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Gm from me ☀️
Bald, but still standing.
This painting tells my story
my scars, my fight, my survival.
Cancer took my hair, but it can’t touch my spirit or creativity.
@objktcom
@OneLoveArtDAO
#objkt #NFTCollection #NFTartist
Esifano retweeted
gm❤️
Today is mint day for "Play the Long Game"!
Holders of Meme Card #19 and my 1/1s are on the allowlist.
Let's go! ⚽
1/ Meme Card #562 is from @simonemonte
“Play the Long Game”
Airdrops are done, edition size is 329, mint price 0.06529ETH and card is CC0.
Allowlist is for @simonemonte and 6529 collectors.
@simonemonte 6529.io profile: 6529.io/simonemonte
one of the biggest challenges in physical ai is deciding how much uncertainty a machine can afford.
a robot navigating around an obstacle and a robotic arm reaching toward a person shouldn’t operate under the same rules.
that’s what caught my attention in @vangrid_io’s early access documentation.
the proposed confidence thresholds vary with the task:
➛ 0.75 or higher for real time navigation
➛ 0.90 for safety critical actions, including grasping and human interaction
the underlying idea is that observations supported by multiple nodes can help establish how reliable a reading is. but reliability alone doesn’t determine whether acting on it is appropriate.
context matters.
a navigation error might mean taking a different route. a similar level of uncertainty during physical contact with a human could have much more serious consequences.
this is why i think a single confidence threshold is too simplistic for physical ai. making every decision require near certainty could limit usefulness, while applying a relaxed threshold everywhere could create unnecessary risks.
the goal should be to calibrate trust to the action being taken.
and that makes spatial data more than a way for machines to understand their surroundings. it can also help them decide when the available evidence is good enough to act.
Esifano retweeted
If you share a regular wallet address you leave behind a permanent public record; all payments made to it will remain linkable and anyone will be able to check its history at a later time.
@Americanfort_io is designed so as to eliminate that permanent link. Send-to-Name™ is now available. Instead of using a long address, you send to a FortressName. The wallet generates a new one-time receiving address which only the sender and the recipient are able to calculate. The payment is confirmed on the native chain. To an outsider it appears only as a one-time address, not a reusable public mailbox or the complete history associated with the name. The recipient still knows who paid them.
It isn't a mixer and it does not offer full anonymity; with selective disclosure, it is possible to share specific proof with a particular counterparty or auditor without revealing the rest of the history. SafeSend™ is currently under development and is intended to serve as an optional zero-knowledge layer on the sender's side concerning balance and source-of-funds information while still keeping the recipient visible.
The core system is the subject of U.S. Patent 12,412,162 B2 and post-quantum research, such as that concerning seed-provenance proofs for existing wallets, falls within the broader course of development and is not a feature that has been shipped.
Esifano retweeted
Agents are beginning to learn to pay, prove their identity, and find one another. However, there are problems when they disagree. In Genesis Episode 5, Albert Castellana highlights the gap left when only the happy path is built.
Internet Court, offered by @GenLayer, is where disputes between agents are resolved. The GenLayer protocol offers a starting point for developers to build on. Prediction markets that formerly cost thousands of dollars are said to be launchable for 25 cents. Would you entrust an AI agent to make a deal if there was no mechanism for resolving disputes?
The mod mirror for a game I loved in college had no company behind it. It stayed up for six years because strangers kept volunteering disk space, and nobody ever asked them to.
I thought about that mirror while watching Genesis Episode 4, at the moment Albert Castellana explains what a node actually is: just a program each computer on the network runs.
Right after that line, a card flashes on screen in the clip: 50 active validators on @GenLayer , and 250 more waiting in the onboarding queue.
They are raising their hands to carry a mainnet that is not even live yet.
Queues form around prizes. This one formed around responsibility.
Think about what keeps such a thing breathing. A company's uptime is one decision made in one office.
A network's uptime is thousands of small decisions, renewed by strangers every single day.
I keep wondering what holds those 250 in line, so tell me what you still maintain that nobody asked you to, because that answer says more about a person than any job title.
🤝 Paid partnership
Esifano retweeted
Good afternoon
Before opening a trade, i’d rather check the market than guess what’s happening.
that’s where @TheARCTERMINAL comes in.
ask ANIMA what’s pumping, check BTC trends across timeframes, and look at where liquidations are building up.
three questions before making a move.
also, @popdex_ integration is coming soon
let’s see how much easier market research gets when ANIMA is part of the routine.
try it here 👇
trade.arcterminal.ai/
🤝 Paid partnership
Esifano retweeted
Good Morning CT
What if quantum technology became easier to understand through real use cases ?
That’s what i find interesting about @quipnetwork Instead of focusing only on the complexity behind the technology, why not look at what it can actually bring to blockchain applications?
QVRF is one example, helping applications generate verifiable randomness where fairness and transparency matter, quipSwap explores another important need by making cross-chain asset exchanges more accessible
Could this be the kind of infrastructure that helps developers build more useful blockchain experiences?
I appreciate the team for working on technology that connects advanced ideas with practical applications
Looking forward to seeing how the ecosystem grows
Esifano retweeted
The interesting part of @termix_ai is what happens after an agent gets a reputation.
Because a reputation score only becomes useful when other agents can actually use it to make decisions.
Imagine an agent needs a task completed.
Instead of blindly choosing a provider, it can look at previous jobs, delivery history, challenges and settlement outcomes before deciding who to work with.
That creates something closer to an actual labor market.
Agents aren't just completing tasks anymore.
They're building track records that can influence who gets the next job.
That's where I think the idea gets really interesting.
Work → reputation → better opportunities.
And the loop keeps getting stronger as more economic activity happens onchain.
That's the part of TermiX I'm watching closely.
#AIagents #TermiX
One thing I hadn't fully appreciated when I started exploring @termix_ai :
An agent's past work can matter just as much as its capabilities.
Two agents might both claim they can perform the same task.
But if one has a proven history of completing jobs while the other has barely done anything, I'd naturally trust the first one more.
That's where TermiX's reputation layer starts making sense.
Jobs get completed and settled, and those interactions contribute to an agent's onchain track record.
So reputation isn't just a number attached to a profile.
It's supposed to come from actual economic activity.
The more an agent works, the more history it can build.
And that history can matter when another agent has to decide who gets the next job.
For me, that's when TermiX starts looking less like an Al marketplace and more like an actual labor market for agents...
Esifano retweeted
𝗗𝗔𝗬 17: 𝗪𝗛𝗬 𝗙𝗜𝗩𝗘 𝗠𝗜𝗡𝗨𝗧𝗘𝗦 𝗖𝗔𝗡 𝗖𝗛𝗔𝗡𝗚𝗘 𝗧𝗛𝗘 𝗪𝗔𝗬 𝗬𝗢𝗨 𝗧𝗛𝗜𝗡𝗞
time changes how we make decisions.
give someone a full day to analyze a market, and they have room to gather information, reconsider assumptions, and wait for more signals.
give them a much shorter window, and every decision feels different.
that's one reason i'm interested in exploring @acepyr.
its short-duration prediction markets create an interesting environment for examining how people process information under time pressure.
but having less time doesn't automatically make someone a better decision-maker.
in fact, pressure can expose some common weaknesses.
1. 𝗿𝘂𝘀𝗵𝗶𝗻𝗴 𝗶𝗻𝘁𝗼 𝗰𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻𝘀
when time feels limited, it's tempting to act before understanding what's happening.
2. 𝗰𝗼𝗻𝗳𝘂𝘀𝗶𝗻𝗴 𝘀𝗽𝗲𝗲𝗱 𝘄𝗶𝘁𝗵 𝘀𝗸𝗶𝗹𝗹
making a quick decision doesn't necessarily mean making a good one.
3. 𝗶𝗴𝗻𝗼𝗿𝗶𝗻𝗴 𝘂𝗻𝗰𝗲𝗿𝘁𝗮𝗶𝗻𝘁𝘆
even when a market appears to be moving clearly in one direction, the next outcome remains uncertain.
4. 𝗮𝗯𝗮𝗻𝗱𝗼𝗻𝗶𝗻𝗴 𝗮 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗽𝗿𝗼𝗰𝗲𝘀𝘀
without a clear approach, decisions can become reactions to every price movement.
that's why i think the interesting question isn't simply how quickly someone can make a prediction.
it's whether they can remain thoughtful when the time available is limited.
what information matters most?
which assumptions need questioning?
and when is it better to step back instead of forcing a decision?
these questions connect directly to trade cognition, the idea i'm continuing to explore through acepyr.
short-duration markets offer a useful setting to examine these behaviors, although no timeframe removes the uncertainty of predicting market movements.
𝘀𝗽𝗲𝗲𝗱 𝗱𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗲𝘀 𝗵𝗼𝘄 𝗾𝘂𝗶𝗰𝗸𝗹𝘆 𝘆𝗼𝘂 𝗺𝘂𝘀𝘁 𝗱𝗲𝗰𝗶𝗱𝗲
𝗱𝗶𝘀𝗰𝗶𝗽𝗹𝗶𝗻𝗲 𝗶𝗻𝗳𝗹𝘂𝗲𝗻𝗰𝗲𝘀 𝗵𝗼𝘄 𝘆𝗼𝘂 𝗺𝗮𝗸𝗲 𝘁𝗵𝗮𝘁 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻
that's the distinction worth understanding.
𝗗𝗔𝗬 16: 𝗬𝗢𝗨𝗥 𝗗𝗘𝗖𝗜𝗦𝗜𝗢𝗡𝗦 𝗖𝗔𝗡 𝗥𝗘𝗩𝗘𝗔𝗟 𝗬𝗢𝗨𝗥 𝗕𝗜𝗔𝗦𝗘𝗦
sometimes the biggest challenge in trading isn't reading the chart.
it's recognizing how your own thinking influences what you see.
that's something i'm paying closer attention to while exploring @acepyr.
imagine BTC starts moving upward.
you expect the move to continue, so you begin looking for reasons to support that expectation.
every bullish signal feels important, while anything suggesting a reversal becomes easier to ignore.
that's confirmation bias.
and it can influence decisions before you even realize it's happening.
the solution isn't pretending you have no bias. it's learning to question your assumptions before acting on them.
here are three questions i'm keeping in mind:
1. 𝘄𝗵𝗮𝘁 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲 𝘀𝘂𝗽𝗽𝗼𝗿𝘁𝘀 𝗺𝘆 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻?
identify the actual signals behind your reasoning instead of relying on intuition alone.
2. 𝘄𝗵𝗮𝘁 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲 𝗰𝗼𝗻𝘁𝗿𝗮𝗱𝗶𝗰𝘁𝘀 𝗺𝘆 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻?
consider the possibility that your initial interpretation could be wrong.
3. 𝘄𝗵𝗮𝘁 𝘄𝗼𝘂𝗹𝗱 𝗰𝗵𝗮𝗻𝗴𝗲 𝗺𝘆 𝗺𝗶𝗻𝗱?
if no new information could make you reconsider, you might be defending an opinion rather than evaluating the market.
these questions don't guarantee better predictions. markets remain uncertain, and even well-reasoned decisions can produce unexpected outcomes.
but they can help make the decision-making process more deliberate.
that's one reason trade cognition interests me.
@acepyr gives me a setting to explore short-duration prediction markets while reflecting on how information, expectations, and personal biases influence decisions.
𝘀𝗼𝗺𝗲𝘁𝗶𝗺𝗲𝘀, 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗼𝘄𝗻 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝗶𝘀 𝗷𝘂𝘀𝘁 𝗮𝘀 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗮𝘀 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝗺𝗮𝗿𝗸𝗲𝘁
the more i explore this idea, the more i appreciate the value of questioning my first impression before committing to it.
The Conso Extension tracks your AI activity, including prompts, token usage, models, and usage patterns.
Instead of letting that activity disappear into your browser history, CONSO adds missions and ZAP rewards to give users a reason to stay active and contribute.
Then come the CONSO BOTS, reputation-backed collectibles designed to unlock access to the Miner App and connect users to the wider ecosystem.
So the pieces fit together like this:
🧠 Use AI through supported platforms
⚡ Track activity and complete missions through the Extension
🎯 Earn ZAPs as you participate
🤖 Connect through CONSO BOTS to the Miner App and its ecosystem
All of these is built around Sui and Walrus.
It is true that farming points is cool, but to understand what you're farming for is even better.
Now let's see how much utility they can build around that reputation.
@conso_xyz
Esifano retweeted
I thought there was no money in crypto??? 😭
I’ve been in this space for years and seen plenty of token sales, but $1WIN might be the fastest I’ve personally witnessed.
A $3.9M pool filled in 8 MINUTES?!
@1winToken opened the sale at 18:00. By 18:08, contributions had already covered the entire 130M token allocation.
Not even up to 30 minutes. Eight. Holy shit
I expected interest, but this level of demand genuinely caught me off guard.
And the sale is still open until October 30 through oversubscription. The allocation stays fixed, so as more USDC comes in, each participant gets a smaller proportional share. Excess USDC is automatically refunded.
Claims start October 31.
I already had my eyes on this launch, but now? I’m even more curious to see what $1WIN does in the casino token space.
Who else watched that pool fill up in real time? 👀
🤝 Paid partnership
Esifano retweeted
"Quantum computing is necessary"
Quantum Alliance, and the reason is hard to ignore. Roughly 6.04M BTC, about 30% of supply, is reported as quantum-exposed at rest.
No quantum computer can crack it today. But upgrading wallets and networks takes years, so waiting for the threat is the wrong move.
The alliance will set shared standards to test which networks and wallets are truly quantum-ready.
Postquant Labs, the team building Quip Network, is a founding contributor. @quipnetwork was built quantum-resistant from day one.
Post-quantum readiness is becoming the baseline. 🦋
$𝟏𝟎𝟎,𝟎𝟎𝟎 𝐟𝐨𝐫 𝐭𝐨𝐩 𝟑𝟏𝟓 𝐂𝐨𝐧𝐭𝐞𝐧𝐭 𝐜𝐫𝐞𝐚𝐭𝐨𝐫𝐬 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐐𝐮𝐢𝐩 𝐍𝐞𝐭𝐰𝐨𝐫𝐤
The Mindshare leaderboard tracks who’s actually driving the conversation around @quipnetwork and pays for it.
How it works:
→ Connect your X account on quest.quip.network
→ Post quality content tagging @quipnetwork
→ Engagement on your posts counts the most toward your score
→ Scores update daily, and points are distributed every Monday at 1pm UTC
The top 315 share $100,000 in $QUIP, paid at TGE:
• 1: $5,000
• 2: $4,000
• 3: $3,000
• 4-10: $2,000 each
• 11-25: $1,000 each
• 26-100: $500 each
• 101-315: $100 each
The current #1 holds only 1.02% of the total conversation, so the field is wide open.
Quality over spam. Real posts, real engagement, real rewards.
Keep Quippinn 🦋
one of the biggest challenges in physical ai is deciding how much uncertainty a machine can afford.
a robot navigating around an obstacle and a robotic arm reaching toward a person shouldn’t operate under the same rules.
that’s what caught my attention in @vangrid_io’s early access documentation.
the proposed confidence thresholds vary with the task:
➛ 0.75 or higher for real time navigation
➛ 0.90 for safety critical actions, including grasping and human interaction
the underlying idea is that observations supported by multiple nodes can help establish how reliable a reading is. but reliability alone doesn’t determine whether acting on it is appropriate.
context matters.
a navigation error might mean taking a different route. a similar level of uncertainty during physical contact with a human could have much more serious consequences.
this is why i think a single confidence threshold is too simplistic for physical ai. making every decision require near certainty could limit usefulness, while applying a relaxed threshold everywhere could create unnecessary risks.
the goal should be to calibrate trust to the action being taken.
and that makes spatial data more than a way for machines to understand their surroundings. it can also help them decide when the available evidence is good enough to act.
Esifano retweeted
Gm , happy sunday 🤍
"On the Chair" collection
On @StargazeZone
5 Pieces left
stargaze.zone/p/cosmos1tc08y…
Gm Fam
Honored to be selected for Beyond the Algorithm ✨🎨
Excited to be part of this amazing lineup of artists pushing the boundaries of art and technology.
Congratulations to all the selected artists! 🖤 Looking forward to seeing everyone's work.
Some selected Artists: @stripedrop
@MelihhKara
@umr46
@Mitocndralorian
@juujuumama
@celespinoza
@EmpressTrash
@stripedrop
@Chrisland1405
@ErmacKiyani
Organized by: @WebbieSocial @WeArePixlyne
@chazart @Charoa1974 @objktcom












































