This is a guest post by one of our most esteemed clients, Manuel Herranz, CEO of Pangeanic. We collect, classify and supply data for AI training at NLP Consultancy: and working with data allows us to test models and understand what the market wants. Our close relationship with Pangeanic as
A persistent reliability gap exists between AI’s theoretical capabilities and real-world performance. Human-in-the-loop (HITL) systems offer a powerful solution by integrating human expertise directly into AI processes, creating a collaborative framework that enhances accuracy, reduces bias, and builds trust
In an ever-more-complex and competitive landscape dominated by titans like ChatGPT-4 and Anthropic’s Claude, DeepSeek-R1 has emerged as a surprising frontrunner. Although it has become clear that DeepSeek wasn’t built on $5M budget, this new language model not only competes with industry giants but also outperforms them in critical benchmarks.
The demand for high-quality datasets has never been more critical. Among these datasets, long-form parallel corpora are standing out as indispensable resources for advancing multilingual communication and linguistic automation. This is due to the new fluency by LLMs we have grown used to since late 2022 with the advent of
Artificial intelligence (AI) is fast becoming a daily tool in our daily lives, not only transforming the way we live and work, but also how we humans interface with machines and with each other. We are offering this AI Training Data Guide because as AI continues to advance, it’s crucial
As we continue to embrace globalization and digitization, machine translation systems (MT) are playing an increasingly pivotal role in our interconnected world. By breaking down language barriers, these sophisticated tools foster cross-cultural understanding and facilitate seamless communication. However, as is the case with any technology, MT systems aren’t without their
What is Named Entity Recognition (NER)? Named Entity Recognition (NER) represents a subdivision of Natural Language Processing (NLP) tasked with the automatic detection and classification of named entities present within a given text. Named entities, in this context, refer to explicit references to individuals, organizations, geographic locations, dates, or any
Voice /Speech Data for Machine Learning Building Ethical AI into all our data processes is at the heart of what we do. We legally collect voice / speech data from our multilingual pool of talent distributed around the world so you can train and improve your Automatic Speech Recognition systems
Our linguists are skilled in understanding and interpreting day-to-day, conversational and nuanced language so you can improve your translation systems.NLPC has the ability to create parallel corpora data sets from and into English from most languages in the world. With a diversified team of linguists around the world, we have
If you are developing a computer vision system, you will need thousands, millions of images, videos, and sensor data to train machine learning models for computer vision. – NLPC can provide both the Data Sets for Computer Vision and the annotation services to make your project a success. The types
Feel free to contact us at any of our locations, fill in our contact form or write to us at info@nlpconsultancy.com
Founded in 2022, our mission is to make AI more multilingual and accurate thanks to expert data annotation and data labeling services for the creators of the future.
Designed by CoreConcepts
