NLP++ in VS Code: Everything New in Version 3
Version 3 has been the biggest chapter yet for the NLP++ extension for Visual Studio Code. […]
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Compiling NLP++ analyzers is now a single click. Version 3 brings native-code speed and lets you deploy analyzers without exposing your source.
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Version 3 has been the biggest chapter yet for the NLP++ extension for Visual Studio Code. What started as a way to compile and run analyzers has grown into a complete development environment for the NLP++ language — with the kind of code intelligence you’d expect from a first-class programming language. […]
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Yes, you can have Claude write NLP++ for you — and no, that doesn’t make it another black box. This step-by-step guide takes you from a blank machine to a working analyzer: install VS Code, add the NLP++ extension, run Claude Code, and use the built-in prompts to generate real, glass-box code. What you keep is deterministic, auditable, and runs on its own — no model required.
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I spent the last 8 weeks using Claude to eventually replace Claude. Ironic…
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One of the strengths of NLP++ is that once you’ve written an analyzer in the VisualText VS Code extension, you are not locked into a single way of running it. The same glass-box, 100% rule-based analyzer can be driven from Python, from Node.js, from TypeScript, or straight from the command […]
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For most of its life, the NLP++ engine has been a powerful tool for writing rule-based analyzers — explainable, glass-box, and deterministic natural-language processing you can actually read, debug, and reproduce exactly. It has run on Windows, Linux, and macOS for years. What Version 3 changes is how you build, […]
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LLMs guess. NLP++ understands. And that difference is exactly why NLP++ is the only technology positioned to eventually replace large language models in real‑world text processing. LLMs are probabilistic black boxes. They don’t know anything; they predict. They require teaming — layers of prompts, validators, guardrails, and secondary models — […]
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With our NLP++ textbook coming out world-wide this month (it may be already out by the time you read this), people are asking: what is the difference between LLMs and NLP++? Here is a first attempt of mine to explain. NLP++ and LLMs aren’t two approaches to the same problem. […]
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Our neural network brains are bamboozled by the “average”, but we “average” people are waking up. This explains why we are so easily fooled and how human ingenuity can get us out of this (A)verage (I)ndustry mess.
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In recent comment threads and after reading the ubiquitous posts on “AI” on LinkedIn, I have come to the revelation that we are living in the “era of shallow thinking”. And it is this problem that is holding us back from doing more “profound” things in computer science.
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Muhammad Ahmad: Pioneering Decentralized AI with a Human-Centric Approach Muhammad Ahmad is a distinguished blockchain developer and researcher whose expertise lies at the critical intersection of decentralized systems, Artificial Intelligence, and secure data interaction. A Computer Science graduate from FAST NUCES, he consistently demonstrated academic excellence, earning recognition on the […]
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Sachi Patel is a Data Engineer who recently received her Master of Science in Data Analytics Engineering at Northeastern University. She specializes in architecting and optimizing end-to-end ETL pipelines, leveraging technologies such as Apache Spark, AWS, and Apache Airflow to ensure reliable, scalable data integration and processing. With a strong […]
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Niranjan Kumar Ilampooranan recently earned his Master’s in Robotics Engineering from WPI, where he was also a graduate research assistant in the ELPIS (Efficient Learning and Planning for Intelligent Systems) lab. He is also a recipient of Dr. Glenn Yee Graduate Student Tuition Award, a scholarship awarded to outstanding robotics […]
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Northeastern University is launching an innovative, zero-credit course that leverages blockchain technology and the rule-based programming language NLP++ to build a decentralized, human-driven natural language processing ecosystem.
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David de Hilster is on the warpath. He is tired of all the “hype” vocabulary used in “AI”. Find out how he plans to change this with simple word changes.
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