Naver’s supersized AI research strides towards commercialization
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According to sources on Sunday, nine articles from researchers affiliated with Naver AI Lab and Clova under the Korean IT giant were adopted by the Empirical Methods in Natural Language Processing (EMNLP) held last month. EMNLP is a leading global conference in the area of natural language processing and artificial intelligence.
Among the papers adopted this time, the company’s new technology dubbed Alpha Tuning drew great attention from researchers around the world as it is used to commercialize Naver’s supersized AI platform HyperCLOVA.
Alpha Tuning developed by Naver Clova’s Efficient AI team presented a new breakthrough in the field of data weight reduction and optimization, which are two key things worldwide researchers are concentrating on to improve AI performance.
The performance of supersized AI is usually evaluated by the number of parameters. HyperCLOVA unveiled by Naver in May last year achieved a scale of 204 billion parameters, more than that of Open AI GPT-3 (Open AI), which was once known as the most outstanding supersized AI.
The more parameters, the greater number of graphic processing units (GPUs) becomes in need. But the Naver team has implemented lighter and more efficient AI through quantization and data compression techniques.
Alpha Tuning research is a key technology to improve AI data weight loss and optimization through a new quantization-based additional learning technique, said a company official, adding this technology will be used to introduce supersized AI into various services in the future.
Naver continues to invest in AI research despite losses in the area for many years. The company has invested about 25 percent of its revenue in R&D over the past several years. In 2017, it acquired France’s Xerox Research Center Europe and created it into Naver Labs Europe.
Naver’s research performance is also evidenced by the number of research papers. The number of Naver Clova papers accepted at major professional societies around the world, including the top three AI societies (ICLR, CVPR, EMNLP), increased to 97 this year from 43 in 2020.
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