Most Embodied AI data is still just volume.
@InvLambda is building the layer that turns human teleoperation into verified trajectories that can actually train robots.
Full deep dive ↓ https://t.co/xKbuGrXyUr
A founder (Anna) has built an AI app called Anna. It works. Almost nobody has heard of it.
To change that, the founder wants creators to introduce Anna to a new audience.
Finding the right creators means messaging strangers one by one and waiting for replies. Paying up front means trusting someone you have never worked with.
And creators face the mirror image: is this project real, and will I actually get paid? Both sides are guessing.
That are the problems @Lid_onchain solves
One thing I hope @onlystreetsfun gets right is knowing when a moment is worth turning into a coin.
Not every funny picture needs a ticker. Not every random discovery deserves a launch.
I would rather see a few creations that genuinely make people stop, laugh and remember them than hundreds nobody cares about after a day.
For me, that's where the real challenge begins.
Making a coin is easy. Giving people a reason to care about it is the hard part.
What if the fastest bot on the chain is the one paying for everyone else's entry? That's the structural irony between @hypesium and @RebateLaunch.
@hypesium is built for absolute speed on Elysium. The chain produces a block every 100ms with no public mempool, so the bot pre-signs your transaction and fires on the pool's creation log. It targets an opening-block entry in under 5ms, engineered to beat everyone else to the punch.
@RebateLaunch turns that speed into a penalty. For the first three seconds of a launch, a snipe tax steps down from 99% to zero. If a sniper lands in that window, they pay the maximum rate. That money doesn't go to the team. It routes straight into the locked treasury that funds the bonus tokens for real buyers.
So the bot that wins the race to block zero ends up subsidizing the crowd. It pays the penalty so the next hundred buyers get a head start.
One tool is built to win the opening seconds. The other is built to monetize them. Both are live. Both understand that the first block is where the entire game is decided.
@hypesium@RebateLaunch.
transaction in @hypesium uses four separate connections: two persistent WebSockets and two keep-alive HTTP connections. All four send the same signed transaction as soon as the trigger fires..
1 . The idea is simple: don't depend on a single connection when timing matters. Having multiple routes gives the transaction more chances to reach the sequencer without unnecessary delay.
Most people approach investing by searching for stocks or crypto assets to buy. @Ulys_AI takes a different approach by starting with what you believe will happen in the market.
With Ulys, you can turn an idea like “AI will need more computing power” or “Gold is making a comeback” into an investment strategy.
Its AI researches the idea, builds a basket of relevant assets across stocks, crypto, gold and commodities, then shows you the reasoning and sources behind its choices.
You remain in control. Nothing gets invested until you review and approve it by sliding to invest.
Ulys also comes with a non-custodial wallet, so you don’t have to manage a seed phrase.
It’s now available on iOS, with Season One points and referral bonuses live.
Check it out: https://t.co/KOUS5Tpwxv
Not financial advice. Markets carry risks, and tokenized assets are not the same as owning actual shares.
A city can be mapped and still be missing the one loading bay a robot needs.
That's the problem I keep coming back to with @vangrid_io.
A mapping fleet can cover the roads. Satellites can show rooftops.
Neither tells you whether a specific stairwell, warehouse aisle, or polytunnel was captured recently enough to be useful.
And having millions of phones available doesn't solve that by itself.
Someone still has to ask for the right place.
That's where the bounty board matters.
A buyer funds a specific capture in USDC. A contributor walks the location with a phone. The buyer reviews a preview before accepting it, and reconstruction produces the 3D asset.
The capture also has a fingerprint anchored onchain, giving the buyer a record to check.
That record doesn't prove the geometry is accurate. Buyer review and capture quality still matter.
But the workflow connects three things that are usually separate.
A place someone needs.
A person who can capture it.
A payment for getting the job done.
That's more interesting to me than another claim about how many cameras exist.
The open bounties show where buyers are asking for coverage. Settled bounties show which jobs have completed the payment workflow.
Neither number alone tells you how useful the resulting meshes are.
But together, they give a more concrete picture of demand and execution than a map of potential coverage.
The bottleneck isn't just the camera.
It's getting the right place captured for someone who actually needs it.