GM, this is your Daily Bolt briefing.
In this edition, we’ll be giving you a follow-up report, detailing the Ledger leadership team’s response to the backlash they received. Following an update to their hardware wallet that enabled seed phrases to potentially be shared with other people besides a wallet’s owner, Ledger received criticism from people across the crypto ecosystem. Now, they’re trying to rectify their mistake; read below to learn how.
In this edition, we’ve also included Justin Sun’s insights on how CEXs should navigate current market and regulatory conditions, as well as when we can expect a market recovery.
Keep your guard up in the markets⬇️
1/ Arbitrum Twitter Spaces - Arbitrum X dHEDGE
Preview: In this Arbitrum Twitter Spaces, Anna, the Community Manager at the Arbitrum Foundation, hosts Edson Ayllon from dHEDGE Protocol to an AMA, where they talk about dHEDGE and the problem it aims to solve Click here to listen to the full episode (35 mins).
Read our Note (5 mins) and save 16 mins.
Here are some key takeaways:
dHEDGE is an asset management protocol that facilitates a censorship-resistant and non-custodial connection between individuals seeking to allocate funds and asset managers.
Edson explains that dHEDGE offers tokenized vaults that allow people to deposit into the vault. The manager can then manage those assets for those who deposited them. dHEDGE Managers can set certain fees, such as performance fees, minted when the performance is at a new all-time high, and management fees, minted every block.
Edson explains that the primary benefits of the integration with Arbitrum would be lower transaction fees and improved execution speed. He suggests this integration would enable participation with lower capital and quicker investment withdrawals.
He mentions that potential managers were previously hesitant to start on dHEDGE due to Ethereum's unpredictable transaction fees, which could negatively affect time-sensitive trades. He also mentions the benefits of integrating with other platforms such as GMX and Camelot, that exist within the Arbitrum ecosystem, to create compelling strategies for the vaults.
Edson talks about dHEDGE's governance token, $DHT, and its associated governance process. He explains that dHEDGE Feature Proposals (DFP) can be created on the dHEDGE forum and, after discussion, core developers can implement the integration after testing and reviewing the code. These integrations may introduce novel financial tools, act as backups in case an existing dApp isn't working, or create better yields.
Edson explains that an asset must have sufficient liquidity to be listed on dHEDGE. If an asset doesn't have the necessary liquidity, it is usually not listed. He mentions that dHEDGE has even unlisted tokens before due to insufficient liquidity, citing LUNA as an example. For certain tokens, dHEDGE uses Synthetix to solve the liquidity issue if they have deep enough liquidity through their protocol. He also mentions that they use time-weighted average price to handle price volatility.
dHEDGE is in the process of integrating with Balancer and Matcha for trades on Arbitrum. They're also in discussions with GMX and are excited to begin integrating and creating products with them.
Edson shares that dHEDGE is launching products on Arbitrum using dHEDGE contracts. These include a delta-neutral stablecoin that generates yield on $ETH and an $ETH-backed stablecoin, still in the design phase.
Blockcrunch - Use Cases and Intersection of AI and Crypto
In this episode of Blockcrunch Podcast that took place on May 17th, 2023, Jason Choi invites Jake Brukhman, the founder of CoinFund to discuss several topics including the intersection of AI and Crypto, use cases for AI in Crypto, and more.
Background
Jason Choi (Host) - Founder of Blockcrunch Podcast and founding team member at Contrary
Jake Brukhman (Guest) - Founder of CoinFund and Curator at First Edition
Introduction to Crypto and AI Overlap
Jake mentions that new companies in crypto find synergies between Web3 and AI.
Jake states that many investors and founders may pivot away from crypto to work on AI.
Jake Brukhman says that, according to SEC Chairman Gary Gensler, the future of American innovation is rooted in AI rather than crypto.
Interest in AI
Jake says that he studied math and computer science and has always been interested in AI. He states that he has never worked in AI but knows enough math to understand neural networks.
Jake says that he had a startup with a friend using machine learning to understand brain data.
He says that he observes that Web3 and AI are slowly converging over time.
According to Jake, CoinFund made its first investment in Jensen AI, a company that manages lead generation for other companies, and uses a decentralized network for neural network training.
Jake mentions that the launch of ChatGPT was an inflection point for the adoption of AI.
Jake believes that ChatGPT is an incredible demonstration of low-friction application layer technology.
He states that ChatGPT is the fastest-adopted product ever with over 100 million users in 2 months.
Jake says that AI has become mainstream in ways that crypto has not.
According to Jake, Peter Thiel once said that AI is authoritarian while crypto is libertarian.
Jake and Jason diverge from Peter Thiel’s view as they believe in turning AI into an open space like blockchain and decentralization technologies.
Democratizing AI through Web3 Primitives
Jake states that the pipeline for creating AI models is currently owned by a handful of large technology companies. This pipeline consists of four stages: Data Handling, Model Learning, Software Development, and System Operations.
Jake believes that Web3 primitives can democratize this pipeline by making it open and self-sovereign.
He also believes that data should be governed and controlled by people who own the AI models themselves, enabling innovation to be open.
Decentralized Networks for AI and Challenges
Jake believes that computing for AI should be run on decentralized networks because of the value of openness.
Jake thinks that replacing data centers with decentralized networks would result in slower computation and loss of hardware optimizations.
However, he says that if one prioritizes openness over-optimization, decentralization makes sense as the most proper way forward to work with this technology as humanity.
He states that solving technical problems involving zero-knowledge-proof systems will enable the safe training of models on decentralized networks.
AI and Crypto Future
Jake believes that all datasets should be publicly sourced, trained for, and governed by the public in a crypto future.
According to Jake, open-source models are essential because they allow for greater transparency and accountability. He believes that proprietary models will not dominate in the medium to long term.
Use Cases of AI in Crypto
Jake highlights the use of AI models like ChatGPT for transforming human language prompts into SQL queries or Solidity code for querying on-chain data. This use case aims to simplify interactions with blockchain and make it more user-friendly.
He mentions that one could use AI AI to screen stocks or cryptocurrencies based on certain criteria or to identify investment trends and opportunities.
Jake touches on the potential of incorporating AI into smart contracts, enabling them to perform more sophisticated functions and interact with external data sources. This could open up new possibilities for AI-driven decentralized applications and services on the blockchain.
Jake mentions that AI could be used as a tool for analyzing and recommending investment opportunities in both traditional markets and the crypto space.
According to Jake, AI algorithms can be utilized in cryptocurrency trading to analyze market data, identify patterns, and make informed trading decisions. He believes that machine learning and deep learning techniques can be applied to predict market movements and optimize trading strategies.
He mentions that blockchain technology provides a decentralized and secure framework for managing AI-related data. It enables transparent and immutable recording of data transactions, which can be beneficial for data integrity, privacy, and accountability in AI applications.
He states that AI algorithms can play a role in decentralized governance mechanisms within blockchain networks. They can be used for consensus protocols, voting systems, and decision-making processes to enhance efficiency and fairness.
Jake also believes that AI can be employed to enhance security measures in the crypto space. It can help detect and prevent fraud, identify malicious activities, and strengthen cybersecurity protocols within blockchain networks.
Embracing Openness and Working on Alignment Problems
Jake believes that the crypto market embraces openness, and everyone in the crypto space should embrace it.
According to him, there are risks associated with connecting AI models to real-world systems, such as trading. To mitigate these risks, everyone in the field needs to work on alignment problems.
According to Jake, educating people and getting models to do what we want them to do is crucial.
Opportunities for Crypto Founders
According to Jake, there is a lack of sophistication in training AI models, presenting a wealth of potential opportunities.
Jake says that the commercialization of smart contracts that use AI for applications is an open field.
He says that there is a lack of products that use generative AI outputs or facial recognition on-chain.
He believes that autonomous OCR and other applications are possibilities that people could be working on.