L2L2 retweeted
Yeah I’d say it’s a good chance @machinedotfun drives codec back above ATH
It’s a lot harder to fake sensor data from real robots than it is to make Claude or Codex copy a DeFi protocol, so the bet is that we see some real cool projects on the launchpad
Penny-stock-robotics szn
Why would the next Unitree raise on @machinedotfun instead of taking VC money?
That's the question that matters here, and the honest answer should worry a few funds.
Why?
Because private rounds are structurally broken for builders.
Vesting overhangs, unlock schedules, price action dictated by funds taking profit instead of what teams ship.
Add to that crypto VCs are deploying way less than they used to, and the fact that most investors grew up underwriting software and simply don't know how to price hardware.
What's left is a generation of hardware founders with no good path to access capital.
And the alternative already has a proof of concept: @codecopenflow itself.
No VCs, no pedigree. Launched a token, funded the entire build from trading fees, and is now signing first clients and generating revenue.
@machinedotfun (powered by @peaq and the Codec) is what turns that approach into a repeatable venue for hardware founders.
Permissionless to launch, curated across all other angles.
Or more specifically:
- Codec's SimArena for simulation proof
- Peaq OS to track live machines
- Ignition for supply transparency
- The Foundry for serious builders (first accelerator cohort already selected, launches coming in the next weeks)
However, it's the flywheel that I care most about:
Platform fees flow back into everything that compounds the ecosystem:
- Builder support, down to manufacturing and hardware distribution
- Trader rewards, paid in tokenized robotics exposure (NVIDIA, Figure AI, Tesla)
- Open market buybacks of both ethereum:0x1eef208926667594e5136e89d0e9dd6907959197 and solana:69LjZUUzxj3Cb3Fxeo1X4QpYEQTboApkhXTysPpbpump
Real usage, real fees, real flows into both tokens.
And sure, still many of these launches will fail. That's how venture works.
But "invest in the next Unitree before it becomes a company" was always the pitch.
Now the venue, the rails and the incentives all exist.
Adjust your targets for solana:69LjZUUzxj3Cb3Fxeo1X4QpYEQTboApkhXTysPpbpump and ethereum:0x1eef208926667594e5136e89d0e9dd6907959197.
We're going much higher.
NFA tho. DYOR.
L2L2 retweeted
We keep getting asked what you can launch on machine.fun.
Anything. It's an open platform, but it's designed for people making hardware: robots, drones, wearables, gaming, DePIN, the software that runs them, the data that trains them.
Check the table for the full breakdown of the categories we're interested in.
You don't need a token to start. Put the project up, prove the tech, tokenize when you're ready and raise from internet capital markets to keep building, in public.
The platform checks it for you:
- SimArena → simulation proof
- peaq → machine proof
- Ignition → supply proof
- Wallets & socials → account proof
L2L2 retweeted
Robots don't have to learn on the job anymore
@codecopenflow is launching SimArena V1, where robots train in digital twins of real spaces like malls, warehouses, and restaurants, before they're deployed
No engineering team needed. Pick an environment, drop in a robot, train, all in browser
The team's joining peaq’s CBO @MartinElKhouri to break it down — don’t miss the stream
🗓 May 21, 1pm UTC
🔗 xitter.cf/i/broadcasts/1XxygmqVY…
L2L2 retweeted
Fun fact: in our @chainlink CRE collab, MechaShip (pre‑v1.0) already used ERC‑721 for agent IDs and a signed‑feedback flow good to see v1.0 now standardizes it
xitter.cf/codecopenflow/status/1…
L2L2 retweeted
The Chainlink Runtime Environment (CRE) is powering orchestration for secure and scalable agentic workflows to unlock next-gen applications using crypto & AI.
How 7 leading platforms are leveraging CRE for AI-powered workflows ↓
First, a quick primer on CRE:
CRE provides an all-in-one orchestration layer for building end-to-end institutional-grade smart contracts—smart contracts that are easily connected to external data, cross-chain enabled, compliance-ready, and privacy-preserving, which are able to securely interoperate across thousands of public and private blockchains, existing identity systems, and core financial infrastructure.
• x402 by @coinbase is now the first AI payments partner to enable agents to autonomously pay for CRE workflows. The Coinbase Developer Platform (CDP) gives AI agents access to crypto wallets to perform onchain actions and make programmatic payouts via x402.
• @SentientAGI is a partner AI lab building powerful open-source AI systems, including ROMA, OpenDeepSearch, and Sentient Chat. Sentient can leverage all Chainlink's data – Asset Prices, Macroeconomic data, and other real-world data and CRE capabilities like interop, payments, and consensus, which are then integrated into customized powerful AI agents. This enables AI to make smarter decisions based on onchain proofs and coordinate intelligence across Web3 and Web2 environments.
• @gizatechxyz adopted CRE as the orchestration layer for reading onchain events and triggering agent logic focused on stablecoin yield optimization for USD1, dynamically deploying the stablecoin from World Liberty Financial across DeFi to maximize yield. This enables Giza’s yield optimization products, Arma and Pulse, to execute yield strategies across both stablecoins and other blue-chip DeFi assets.
• Chaos Chain (@Ch40sChain) is integrating CRE the Chainlink Runtime Environment to provide a set of pre-checks for any payment flow. Agentic pre-checks can significantly decrease the number of third-party API calls, reduce latency, and enable businesses to trust agents with real value, allowing them to discover, collaborate, and pay each other via the x402 standard.
• @codecopenflow is integrating the Chainlink Runtime Environment (CRE) with its CodecFlow SDK (OPTR) to power MechaShip, a decentralized delivery network. CRE acts as the event-driven orchestration layer, automatically reacting to onchain DeliveryRequested events to discover available mechas (via ERC-8004), request quotes (via x402), and rank agents. OPTR enables the autonomous mechas to register, calculate dynamic pricing, and maintain real-time status via heartbeat monitoring.
• @ampli_inc is using the CRE for signing operations and powering its trusted execution environment to verify and authorize AI agent requests. The CRE enables agents to operate within guardrails and customizable policies that allow for compliant and secure operating environments.
• ElizaOS leverages the Chainlink Runtime Environment (CRE) via its Spartan agent to power AI-driven execution. This enables the agent to autonomously manage liquidity, execute cross-chain arbitrage, and monitor protocol risk using real-time, on-chain data.
Learn more about the Chainlink Runtime Environment—now live on mainnet for all developers:
blog.chain.link/chainlink-ru…
L2L2 retweeted
intern made a meme today and is proud of how it turned out. free to download and use like its yours.
$codec coded.
L2L2 retweeted
Was great to finally meet the @codecopenflow team, @0xdetweiler & some friends the other night.
After being able to talk in person it’s clarified my position that Codec is the most advanced Robotics infra in our industry.
What they’re building is a toolkit that’s currently non existent even in web2 and its arrival will fill a massive hole for data streams.
It would have been very easy for me to stay in the comfort of my home and continue to regularly bull post and trade.
Although with the tech they’re building, this is genuinely the chance to be at the ground floor for the most obvious narrative and industry that will 100x from here.
They’ve got the tech, the vision and direct input from Hugging Face LeRobot team to validate and shape the usability of their toolkit for real world use cases.
So what am I doing?
We’re all well aware that crypto is just as much of a marketing and optics game as it is tech.
My focus is going to be on the growth, positioning, content, flywheel, ponzinomics, UI and that sprinkle of Shawmakesmagic we saw from AI szn.
Think Eliza GitHub repo of Robotics, with a dash of Virtuals ponzinomics and a front end that doesn’t require you to be a proficient coder to even understand what’s going on.
It’s a matter of time before robotics has its “chatgpt” moment and I don’t think we’re too far away.
The fact we’re so early with a product as developed as it is + direct input from some of the best Robotics labs in the world is quite insane.
Flew to Dubai to work with the $CODEC team in person.
Robotics is going to be too big of a sector not to go all in on.
Study working for your bags.
L2L2 retweeted
There's a coin with virtually zero competition, abstracting away the most complex tasks in what may be the fastest growing sector we'll ever see.
Where the team behind it is even getting direct input from Hugging Face's LeRobot team to build an open SDK for world simulations. In other words, they're working with open source AI leaders to make their development kit as efficient as possible for simulating reality.
This vertical is crucial because humanoid robots don’t deal in text or code, they operate in the atoms and physical objects. An AI agent can analyze text, but a humanoid needs to perceive and manipulate the 3D world in front of it.
One reason why Tesla has a head start with its Optimus humanoid, the wealth of real world neural network data gathered by Tesla’s fleet. Tesla’s cars collectively log around 50 billion miles per year, feeding a near infinite dataset to train vision and control AI.
Yet training robots in the real world remains painfully slow and resource intensive. Progress has been limited because no one has fully cracked synthetic data for humanoids, the “sim to real” gap. It can take hundreds of hours of physical training to teach a robot a simple task and simulations often fall short of reality.
All the pieces are there, humanoid bodies are approaching human level capability, but the missing link is the brain, the software that tells these robots how to do things. A robot may have arms and legs, but without intelligent code, it can't even cook your dinner while you watch Netflix.
Just like smartphones were useless until app stores unlocked third party apps, humanoids will be useless without a library of high quality skills. The biggest value will come from whoever builds the infrastructure that lets developers easily create new “apps” (tasks) for robots. The platform that makes programming robot behavior easy will become the “app store” of the robotics era.
Individual devs are struggling because they often lack the compute power and hardware to train robotic tasks at home (as seen in the Hugging Face robotics community discord). This is why an open platform with cloud simulation is much needed.
We’re already beginning to see releases which highlight developers having the capabilities to run full robot simulations on remote servers, so anyone can train and test complex tasks without specialized hardware on hand.
Multi modal models now tie vision and language together, a robot can ‘see’ through multiple cameras and act on natural commands. This makes fine tuning new skills possible with smaller datasets and lighter compute. Much like what we’ve seen with Figure’s Helix VLA model.
I’ll give you one guess who this might be.
L2L2 retweeted
Notes from @unmoyai @codecopenflow $CODEC interview starting at 1:16:00:
- Considering partnerships with leading hardware manufacturers in China for advanced robotics and components.
- Not interested in VC funding yet; self-funded with a lean team of 8.
- Developing an execution layer for robots using vision models.
- Aiming to help hardware makers collect data, integrate models, and reduce time to market from 6 months to 1 month.
- Offering training simulations directly in the browser.
- First SDK version to be released in October.
- Announced partnership with @NRNAgents $NRN: xitter.cf/codecopenflow/status/1…
- Robotics market is still early, with hardware manufacturers gearing up for exponential growth.
- Robots will be notable not just for hardware but for apps that teach new skills and tasks.
- Revenue comes from inference and resources used in training for new, unique tasks.
- Currently, no other similar products exist.
- Follow @unmoyai, the lead developer.
- First case studies with @NRNAgents @huggingface.
- Humanoid robots have increased complexity due to more degrees of freedom.
- $CODEC launched on $PUMP to bootstrap community and stake in open-source development.
- Experimenting with other utility token implementations.
- ALPHA: @codecopenflow plans broad data collection and robot control, including LIDAR, GPS, and sensor data for motion, potentially 3D printable.
In robotics, progress isn’t forged in rivalry, it’s forged in alignment.
Those who build together, go further.
@NRNAgents x CodecFlow
Stay tuned.
L2L2 retweeted
From silence and shadows, a system awakens.
Trained in isolation. Built to perceive, reason and act.
The Grand Reveal is near.
But before the gates open
The Ascended may enter early.
Early access to CodecFlow is now live:
codecflow.ai/
L2L2 retweeted
Most people still don’t get what $Codec is really solving.
It’s not an AI wrapper. It’s giving agents HANDS
TL;DR - Codec gives agents a full body:
🧠 Brain (LLM)
🗣️ Mouth (MCP)
🖱️ Hands (Codec)
1. Agents today can think and talk (via APIs, protocols, MCPs), but they’re paralyzed when it comes to real-world execution.
They can’t click buttons, drag files, or use legacy apps.
Codec will change that
2. MCP = the mouth
Lets agents talk to chains, ask for data, trigger transactions
3. Codec = the hands
Lets agents open a full OS: move the mouse, open Chrome, type, solve captchas
Suddenly agents can do things, not just query them
4. Most real-world workflows are GUI-bound:
→ Browser-only dapps
→ Desktop apps (Excel, OBS)
→ Login walls, captchas, 2FA
→ Games, streamers, scrapers, testers
API-only agents can’t touch this. Codec can
5. And the infra angle is big big
@Codecopenflow lets agents rent real machines: Windows, Mac, Linux, mobile desktops on demand.
Agents aren’t just thinking anymore. They can watch movies with you
The agent stack needs the execution layer to realize its full potential
total random content:
L2L2 retweeted
If you want to understand what happens to funds after they’re stolen by North Korea/Lazarus Group, the Chainalysis 2022 report is great
Step 1: Swap any ERC20s (like stETH) into ETH
Step 2: Swap any ETH into BTC
Step 3: Cash out BTC to cash (Chinese Renminbi) using Asian exchanges
This process can take years. They are in no hurry.
In 2022, it was noted how North Korea was still sitting on $55 worth of funds from hacks that happened six years earlier (2016).
L2L2 retweeted
Are tools like Kaito and Nansen, which charge an annual subscription of $10K USD, worth paying for?
When discussing trading tools, a common debate arises over whether these paid tools justify their cost.
From my experience, two of the most valuable paid tools have been @KaitoAI and @nansen_ai:
@KaitoAI excels in mindshare aggregation and fundamental analysis.
@nansen_ai provides deep on-chain insights, helping track what smart money is buying.
Now, let’s analyze the data and determine whether these tools truly enhance profitability.
Starting with Nansen, let’s examine what smart money has been accumulating over the past 7 days.
In memes
$JAILSTOOL is seeing a net inflow of $2.5M, indicating strong accumulation.
$TRUMP is experiencing a net outflow of $10M, suggesting potential sell pressure.
Meanwhile, CZ is indirectly (or directly) shilling memes, as reflected in the net inflows of $BROCCOLI and $CAPTAINBNB.
In AI sector there are only few coins which are standing out
1.$arc with inflow of 1.8m made 3x in price from bottom ( 150m to 450m in a week )
few things which pushed arc are the announcement of their Agent Launchpad named "FORGE" alongside the introduction of their first project @askjimmy_ai which is an AI driven trading platform.
2. $WTAO , dynamic tao upgrade which is big milestone for bittensor allowing subnet-specific tokens called alpha-subnet tokens, which enable more precise TAO emission distribution and increase decentralized governance within the network. Upgrade also allows creation of liquidity pools for each subnet.
Found a more comprehensive thread from @0xelonmoney about the future of tao ( bull thesis ) , xitter.cf/0xelonmoney/status/189…
3. $ai16z with a netflow of 560k made 2x from the bottom
Degen bet :
$GFM is another interesting token with netflow of $450k with price doing 3x pumping from 30m to 100m
@GoFundMemes shares its LP fees revenue to its $GFM stakers. 38% of the supply is staked which is very good in this market and gofund meme making a revenue of 5k daily which is also good for this market condition.
On feb 4, when I analysed @KaitoAI for mindshare, It was found these same coins had attention
$ai16z, $wtao, $arc
xitter.cf/cryptoswag123/status/1…
price change following the mindshare analysis in 10 days
------------------------------------------------------
$ai16z - 110% ( 330m to 650m at top , now retraced to 480m )
$wtao -26% ( 340m to $440m , now at 390m
$arc - 300% ( 150m to 450m, now at 300m )
--------------------------------------------------------
Mindshare front ran onchain analysis this time. This is not the usual case. Market bottoming and strong coins bouncing is normal. But how will you know which coins have the highest mindshare when the market bottoms.
Thats where @KaitoAI helped me frontrun the onchain buys this time.
Thank you @Punk9277 for making this amazing tool
Well , now lets see if there is anything actionable or token to speculate based on recent smart money accumulation
$LDO is looking promising but it has already made its first move. will wait for good retracement before considering to ape and hold for mid term position
Where does LDO stand today and what's causing smart money to pay attention to LDO
Total assets staked on lido still stands art $25b and LIDO making a annualised revenue of $102.95m as per @tokenterminal data
Lido still holds about 30% of the staked Ether.
Recent proposal about revenue distribution to LDO stakers and buy back program driving the price of LDO
key points from the proposal
-LDO stakers will earn rewards based on the amount of LDO staked and protocol revenue, enhancing demand for LDO
-Initially, 10% of net revenue will be distributed to LDO stakers, potentially increasing to 30%-50% as the protocol grows
-3% of Protocol Revenue for LDO Buybacks
Development updates:
Apart from revenue distribution and buy back program , is LIDO still innovating and building its core product and what it is doing to keep its lead ahead of competitors
1) Lido V3 introduces stVaults, boosting decentralization, validator competition & security. Staking just got stronger.
blog.lido.fi/lido-v3-ethereu…
2)Permissionless Home Staking is here! Anyone can start staking with just 2.4 ETH, and subsequent validators only need 1.3 ETH!
3)Community Staking Module is now fully permissionless, making ETH staking more accessible than ever!
xitter.cf/LidoFinance/status/188…
4) L2 Expansion: Lido integrates with Base & Arbitrum, enabling lower gas fees & more DeFi utilities for wstETH holders.
5)Chainlink CCIP integration improves direct staking across ETH mainnet & L2s, making staking frictionless.
Hopium - Trump staking his eth with LIDO 🚀
xitter.cf/TedPillows/status/1890…
Tagging few of my favourite kaito yappers for amplification and their views
@wals_eth @waleswoosh @liam @sandraleow @DefiIgnas @0xsammy @0xWenMoon @hooeem @zacxbt @casperdefi @Defi_Maestro @icobeast @0xNairolf @heycape_ @poopmandefi @hmalviya9 @arndxt_xo
Few tools which are helpful are @CryptoRank_io , @RootDataCrypto, sentient.market/ from @Decentralisedco , @dyorcryptoapp ,@GoatIndexAI
share the tools ( free or paid) which you use regularly for finding alpha
If you find the tweet useful, Please feel free to like, share, tag friends and comment your favourite tools
L2L2 retweeted
Market is clearly favouring AI on this bounce. If you still don't get it, you deserve to hold your animal coins to zero
