Reading Hub

Current readings and AI-powered research insights

12
Currently Reading
45
Papers Read
28
Saved Insights

Current Reading Queue

Healthcare AI

Attention Is All You Need (Transformer Architecture)

Vaswani et al. (2017) - NeurIPS

Est. 45 min • Priority: High
Business AI

Explainable AI: A Review of Machine Learning Interpretability Methods

Linardatos et al. (2020) - Entropy

Est. 60 min • Priority: Medium
Methodology

Federated Learning: Challenges, Methods, and Future Directions

Li et al. (2020) - IEEE Signal Processing Magazine

Est. 50 min • Priority: High

Recent Insights (from Perplexity)

"Transformer models have revolutionized NLP by enabling parallel processing of sequences, making them significantly faster than RNNs while capturing long-range dependencies more effectively."

Source: "Attention Is All You Need" • Saved: Oct 8, 2024

"XAI methods fall into three categories: feature importance (SHAP, LIME), example-based (prototypes), and self-explaining models. Each has trade-offs between accuracy and interpretability."

Source: Explainable AI Review • Saved: Oct 7, 2024

"Federated learning enables training on decentralized data without sharing raw information, critical for healthcare applications where privacy is paramount. Challenges include non-IID data and communication efficiency."

Source: Federated Learning Survey • Saved: Oct 6, 2024

Reading by Category

Healthcare AI (18 papers)

  • • Medical image analysis (7)
  • • Disease prediction (5)
  • • Clinical NLP (4)
  • • Drug discovery (2)

Business Analytics (12 papers)

  • • Customer analytics (4)
  • • Forecasting (3)
  • • Decision support (3)
  • • Fraud detection (2)

ML Methods (15 papers)

  • • Deep learning architectures (6)
  • • Explainable AI (4)
  • • Federated learning (3)
  • • Transfer learning (2)

AI Ethics (8 papers)

  • • Fairness & bias (3)
  • • Privacy preservation (3)
  • • Responsible AI (2)

AI Reading Assistant

Use Perplexity AI to enhance your reading experience

Find Related Papers
Summarize Complex Topics
Ask Deep Questions