Tag

#NLP

14 articles

Perplexity AI Releases WANDR: An Open Benchmark Evaluating Research Agents That Must Search Wide And Deep

Learn to build a research agent framework similar to Perplexity's WANDR benchmark that evaluates AI systems' ability to discover evidence and provide verifiable sources.

Jul 1816

tech

Indian tech tycoon bets $30M of his own money to build AI alternative to Microsoft Office

Learn to build an AI-powered document processing system that mimics core Office functionality using Python, NLP libraries, and machine learning frameworks.

Jul 141

It’s hot IPO summer, and the MANGOS are ripe

Learn to build and deploy an AI-powered sentiment analysis tool using OpenAI, Hugging Face transformers, and GPU acceleration - similar to technologies used by MANGOS companies.

Jun 1250

tools

Perplexity AI Open-Sources Unigram Tokenizer That Achieves 5x Lower p50 Latency Than Hugging Face tokenizers Crate

Perplexity AI open-sources a new Unigram tokenizer that reduces p50 latency by 5x and cuts CPU utilization by 5-6x compared to Hugging Face tokenizers.

May 2858

96% of IT pros use AI now: Their top 7 agentic applications and biggest implementation roadblocks

Learn to build a practical AI output validation system that combines multiple NLP techniques to assess the quality and reliability of AI-generated content, addressing the growing need for validating AI outputs in professional environments.

May 2149

tools

How to Build Knowledge Graph Generation Pipelines From Text With kg-gen, NetworkX Analytics, and Interactive Visualizations

A tutorial from MarkTechPost demonstrates how to build knowledge graph generation pipelines using kg-gen, NetworkX, and interactive visualizations for extracting structured insights from text.

May 2053

Arxiv cracks down on unchecked AI-generated content in research papers

Learn to build a Python-based tool that detects potential AI-generated content in research papers, helping maintain academic integrity in the face of stricter arXiv policies.

May 1562

What is Tokenization Drift and How to Fix It?

Tokenization drift is a subtle but critical issue in AI where minor formatting differences in input text cause models to behave inconsistently. This phenomenon can lead to unexpected performance drops without any changes to data or logic.

May 276

tech

Google Search queries hit an ‘all time high’ last quarter

Learn to build an AI-powered search query analyzer that can categorize and visualize search trends similar to Google's AI systems. This intermediate tutorial covers NLP preprocessing, TF-IDF vectorization, and clustering techniques.

Apr 2941

tech

How to Build Smarter Multilingual Text Wrapping with BudouX Through Parsing, HTML Rendering, Model Introspection, and Toy Training

This explainer explores BudouX, an advanced tool for intelligent multilingual text wrapping that uses NLP and machine learning to break lines at semantic boundaries, improving readability and user experience across different languages.

Apr 2672

Tokenmaxxing, OpenAI’s shopping spree, and the AI Anxiety Gap

Learn to build an AI-powered recommendation system using Python, NLP, and transformer models. This tutorial demonstrates how companies like OpenAI and Anthropic approach AI infrastructure development.

Apr 1790

tech

Study maps developer frustration over "AI slop" as a "tragedy of the commons" in software development

Learn to build a practical AI quality assessment tool that helps developers identify low-quality AI-generated content, or 'AI slop,' in software development.

Apr 5104