Redbrick aims to bring together both Web2 and Web3 worlds, enabling anyone to easily create, publish, and monetize games. Catering to a broad audience—from individual content creators to professional studios, regardless of technical expertise—the platform is built on the vision of “democratizing game production.”

Why is the Web3 Gaming World Problematic?

Redbrick’s starting point lies in the structural problems of the current Web3 gaming ecosystem. Most Web3 games today prioritize token economics over entertainment, turning games into “profit-focused tasks” rather than enjoyable experiences for players.

Key Problems

• Game development is too slow: Even producing a simple prototype can take weeks or months. Developers must deal with complex tools, thousands of lines of code, and continuous testing processes.
• Proliferation of blockchains: Choosing which chain to develop on creates significant uncertainty for developers. Each network has different tools, user bases, and standards.
• Fragmented communities: Web3 gaming communities are divided across different chains and platforms, making it difficult to build a sustainable user base.
• Poor gameplay quality: Many Web3 games prioritize financial incentives over entertainment, causing mainstream gamers to shy away from Web3 gaming.

How Does Redbrick Engine Solve These Problems?

Redbrick adopts an AI-centric approach to accelerate and make game production accessible. The platform’s AI-powered game engine allows users, even those without coding knowledge, to create games.

The Redbrick Engine offers a structure that generates a game’s logic, assets, and core mechanics from text inputs, reducing content creation time from weeks to hours.

Redbrick (BRIC) Platform and Ecosystem Data

Redbrick already boasts a strong user and content creator community:

• Over 7.6 million registered users
• 5.9 million active wallets
• More than 53 million games played
• Over 78 million on-chain transactions
• Daily average of over 60,000 active users
• Monthly over 170,000 active users
• Over 51,000 unique active wallets

On the community side:

• Over 368,000 Discord members
• More than 500,000 X (Twitter) followers
• Over 200,000 content creators
• More than 600,000 created content pieces

Why is Redbrick (BRIC) Different?

Redbrick enables the production of both Web2 and Web3 games on the same infrastructure through its cloud-based AI game engine and advanced content service layer. This structure makes the platform not just a game engine but also a comprehensive content and economy platform.

Redbrick for Content Creators

Redbrick enables everyone, developer or not, to create games.

Offered Tools

• Text-to-game production
• Visual block coding system
• Unity integration
• NFT and token integration
• Telegram and Discord integrations

Content creators can build games, educational modules, branded worlds, or IP-based experiences. In-game assets can be produced, sold, and monetized.

Redbrick for Players

Players can play both Redbrick Originals and community-created games on the Redbrick platform. They can participate in tournaments, win rewards, and support content creators.

BRC:ID Standard

With Redbrick’s BRC:ID standard, players can:

• Package their in-game progress
• Achievements
• Assets

into a single on-chain asset. This package can be minted as an NFT and bought or sold on marketplaces.

Redbrick for Partners

Redbrick’s chain-agnostic structure enables game production on various blockchains. Partners can:

• Directly use the AI game engine
• Collaborate with the content creator network
• Develop custom games for NFT collections and Web3 projects

Technology Infrastructure

AI Engine

At the heart of Redbrick lies the AI Engine, consisting of three main components:

• AI Game Engine: Game and asset production from text inputs
• 2D / 3D Engine: 2D, 3D, VR, and AR experiences
• Visual Coding Engine: App development without writing code

This structure caters to both professional developers and beginners.

Multi-Chain and Account Abstraction

The Redbrick Engine works compatibly with Ethereum, BNB Chain, Polygon, Monad, and various L2 solutions. Thanks to account abstraction, users can:

• Create wallets more easily
• Interact without feeling the complexity of gas and transactions

This approach brings the Web3 gaming experience closer to Web2.

Redbrick (BRIC) Tokenomics

The BRIC tokenomics structure is designed to ensure long-term sustainability and balanced growth in the Redbrick ecosystem.

Token distribution offers a balanced structure between reward mechanisms incentivizing content creators, ecosystem development, and operational continuity. This approach aims to create a robust economic model for both users and developers.

Total Supply: 1,000,000,000 BRIC

• Reward Pool: 27%
• Treasury: 15.74%
• Marketing: 12%
• Team and Advisors: 15%
• Binance Alpha: 6%
• Investors: 6.26%
• Airdrop Participation: 3%
• Liquidity: 5%
• Ecosystem Incentives: 10%

Redbrick (BRIC) Token and Use Cases

$BRIC is the utility token at the center of the Redbrick ecosystem.

For Content Creators

• Earning BRIC as games are played
• Share of advertising revenue
• In-game asset sales
• Bonus rewards tied to growth targets
• Paying platform fees with BRIC

For Players

• Earning points by playing
• Converting points to BRIC
• Earning tokens from tasks and events
• In-platform payments

Staking

• Earning rewards by staking BRIC
• Access to exclusive tournaments
• Early access to new games
• Increased visibility for content creators

Protocol Revenue Model

Redbrick’s revenue sources include:

• AI Engine premium plans
• Advertising revenue
• In-game transactions
• Marketplace commissions
• Platform service fees

A portion of these revenues is used for token buybacks and burns.

Creator Economy

Redbrick uses a dual-currency system:

• Off-chain points: Used for engagement, tasks, and donations
• On-chain BRIC: Used for real economic value, asset trading, and monetization

Vision and Roadmap

Redbrick’s vision is to create an inclusive ecosystem where content creators and players can directly convert their skills into economic value.

Roadmap Summary

• Phase 1: Onboarding and gaming infrastructure
• Phase 2: BRIC token economy and staking
• Phase 3: Marketplace, automation, wallet, and asset interoperability

Redbrick (BRIC) Partners

Redbrick continues its efforts with a broad network of partners to strengthen its multi-chain and scalable gaming infrastructure. Strategic partnerships with various blockchain networks, infrastructure providers, and Web3 projects significantly enhance the platform’s technical capacity and ecosystem reach.

The partner network includes Layer, Fusionist, Bitlayer, MODE, Token Pocket, Smart Layer, Berachain, BNB Chain, Monad, ZetaChain, Kaia, Kroma, and Hub71, among others.

Official Links

• Website
• X (Twitter)
• Whitepaper

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Binance Alpha Listing – What is PROMPTALE AI (TALE)?

PrompTale AI (TALE) is an AI-powered content platform that evolves continuously through community input. Its powerful AI engine learns and improves with the help of users, enhancing both the quality and diversity of the generated content.

The project’s core vision is to produce high-quality and relevant content by allowing users to directly contribute to the system’s development. Users are not only consumers of content but also active participants in shaping how the AI evolves.

Click to Register on Binance Exchange with a 20% Commission Discount!

Why Is It Gaining Attention?

• It’s a project focused on current AI trends

• Offers a constantly evolving AI engine powered by user feedback

• Aims to build a community-driven ecosystem

• Listed on a prestigious platform like Binance Alpha

What Is the Use Case for TALE Token?

TALE plays multiple roles within the platform, including reward distribution, contribution incentives, and ecosystem utility. Users can earn TALE by contributing to content generation or use the token to access specific content within the platform.

You can freely share your thoughts and comments about the topic in the comment section. Additionally, don’t forget to follow us on our Telegram  ,YouTube and Twitter channels for the latest news and updates.

The post Binance Alpha Lists an AI-Focused Altcoin! appeared first on Coin Engineer.

These intelligent systems instantly assess market movements, perform sentiment analysis and identify the best trading opportunities with self-optimizing algorithms. However, developing a successful AI agent requires the right data, a powerful algorithm and a comprehensive risk management system.

What is an AI-Powered Crypto Trading Agent and Why is it Important?

Unlike traditional bots, AI-powered trading systems are data-driven, dynamically adaptive and continuously improve their decisions.

• Machine Learning (ML): Predicts possible future price changes by analyzing past market movements.
• Deep Learning (DL): Identifies trading opportunities by learning more complex patterns.
• Natural Language Processing (NLP): Evaluates market expectations by analyzing sentiment on social media, news and forums.

For example, large language models like ChatGPT can make predictions about the market by analyzing news headlines and social media sentiment.

Skills Required to Develop an AI-Powered Trading Agent

To develop a successful AI-powered trading bot, it is necessary to have both technical and financial knowledge. Here are the most critical skills:

• Machine Learning and Artificial Intelligence: Developing algorithms that can predict markets and optimize strategies.
• Programming and Data Analytics: Model building and data processing with tools such as Python, TensorFlow, Pandas.
• Finance and Trading Mechanisms: Knowledge of technical analysis, risk management and trading strategies.
• API Integration: Feeding AI models with live data from crypto exchanges.
• Blockchain and Onchain Analysis: Analyzing whale movements, smart contract activity and market liquidity.

Developing a powerful AI agent requires an interdisciplinary approach. By bringing together data engineers, financial experts and AI researchers, an optimally performing trading bot can be created.

Steps to Develop an AI-Powered Crypto Trading Agent

1. Strategy Identification

Every AI-powered trading agent should work within the framework of a specific strategy:

• Trend Following: Tracks bullish or bearish trends by analyzing price movements.
• Arbitrage Trading: Seeks to profit by exploiting price differences between exchanges.
• Market Making: Provides liquidity by using small spreads between buy and sell orders.
• News and Sentiment Analysis: Attempts to predict price movements by analyzing news feeds and social media interactions.

The chosen strategy determines how the AI model will work and what data it will process.

2. Data Collection and Preprocessing

The success of an AI trading agent depends on the accuracy and scope of the data it analyzes.

• Exchange Data: Price history, order book depth, trading volume and market liquidity.
• Onchain Data: Transaction activity on major blockchains such as Bitcoin and Ethereum, activities of large investors (whales).
• Market Sentiment Data: Data collected from social media, news sites and forums.

The collected data is enriched with technical indicators such as RSI, MACD, Bollinger Bands to enable the model to perform better analysis.

3. Training and Optimization of the AI Model

For the AI model to be efficient and successful, it needs to be trained correctly.

• Supervised Learning: Optimizes price predictions by training with historical market data.
• Reinforcement Learning (RL): Improves performance by learning to make decisions in simulated trading environments.
• Hyperparameter Tuning: Optimize the model’s learning speed, data processing capacity and accuracy.

A successful model should be able to make correct decisions by eliminating false signals.

4. Backtesting and Simulation

To test the success of the model, simulation should be done in past market conditions.

• Backtesting: Test the model’s decisions with historical market data.
• Performance Measures: Sharpe ratio (risk-adjusted return), maximum drawdown (worst loss scenario) are analyzed.

If a model only works well in bull markets, it should be retrained with a more balanced data set.

5. Live Market Deployment and Risk Management

Once the AI model is validated, it must be integrated into the real-time trading environment.

• Smart Order Routing (SOR): Determines the best price and liquidity between different exchanges.
• Low Latency Trading Engines: Executes orders in milliseconds, minimizing the risk of slippage.
• Dynamic Risk Management: Stop-loss orders, position size adjustments and filters analyzing market manipulations are applied.

AI agent can analyze flash crashes and fake orders to prevent market manipulations.

The Future of AI-Powered Crypto Trading

AI-powered trading systems offer great advantages to traders by providing speed, accuracy and adaptability in crypto markets.

However, data quality, algorithmic accuracy and continuous improvement are critical to the success of AI-based trading.

Major developments are expected in this area with blockchain technology, quantum computing and decentralized AI solutions. The future of AI in crypto trading will be shaped by regulations and technical innovations.

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Interest Rate Intervention Request

Trump’s statement comes just a week before the Fed meeting in Washington on January 29. However, borrowing costs are often determined by various economic factors, such as market dynamics and US Treasury yields. The Federal Reserve (Fed), as an independent institution, makes decisions aimed at price stability and maximum employment. Trump’s criticism of Fed Chairman Jerome Powell came up frequently during his presidency.

Powell had previously given a clear “No” when asked at a press conference whether he would resign if Trump ordered him to do so. The Fed’s independence and the principle of making decisions based on economic data call into question the feasibility of such demands.

Biden and Inflation Criticism

Trump harshly criticized the Biden administration, claiming that high inflation in the US has reached “the worst level in history”. However, it was stated that some of Trump’s data on inflation were not accurate. Although Trump claimed that inflation reached record levels under the Biden administration, it was noted that these claims were not true, and that the highest inflation rate in US history was 23.7% in 1920.

Trump also claimed that the US is “50% higher than the historical inflation target”. However, the Personal Consumption Expenditures (PCE) price index, which the Fed considers as its benchmark, has increased by 2.4% as of November 2024, quite close to the Fed’s 2% target.

USA: Artificial Intelligence and Cryptocurrency Capital

In his speech, Trump not only touched on interest rate policies, but also emphasized the US’s claim to leadership in the field of technology. “America will be the capital of artificial intelligence and cryptocurrency,” Trump said, signaling that stronger policies will be pursued in these areas.

The US President’s statements reopened the debate on the impact of cryptocurrency and blockchain technologies on economic growth and innovation. In addition, markets have wondered whether such promises would be backed by concrete policy steps.

“Common Sense Revolution” on the Economic Agenda

Describing his presidency as a “common sense revolution”, Trump stated that the US would become a “stronger, richer and more united” country. He also described the economic policies of the Biden administration as a “failure” and claimed that these policies led to chaos in the economy.

These statements are considered as part of the debate on economic policies as well as efforts to redefine the US’s global economic role. However, some of Trump’s claims are disputed by experts in terms of accuracy.

Also, you can freely share your thoughts and comments about the topic in the comment section. Additionally, please follow us on our Telegram, YouTube and Twitter channels for the latest news and updates.

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