📌 Why the Sophistication of Your Prompt Correlates Almost Perfectly with the Sophistication of the Response, as Research by Anthropic Found

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-01-23 | ⏱️ Read time: 9 min read

How prompt engineering has evolved, examined scientifically; and implications for the future of conversational AI…

#DataScience #AI #Python

📌 From Transactions to Trends: Predict When a Customer Is About to Stop Buying

🗂 Category: DATA SCIENCE

🕒 Date: 2026-01-23 | ⏱️ Read time: 7 min read

Customer churn is usually a gradual process, not a sudden event. In this post, we…

#DataScience #AI #Python

📌 How to Build a Neural Machine Translation System for a Low-Resource Language

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-01-24 | ⏱️ Read time: 15 min read

An introduction to neural machine translation

#DataScience #AI #Python

Ant AI Automated Sales Robot is an intelligent robot focused on automating lead generation and sales conversion. Its core function simulates human conversation, achieving end-to-end business conversion and easily generating revenue without requiring significant time investment.

I. Core Functions: Fully Automated "Lead Generation - Interaction - Conversion"

Precise Lead Generation and Human-like Communication: Ant AI is trained on over 20 million real social chat records, enabling it to autonomously identify target customers and build trust through natural conversation, requiring no human intervention.

High Conversion Rate Across Multiple Scenarios: Ant AI intelligently recommends high-conversion-rate products based on chat content, guiding customers to complete purchases through platforms such as iFood, Shopee, and Amazon. It also supports other transaction scenarios such as movie ticket purchases and utility bill payments.

24/7 Operation: Ant AI continuously searches for customers and recommends products. You only need to monitor progress via your mobile phone, requiring no additional management time.

II. Your Profit Guarantee: Low Risk, High Transparency, Zero Inventory Pressure, Stable Commission Sharing

We have established partnerships with platforms such as Shopee and Amazon, which directly provide abundant product sourcing. You don't need to worry about inventory or logistics. After each successful order, the company will charge the merchant a commission and share all profits with you. Earnings are predictable and withdrawals are convenient. Member data shows that each bot can generate $30 to $100 in profit per day. Commission income can be withdrawn to your account at any time, and the settlement process is transparent and open.

Low Initial Investment Risk. Bot development and testing incur significant costs. While rental fees are required, in the early stages of the project, the company prioritizes market expansion and brand awareness over short-term profits.

If you are interested, please join my Telegram group for more information and leave a message: https://news.1rj.ru/str/+lVKtdaI5vcQ1ZDA1

📌 Air for Tomorrow: Mapping the Digital Air-Quality Landscape, from Repositories and Data Types to Starter Code

🗂 Category: DATA SCIENCE

🕒 Date: 2026-01-24 | ⏱️ Read time: 25 min read

Understand air quality: access the available data, interpret data types, and execute starter codes

#DataScience #AI #Python

📌 Azure ML vs. AWS SageMaker: A Deep Dive into Model Training — Part 1

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-01-25 | ⏱️ Read time: 11 min read

Compare Azure ML and AWS SageMaker for scalable model training, focusing on project setup, permission…

#DataScience #AI #Python

📌 SAM 3 vs. Specialist Models — A Performance Benchmark

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-01-25 | ⏱️ Read time: 19 min read

Why specialized models still hold the 30x speed advantage in production environments

#DataScience #AI #Python

Data Science Interview questions

#DeepLearning #AI #MachineLearning #NeuralNetworks #DataScience #DataAnalysis #LLM #InterviewQuestions

https://news.1rj.ru/str/CodeProgrammer

📌 Causal ML for the Aspiring Data Scientist

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-01-26 | ⏱️ Read time: 18 min read

An accessible introduction to causal inference and ML

#DataScience #AI #Python

📌 How Cursor Actually Indexes Your Codebase

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-01-26 | ⏱️ Read time: 10 min read

Exploring the RAG pipeline in Cursor that powers code indexing and retrieval for coding agents

#DataScience #AI #Python

📌 Ray: Distributed Computing For All, Part 2

🗂 Category: PROGRAMMING

🕒 Date: 2026-01-26 | ⏱️ Read time: 11 min read

Deploying and running Python code on cloud-based clusters

#DataScience #AI #Python

📌 How Convolutional Neural Networks Learn Musical Similarity

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-01-26 | ⏱️ Read time: 13 min read

Learning audio embeddings with contrastive learning and deploying them in a real music recommendation app

#DataScience #AI #Python

📌 Going Beyond the Context Window: Recursive Language Models in Action

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-01-27 | ⏱️ Read time: 24 min read

Explore a practical approach to analysing massive datasets with LLMs

#DataScience #AI #Python

📌 Data Science as Engineering: Foundations, Education, and Professional Identity

🗂 Category: DATA SCIENCE

🕒 Date: 2026-01-27 | ⏱️ Read time: 15 min read

Recognize data science as an engineering practice and structure education accordingly.

#DataScience #AI #Python