“I’m in it for the tech,” is a phrase commonly used in the cryptocurrency ecosystem by many who want to express a deeper motivation for being involved with blockchain technology beyond the significant gains that are known to happen in the volatile asset class.
One project that has quietly climbed the charts without the need to jump on the decentralized finance (DeFi) or nonfungible token (NFT) trend is Vectorspace AI (VXV), a protocol building correlation matrix datasets capable of detecting hidden relationships in data and training artificial intelligence (AI) systems.
Data from Cointelegraph Markets Pro and TradingView shows that since hitting a low of $0.71 on May 23, the price of VXV has skyrocketed 2,267% to a record high at $19.47 on Sept. 16 before experiencing a significant pullback alongside the rest of the crypto market.
This week, the price action for VXV is once again on the rise as its 24-hour volume spiked 380% to $9.37 million on Nov. 11, resulting in an overnight price increase of 32.42% to an intraday high at $16.18.
The sudden boost in price and trading volume comes as VXV listed on the KuCoin exchange, the sixth-largest cryptocurrency exchange by trading volume.
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Flying under the radar
Aside from the above tweet announcing the KuCoin listing, the team at Vectorspace AI keeps a pretty low-key profile in terms of project announcements and marketing. Most of the project's Twitter feed features some of the latest developments and discoveries in the field of data analysis and bio-science.
With a focus on “context-controlled NLP/NLU (Natural Language Processing/Understanding)” and using AI to “discover hidden relationship detection in data related to space biosciences,” Vectorspace lacks many of the bells and whistles that catch the eye of the average crypto holder.
But to anyone who has been paying attention to the rising value and importance of data in the digital age, the ability to correlate and analyze large amounts of data to discover solutions that would take human years to manually analyze is the “holy grail” in the world of data analysis.
For example, early on in the COVID-19 pandemic, Vectorspace technology was able to analyze years of medical research and findings to recommend a shortlist of substances that could possibly be used as treatment, helping scientists narrow down their search and save valuable time.
The ability to generate on-demand NLP/NLU correlation matrix datasets is a highly sought-after feature for researchers, especially when it comes to finding a way to “get machines to trade information with one another or exchange and transact data in a way that minimizes a selected loss function.”
According to the project’s website, the current list of partners and collaborators include PubMed.gov, the United States Department of Energy, the National Library of Medicine, the European Molecular Biology Laboratory, the Lawrence Berkeley National Laboratory and CERN.
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