ChatGPT explained – everything you need to know about the AI chatbot

Natural Language Processing

Natural Language Processing (previously Natural Language Engineering) is an open access journal which meets the needs of professionals and researchers working in all areas of natural language processing (NLP). Its aim is to bridge the gap between traditional computational linguistics research and the implementation of practical applications with potential real-world use. The journal publishes original research articles on a broad range of methods and resources applied in NLP, language processing tasks and NLP applications, including (but not limited to) machine translation, translation technology, sentiment analysis, information retrieval, question answering, text summarisation, text simplification, and speech processing. Natural Language Processing invites novel studies employing the latest deep learning methods and large language models. It encourages submissions reporting the findings from multilingual and low-resourced language projects. The journal publishes special issues on timely NLP topics of wide interest as well as squibs and book reviews. It welcomes survey papers describing the state of the art of a specific topic. Natural Language Processing also features the popular Industry Watch and Emerging Trends columns.

Natural Language Processing Features Enhance NI Labview

Emerson's Test and Measurement business, formerly NI, reaffirmes its commitment to its comprehensive test approach and unveils significant updates to its core software products, including NI LabVIEW™ and shares its vision for intelligent test strategies. At NI Connect 2024, a conference for customers, partners, and industry leaders, Emerson showcased the latest advancements in NI hardware and software that improve the efficiency of engineers so they can spend more time on root cause analysis and collaboration across their organisation.

"Our software-centric, modular hardware approach to test is our unique value proposition and a differentiator for our customers," said Ritu Favre, group president of Emerson's Test and Measurement business. "We are excited to share our vision for harnessing the power of AI in test and measurement and to continue our commitment to innovate on our industry-leading NI products. Through our innovative, secure and expert-led approach, we will revolutionize intelligent test across the industry."

Emerson is committed to providing robust support for R&D efforts in core NI-branded products such as LabVIEW and TestStand™, and to building a comprehensive, connected workflow with complementary products within the NI LabVIEW+™ suite to maintain the drumbeat of continuous improvement in the NI technology and software roadmap. New NI product advancements introduced at NI Connect include:

The latest iteration of NI LabVIEW focuses on collaborative engineering workflows, integrating new features such as enhancements in diff and merge functions, version management and support for calling .NET Core Assemblies (.NET 8). 

NI experts demonstrated how AI could be leveraged within development tools such as LabVIEW to increase user productivity. Capabilities include automating code description and documentation – a must-have feature for the common use case of an engineer inheriting code with unclear operation. In addition, the NI team is trialing AI technology with LabVIEW and collecting registrations for a broader program to launch soon. 

LabVIEW "Community Edition" free for students

Expanding on these investments, the company announced that NI LabVIEW Community Edition, originally introduced in 2019, is now free for students. Parts of NI LabVIEW, starting with Icon Editor, will also become open source to drive greater community collaboration.

NI PXI Hardware news

Emerson continues to strengthen its NI PXI hardware portfolio, incorporating recent additions such as the NI PXIe-5633 Vector Network Analyzer (VNA) add-on module, the PXIe-6571 Digital Pattern Instrument and family of new controllers built on 11th generation Intel Core processors. These efforts underscore Emerson's commitment to enhancing its catalogue of solutions, like the NI Semiconductor Test System (STS), which is celebrating its 10th anniversary. 

Deep Learning For Natural Language Processing

Deep Learning is becoming increasingly important in a technology-dominated world. However, the building of computational models that accurately represent linguistic structures is complex, as it involves an in-depth knowledge of neural networks, and the understanding of advanced mathematical concepts such as calculus and statistics. This book makes these complexities accessible to those from a humanities and social sciences background, by providing a clear introduction to deep learning for natural language processing. It covers both theoretical and practical aspects, and assumes minimal knowledge of machine learning, explaining the theory behind natural language in an easy-to-read way. It includes pseudo code for the simpler algorithms discussed, and actual Python code for the more complicated architectures, using modern deep learning libraries such as PyTorch and Hugging Face. Providing the necessary theoretical foundation and practical tools, this book will enable readers to immediately begin building real-world, practical natural language processing systems.

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