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Quantum computing is still evolving but blockchain developers already have a reason to think ahead.
@Starknet is taking an interesting approach by looking beyond the security assumptions used today.
Its STARK proofs rely on hash-based cryptography while other parts of the ecosystem may need different solutions as quantum technology advances.
What makes this worth exploring is the ability to adapt over time.
Smart contract accounts can update their signature verification logic without changing wallet addresses while experimental Falcon-512 integration explores quantum-resistant authentication.
The goal isn't just to make blockchain secure today.
It's to make sure the infrastructure can evolve when tomorrow's security requirements become different.
Prediction markets are becoming easier to explore but the real challenge is making the experience simple without losing the depth.
That's where @bagel_win stands out to me.
Bagel brings Polymarket's existing markets and liquidity into a mobile-friendly app giving users a more convenient way to follow events and explore probabilities.
You can enter at the current price set a limit order for your preferred entry or combine multiple outcomes through combo orders.
There's also an AI layer to help users understand market movements and explore different possibilities.
What I like about this direction is that it gives people more flexibility without making every decision for them.
You still need to do your own research, understand the risks and decide which positions make sense.
Bagel is making prediction markets more accessible and that's a meaningful step forward.
Mobile-first prediction markets are making it easier to participate in global events anytime, anywhere.
bagel.win/?ref=EEX2HK
That's what makes @bagel_win worth exploring.
Bagel brings a mobile-first prediction market experience to users in 150+ countries and regions, leveraging Polymarket's markets and liquidity.
Beyond simply predicting outcomes, Bagel introduces AI-powered market insights and recommendations to help users better understand market trends and make more informed decisions.
It also supports different trading strategies:
🔹 Market Orders: Enter a position instantly at the best available price.
🔹 Limit Orders: Set your preferred price and wait for execution.
🔹 Combo Orders: Combine multiple predictions into one position for a more flexible strategy.
For me, the interesting part is how Bagel combines mobile accessibility, AI insights and existing prediction market liquidity into one experience.
Prediction markets are becoming more accessible, and Bagel is worth keeping an eye on.
Not financial advice.
AI agents don’t need to know how to do everything.
They need a way to find the right agent for the job.
That’s what makes @termix_ai interesting to me.
Through agent family an agent can offer its own services receive paid tasks or hire another agent when it needs skills beyond its capabilities.
The process goes beyond simple communication.
Services can be purchased through escrow, with payment released after the work is completed and accepted.
This opens up a different way to think about AI.
Instead of one agent handling every request, specialized agents can work together, exchange services and build their own commercial relationships.
The future of AI may not be about having one agent that does everything, but an entire network of agents that know how to get things done.
That’s the direction @termix_ai is exploring.
What if prediction markets were more than just numbers moving on a screen?
That’s an interesting angle to explore with @bagel_win
Bagel brings Polymarket markets into a mobile-friendly environment where users can explore different outcomes, follow experienced predictors, and discover what others think about upcoming events.
The platform combines:
→ Social conversations around market outcomes
→ AI-powered insights and analysis
→ One-tap copy trading
→ Market, limit, and combo orders
→ Rewards through referrals and copy trading fees
The part I find interesting is how Bagel connects market information with community perspectives.
Instead of viewing odds in isolation, users can explore the reasoning and sentiment behind different predictions.
Of course, market access and participation depend on local regulations, and financial risks should never be ignored.
With @bagel_win I’m curious to see how social discovery and prediction markets evolve together.
예측 시장과 야핑, 무엇을 주의해야 할까요?
웹3에서 예측마켓의 인기와 영향력은 점점 커지고 있습니다 !
정치, 경제, 스포츠, 암호화폐 등 다양한 사건의 결과를 예측하고 거래할 수 있다는 점에서 새로운 시장으로 성장하고 있습니다.
하지만 이와 별개로 대부분의 국가에서 이런 예측마켓을 자유롭게 이용할 수 있는 것은 아닙니다. 되게 모순적인 상황인거 같더라구요
이번에 @KaitoStudio_ 에서 @bagel_win 이라는 신규 예측마켓 플랫폼 야핑캠페인이 열렸습니다!
그럼 이런 예측마켓 카이토 야핑을 누가 자유롭게 할수 있는것인가 갑자기 꿀꿀존이 궁금해져서 알아봤습니다!!
나라별 예측마켓 규제를 살펴볼까요?
국가별 규제 차이
✅ 합법·규제 체계가 있는 곳
🇺🇸 미국: Kalshi 등 CFTC 감독을 받는 플랫폼이 있지만, 상품별·주별로 법적 쟁점이 존재
(⚠️ 미국에서도 스포츠 관련 계약은 일부 주에서 법적 분쟁이 진행되고 있습니다.)
🇬🇮 지브롤터: 예측 시장 관련 규제 체계의 구체적인 시행 여부와 범위 확인 필요
🚫 이용 제한 및 규제 리스크가 있는 국가
🇪🇺 프랑스, 스페인, 이탈리아, 독일, 영국 등 유럽 일부 국가
🇰🇷 한국 (한국은 일부 플랫폼 접속 차단 및 이용자 수사 관련 이슈 존재)
🌏 인도, 호주, 뉴질랜드, 필리핀 등
🌎 브라질 등 중남미 일부 국가
이렇게 되면 거의 대부분의 나라에서는 예측마켓을 허용하지 않고 있는 상황에서 우리는 어떻게 야핑을 해야할까요?
@grok 에게 물어보니 이렇게 답해줬습니다!
프로젝트를 소개하고, 시장의 흐름을 분석하며, 커뮤니티와 소통하는 것은 InfoFi 활동의 중요한 부분입니다. 하지만 프로젝트의 기술과 산업 동향을 소개하는 것과 특정 플랫폼의 이용을 적극적으로 유도하는 것은 구분할 필요가 있습니다.
✅ 예측 시장의 작동 원리와 기술적 특징 소개
✅ 규제 동향과 글로벌 시장 변화에 대한 정보 공유
✅ 유동성, 가격 형성, 시장 참여자의 기대 심리 분석
✅ 프로젝트의 투명성, 정산 구조, 리스크 관리 방식에 대한 논의
반면 다음과 같은 활동은 더욱 신중해야 합니다.
⚠️ 국내에서 이용이 제한된 플랫폼의 우회 접속 방법 안내
⚠️ 레퍼럴 링크나 보상을 통해 이용자의 참여를 적극적으로 유도하는 행위
⚠️ 국내 이용이 합법적으로 보장된 것처럼 표현하는 홍보
⚠️ 금융적·법적 위험을 축소하거나 수익을 과장하는 콘텐츠
특히 한국에서는 도박 관련 법률이 엄격하게 적용될 수 있으며, 해외 플랫폼을 이용한다고 해서 국내 법률의 적용 가능성이 자동으로 사라지는 것은 아닙니다.
물론 모든 예측 시장이 동일하게 취급되는 것은 아닙니다. 상품의 구조, 거래 대상, 금전적 가치의 유무, 정산 방식, 운영 주체 등 구체적인 사실관계에 따라 법적 판단이 달라질 수 있습니다.
꿀꿀존의 생각 🐷
사실 아직까지 직접 예측마켓을 이용하지 않는 이상 X 에 포스팅 하는 걸로는 처벌이나 제재를 받은 적은 없던거 같습니다
수많은 크리에이터들이 예측마켓 포스팅을 해왔고 하고 있는 이유겠죠?
그래도 그록이 알려준 최소한의 유의사항은 꼭 주의 하면서 야핑을 해볼까요?
그럼 전 Bagel 플랫폼의 기술적 특성에 대해 이번에 알아보겠습니다!
@bagel_win 은 150개 이상의 국가와 지역에서 Polymarket의 마켓과 유동성을 모바일 환경에서 편리하게 이용할 수 있도록 설계된 예측시장 플랫폼입니다.
원탭으로 상위 예측가의 거래를 카피 트레이딩하고, 소셜 토론과 AI 기반 시장 분석 및 추천을 통해 더 나은 의사결정을 지원합니다. 또한 콤보 주문, 시장가 주문, 지정가 주문을 제공하며, Rewards Center에서는 추천 및 카피 트레이딩 수수료 수익과 VIP 배지, 등급별 혜택까지 제공합니다.
오늘 엄청 글이 길었네요
다들 행복한 하루 시작하세요🐷
An AI agent can perform tasks but turning that ability into a paid service is where things get interesting.
That’s the idea behind @termix_ai .
Instead of keeping agents limited to individual tools TermiX is building a marketplace where they can discover services collaborate and exchange value.
→ Agents can find specialized skills
→ Tasks can be coordinated between different agents
→ Payments can be handled through on-chain infrastructure
The bigger opportunity is making AI useful beyond a single conversation.
If agents can reliably deliver work and get paid for it they become more than assistants.
They become participants in a digital economy.
That’s what makes the agent economy worth watching.
The future of finance isn't just about moving assets onchain.
It's about making that transition without exposing everything behind every transaction.
DTCC's new Tokenization Service is a meaningful step with 20 participants joining on day one.
@zksync is one of the firms collaborating with DTCC with Matter Labs providing privacy features through Prividium.
Because institutions need more than blockchain access.
They need privacy, control and infrastructure that fits the way they already operate.
This is where tokenization starts becoming practical for traditional finance.
A strong signal for the future of $ZK.
Congrats to @The_DTCC on the launch of its Tokenization Service. We’re proud to be among the firms collaborating with DTCC.
@the_matter_labs is providing privacy features with Prividium.
DTCC provides custody and asset servicing for more than $114 trillion in securities.
Rida retweeted
Congrats to @The_DTCC on the launch of its Tokenization Service. We’re proud to be among the firms collaborating with DTCC.
@the_matter_labs is providing privacy features with Prividium.
DTCC provides custody and asset servicing for more than $114 trillion in securities.
Most people think privacy in DeFi means keeping their wallet address hidden.
But what about the financial patterns behind it?
Your balance transaction history and trading decisions can reveal a lot about you even without knowing your identity.
That’s why I find the work of @primus_labs worth following.
With FHE the idea is to let financial data remain encrypted while computations still take place.
Imagine being able to use DeFi without exposing every detail of your financial activity.
That could change how people interact with onchain finance.
Privacy shouldn't mean giving up utility.
AI agents are becoming more capable but the next step is giving them a way to work together and create real value.
That’s what makes @termix_ai interesting to me.
Through its AACP infrastructure agents can offer services hire others and handle payments through onchain escrow.
Reputation and dispute resolution add another layer of accountability which becomes important when agents start doing business with each other.
The Skills integration also opens up new possibilities.
Compatible coding agents can connect through Agent IDs and communicate beyond a single marketplace.
I think the bigger opportunity is turning AI from something that simply assists people into something that can participate in a working economy.
And TermiX is exploring that direction.
DeFi needs a better balance between transparency and privacy.
Not every financial detail should be public just to prove something is legitimate.
This is where @primus_labs brings an interesting approach.
With zkTLS for data verification and FHE for encrypted computation Primus is exploring how users can prove what matters without exposing everything behind it.
This could make privacy-preserving lending, asset verification and other DeFi use cases more practical.
The goal is simple: build trust without giving up control over personal data.
A direction worth watching as Web3 evolves.
Trust is important in Web3 but sharing private data just to prove something shouldn't be the only option.
This is the problem @primus_labs is working on with zkTLS.
It helps verify information from Web2 platforms through cryptographic proofs reducing the need to rely on screenshots or expose sensitive account details.
The potential goes beyond identity or social activity.
Verified offchain data could also help AI agents and Web3 applications make decisions based on information they can actually prove.
Privacy and verification don't have to compete with each other.
Physical AI needs more than powerful models.
It needs a better understanding of the places where it operates.
That’s where @vangrid_io is taking an interesting approach.
Instead of collecting random footage and hoping someone needs it later Vangrid allows specific locations and capture tasks to be requested through its bounty system.
Contributors visit those places record them with smartphones and turn the footage into 3D reconstructions that buyers can review.
The interesting part is how this connects real-world data collection with actual demand.
→ Buyers define what they need
→ Contributors capture the environment
→ 3D data is generated and reviewed
→ Payments are linked to accepted work
For robotics and autonomous systems, having updated information about real environments could make a meaningful difference.
Of course the real challenge is maintaining data quality coverage and reasonable capture costs as the network grows.
Vangrid is exploring a practical question: can real-world spatial data become something AI systems request when they need it rather than relying only on what has already been collected?
What if proving you’re trustworthy didn’t mean giving up your privacy?
That’s an important challenge for onchain finance and one @primus_labs is working to solve.
By combining zkTLS with Fully Homomorphic Encryption (FHE), Primus is exploring how information can be verified and used without exposing the underlying data.
I think this is a key piece of building a financial system where trust comes from proof, not from revealing everything.
The goal shouldn’t be less privacy to gain more trust. It should be both.
Trading capital is more useful when it doesn’t have to sit idle just to earn a return.
That’s the idea behind Yield as Margin in @grvt_io’s upcoming Grvt 2.0.
Eligible Earn balances are expected to support trading margin while continuing to generate yield giving users a way to put the same capital to work in two different ways.
The key question is how smoothly this works under real market conditions, especially when margin requirements change quickly.
If executed well this could be a meaningful improvement in capital efficiency.
Grvt 2.0 is expected to bring this feature in November.
Worth watching how it performs beyond the concept.
🤝 Paid partnership
AI is becoming better at understanding digital information but understanding the physical world brings a different challenge.
This is where @vangrid_io comes into the picture.
Through smartphone captures Vangrid is helping turn real-world environments into 3D data that AI systems and machines can use to better understand physical spaces.
The interesting part is how this approach connects everyday contributors with a growing need for real-world spatial data.
More diverse environments could help make these datasets useful across different applications from robotics to Physical AI.
Of course data quality and coverage will matter just as much as quantity.
For me, Vangrid is worth watching because it focuses on a practical problem: giving machines better information about the world they need to operate in.
The next step is seeing how effectively this data translates into real-world use cases.
One capture at a time the network is moving toward that goal.
🤝 Paid partnership
A trading platform becomes more interesting when it starts thinking about what happens to capital between trades.
That’s one area I’m watching with @grvt_io .
Instead of treating trading and earning as completely separate activities GRVT is exploring ways to make eligible Earn balances useful as margin while they continue generating yield.
For me the bigger story is capital efficiency.
Traders want flexibility but they also need clear margin rules and reliable risk management when volatility picks up.
If GRVT can make both sides work smoothly it could offer a more practical way to manage trading capital without leaving earning potential behind.
The real value will come from how well it works in actual market conditions.
🤝 Paid partnership
Rida retweeted
The Base Track in @gmgnai’s Global Championship runs through October 26, with $20K and a fast-track spot at the London finals up for grabs.
This comes right after the Base Meme Summit, where @jessepollak talked about bringing more traders and communities to @base.
GMGN is also hosting a Base Day livestream on October 26, so there's something to follow even if you're sitting out the competition :)
A few things to remember if you're entering:
1. $2K starting cap across all competition wallets
2. No outside top-ups after joining
3. All trades must go through GMGN
4. Only realized PnL counts in the final rankings
At the finals, traders will have a chance to compete for a custom Aston Martin Vantage.
This is a good example of how Base keeps pushing its meme ecosystem.
So if you're entering, check out the full details and rules, otherwise I'll see you on the stream: gmgn.ai/ggc
🤝 Paid partnership
BASE TRACK IS COMING TO #GGC .
Starting TODAY through October 26, we're taking the competition to @base .
Trade Base coins and climb the leaderboard.
$20,000 prize for the track winner
1 Fast-track entry to the GGC London Finals
A shot at winning an Aston Martin Vantage
Tune in on October 26 for a special Base Day livestream with guests from the ecosystem.
Good morning everyone 🥰
Physical AI needs more than powerful models.
It needs accurate data from real places.
That’s where @vangrid_io comes in. People can capture their surroundings using smartphones, helping create 3D spatial data for AI and robotics.
The interesting part is how real-world contributions connect with blockchain verification and USDC payments for accepted work.
Vangrid is building a system where everyday people can contribute to the data infrastructure that future AI systems may depend on.
The world is changing every day, and AI needs data that keeps up with it.
🤝 Paid partnership
Most trading capital has one job: sit there as margin.
@grvt_io is exploring a different approach with Grvt 2.0 where eligible assets could earn up to 11% APY while also supporting trading positions.
It’s a shift from simply holding collateral to making capital more productive.
Of course yield comes with risks and isn’t guaranteed.
The real question is how much more efficient trading capital can become.
🤝 Paid partnership
