Top-class partnerships and the focus on the use of artificial intelligence (AI) and big data to solve complex problems are driving Vectorspace AI (VXV) to the next level: new all-time high (ATH).
“I’m in the technology” is a phrase that is often used in the cryptocurrency ecosystem to express a deeper motivation to participate in blockchain technology beyond its known advantages. It is a volatile asset class.
One project that has quietly climbed the charts without breaking into the DeFi or NFT trends is Vectorspace AI (VXV), a correlation matrix dataset creation protocol that can detect correlations. Train hidden systems in data and AI programs.
Data from TradingView shows that VXV’s price has risen from its low of $ 0.71 on Jan.
VXV / USD 1-day chart | Source: CoinGecko
This week, VXV’s price action spiked again as its 24-hour trading volume rose 380% to $ 9.37 million on November 11, causing it to climb 32.42% to the high.
The sudden increase in price and trading volume occurs when VXV listing on KuCoin, the sixth largest exchange by trading volume.
Aside from the announcement tweet about the listing on KuCoin, the Vectorspace AI team didn’t have many project and marketing announcements. The project’s Twitter account contains just a few of the latest developments and discoveries in the fields of data analysis and life sciences.
With a focus on context-driven NLP / NLU (Natural Language Understanding / Processing) and using AI to uncover hidden relationships in spatial science data, Vectorspace hasn’t attracted much attention from the average crypto owner.
But for anyone paying attention to the growing value and importance of data in the digital age, the ability to correlate and analyze large amounts of data to find solutions that people would lose is of data analysis.
For example, at the start of the Covid-19 pandemic, vectorspace technology was able to analyze years of research and medical literature to recommend a short list of substances that could be used for treatment, helping scientists narrow down their searches, and saving valuable time.
The ability to create on-demand NLP / NLU correlation matrix datasets is a feature that is much sought after by researchers, especially when it comes to figuring out how “machines exchange information” or exchange data in one way and the other act that minimizes a selected loss function “.
According to the project’s website, the current list of partners and contributors includes PubMed.gov, US Department of Energy, National Library of Medicine, European Molecular Biology Laboratory, National Laboratory Lawrence Berkeley, and CERN.
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According to Cointelegraph