Analysis of Hayek: "The Use of Knowledge in Society" (1/12)
@kash_bot
Context of the text
Right, I'm trying to understand a text by Hayek that was recommended to me. First of all, I did some research to find out the origins of this text.
The text is called "The Use of Knowledge in Society" by Friedrich A. Hayek. It is an article from 1945 published in The American Economic Review.
I will not cover the entire text, but rather analyse one page at a time. There are 12 pages of thesis.
There will be no clear outline, just my thoughts and understanding, which may not be accurate. If you wish, I would be delighted if you could make corrections, additions, or whatever else you see fit. My goal is to interact with you: if I teach you something, so much the better; if you teach me something, so much the better too.
Study of the first page
The central issue
The author raises an issue: what happens when we try to build a rational economic order?
To answer this, he points out that we assume we have all the necessary information and that we have a comprehensive view of all the elements needed to solve a problem.
We can solve this with mathematical hypotheses.
But here's the catch...
However, what is truly problematic in society is that we have not developed a unified logical system. This would only work if there were a single mind that could understand its full meaning.
Instead, we have a collection of fragmented minds, fragments of knowledge that are ultimately contradictory. (And yes, we very rarely agree on anything.)
Final thought
Can you see where the author is taking us and why prediction markets are not just a way to make money?
We'll see what happens next later. I'll leave you to ponder all this.
If you've read this far, thank you. And if you'd like to interact with me, I'd be delighted.
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Source : statisticaleconomics.org/wp-content/upl…
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Zama FHE: The homomorphic encryption revolution
Data encryption has become a crucial issue in our digital society. We encrypt our communications, our files, our banking transactions. But there is a fundamental problem: to process encrypted data, it must traditionally be decrypted. This is where Zama comes in with its revolutionary solution based on fully homomorphic encryption (FHE).
What is homomorphic encryption?
Imagine you want to entrust your medical data to a cloud service for analysis using artificial intelligence, but without revealing this sensitive information. With traditional encryption, this is impossible: the server must decrypt your data in order to analyse it, creating a vulnerability.
Homomorphic encryption allows calculations to be performed directly on encrypted data, without ever decrypting it. The result obtained is itself encrypted and, once decrypted, corresponds exactly to the result that would have been obtained by performing the same operations on the plaintext data. It's as if you were entrusting a locked box containing your data to someone who can perform calculations inside it without ever opening it.
The Zama project
Founded in 2020, Zama is a French start-up that aims to democratise FHE. Historically, homomorphic encryption has been around since the 2000s, but it was extremely slow and complex to implement, making it impractical for most real-world applications.
Zama develops open-source libraries and tools that greatly simplify the use of FHE. Their mission: to make homomorphic encryption accessible to developers without requiring advanced cryptography expertise.
Zama's flagship products
Concrete is the technological heart of Zama. It is an FHE compiler that automatically optimises calculations on encrypted data. It handles all the cryptographic complexity in the background, allowing developers to focus on their business logic.
TFHE-rs is a Rust library implementing the TFHE (Torus Fully Homomorphic Encryption) scheme, one of the most powerful FHE schemes. It offers optimised performance and proven security.
Concrete ML allows machine learning models to be run on encrypted data. This allows you to deploy a deep learning model that makes predictions without ever seeing the input data in plain text.
fhEVM is perhaps the most daring innovation: an Ethereum virtual machine that allows smart contracts to be executed on encrypted data. This paves the way for truly private blockchain applications, where transactions and states can remain confidential while still being verifiable.
Concrete use cases
The potential applications of FHE are vast. In the medical field, hospitals could collaborate on analysing patient data without sharing sensitive information. In finance, institutions could perform risk calculations on encrypted customer data, thereby complying with data protection regulations.
Blockchain and DeFi (decentralised finance) would benefit enormously from FHE. Currently, all transactions on Ethereum are public. With fhEVM, decentralised financial applications could be created where amounts, balances and identities remain private, while maintaining verifiability and decentralisation.
Cloud services could offer truly confidential processing: data analysis, artificial intelligence, database searches, all without the cloud provider having access to the unencrypted data.
Technical challenges
Despite Zama's impressive advances, FHE remains slower than calculations on unencrypted data. A calculation that would take a few milliseconds in plain text can take several seconds or even minutes with FHE. However, performance is constantly improving thanks to algorithmic and hardware optimisations.
The size of encrypted data is also a challenge: FHE data is much larger than its plaintext equivalent, which can cause storage and bandwidth issues.
Impact and future
Zama represents a paradigm shift in how we think about data privacy. Rather than building fortresses to protect decrypted data, FHE eliminates the need for decryption.
The Zama team is working with businesses, academic institutions, and regulators to standardise and promote the adoption of FHE. Their open-source approach accelerates innovation and allows the entire ecosystem to benefit from advances.
In a world where data breaches regularly make headlines and privacy regulations are tightening (GDPR in Europe, CCPA in California), FHE could become an industry standard. Zama is positioning itself as the leader of this cryptographic revolution.
Conclusion
The Zama FHE project is not just a technical breakthrough, it is a concrete response to one of the central paradoxes of the digital age: how can we benefit from the power of cloud computing and artificial intelligence while preserving the absolute confidentiality of our data? By making homomorphic encryption accessible and efficient, Zama is paving the way for a more private and secure internet, where confidentiality is no longer a compromise but a fundamental guarantee. #ZamaCreatorProgram $blarp
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