iCode โช๏ธ iWrite
Joined March 2024
- Tweets71.3K
- Following1.1K
- Followers5.1K
- Likes51.7K
๐๐๐๐ retweeted
My Entry on this MEME CONTEST
One handshake, two legends, one unstoppable meme culture ๐ธ๐ฅ
@apepeofficial ๐ค @TurboToadToken
Different identities, same mission: creating memes and making history
APEPE ร TURBO. CREATE MEMES. MAKE HISTORY.
๐จ APEPE & TURBO MEME CONTEST
๐ A total reward pool worth 10,000 USDT
Two memes unite โ your creations become MEMONS cards!
๐ How to Participate
โธ Follow @TurboToadToken and @apepeofficial
โธ Create an image featuring both TURBO and APEPE, without text, captions, or speech bubbles
โธ Quote this announcement with your creation
โธ Tag both official accounts and include the slogan below:
โAPEPE ร TURBO. CREATE MEMES. MAKE HISTORY.โ
๐ MYTHIC โ 5 winners: One card worth 800 USDT per winner
๐จ LEGENDARY โ 10 winners: One card worth 300 USDT per winner
๐ช EPIC โ 85 winners: One card worth 25 USDT per winner
๐ Participation Rewards โ 500 randomly selected participants receive 2 USDT worth of TURBO each
๐
October 29 โ November 7, 2026
โป Winning entries will be released as cards that can be collected and traded on MEMONS.
๐๐๐๐ retweeted
You spent good money installing a strong lock on your door because you wanted to keep your home safe.
For years, it did exactly that.
Then one day, someone discovers a way to break that type of lock.
Would you keep using it simply because it had protected you all those years?
Thatโs a question the blockchain industry needs to think about too.
The cryptographic methods protecting blockchain networks today may face new challenges as quantum computing advances. And when those methods become vulnerable, networks need a way to upgrade their security.
This is where @Starknetโs approach becomes interesting.
Starknet uses hash-based STARK proofs, which are considered promising against quantum attacks. It also has programmable accounts that can support new transaction signature methods without requiring users to change their addresses or move their funds.
This ability to change cryptographic methods as security requirements evolve is called cryptographic agility.
And itโs an important part of preparing for a future where todayโs security assumptions may no longer hold.
Starknet isnโt claiming that every quantum-security challenge has been solved. Itโs working towards infrastructure that can adapt.
Explore the Quantum Hub: quantum.starkware.co/
๐๐ก๐ฒ ๐ฐ๐จ๐ฎ๐ฅ๐ ๐๐ง ๐๐ญ๐ก๐๐ซ๐๐ฎ๐ฆ ๐๐ ๐๐จ๐ง๐ฌ๐ข๐๐๐ซ ๐๐๐๐จ๐ฆ๐ข๐ง๐ ๐ข๐ญ๐ฌ ๐จ๐ฐ๐ง ๐๐?
@Starknet is exploring this possibility, and thereโs an important reason behind the discussion: security autonomy.
As an Ethereum Layer 2, parts of Starknetโs wider security architecture depend on Ethereum, including its cryptography and migration timeline.
But what happens when Starknet needs to make important security upgrades and its timeline doesnโt align with Ethereumโs?
This is one of the questions driving its independent L1 exploration.
Having its own L1 could give Starknet greater control over its core security roadmap and how quickly it can respond to emerging cryptographic threats.
The conversation gained momentum after a non-binding community vote closed on October 22, with overwhelming support for researching the proposal.
A joint working group from StarkWare and the Starknet Foundation is now examining the technical benefits, security assumptions and trade-offs.
Importantly, this vote did not approve a migration. More research and community decisions are still needed.
Blockchain security isnโt only about the technology you build with. Itโs also about having control over how and when that technology evolves.
Read more: quantum.starkware.co/
๐๐๐๐ retweeted
MY ENTRY FOR #Gamdom100kRound2
ZERO TO HUNDRED
A story about almost giving upโฆ until GAMDOM changed everything
@Gamdom @stevewilldoit @kingadukes
Username: Zedie
๐๐๐๐ retweeted
What if you could participate in an NFT auction without revealing how much you're willing to pay?
That's the interesting idea behind @FungoLabs
Most NFT auctions expose bidding activity, giving participants information they can use to adjust their next move.
FungoLabs is exploring a different model with encrypted NFTs built using Fully Homomorphic Encryption (FHE) from @zama.
The goal is simple but powerful: make NFT interactions private without losing the ability to verify outcomes.
I think this is an important direction for Ethereum.
Because privacy shouldn't be an afterthought in digital ownership. It should be part of the foundation.
Keep an eye on @FungoLabs.
๐๐๐๐ retweeted
my entry for #Gamdom100kRound2
I took the opportunities of @gamdom to my Cuty in Port Harcourt
Ensure you use the code โSTEVEโ to sign up and get started on @gamdom
username: drbells005
@stevewilldoit @kingadukes @SirGamby
weโre running # #Gamdom100kRound2 challenge BACK ๐๐ฟ๐๐ซก
10 people. $10,000 EACH.
make a 30+ second video promoting gamdom and post it with ##Gamdom100kRound2 .
ends november 5th. iโll be quoting good videos and giving out A LOT of nibbles along the way. letโs see what you got
#Gamdom100kRound2
Must fight back when kicked down.
๐๐๐๐ retweeted
AI has come a long way.
Today, we have systems that can write code, generate images and videos, analyse information, follow complex instructions and handle tasks that used to require a lot of human effort.
But there's another side of AI that I think deserves more attention: giving machines the ability to interact with the physical world.
Think about a robot picking up a glass. Recognising the glass is easy enough. But actually picking it up is a different story.
The robot needs to know where the glass is, how to approach it, how firmly to hold it and how to adjust if something doesn't go as planned.
That's where Embodied AI comes in.
It focuses on intelligent systems that can perceive their surroundings, make decisions and take actions in the real world.
A 2025 research survey, Embodied AI: A Survey on the Evolution from Perceptive to Behavioral Intelligence (onlinelibrary.wiley.com/doi/โฆ), breaks this down into three key areas:
- Perception: Understanding what's happening in the environment through cameras and other sensors.
- Decision-making: Processing that information and figuring out what to do next.
- Execution: Turning those decisions into actual physical movements.
All three have to work together. Recognising an object doesn't automatically mean a robot knows how to handle it.
It also needs to understand distance, position, physical properties and how its actions affect the environment.
And that's where things get complicated.
The physical world doesn't always behave as expected. Objects move, surfaces differ, lighting changes and sensors aren't always accurate. Sometimes, an action simply doesn't produce the expected result.
A paper published in ACM Computing Surveys, "Embodied Intelligence: A Synergy of Morphology, Action, Perception and Learning" explores how an intelligent system's body, actions, perception and learning all work together.
I find this particularly interesting because it shows that intelligence isn't just about what a machine knows. It's also about how it interacts with its environment and learns from those interactions.
This also means that building better physical AI requires more than just powerful AI models.
We need realistic environments for training, quality interaction data, proper evaluation methods and infrastructure that can support the entire process.
The goal is no longer just to build machines that understand the world. It's to build machines that can actually function in it.
As AI continues moving into robotics, manufacturing, logistics and everyday physical environments, the infrastructure behind this transition will matter a lot.
And that's an important part of the conversation around Embodied AI and what Inverted Lambda is building.
The next frontier isn't just AI that can tell us what to do. It's AI that can learn to do things itself.
@InvLambda ๐งต
๐๐๐๐ retweeted
What comes to mind when you hear @gamdom ?
Over 7,00 games, Casino, Sports, Gamdom Originals, Rewards, and plenty of ways to enjoy the platform.
There's something for different interests and different kinds of players.
And who says a lady can't be in the casino?
The Boss Lady is here to challenge that stereotype.
Women belong in gaming spaces too.
Gamdom is for everyone!
But there's more to the experience than playing games.
Imagine being new to Gamdomโฆ
You have questionsโฆ
You want to understand how the platform works, explore its features, or find your way aroundโฆ
That's where the idea of Gamdom AI comes in.
An intelligent guide that could help users understand the platform, explore its features, navigate the games, and get answers to common questions.
It's a concept with the potential to make Gamdom more accessible and welcoming, especially for new users.
And then there's The Companion, The Gamdom Dog!
Representing loyalty, companionship, and community, our furry friend brings a little extra personality to the experience.
Three characters, each representing a different part of what makes the experience special: confidence, intelligent assistance, and companionship.
Gamdom is more than a place to play.
It's a destination for gaming, entertainment, discovery, and experiences.
Start on Gamdom.com today.
Use the code STEVE to register
@stevewilldoit @kingadukes @gamdomย
#Gamdom100kRound2
You called for itโฆ
No AI? so we brought it to live.
Meet the human face of Gamdom AI! Your intelligent guide to navigating the Gamdom platform with ease.
And who said the casino floor isn't for the ladies? Certainly not GAMDOM!
@gamdom is built for everyone.
Full video incoming!
Code: STEVE
#Gamdom100kRound2
๐๐๐๐ retweeted
with how the market has been lately, i think itโs worth paying attention to memes that have built genuinely strong communities.
hype comes and goes, but having people who stick around through different market conditions matters.
almost 6 months in and $DINKY is still here.
sooo, dudes and dudettes, what are you waiting for?
๐ค Paid partnership
AI has come a long way.
Today, we have systems that can write code, generate images and videos, analyse information, follow complex instructions and handle tasks that used to require a lot of human effort.
But there's another side of AI that I think deserves more attention: giving machines the ability to interact with the physical world.
Think about a robot picking up a glass. Recognising the glass is easy enough. But actually picking it up is a different story.
The robot needs to know where the glass is, how to approach it, how firmly to hold it and how to adjust if something doesn't go as planned.
That's where Embodied AI comes in.
It focuses on intelligent systems that can perceive their surroundings, make decisions and take actions in the real world.
A 2025 research survey, Embodied AI: A Survey on the Evolution from Perceptive to Behavioral Intelligence (onlinelibrary.wiley.com/doi/โฆ), breaks this down into three key areas:
- Perception: Understanding what's happening in the environment through cameras and other sensors.
- Decision-making: Processing that information and figuring out what to do next.
- Execution: Turning those decisions into actual physical movements.
All three have to work together. Recognising an object doesn't automatically mean a robot knows how to handle it.
It also needs to understand distance, position, physical properties and how its actions affect the environment.
And that's where things get complicated.
The physical world doesn't always behave as expected. Objects move, surfaces differ, lighting changes and sensors aren't always accurate. Sometimes, an action simply doesn't produce the expected result.
A paper published in ACM Computing Surveys, "Embodied Intelligence: A Synergy of Morphology, Action, Perception and Learning" explores how an intelligent system's body, actions, perception and learning all work together.
I find this particularly interesting because it shows that intelligence isn't just about what a machine knows. It's also about how it interacts with its environment and learns from those interactions.
This also means that building better physical AI requires more than just powerful AI models.
We need realistic environments for training, quality interaction data, proper evaluation methods and infrastructure that can support the entire process.
The goal is no longer just to build machines that understand the world. It's to build machines that can actually function in it.
As AI continues moving into robotics, manufacturing, logistics and everyday physical environments, the infrastructure behind this transition will matter a lot.
And that's an important part of the conversation around Embodied AI and what Inverted Lambda is building.
The next frontier isn't just AI that can tell us what to do. It's AI that can learn to do things itself.
@InvLambda ๐งต
Inverted Lambda has an ambitious vision, but building useful infrastructure for Embodied AI isn't going to be easy.
There are still some major challenges the industry needs to figure out.
First, simulation accuracy.
A virtual environment can look exactly like the real world and still behave differently. Robots have to deal with things like friction, weight, contact and all the little surprises that come with physical environments.
Second, data quality.
Collecting more demonstrations doesn't automatically make robots better. The data needs to be useful, consistent and relevant to the tasks they're expected to perform.
Third, evaluation and reliability.
A robot completing a task once doesn't mean it can do it again successfully. We need to know whether it can perform consistently and safely, even when conditions change.
Finally, accessibility and trust.
If people are going to contribute environments, demonstrations and evaluations, they need clear qualification standards, transparent rewards and a way to see the value of their contributions.
These aren't just theoretical concerns.
NVIDIA's simulation-to-reality guide explains some of the difficulties involved in transferring simulated learning to real robots.
For Inverted Lambda, the opportunity is to bring several parts of this process together through its product ecosystem.
But having a promising vision is only the starting point.
What will really matter is what the infrastructure can deliver in practice: robots that perform reliably, contributions that have real value and measurable improvements over time.
That's where the real test begins.
We've looked at the technology, the products, the challenges and the opportunities surrounding Embodied AI.
And if there's one thing I keep coming back to, it's that building intelligent machines takes more than just building robots.
It takes the right infrastructure, useful data and people who contribute to making these systems work in the real world.
That's what makes Inverted Lambda's vision worth paying attention to.
If you want to learn more, check them out:
Website: invertedlambda.com/
X: nitter.cf/InvLambda
#InvertedLambda
