Onchain. Early. Curious. Web3 🦊
Joined November 2018
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- Followers4.6K
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GM, gRARE ct 💛🧡
WEB3 DOESN’T NEED MORE NOISE. IT NEEDS CONTRIBUTORS WHO ACTUALLY ADD VALUE.
That’s the idea I find interesting about @rarelistio .
Instead of treating every project as another isolated campaign, Rarelist connects creators with emerging projects through a platform where content, participation, and contribution can translate into rewards.
Season 1 is live with a $50,000 prize pool. Creators can publish on X, earn RARS, climb the leaderboard, and work toward future $RARE conversion.
What matters now is whether the platform can reward genuine insight over recycled narratives and empty engagement.
Because the real test of a creator rewards platform isn’t how many posts it generates.
It’s whether those posts help people discover, understand, and support projects worth paying attention to.
I’m watching how @rarelistio approaches that challenge. 👀
🔗 rarelist.io/r/Raven_slb
#Rarelist #Web3
RAVEN.fi ✦ retweeted
Everyone has a thesis. Few have a way to put one price on it.
That's the part @PoiseFinance solves: choose tokenized stocks, set the weights, and your basket trades like one asset with one continuously updated price.
Round 2 adds crews. It's free, no wallet needed, and you need 4 people.
What's the one theme you'd build around?
Conviction Tokens. Anywhere, anytime.
Beta access: 27th October
Join groups, add friends, get beta codes, earn fees.
poise.finance/campaign
RAVEN.fi ✦ retweeted
A Kaito ping made my day: #248 in Epoch 1.
Then Epoch 2 ended 29 days later. CT posted rankings; my phone stayed quiet.
I checked: #1,171, outside rewards. Silence was the notification.
@RallyOnChain only shows wins. Why leave a campaign that celebrates your wins?
GM gQuip CT 🧡🥱
WHAT IF YOUR CODE DIDN’T CARE WHICH COMPUTER SOLVED THE PROBLEM?
That’s the idea behind @quipnetwork QVM, now live on the Aglais testnet.
Quantum computing has a portability problem. Different machines speak different languages, and moving a workload between them can mean rewriting the entire approach.
Quip is building a different path.
⚡ Write the problem once.
🧠 Compile it for quantum or classical hardware.
🔍 Verify the result instead of blindly trusting it.
QVM combines a shared execution environment with gas-based pricing, upfront cost limits, and multiple layers of result verification.
And it goes beyond computation: quantum smart contracts bring this execution model onchain.
The bigger opportunity isn’t simply accessing quantum hardware. It’s making that computing power programmable, verifiable, and accessible through a common infrastructure.
Quantum computing needs more than powerful machines.
It needs a system that makes them work together.
That’s what makes @quipnetwork worth watching.
Explore QVM: quip.network/qvm/
#Quip #QuantumComputing
RAVEN.fi ✦ retweeted
What I appreciate about @grvt_io is the transparency behind its decisions.
The first 1.1M $GRVT buyback has already been completed, and those tokens were permanently burned. What makes it more interesting is that an independent execution partner handles the purchases, while the public dashboard lets anyone verify the transactions and track the results.
That level of transparency is worth paying attention to.
Now, GRVT 2.0 is on the way, with Earn expected in late October, Stable Funding Perps and Yield as Margin in November, followed by the new app in late November.
The app is what interests me most, especially the idea of bringing trading, yield and a unified self custodial balance into one place.
The buyback program is intended to continue monthly, although future purchases remain discretionary, so the next updates will be worth watching.
I'm curious to see how everything comes together as the team moves toward its 2027 roadmap.
Which part of GRVT 2.0 are you looking forward to the most?
RAVEN.fi ✦ retweeted
Cannonball is already making noise 💥
Seeing all these wins and reactions, @Duelbits might have found another community favorite. The new Original is getting plenty of attention 👀
RAVEN.fi ✦ retweeted
SCOOBY THOUGHT THIS SPIN WAS ABOUT TO HIT… THEN THE BOARD DISAPPOINTED 😭💀
“Bro, that’s so bad!” 😂
The board is filling up, the symbols are stacking, and Scooby is trying to figure out where the big win is hiding. 👀🎰
Ft. @Scoobyz88 x @Stake
RAVEN.fi ✦ retweeted
I spent an hour reading through @vangrid_io's API docs this morning, and the most interesting part isn't the spatial data. It's the constraint that makes the whole system work.
When you pull a bounty through the API, you don't get the raw video. You get the reconstructed 3D model. The original footage stays with the contributor.
For a tech director building a robotics pipeline, that's a massive architectural difference. You're not ingesting a chaotic folder of phone videos with varying lighting, angles, and metadata. You're getting a clean GLB file, grounded to real-world coordinates, with a ground_truth_score attached to tell you exactly how much the multi-node corroboration trusts that specific capture.
The API puts a hard limit on how much money an AI agent can spend without a human checking the receipts. Spend caps constrain the signing. They don't constrain the two calls that actually move money: accepting a submission and cancelling a bounty. Both are irreversible. The docs explicitly tell you to gate those behind human approval if the agent is unattended.
It's an honest design. It admits that autonomous agents are great at requesting data, but humans still have to verify the output before the escrow clears.
The API isn't just a data pipe. It's a framework for how machines and humans negotiate reality.
vangrid.io
RAVEN.fi ✦ retweeted
Another week is coming to a close. For weeks, days on end we’ve been pushing hard to build and sustain mindshare for @quipnetwork . I truly hope these efforts pay off. Who else feels the same way? As for me, I’m in the state shown in the image. How are things on your end?
Listen up friends, the Quip side walked through the XQuad toolchain with two different demos.
@quipnetwork’s blog describes XQuad turning QUBO and Ising models into a constraint language (xqcp); you write the program once, XQVM compiles it to a quadratic model, and xqsa can send that same model to a D-Wave, local annealer, GPU, or the network.
The trading game demo plugs an existing QUBO into the solver layer, while Parcel Forum builds the logistics plan from constraints like EXCLUDE, SLACK, and ATLEASTW from the start.
On the port check the matrix coefficients matched exactly and the answers lined up almost one-to-one.
On Advantage2 the XQuad path stayed in the same band as the classical alternatives.
(📷According to X rules, a paid partnership has been selected. It is not investment advice or a paid partnership.)
RAVEN.fi ✦ retweeted
💡 Not every dollar in a portfolio needs to play the same role.
If I were organizing a portfolio, I wouldn't evaluate every position using one question: "How much can this earn?"
I'd also ask what job that capital is supposed to do.
Money allocated for a near-term opportunity has a different purpose from capital intended to generate income over a longer horizon. Treating both the same can lead to decisions that look attractive on paper but don't fit the actual objective.
This is why I'm interested in the direction of GRVT Earn.
Rather than presenting yield as one universal number, @grvt_io planned fixed-income offering includes different strategies with different target returns and underlying exposures.
For example:
🏦 Balanced Bundle: targets approximately 4.5% APY, with exposure described as including AAA-rated collateralized loan obligations.
📈 Opportunistic Bundle: targets approximately 11% APY, with an example involving card receivables settled through payment networks such as Visa and Mastercard.
These targets aren't guaranteed returns, and the higher figure shouldn't automatically be interpreted as the better choice. Underlying exposures, credit risk, liquidity, and the structure of each strategy all matter.
To me, the useful question isn't simply which product offers the biggest percentage. It's whether the strategy fits the purpose of the capital being allocated.
Tokenization can make these opportunities more accessible, but accessibility doesn't remove the need to understand what sits underneath the yield.
Let's compare how we think about this:
If you had to choose between a strategy targeting 4.5% APY and one targeting 11% APY, what would you investigate first before deciding?
Would it be the underlying assets, the liquidity terms, the manager's track record, or something else? Share your first priority and why.
RAVEN.fi ✦ retweeted
I hadn’t thought about how much money gets spent just enforcing a system that should be accountable in the first place..
If tax flows can be tracked automatically and people can decide together how that money is used, that changes more than transparency… it changes the relationship between people and the system they fund.
It also raises a bigger question I explored in my article :
what would it take to build a society where people have more say in the systems that govern them?
@ProtocolSociety
Read here- xitter.cf/yocodedx/status/211314…
RAVEN.fi ✦ retweeted
up to 11% APY, earning yield while trading, and keeping control of your assets.
now you see why i'm paying attention to what @grvt_io is building.
most traders focus on finding the next good entry, but what if there's another way to put your capital to work without giving up the ability to trade?
that's the idea behind grvt earn and the upcoming yield as margin feature.
GRVT EARN plans to offer tokenized fixed-income strategies with target yields of up to 11% APY on eligible assets.
and here's where it gets interesting.
with YIELDS as MARGIN, eligible earn balances are planned to support trading positions while continuing to accrue yield.
so instead of treating earning and trading as two completely separate activities, you could potentially do both with eligible funds.
there's also the question of ASSET SECURITY and CONTROL. when putting your money to work, it's important to understand how your assets are held, what control you retain, and the risks involved. that's something i'd look into before committing capital.
the bigger picture is worth watching too.
the global fixed-income market is estimated at around $160 trillion, and GRVT wants to make a share of these traditionally institution-focused opportunities more accessible onchain.
of course, 11% APY is a target, not a guaranteed return. yield as margin is also a planned feature, so i'll be watching how it works once it's available.
another development worth noting is that grvt has completed its first $GRVT buyback and burn.
1.1 million $GRVT tokens were purchased from the open market and permanently burned, representing approximately 0.96% of the circulating supply at the time.
you can verify the buyback records here:
grvt.io/exchange/buybacks
personally, i want to see how GRVT brings all these pieces together. the combination of fixed-income opportunities, trading flexibility and user control is worth keeping an eye on.
would you explore earning yield while trading, or do you prefer keeping your earning funds separate from your trading capital?
🤝 Paid partnership
RAVEN.fi ✦ retweeted
gVANGRID
AI can generate worlds. But can it understand the one we actually live in? 🌍
That’s where @vangrid_io gets interesting.
Robots and Physical AI systems need more than text and synthetic simulations. They need accurate, ground-level data about real places—and the world changes faster than traditional mapping can keep up.
Vangrid is building a decentralized spatial data network that turns smartphone footage into 3D reconstructions, with onchain attestations that help establish where the data came from.
And now, AI tools can get closer to the physical world itself.
With Vangrid’s MCP integration, tools like Claude and Cursor can search spatial captures, inspect existing data, verify records, and even initiate requests for new captures through bounty workflows.
Think about the possibilities: an AI agent identifies a gap in its understanding of a real location, requests fresh footage, and receives a reconstruction built from human-collected data.
That’s a much more interesting model than asking AI to guess what reality looks like.
The next breakthrough in AI might not come from generating more data—but from connecting intelligence to the world as it really is.
The grid is inevitable.
Explore: data.vangrid.io/
#Vangrid #PhysicalAI #DePIN
Vangrid has raised $9M.
Thank you to our partners, supporters, and stakeholders for the conviction.
LLMs hit the text data wall. The next frontier is Physical AI and autonomous systems are starving for real-world spatial ground truth.
Satellites can't see sidewalks. Corporate fleets can't scale.
Vangrid turns 3 billion civilian smartphones into a decentralized perception grid.
Captured at the edge, verified onchain, delivered as ground truth for World Models and Sovereign Systems.
100K+ verified captures. Live bounty system. Real settlements on Base.
The grid is inevitable.
