Cryptocurrency
Garbled Circuits 101: What Could They Enable for Blockchain Privacy?
Blockchains were originally designed to be transparent, with every wallet and transaction on public display. Many supporters see this ‘trustlessness’ as a strength, but there are some obvious drawbacks, such as the security risk of having all of your financial activity available on-chain.
We can see this in the rates of illicit activity around blockchain, with bad actors accounting for $39.6bn of transaction volume in 2022.
We are also seeing a growing tactic of frontrunning for personal gain, where users with the technical skills to do so, reorder trades before they are committed to a block. By doing this they can ensure their own trades are always profitable.
These are just two examples of why transparency is often seen as a bug, and it’s also why the search for blockchain privacy is heating up. We are now seeing a flurry of innovation within the ecosystem to push for privacy solutions, arguably the last frontier for blockchain.
Blockchain Privacy Solutions
You may already be familiar with Zero-Knowledge proofs or ZKPs, one of the first blockchain privacy solutions to gain widespread adoption. ZKPs allow data to be shared between two parties without revealing any sensitive information. However, they fall short when handling more complex computations.
In many instances blockchain applications need multiple parties to compute solutions together, known as Multi Party Computation (MPC). This is where Fully Homomorphic Encryption (FHE) came into play. About four years ago, FHE emerged as an elegant solution to solve the MPC problem. FHE enables multiple parties to carry out computations on encrypted data without needing to disclose or know the underlying data points in order to retrieve the end result. However, FHE faces significant scaling issues given its high computing costs.
Garbled Circuits, High-speed, Lightweight Blockchain Privacy
Garbled Circuits – a technology developed by Soda Labs and implemented exclusive by COTI – aims to solve the MPC problem with much lower costs to run and far better performance.
In essence Garbled Circuits can be used to make confidential multi-party computations of varying complexity with any number of participants providing inputs. This makes it suitable for complex applications on blockchain protocols including private smart contracts. However, tweaks to the technology today mean that it is less computationally intensive, giving it the ability to scale.
How do Garbled Circuits work?
The concept of Garbled Circuits actually dates back to the late 80s, when it was proposed as a solution to Yao’s Millionaires’ Problem by famous cryptographer Andrew Yao. Imagine that there are two millionaires, Alice and Bob, who want to know who between the two of them has more money. The problem is that no one wants to reveal how much they have exactly. Instead of revealing the amount of money each of them has, they can solve their dispute with the help of Garbled Circuits.
Alice and Bob each write down their net worth in encrypted text, as a string of letters and numbers. Both of them put this piece of paper into a black box, and after a split second, a piece of paper is ejected with the name of the richer person. In this example, the black box is the Garbled Circuit, a powerful computer program that can perform complex calculations on encrypted data without leaking any information.
Garbled Circuits introduce new levels of confidentiality to Web3, protecting data and metadata to enable confidential payments, private/blind auctions and the secure management of sensitive information on-chain without sacrificing performance. COTI has demonstrated the technology’s effectiveness ahead of its integration with Ethereum-based Layer-2 network, COTI V2, which launched in April.
Web3 Use Cases for Garbled Circuits
As blockchain applications grow more complex, a privacy solution is needed that can handle secure MPC without any limit to the number of inputs. In these instances, Garbled Circuits have huge potential.
Confidential DeFI: Garbled Circuits enable confidential transactions, allowing Decentralized Finance (DeFi) apps to maintain regulatory requirements while solving losses from MEV by encrypting transaction data, shielding them from sandwich bots. Just some of the DeFi use cases of GC include private Automated Market Makers (AMMs), undercollateralized lending, dark pools and hybrid exchanges. These can leverage both centralized and decentralized elements while keeping trade details confidential.
Dynamic Decentralized Identification (DID): Garbled Circuits facilitate identity verification and personal information sharing, calculation, and storage without revealing actual data to other parties, ensuring KYC compliance while maintaining user privacy. For instance, decentralized lenders can now establish someone’s suitability for a loan without the individual exposing their wallet address or personal information. The GC breakthrough preserves privacy whilst fulfilling regulatory requirements.
On-Chain Sensitive Data Management: Garbled Circuits allow for encrypted data storage on-chain, enabling analysis of sensitive information without compromising privacy. Data can be safely shared across sites, preventing companies from scraping and selling it. Some of the applications that become possible include confidential on-chain voting systems and healthcare services. By storing encrypted data on-chain, GC satisfies stringent data protection standards whilst still providing the benefits of blockchain data storage and analysis.
One of the main characteristics of Garbled Circuits is their efficiency. Benchmark tests have shown that Garbled Circuits are much faster, lighter and cost-effective than any other privacy-preserving technology available today. This makes GC highly scalable, ensuring that the technology can grow alongside expanding markets such as Real World Assets (RWA) and Artificial Intelligence (AI).
Confidential Transactions for Payments, Stablecoins and RWA. Garbled Circuits maintains fund flow transparency while encrypting transaction details, ensuring regulatory compliance for payments, stablecoins, and real-world assets (RWA). RWAs include assets like real estate, commodities and securities that require high levels of privacy. GCs ability to ensure privacy, meet regulatory requirements, enhance security, and scale efficiently makes them an ideal choice.
Confidential Machine Learning & AI. Garbled Circuits also enables secure, private interactions with AI and large language models (LLMs), safeguarding data model confidentiality and data source privacy as required by law. GC can be used to enable decentralized and democratic ML model development and opens up new possibilities for privacy-focussed data marketplaces allowing researchers and businesses to work with datasets without exposing sensitive information.
Summary
To summarize, Garbled Circuits are revolutionizing privacy in blockchain applications, offering solutions that cater to various sectors, including DeFi, identity management, sensitive data handling, and AI. With their increased performance and scalability over other privacy solutions like FHE, Garbled Circuits are set to play a pivotal role in the future of Web3.
Authored by: Shafah Ban-Geffen, CEO and CO-Founder of COTI
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Cryptocurrency
PIN AI secures $10M from a16z CSX, Hack VC, and All-Star angels to launch open platform for personal AI
[PRESS RELEASE – San Francisco, United States, September 9th, 2024]
Innovative startup from Ethereum Core research, Google Brain, Stanford, MIT, and CMU aims to democratize on-device intelligence, empowering users with control over their personal AI, and receiving investment from a16z CSX, Hack VC, and investors from projects like Solana, Polygon, Near, Worldcoin, etc.
PIN AI, a pioneering AI infrastructure company, announces $10 million in pre-seed funding to develop the world’s first open-source Personal Intelligence Network (PIN). A16z CSX, Hack VC, and notable investors, including Blockchain Builders Fund (Stanford Blockchain Accelerator), Illia Polosukhin (Transformer paper author; Founder, NEAR Protocol), Anagram/Lily Liu (President, SOL Foundation), Symbolic Capital (Co-Founder, Polygon), Evan Cheng (CEO, Mysten Labs/SUI), dcbuilder (Worldcoin Foundation), Foresight Ventures (parent company of the Block), Nomad Capital, Tim Shi (Co-Founder, Cresta), Ben Fisch (CEO, Espresso), Scott Moore (Co-Founder, Gitcoin), Alumni Ventures, and Dispersion Capital, have backed the project.
Offering an open-source, web3-enabled alternative to Apple Intelligence, PIN AI’s platform turns smartphones into privacy-focused AI personal assistants. By redirecting profits from users’ data and attention, it empowers users to regain control and monetize their data. The platform leverages personal, contextual data and cryptography, deploying cutting-edge AI models on-device to handle tasks across apps—like shopping, ordering food, wealth management, and interacting with centralized exchanges, DeFi, and prediction markets.
This AI-driven assistant ensures robust privacy and user-controlled data management, disrupting ultra-profitable models of web2 giants, including Apple’s 30% app revenue cut (over $100 billion) and Google’s mobile ads and Android store revenue cuts.
Davide Crapis, Co-Founder leading Protocol Research, said, “We’re building a movement towards an open-source future where personal AI assistants can work on PIN AI’s platform like smart contracts on Ethereum.” He added, “PIN AI will take back the $100b+ profit from tech giants and return it to users, allowing them to control and monetize their data. Our platform offers access to a wider range of AI agents, developed by the open-source community, capable of handling tasks across popular apps.”
PIN AI’s mission is to foster innovation for personal AI agents by offering access to personal, contextual data that reflects individual users’ needs and preferences. Unlike closed ecosystems like Apple, PIN AI’s open platform connects privacy-protected user data via a Layer-2 blockchain. This enables more flexibility in AI application development without the constraints of traditional, closed systems.
Bill Sun, Co-Founder and Chief Scientist, said, “On-device multi-modality models will revolutionize daily life. We are building a personal index for each user to create an on-device model that evolves via distributed training on the user’s phone. Soon, users won’t need to open multiple apps to complete tasks. The personal AI assistant will understand preferences and manage tasks efficiently.” PIN AI’s assistant will connect users with apps and services bidding on its blockchain protocol to fulfill tasks like shopping or crypto activities.
PIN AI shifts data monetization from big tech to users, allowing secure monetization of personal data. Users receive token incentives through data onboarding and intent fulfillment, only providing necessary data with matched Personal AI Agents, while maintaining control of their information.
At launch, PIN AI partners with Worldcoin and is developing a front-end product similar to Siri, expanding its reach and enhancing user experience.
Leading the team are co-founders Davide Crapis and Ben Wu. Crapis, formerly of Ethereum Core Research, leads Protocol Research. Ben Wu, heading Strategy, is an MIT graduate, Y Combinator alum, and serial entrepreneur. The technical leadership includes Bill Sun, a Stanford AI/Math PhD and early Google Brain researcher, as Chief AI Scientist, and Regan Peng, a CMU graduate and former lead at Didi Fintech and Yahoo Data Infra, as Founding Head of Engineering.
PIN AI collaborates with a16z crypto research, Flashbots, Espresso Systems, and academics from Stanford, Columbia, and NYU. Ben Wu emphasized the importance of an open platform, saying, “The open internet has made large language models possible. We need to build an open platform for users on their trusted device, allowing access to their various data, making their Personal AI possible.” Unlike Apple Intelligence, PIN AI’s system can run on low-spec smartphones by dynamically shifting between edge AI (on-device) and server AI to optimize performance, ensuring wide accessibility.
The funding will expand research, grow the team of AI and blockchain experts, and accelerate the deployment of PIN AI’s technology. The company will join the a16z CSX Fall 2024 cohort in New York City.
About PIN AI
PIN AI is developing an open-source personal AI operating system that leverages smartphone and app data to empower users with control and privacy. The company’s approach aims to connect AI developers with users, promoting data sovereignty and developer empowerment. PIN AI collaborates with Ethereum Core Research and is committed to privacy and innovation.
For more updates, visit pinai.io, X (formerly Twitter), Telegram, Discord, and Linkedin.
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Cryptocurrency
Panda Ling ($LING) Unveils TRON-Based Tap2Earn and Task2Earn Platform – Presale Event Announced
[PRESS RELEASE – Zurich, Switzerland, September 9th, 2024]
Panda Ling, the latest meme token to emerge on the TRON blockchain, has introduced a Tap2Earn and Task2Earn platform designed to revolutionize crypto earning models. With its user-friendly interface and focus on engagement, the platform allows participants to earn $LING tokens by completing daily tasks and activities through its Telegram-based app.
Ling integrates memes, gaming, and blockchain technology to create an accessible and enjoyable way for users to accumulate $LING tokens. The platform’s “Ease 2 Earn” (E2E) model enables users to earn tokens by performing simple actions, making crypto accessible to all. Points earned from these tasks can be converted into $LING tokens, giving users real-world value for their participation.
Built on TRON for Scalability and Efficiency
The decision to build Ling on the TRON blockchain was driven by TRON’s scalability, low transaction fees, and high transaction speeds, making it an ideal choice for the platform’s high-volume, engagement-driven ecosystem. TRON’s infrastructure ensures that users can participate in the Tap2Earn and Task2Earn activities without concerns about network congestion or high transaction costs.
Key Features of the Ling Platform:
- Tap2Earn & Task2Earn: Users earn $LING tokens by engaging with the platform through simple tasks and games.
- Community Rewards: 80% of the total $LING token supply is dedicated to rewarding and incentivizing the most engaged participants.
- Seamless User Experience: The platform operates as a Telegram mini-app, ensuring a barrier-free experience for all users, regardless of their technical expertise.
- TRON-Based: TRON’s high throughput and low fees allow for an optimized user experience focused on earning rewards.
Ling’s Tokenomics: Sustainable and Community-Driven
Ling’s tokenomics, known as “Lingnomics,” is designed to foster long-term sustainability and community engagement. Key components of the token allocation include:
- Total Supply: 10 billion $LING tokens
- Presale Allocation: 4%
- Community & Incentives: 80%
- Team Allocation: 3%
- Liquidity Allocation: 5%
- Key Opinion Leaders (KOLs): 3%
Ling Presale Event: A Chance to Participate Early
Ling’s presale event, consisting of 8 rounds, offers participants an opportunity to acquire $LING tokens at an early stage. The initial seed round will make 400 million tokens available, priced at $0.014 USD per token. With a soft cap of $2.5 million and a hard cap of $15 million, the presale is positioned to provide a strong foundation for the platform’s growth.
No KYC Required for Presale Participation
The presale process is streamlined for user convenience, requiring no Know Your Customer (KYC) procedure. Participants can simply connect their TRON wallets to purchase $LING tokens securely and efficiently.
About Ling
Ling is a next-generation Tap2Earn and Task2Earn platform built on the TRON blockchain. With a focus on community engagement and real-world rewards, Ling offers a seamless, rewarding experience for users worldwide.
For more information and updates on the presale, readers can follow Ling:
Website: lingontron.com
Twitter(X): https://x.com/LingCommunity
Telegram: https://t.me/lingontron
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Cryptocurrency
Michael Saylor Predicts Bitcoin Will Reach $13 Million Per Coin
MicroStrategy Executive Chairman Michael Saylor predicted on Monday that Bitcoin will reach $13 million over the next two decades.
The billionaire explained why the leading digital asset’s recent volatility hasn’t frightened his company, and the advantages for investors to buy into MSTR instead.
Bitcoin To $13 Million, Says Saylor
During an interview with CNBC, Saylor forecasted that Bitcoin will retain its 44% compound annual growth rate in the short term, before that growth steadily declines by roughly 5% per year as the asset matures.
“My long-term forecast is it’s going to go to $13 million over 21 years,” said Saylor. “At some point, it’ll be the S&P return plus 8%, and it’ll be the S&P vol plus 8%.”
To reach that price by 2045, Bitcoin would need to maintain an average CAGR of 29.56%.
Saylor initially put forward a similar price forecast during his speech at Bitcoin 2024 in Nashville. While $13 million was his “base case”, his “bear case” was $3 million (in line with VanEck’s predictions), and his bull case was a whopping $49 million – almost 1000X higher than today.
In the meantime, Saylor expects continued BTC volatility – largely because it is a globally traded, 24/7 asset that is highly liquid.
“If you’re worried about a missile strike, you can’t teleport your ten million dollar apartment to Singapore, lever it up 10 to 1, and short $100 million worth of New York real estate,” he explained. “But you can short $100 million worth of Bitcoin by borrowing $10 million.”
Regarding MicroStrategy (MSTR), Saylor argued that the company has “pioneered” the Bitcoin-backed bond market by issuing billions of dollars in convertible bonds to buy BTC.
As an investment, he says MSTR is like a “tax deferred” BTC yield” instrument, effectively letting users borrow money to buy BTC at rates they could not access as an individual. Since adopting a BTC reserve strategy in 2020
Peter Schiff Disapproves
Bitcoin critic Peter Schiff called out Saylor for boasting about the gains of both BTC and MSTR, calling his ideas “a bunch of nonsense.”
“MSTR is down 40% from its 52-week high and is 6% below its 2021 high. The actually returns are not nearly as rosy as you describe and will soon get worse,” he argued over Twitter on Monday.
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