Happy International Museum Day
We at Gavagai wanted to pay homage to museum day by analyzing museums that are specialized in art from different eras! The journey will start in ancient Peru and end in the 1970s postmodernism.
Read more: https://www.gavagai.io/blog/2020/05/18/museum-day/
However, since most museums are closed these days due to the pandemic Covid19, we also decided to investigate an alternative. Namely, virtual museums https://www.gavagai.io/blog/2020/05/17/virtual-museums/
Kungsgatan 60, 111 22 Stockholm
Gavagai is a Swedish language technology company spun off from the Swedish Institute of Computer Science. The team at SICS, which later became Gavagai, participated in the Real World Intelligence research program, in the 1990:s. We are pioneers in language AI and have developed our Word Space Technology for more than 20 years. Our research team has published more than 400 academic papers.
Extreme scalability, learning, automation and language agnosticism are some features of our technology, which is based on a neurologically plausible method that models meaning on-the-fly.
We have achieved state-of-the-art solutions to some of the major problems in the IT industry. We anticipate a transformative shift towards meaning-based data management and analysis.
The unique capabilities of our technology include continuous and incremental on-the-fly learning of unigrams and n-grams from vast streams of data, without a re-train/re-deploy cycle.
We see this as absolutely necessary to keep up with the novelty and extreme variability in actual language usage and to solve most real life NLP tasks. We have native language support for 45 languages.
We have recently implemented our research in a scaleable industrial system, on top of which we have built a next generation insight tool, The Explorer, with unparalleled performance.
Our aim is to establish our unsupervised language AI as the global standard for a semantic base layer which will be an integral and fundamental part of all emerging technologies and solutions dealing with large amounts of unstructured language data.
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