Freedom Seeker
The Swamp
Joined April 2022
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I never left, have been adding to my bag and conviction for more than a year but I can understand how everything is different wen you are on the inside, having said this WE ARE SO BACK. I think @Cryptotrissy is one of the best tek KOLs in the game, if he has developed a new conviction over the past 2 months on solana:69LjZUUzxj3Cb3Fxeo1X4QpYEQTboApkhXTysPpbpump then basically moon falls short from where we are going. Congrats to @unmoyai @0xdetweiler and the team for treating this as a real startup project rather than your classic 99.9% vaporware web3 BS. Excited to see where we go next
After many months of research and consideration, $CODEC is once again my highest conviction trade.
My bullishness for robotics never left, however the environment clearly wasn’t favourable and products were still too immature to have a real impact on development.
So why the sudden change of mind? What’s so interesting that’s brought me back?
Firstly, this wasn’t an overnight decision. Around 3 months ago I was coming back from a trading hiatus, since my read on the market wasn’t great, a protocol I have to better my edge is reading as much non crypto related material as possible. This is my favourite tool in the arsenal to respark my curiosity, which is one of, if not the most valuable trait when becoming interested in your craft again.
By reading about non crypto related sectors, it helps open my mind on potential possibilities through breaking a close minded state. You realise how much opportunity, innovation and capital flows through society as a whole. As you can probably guess, one of these topics was related to robotics.
In my telegram channel, I spoke about the introduction of World Action Models (WAM) and Egoscale + Scaling Laws. Very quickly I realized how much the space had progressed over just a 6-9 month period. A complete step change had been made across nearly every vertical, many of the theses I had a year ago have arrived and are showing rapid improvement. Since then, it’s been the core narrative sitting in the back of my mind that I haven’t been able to shake.
I’ll try to keep the key points short as each of them deserves their own article, which I’ll hopefully write in the near future.
1. World Action Models (WAM) - a new architecture which builds on VLA’s/VLM’s by adding prediction. Instead of only choosing an action, they try to predict how the scene will change after that action. Data collection through teleoperation is largely inefficient, humanized sensors are massively growing and companies adjacent to them. Nvidia defines them as models that predict future world states and actions. DreamZero see’s WAMs as a way to learn physical dynamics and generalize to unseen motions where standard VLAs can struggle. Robotics is moving from task specific policies toward general purpose physical intelligence.
2. EgoScale and Scaling Laws - trained a VLA on 20k hours of action labeled egocentric human video, found a log linear scaling law between human data scale and validation loss, showed that validation loss strongly tracks downstream robot performance and reported a 54% average robot success improvement over no pretraining on a 22 DoF dexterous hand. This has been proof that dexterity can improve with better and more data.
3. In context learning - In context learning lets models learn new tasks from examples instead of by changing weights. This is not the same as permanently learning a skill. The robot changes its behavior while the demonstration is in context, but its model weights are not updated. So in the next session, that skill is gone. Generalist AI’s GEN 1.5 shows that a robot can take a short demo video as a “prompt” and immediately perform the task. In trials on simple tasks, it learned from just one demonstration with no extra training. This proof of concept suggests robot skills can be transferred by demonstration much as GPT learns from text prompts, although this is only for short horizon context, not long tasks. Prompted skills aren’t as good as fine tuned ones. Nevertheless it’s a massive progression.
4. Simulations - They’ll never capture everything that happens in the real world, but what they do give us is access to information that is difficult to get from videos alone such as the exact position of objects, contact points, forces, and robot movements. That makes simulation a useful complement to real world data. Codec (SimArena) can help by providing realistic, calibrated simulations and task setups that match the robot being used. This gives the model more examples to learn from and helps it make better predictions
5. Systems - As tooling, benchmarking, authoring layer, system ID etc become more advanced, robotics slowly becomes a compute problem. Different physical robots and even two nominally identical copies do not behave identically. Simulation tooling can’t accurately correlate between foundation models. System ID is the missing layer and where simulation tooling like Codec will be able to abstract calibrations, giving more confidence for deploying in reality.
So what specific tasks am I focused on?
- Publicising robotics research and being in the weeds for every new innovation that’s coming out on a daily basis
- Positioning Codec’s marketing so it fully captures how the architecture is aligned with industry standards and future bottlenecks
- Help @unmoyai put his big brain thoughts onto this app as there’s very few people with his technical knowledge + experience
- Simplify and point readers of my page in the right direction, the entire sector has multiplied. There’s so many new sub fields and interesting experiments happening that are often complex and hard to keep track of
- Bullposting
I’ll address the elephant in the room and explain why I left unannounced previously, which I want to apologise for.
With start ups and especially in crypto, small decisions make a massive difference. Everything is about attention to detail and rapid execution. I was extremely hands on with product positioning, marketing, business analysis etc alongside my own bullposting and trading, which was a position I was comfortable to be in, since I’ve scaled multiple companies before.
Due to being so hands on, I was very passionate and strong minded on certain decisions, I treated the product like it was my own and even wrote a 30 page product and business analysis on every vertical. At some stage myself and the team had weak communication while trying to move at a high growth start up pace. This eventually led to myself being frustrated as there was too many chefs in the kitchen and conflict from multiple marketing heads.
So with this conflict, I silently stepped away as I had too much respect for the @codecopenflow team, @0xdetweiler and everyone else involved behind the scenes who put so much effort in. Looking back, did I handle the situation well? Probably not, but when I become passionate on my work I treat it like life or death. With my departure I gave a list of items which needed to be improved from my perspective regarding processes, operations, positioning and overall structure. I can confidently say these have greatly improved and with my inputs I should be able to help put the icing on the cake.
Due to past experiences, I know there will be some people uncertain of my commitment. To help with my transparency towards being dedicated for the long term, you’ll be able to watch my Fomo account.
I wished I could have made this post when the price was ranging at 2-3 mil. However this wasn’t a decision I took lightly and I wasn’t risking my reputation, I’ve spent over 2 months going back and forth with the team making sure I understand every vertical to a tea. This wasn’t a decision I was going to make without seeing a clear long term roadmap that matches how I see the robotics industry evolving.
As the terminator once said: “I’m back”
Codec coded.
machine.fun is about to go live 👀🤖
Hodlo retweeted
When CodecFlow started last year, robotics was barely on crypto’s radar.
The goal was to change that by bringing the whole robot development cycle into the crypto-native world, from the first test to the finished machine.
Talking to other builders and looking at the problem as a whole, the same conclusion kept coming up: building a robot is brutally hard, for three reasons.
I. Nowhere to test it.
Labs and hardware cost more than most ideas are worth, so the first thing we built was a way around them. SimArena lets anyone check whether a robot idea works in simulation before spending anything on equipment. This week, around 80 teams at the robo.innovate hackathon in Munich are using it for their challenges.
II. Nothing to train it on.
Robots learn from examples, and the examples they need either don’t exist yet or aren’t labelled in a way a robot can learn from. It’s one of the quietest bottlenecks in robotics and one of the hardest to fix, but there’s news on it coming soon.
III. No money or network to build it.
Once a robot works in simulation, getting it into production takes real capital, factory connections, a supply chain and customers waiting to buy it. This is where most robotics startups die. That’s why we teamed up with @machinedotfun and @peaq on a launchpad and accelerator built for exactly this stage.
Through partnerships and integrations with @solana, @Raydium, @sunrise and @peaq, the goal is to give machines something they’ve never had: capital markets of their own, where a robot is tradable from day one, and anyone who believes in it can take a position before the rest of the market catches on.
For the first time, the whole robotics lifecycle, in one place: design it → train it → build it.
We’re excited to open that door to anyone, anywhere, and help them take a machine from prototype to business.
@machinedotfun launches in the next 48H.
Hodlo retweeted
Capital markets, built for robots.
Coming to @solana.
Hodlo retweeted
1/6 — SolHandle Identity
SolHandle is now more than just minting @handles.
Claim your own NFT-based name on Solana, manage your handles and set your Primary Handle.
Your wallet. Your name. Your identity.
This is where our ecosystem begins.
solhandle.io
#SolHandle #Solana
Hodlo retweeted
We’re bringing SafeCircle to schools!
Excited to share a first look at SafeCircle for Schools, our dedicated platform for teachers and school administrators.
One place to manage classrooms, students, devices, and safety alerts.
Our goal is to extend online protection beyond the home and give educators the tools they need to create safer digital environments for students.
Protecting children online shouldn’t stop at home.
And we’re building the tools to make that possible.
Hodlo retweeted
I know I've been quieter than usual lately.
But trust me, it's the calm before the storm.
I've been working hard behind the scenes on something that could change how we use identity on Solana.
And the best part? The entire Solana community could be part of it.
I'm not ready to reveal everything just yet, but we're thinking much bigger with SolHandle.
Your @ handle might soon mean a lot more than you think.
#SolHandle #Solana #Web3 #SolanaEcosystem #SocialFi
Hodlo retweeted
Before a robot ever shows up in a demo video, it looks like this for most of a year.
Every bearing, gear and bracket gets designed, ordered, tested and redesigned.
@machinedotfun is built for this stage.
Teams raise in public while the parts are still in pieces, and the people backing them get to watch it all come together.
Hodlo retweeted
Onchains been hot for over 3 months and we’re yet to see a real utility meta.
So far it’s been a blend of memes, stock coins and a few private inference plays.
Launchpad mechanics thus far have been anti longevity other than Long XYZ, which still doesn’t really support utility projects in a meaningful way as their entire business moat is supporting an arbitrage flywheel.
Don’t get me wrong, I’m still a big fan of Long and they deserve their flowers with how they optimized deeper liquidity and dynamics of LP structures, I believe every team should carefully study the progressions they’ve made. Although deeper pools alone hasn’t been enough to spark real businesses on their platform.
How you approach designing a launchpad is a very philosophy debate. High taxes means you need to be giving traders a favourable environment, just like you would give people better living conditions in a high tax first world country.
No taxes means the traders are the product and you’re expecting value capture to come through either selling native tokens or the volume you’re generating (Long’s arbitrage flywheel).
Then when looking from a traders perspective you need to make the conscious decision of what the launchpads motives are in the short and long term by their fee design. If there’s high taxes, are they being directed in a way which:
1) creates a reflexive ecosystem
2) enables builders to focus on development = volume
3) enough liquidity incentives to encourage long term participation
4) transparent tokenomics
I’ve found it surprisingly strange how many case studies we’ve had for launchpads, what designs have been positive and negative while gauging sentiment to these different mechanisms. Yet there’s always a downfall for every team building in this field as they’re either blinded by internal conflict or the short term revenue was too attractive for them to stick around.
You can reverse engineer the negative proponents while keeping the most successful factors of each one, add some novel features, craft a strong GTM which aligns with future high growth metas that benefit from AI’s advancements and be willing to iterate on feedback from core users.
The biggest mistake I continue seeing with platforms is putting themselves before founders and traders. Due to how successful Pump has been, most launchpads lead with the mindset of a revenue first approach. Long XYZ was the first to play with opposing dynamics and we saw the refreshing response it received.
At this stage of onchains life cycle, there needs to be clear demonstration that a platforms mechanics is honest with the issues of the current environment. It’s one thing to market yourself as a “anti vamp saving grace”, although if your launch mechanisms, fees, tokenomics, ecosystem support, iteration on feedback fail to reflect your messaging, its apparent to even novice traders these days.
You can't expect teams to spend years building products and stake their entire business models on your ecosystem if your commitment only extends to marketing, narratives and growth potential.
It needs to be reflected in your mechanism design, how incentives are aligned and whether the teams building on top of you actually feel supported long term.
Traders are the icing on the cake and the end result in product development. Build the right environment for long term businesses that are able to sustain runway, attention and network in a high growth sector, then the volume is simply a confirmation of your decisions.
@machinedotfun and $CODEC coded.
Hodlo retweeted
Binance, Coinbase and Upbit just listed a robot data token at ~$286M FDV this week.
Meanwhile, the most complete robotics stack in crypto still trades at ~$6.6M. That's $CODEC, and it's my main bet in the vertical rn.
Why?
- Data: SimArena records robot demos in the browser and exports straight to LeRobot, the format the labs train on. It's the sim partner of TUM's robo(.)innovate hackathon starting today, and the team says first university licence revenue is starting to flow in.
- Compute and runtime: Fabric (per-second GPU mesh) and optr (open-source runtime) take one robot program from sim to edge to cloud.
- Payments: an x402 escrow so a robot or an agent can pay for compute it can't price upfront.
- Capital: @machinedotfun with peaq, a launchpad for hardware teams with SimArena built in.
No one else in the set covers more than one of those.
What Axis (focus of quoted post btw) doesn't have?
A proper value accrual mechanism for the token. machine(.)fun committed platform revenue to open-market $CODEC buybacks. And there's no VC overhang on the Codec side either.
What gets $CODEC repriced?
Three things imo, all due by Q1 2027, or more specifically: the first hardware teams launching on machine(.)fun, the first $CODEC buybacks hitting the chain, and SimArena putting numbers behind its licence revenue.
At ~$6.6M none of that is priced in. You're getting the most complete robotics stack in crypto for about half of what Axis raised in its seed round, with the catalysts mostly dated.
That's the asymmetry I'm positioned for.
NFA ofc. DYOR.
Robot models have a data problem the internet can't solve the way it did for LLMs.
The problem: a robot arm learns from examples of a task done well, and those don't exist online like the tons of text that were used to train LLMs.
That means, someone has to produce them.
For example @axisrobotics.
WTF it is?
Think of it as a training gym for robots, run by the crowd.
You open the app, steer a virtual robot arm through a task like putting a mug in a drawer, or film yourself doing chores on your phone. Every attempt gets checked automatically: did the task actually succeed, and does the recording play back cleanly? The ones that pass earn you points, now tokens, and get logged on Base so it's clear who contributed what.
That cleaned data becomes an open dataset of 50K+ robot demonstrations, plus custom "Task Packages" Axis sells to robot makers and labs.
Crowd data is messy tho. Smoothing out the shaky movements cuts jerk by 80.8%, but 13.8% of cleaned recordings then fail the playback test. Quality has a price.
Does it work? On the one benchmark so far, a leading robot model (pi0.5) trained on Axis data scored 88.8 vs 83.9 without it, about 5 points better.
All of that is in simulation, on one tabletop arm. Whether it carries over to a real robot is the open question, and that's exactly what Season 2 is for.
The token?
- $AXIS by @axisrobotics listed on Binance Alpha, Coinbase and Upbit on the 21st of October. Now (time of writing) ~$0.30, a.k.a. ~$298M FDV on a 16.5% float.
- 16.5% liquid at TGE, first-hour high $0.396, ~25% below it now. Team and both private rounds (31.67%) sit behind a 12-month cliff, first insider unlock ~Oct 2027. Sonar buyers paid $0.10, so ~3x in.
- The docs show no fee flow, no buyback, no burn and no path from Task Package revenue to the token. Until a sink shows up, $AXIS is a rewards currency without a real investment case attached beyond speculation.
- Airdrop: Season 1 is 40M AXIS (4%), half unlocked at TGE, ~$11.9M at today's price. Decent for contributors, thin per Binance Alpha account (250 AXIS, ~$74). Season 2 terms still unpublished.
The comps?
- PrismaX: teleop of real arms, $7M raised (incl. a16z CSX), no token. Ahead on real-robot data.
- BitRobot: $8M raised, real-world datasets already open, no token. Hardware-grounded, slower.
- Codec: same browser teleop on the sim side (SimArena), but built as a full stack around it: compute, runtime, payments and a hardware launchpad (@machinedotfun). Partial overlap at most. ~$6.6M mcap, and the team says first licence revenue is in.
Off-chain, any real buyer can also go to Scale-style data vendors, in-house teleop or NVIDIA's simulators. That's the actual competition for a contract.
Axis has the biggest funnel and by far the deepest market of the group. Nobody has shown a sim-to-real result with crowd data yet, and whoever does first owns the narrative.
So in conclusion: Looks like a credible product, with unproven (but imo likely) demand, that's already priced for success.
I'm not holding any $AXIS for now and missed the airdrop and am not looking to enter rn btw (my main robotics play remains $CODEC).
But will keep an eye on this, especially wrt demand side picking up and token potentially accruing value from what could rapidly turn into a major data business.
Definitely interesting, and a successful launch that is yet another step towards full robo szn.
NFA tho. DYOR.
Hodlo retweeted
Scaling Robotics is starting to look a lot like scaling software.
Over the past months we went through more iterations than we’d like to admit, all trying to answer one question: how does hardware get funded, get to market, and survive long enough to ship? Software can launch from a laptop. Anything that has to physically exist needs money (and lots of it), specialized talent, lab space, testing, manufacturing, distribution, the right connections, and time before it can prove anything.
Early on, one thing was clear: we did not want to build another launchpad. We wanted a home for robotics onchain. That meant finding the right partners, getting the tokenomics right, and giving early-stage builders everything they need to go from idea to production.
A few years ago, none of this would have worked. Why now?
To answer that, we have to go back to 2020, when @OpenAI released GPT-3. Most people outside tech didn’t care yet, but if you were playing with it, it was hard to ignore, because a language model could suddenly learn a new task from just one or two examples. There was no retraining involved, you just showed it what you wanted and it figured out the rest.
It felt familiar for a reason. Humans have a remarkable ability to pick up new skills from very little. Watch someone tie a knot once and you can probably do it. A new barista watches one latte pour, and they’re halfway there. In 2020, for the first time, software started learning the same way.
From there, it took off. Within a couple of years, that same ability was writing code, building apps and designing games. Anyone with an idea could ship something on a screen. But it all stayed on the screen.
Fast forward to today, and the same shift is now happening in the physical world. Robots are starting to learn the way GPT-3 did. The clearest example is @GeneralistAI’s GEN-1.5. Show it a few seconds of someone opening a jar or unzipping a pouch, and the robot does it. No new code, no weeks of training. It learns a physical skill the way the barista learned the latte.
The hardware is getting cheaper just as fast. In 2023 a two-arm research rig cost close to $20,000 USD. Right now, an open-source robot arm costs about $230.
That’s why we, along with roboticists across the globe, believe we’re very close to a ChatGPT moment for robotics. Where teaching a machine means showing it, and the parts cost less than a phone, building a robot stops being something only labs can do.
So what’s stopping someone from starting a hardware company? Money.
A prototype has never been cheaper, but turning it into a scalable product still needs manufacturing, certification, distribution and a team, long before the first unit sells.
It’s not that nobody is funding robotics. Robotics startups raised $18.8B in the first half of this year, more than in all of 2025 and more than the 2021 record. But most of it went to a few giant rounds, like @SkildAI’s $1.4B in January. Across venture, over 40% of seed and Series A money now goes into $100M+ rounds.
Right as the tools reach everyone, the money is moving further away from them. Nobody is writing a $100M check for a garage prototype.
That’s the gap MachineFun is built for.
Our vision is that with greater efficiency in hardware scaling, small start ups, prototypes, and passionate entrepreneur now have the ability to create value at the micro level. By providing simulations tooling like SimArena or verifying your robot through peaqOS, founders can now have early backers follow their journey in public while demonstrating evidence through the provided tooling. By giving founders a platform at the foundational level, we see this as a key stepping stone to reaching mass scalability.
The raise is only the start. We also support with what comes after it: getting to market, logistics, and introductions to the manufacturers and partners who can help you build at scale.
If you have a machine, we want to make it fun.
Hodlo retweeted
See you tomorrow at #SECyT!
I’ll be there from 10 to 2, showcasing @SafeCircleAI and sharing what we’ve been building to make the digital world safer for children.
If you’re attending, come say hi! I’d love to meet you and show you SafeCircle in action.
Event: fseneca.es/secyt26/
I’ll be sharing photos and highlights from the event on Friday.
a real business powered by @RobinhoodApp this is what I like to see. Plus, tek protects children. Dev has been looking for info to get into RH hackathons, help please @vladtenev
Our trademark application has officially been published by the Spanish Patent and Trademark Office (OEPM).
Beyond protecting our brand, this is a step toward expanding SafeCircle’s reach in Web2, opening doors to future grants and seed programs, and strengthening our position as a real business building sustainable revenue.
An important step in protecting our brand and establishing SafeCircle's identity as we continue building AI-powered technology to make the internet safer for children.
Hodlo retweeted
robo.innovate starts tomorrow in Munich, six days of teams trying to get a robot to complete a task end to end.
SimArena is the simulation layer, available to every team with no local setup.
solana:69LjZUUzxj3Cb3Fxeo1X4QpYEQTboApkhXTysPpbpump coded as usual
Highlight x402 Projects on Solana Last 7 Days ⚡️
SGL - @x402_Layer
DREAMS - @daydreamsagents
ACE - @acedatacloud
ZAUTH - @zauthinc
PAYAI - @PayAINetwork
SYRA - @syra_agent
CODEC- @codecopenflow
good read so you understand what solana:BLoVgMLRxxhq3X5x9s7KxaNhnQeMf5Lt7MrEpBkjpump is
1/12
I've been researching SolHandle, and I think there's a bigger story here than most people realize.
It's not just about replacing complicated Solana wallet addresses with @usernames.
It's about building a portable identity layer for an entire blockchain ecosystem.
Let me explain. 🧵
