and a good #SocialMining exercise: check those two curves against your own sources
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.
#GoodMorning! Day 2 of trying the @Barbera_1870 samples.
Today it's Baron Blue Java, 100% Robusta from a single estate in Java, Indonesia. Apparently they only make about 50 bags of it a year, so no pressure 😅 Let's go 💪
Peak numbers on a spec sheet are the most misleading figures in compute, and the third part of the DAO Labs compute series explains why in one paragraph
FLOPs measure floating point operations per second. In theory they let you compare NVIDIA, AMD Instinct and custom TPUs on one scale. In practice that theoretical math gets stranded. If memory bandwidth can't feed the chip fast enough, or the compiler is weak, the arithmetic units sit waiting
So a FLOP figure tells you the ceiling, not the floor. It is the same reason the GPU-hour, despite its own flaw (time doesn't guarantee throughput), stays the default contract unit, with indices layered on top to normalize the gaps
The takeaway for anyone writing #SocialMining research on AI networks: quote peak specs only next to the bottleneck that limits them. Readers in the #DAOVERSE deserve the floor as well as the ceiling, and @TheDAOLabs gave us the vocabulary to say it
Peak numbers on a spec sheet are the most misleading figures in compute, and the third part of the DAO Labs compute series explains why in one paragraph
FLOPs measure floating point operations per second. In theory they let you compare NVIDIA, AMD Instinct and custom TPUs on one scale. In practice that theoretical math gets stranded. If memory bandwidth can't feed the chip fast enough, or the compiler is weak, the arithmetic units sit waiting
So a FLOP figure tells you the ceiling, not the floor. It is the same reason the GPU-hour, despite its own flaw (time doesn't guarantee throughput), stays the default contract unit, with indices layered on top to normalize the gaps
The takeaway for anyone writing #SocialMining research on AI networks: quote peak specs only next to the bottleneck that limits them. Readers in the #DAOVERSE deserve the floor as well as the ceiling, and @TheDAOLabs gave us the vocabulary to say it
Okay, first cup of Mago done.
So smooooth! Like, properly smooth, not bitter at all. I expected something super intense because it's Italian, but it's more round and cozy than strong. Nice start to this little #ItalianCoffee tasting from @Barbera_1870.
Okay, first cup of Mago done.
So smooooth! Like, properly smooth, not bitter at all. I expected something super intense because it's Italian, but it's more round and cozy than strong. Nice start to this little #ItalianCoffee tasting from @Barbera_1870.
Close margins are the most interesting part of any leaderboard, and this one had a beauty
Third and fourth in Workdrop 2644 were split by a single cent, $31.96 against $31.95. When scoring gets that fine, it usually means the review behind it weighs real quality rather than raw volume. Curious how @TheDAOLabs tunes that balance across #SocialMining and #DAOVERSE
Workdrop 2644 is in the books!
Social Miners stepped up, delivered quality, and shared a total ( withdrawal ) pool of $688.89.
Top Miners:
🥇 @vry_lle — $54.15
🥈 @ayanlajaayodeji — $34.87
🥉 @LowOnChain — $31.96
4️⃣ @Sayan1188 — $31.95
5️⃣ @Danish3088 — $28.84
Massive respect to all participants for keeping standards high. Be sure to check in the dashboard for full details.
Keep building, engaging, and mining! 🚀⚡️
Cryptographic failure and operational failure can look identical on a block explorer, but they are very different problems
The Binance drain, roughly $6.3B by the exchange's own estimate, belongs to the second group. Keys were reportedly reached through a compromised engineer device, not cracked. Soft Staking at @TheDAOLabs sidesteps that class of risk by design, since the protocol records balances in a non custodial wallet and never needs signing power, which is why #DAOVERSE treats custody as an architecture choice
The recent $6.3B exploit impacting Binance highlights a critical lesson for Web3: the cryptography held, but the operational trust layer failed.
What @TheDAOLabs built with Social Mining and Soft Staking keeps the opposite design.
Users link their own non-custody wallet. The system only snapshots.
Funds stay under the user’s control the entire time.

ALT Split-view key visual for DAO Labs featuring a secured vault door with the Binance logo on a server rack backdrop alongside crypto users holding hardware wallets and seed phrase backups. Overlay text reads: "$6.3B Binance Hack: Web3's Hard Lesson. Social Mining's Soft Staking keeps communities funds under the users' control the entire time."
Somi went full firewall knight this year, armor plated with tiny server racks, a captcha shield and a rate limiter sword.
His superpower is filtering traffic before it lands, so bot farms bounce off @somi_thecat while real human packets pass straight through to #WhoTweets and #SocialMining. Which layer would you add to his stack?
🤖 Made with AI














