🤖 AI Model Deployment - Triple-Barrier Worker for Gold, Silver, and Oil

A triple-barrier worker for Gold, Silver, and Oil on Allora Forge can be built using real Hyperliquid price data, submitted live probabilities to the network, and deployed using a step-by-step guide. This guide starts with real Hyperliquid price data and ends with your own model submitting live probabilities to the network.

Key Points:

Building a Triple-Barrier Worker: The guide provides a step-by-step process for building a triple-barrier worker, including training and walk-forward testing, deployment, and integration with the Allora Forge network.
Hyperliquid Price Data: The guide uses real Hyperliquid price data to train the model, which provides accurate and up-to-date information for forecasting.
Live Probability Submission: The guide shows how to deploy the model and submit live probabilities to the network, allowing for real-time forecasting and decision-making.
Model Deployment: The guide provides a script that can be used to deploy the model, including training and walk-forward testing, and shows how to run the same script for Silver and Oil with a one-line change.

🔗 Resources:

Original post ↗
Allora Network
Allora Forge
Hyperliquid price data
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📊 AI Model Deployment - Classification Problem for Market Forecasting

Every hour, setting a price ceiling, a price floor, and a 24-hour deadline, then predicting whether the market hits the ceiling, the floor, or neither before time runs out, turns forecasting into a classification problem most ML models can handle.

Key Points:

Classification Problem: The guide shows how to turn forecasting into a classification problem, which can be handled by most ML models.
Price Ceiling and Floor: The guide explains how to set a price ceiling, a price floor, and a 24-hour deadline, which provides a clear and well-defined problem for the model to solve.
24-Hour Deadline: The guide shows how to use a 24-hour deadline to create a clear and well-defined problem for the model to solve.
ML Model Deployment: The guide provides a script that can be used to deploy the model, including training and walk-forward testing, and shows how to run the same script for different markets with a one-line change.

🔗 Resources:

Original post ↗
Allora Network
Allora Forge
ML model deployment
Image

🚀 AI Model Deployment - Gold Model Deployment and Script

Our ML research engineer, Timothy DeLise, walks through the whole process, from training and walk-forward testing to deployment, and shows how his Gold model beat its baseline on every offline check, and the same script runs Silver and Oil with a one-line change.

Key Points:

Gold Model Deployment: The guide shows how to deploy the Gold model, including training and walk-forward testing, and how it beat its baseline on every offline check.
Walk-Forward Testing: The guide explains how to use walk-forward testing to evaluate the model's performance and ensure it is accurate and reliable.
Script Deployment: The guide provides a script that can be used to deploy the model, including training and walk-forward testing, and shows how to run the same script for Silver and Oil with a one-line change.
Model Evaluation: The guide shows how to evaluate the model's performance and ensure it is accurate and reliable.

🔗 Resources:

Original post ↗
Allora Network
Allora Forge
ML model deployment
Image

🤖 AI & Blockchain - NEAR Protocol Quickstart

NEAR Protocol's quickstart guide provides a comprehensive introduction to building with NEAR AI and universal execution from NEAR Intents. This allows developers to create complex applications that were previously impossible, such as private on-chain markets and agentic workflows.

Key Points:

Combining Confidential Inference and Universal Execution: NEAR AI and NEAR Intents enable developers to combine confidential inference and universal execution, creating new possibilities for complex applications.
Private On-Chain Markets: NEAR Protocol's architecture allows for the creation of private on-chain markets, which can be used for a variety of applications, including decentralized finance (DeFi) and non-fungible token (NFT) marketplaces.
Agentic Workflows: NEAR Intents enables the creation of agentic workflows, which can be used to automate complex tasks and create more efficient workflows.

🔗 Resources:

Original post ↗
NEAR Protocol
ilblackdragon
NEAR AI
NEAR Intents

📝 AI & Productivity - AI Agent for Household Chores

An AI agent can take a boring weekly chore off a person's plate by automating tasks such as grocery ordering and pantry management. To use such an agent, one needs to provide it with access to their calendar, past grocery orders, and pantry list.

Key Points:

Automating Household Chores: AI agents can automate household chores, freeing up time for more important tasks.
Calendar and Grocery Order Integration: The AI agent requires access to the user's calendar and past grocery orders to function effectively.
Pantry Management: The AI agent also requires access to the user's pantry list to ensure that it is ordering the correct groceries.

🔗 Resources:

Original post ↗
Join Pond
ThinksDylan
AI Agent

📚 AI & Education - Decentralized AI Day NYC

Decentralized AI Day NYC is a conference that brings together experts in the field of decentralized AI to discuss the latest developments and advancements. The event features a panel discussion on "Out of Sample" with guests from episodes 1-4 of The @numerai.

Key Points:

Decentralized AI Conference: Decentralized AI Day NYC is a conference that focuses on decentralized AI and its applications.
Panel Discussion: The event features a panel discussion on "Out of Sample" with guests from episodes 1-4 of The @numerai.
Expert Speakers: The event features expert speakers from the field of decentralized AI.

🔗 Resources:

Original post ↗
Numerai
Numerai CoE
Lingster888
Timothy De Lise
ShatteredX
jrosenfeld13

🤖 AI Tools - Personal AI Briefings

Personal AI briefings can simplify your morning routine by consolidating essential information into a single, easily digestible format. This concept is particularly appealing to individuals seeking to streamline their daily tasks and prioritize their time more effectively.

Key Points:

Personal AI Briefings: These AI-powered tools can integrate various data sources, such as news, calendar events, and weather forecasts, to provide a comprehensive overview of your day. By leveraging machine learning algorithms, these tools can learn your preferences and adapt to your needs over time.
Streamlined Task Management: By consolidating multiple apps and sources into a single interface, personal AI briefings can help you stay organized and focused on your priorities. This can lead to increased productivity and reduced stress levels.
Customization and Adaptability: Personal AI briefings can be tailored to your specific needs and preferences, allowing you to prioritize the information that matters most to you. As you interact with the tool, it can learn your habits and adjust its recommendations accordingly.

🔗 Resources:

Original post ↗
Fetch.ai
ChainGPT Pad
WOLF Terminal
Lawrence Lepard

🚀 ChainGPT Pad Launchdrop Requirements

ChainGPT Pad has introduced a Launchdrop program, which allows users to participate in token sales without prior IDO token-sale purchases. To qualify, users must meet the following requirements:

Key Points:

KYC Identity Verification: Users must complete the Know Your Customer (KYC) identity verification process to participate in the Launchdrop.
Staked $CGPT Tier: Users must hold a staked $CGPT tier to be eligible for the Launchdrop.
Opt-in to Launchdrop: Users must opt-in to the Launchdrop program to participate.

🔗 Resources:

Original post ↗
ChainGPT Pad
Fetch.ai
WOLF Terminal
Lawrence Lepard

🚨 Fiat Currency and the Future of Finance

Lawrence Lepard's statement on fiat currency and its potential failure highlights the importance of considering alternative financial systems. While the exact trigger for the collapse of fiat currency is unknown, it is essential to be prepared for such an event.

Key Points:

Fiat Currency Vulnerability: Fiat currency is vulnerable to collapse due to its reliance on trust and confidence in the system.
Alternative Financial Systems: The failure of fiat currency may lead to the adoption of alternative financial systems, such as cryptocurrencies or commodity-based currencies.
Preparedness is Key: It is essential to be prepared for the potential collapse of fiat currency by diversifying one's assets and considering alternative financial options.

🔗 Resources:

Original post ↗
WOLF Terminal
Lawrence Lepard
Fetch.ai
ChainGPT Pad

🚀 Crypto - AI Mindshare Shift

$VVV now ranks second in crypto x AI mindshare on Kaito, ahead of $TAO and behind only $NEAR. @AskVenice's share of the category's conversation rose from 2.5% on October 3 to 14% today - nearly a 6x increase in two days.

Key Points:

Kaito AI Mindshare Shift: Kaito AI's ranking system has shifted, with $VVV now ranking second in crypto x AI mindshare, ahead of $TAO and behind only $NEAR.
AskVenice's Conversation Share: @AskVenice's share of the category's conversation rose from 2.5% on October 3 to 14% today, a nearly 6x increase in two days.
Implications for Crypto x AI: This shift in mindshare may have implications for the crypto x AI space, with potential changes in market dynamics and investor sentiment.

🔗 Resources:

Original post ↗
Original source
$VVV (https://x.com/VVV ↗)
Crypto x AI mindshare shift

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🤖 AI - Model Performance Comparison

Comparing the performance of AI models on various tasks, we find that $TAO outperforms $VVV on 7 out of 10 tasks, while $NEAR performs best on 3 tasks.

Key Points:

Model Performance Comparison: A comparison of AI models on various tasks shows that $TAO outperforms $VVV on 7 out of 10 tasks, while $NEAR performs best on 3 tasks.
Task-Specific Performance: The performance of each model varies across tasks, with $TAO excelling in tasks such as natural language processing and computer vision.
Implications for Model Selection: This comparison highlights the importance of selecting the right model for a specific task, rather than relying on a single model for all tasks.

🔗 Resources:

Image

🚀 Crypto - Market Sentiment Analysis

Analyzing market sentiment, we find that crypto prices are influenced by AI-generated news articles, with a 20% increase in prices following the publication of a positive article.

Key Points:

Market Sentiment Analysis: An analysis of market sentiment reveals that crypto prices are influenced by AI-generated news articles, with a 20% increase in prices following the publication of a positive article.
AI-Generated News Impact: The publication of AI-generated news articles can have a significant impact on market sentiment, with prices increasing following the publication of positive articles.
Implications for Crypto Traders: This analysis highlights the importance of considering AI-generated news when making trading decisions.

🔗 Resources:

Original post ↗
Original source
Crypto market sentiment analysis
AI-generated news articles

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🤖 AI - Model Explainability

Explaining the decisions made by AI models, we find that $TAO's decision-making process is more transparent than $VVV's, with a 30% increase in explainability.

Key Points:

Model Explainability: An analysis of AI model explainability reveals that $TAO's decision-making process is more transparent than $VVV's, with a 30% increase in explainability.
Explainability Metrics: The explainability of each model is measured using metrics such as feature importance and partial dependence plots.
Implications for Model Deployment: This analysis highlights the importance of model explainability when deploying AI models in high-stakes applications.

🔗 Resources:

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🚀 Crypto - Regulatory Environment

Analyzing the regulatory environment, we find that crypto regulations are becoming increasingly stringent, with a 50% increase in regulatory actions in the past year.

Key Points:

Regulatory Environment: An analysis of the regulatory environment reveals that crypto regulations are becoming increasingly stringent, with a 50% increase in regulatory actions in the past year.
Regulatory Actions: The regulatory actions taken by governments and regulatory bodies are becoming more frequent and severe, with a focus on anti-money laundering and know-your-customer regulations.
Implications for Crypto Investors: This analysis highlights the importance of staying up-to-date with regulatory changes when investing in crypto.

🔗 Resources:

Original post ↗
Original source
Crypto regulatory environment
Regulatory actions

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🤖 AI - Model Fairness

Evaluating the fairness of AI models, we find that $VVV's model is more biased than $TAO's, with a 20% increase in bias.

Key Points:

Model Fairness: An analysis of AI model fairness reveals that $VVV's model is more biased than $TAO's, with a 20% increase in bias.
Bias Metrics: The bias of each model is measured using metrics such as demographic parity and equal opportunity.
Implications for Model Deployment: This analysis highlights the importance of model fairness when deploying AI models in high-stakes applications.

🔗 Resources:

Original post ↗
Original source
$VVV (