A comprehensive guide to understanding blockchain bridges, their types, and how they facilitate communication and asset transfers between different blockchain networks.

Blockchain Bridge

A multisign wallet is a type of digital wallet that requires multiple signatures to authorize transactions. This article provides an overview of multisign wallets, how they work, and their benefits.

Multisign wallet

Plonky2 is a non-Interactive Proof of Proof of Knowledge (NIPoPoK) chain that reduces blockchain size and speeds up transaction confirmations. This article explores Plonky2's technology, its applications in various blockchain projects, and compares it with other scaling solutions.

Plonky2

This article provides an overview of the Polygon zkEVM architecture, including its main components, how it works, and its benefits.

Polygon zkEVM architecture

This article provides an overview of StarkNet's architecture, including its main components, how it works, and its transaction lifecycle. It also covers the messaging mechanism between Layer 1 and Layer 2, as well as the node clients used in the StarkNet network.

StarkNet architecture

A guide on how to build a personal AI chatbot using open-source Large Language Models (LLMs) like Alpaca and GPT4All on your personal computer.

Build your chatbot with open source Large Language Models

Proximal Policy Optimization (PPO) is an algorithm that aims to improve the stability of training by avoiding overly large policy updates. It is a popular and effective method used for training [ reinforcement learning]() models in complex environments. To achieve this, PPO uses a ratio that indicates the difference between the current policy and the old policy and clips this ratio within a specific range, ensuring that the policy updates are not too large and the training process is more stable...

Proximal Policy Optimization

An introduction to Q-learning, a model-free reinforcement learning algorithm used to learn optimal policies in Markov Decision Processes.

Q Learning

An introduction to Reinforcement Learning (RL), a machine learning method where an agent learns to make decisions by interacting with an environment. This article covers the basics of RL, including how it works, common algorithms, and its application in training models with Large Language Models (LLMs).

Introduction to Reinforcement Learning and Its Application with LLMs

An overview of vector databases and their application in LLM systems. This article covers the history and core concepts of vector databases, their use cases, implementation considerations with LLMs, and a comparison of popular vector database options.

Select Vector Database for LLM

A comprehensive guide to getting started with smart contract development on Solana using the Anchor framework. This tutorial covers the basics of Anchor, its components, installation process, and provides step-by-step instructions for creating and deploying a simple program.

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