In the 5th episode of MindChats, streamed on March 7th, the Mind Network delved into the transformative landscape of Fully Homomorphic Encryption (FHE) and the market in general. A stellar lineup of VC specialist speakers, including Kyle Chassé, Mads Pedersen were invited. With 9.1K tuned-in participants, the conversation explored the potential applications of FHE, its challenges, and its strategic placement in the investment theses of venture capitalists.
Time Stamp
Check out the recording of the AMA：https://twitter.com/i/spaces/1ypKdkAyyRdxW?s=20
05:54 Introduction of VCs
11:06 FHE and shared state exploration
22:15 FHE applications in Web3
27:48 ZK and FHE Difference
30:31 DID connection
31:52 Data assets and digital assets
35:10 Talks on Pocket Network (DePIN)
39:08 Steps to make FHE accessible for retail
51:39 Privacy-preserving, privacy infrastructure in investment theses
55:39 Shoutout to the FHE article
58:01 Closer
Key Highlights of the Episode
FHE and Shared State Insights
- Fully Homomorphic Encryption (FHE) removes the decryption requirement across validators, ensuring complete confidentiality in multiplayer scenarios through a shared state.
- Applications range from private lending to secure multiplayer strategy games.
- FHE’s encrypted shared state prevents users from being front-run by others in the game and from having their transaction details seen by unauthorized parties.
- It prevents others from imposing malicious Minimum Viable Validators (MVV) on the user.
Challenges with FHE
- The primary challenge lies in the speed of FHE, with CPUs managing only 2 to 3 transactions per second.
- GPUs offer a modest improvement, reaching around 10 to 15 transactions per second.
Future Applications of FHE
- FHE networks thrive in low-liquidity environments.
- Applications include private voting, secure storage of DIDs, and encrypted credit scores.
- It can be used in gaming, where certain transactional components are encrypted.
- FHE allows for secure computation without prior decryption.
Differentiator between FHE and ZK
- FHE enables computations over encrypted data without prior decryption.
- ZK focuses on proving data validity, but the prover gains access to all user data, which compromises privacy.
- FHE’s confidentiality can be combined with ZK to verify data integrity and with MPC to distribute data across chains.
FHE Accessibility and Appeal
- Ongoing projects like Zama, Elusiv, Fhenix, Inco, and Fair Math aim to make FHE more accessible.
- Tools and frameworks are being developed to integrate FHE into various blockchain layers.
- This enables FHE to become programmatically confidential and adaptable to different use cases.
FHE in Investment Theses
- Programmable confidentiality is acknowledged as a feature, not the entire product.
- Branding solely as a privacy-preserving blockchain can be challenging while penetrating the core user space.
- Privacy features complement the broader product in investment theses.
- Middleware solutions between L1 and L2 can bring better partnership opportunities.
About Mind Network
Mind Network is a Zero Trust (Zero Knowledge Proofs #ZKP + Fully Homomorphic Encryption #FHE) layer aiming to bring the next billion users and trillion dollars to Web3. Mind Network offers a security and data privacy solution that achieves true CrossFi scale, complying with regulatory requirements while staying true to Web3 principles of asset tokenization and individual data ownership.
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The AMA is supported by Moledao, Cointime and MetaEra
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