What will drive NLP growth in the coming year?

A Look Ahead to NLP in 2022

The world is facing a global AI talent shortage, so while there’s a great demand for NLP implementations, the supply of data scientists needed to bring these projects to life are limited. But what if we could democratize NLP, reducing the need for data scientist intervention?

What's next for NLP?

The Trends Shaping Natural Language Processing in 2021

According to research from last year, 2020 had an impact on business globally, but NLP was a bright spot for technology investments. That momentum has carried through to this year, but even still, we are just at the tip of the iceberg in terms of what NLP has to offer.

Interview with Jens Dahl Møllerhøj

Nordic language BERT models: “Languages with fewer speakers are underrepresented on the internet”

BERT models in Danish, Swedish and Norwegian have been released by the Danish company BotXO. We spoke to Jens Dahl Møllerhøj, Lead Data Scientist at BotXO, to find out more. See how these open source models differ from Google’s multilanguage BERT model, what can make creating NLP models for Nordic languages difficult, and where these models can be used.

Natural language generation with 17 billion parameters

Microsoft’s deep learning language model Turing-NLG outperforms GPT-2

Microsoft has announced its deep learning language model Turing-NLG, and its impressive 17 billion parameters make it the largest language model to date. While it is not publicly available, a demo version has been released to a small group for testing purposes. Let’s see if more parameters mean better results, compared to OpenAI’s GPT-2 and NVIDIA’s Megatron-LM.