“I do technology” is a phrase frequently used in the cryptocurrency ecosystem by many who wish to express a deeper drive to participate in blockchain technology beyond the major developments known to occur in the volatile asset class. …
One project that has quietly climbed the charts without resorting to the trend of decentralized finance (DeFi) or non-fungible tokens (NFT) is Vectorspace AI (VXV), a correlation matrix dataset for building a protocol capable of discovering relationships hidden in data. and artificial education. Intelligence Systems (AI).
Data from Cointelegraph Markets Pro and TradingView shows that after hitting a low of $0.71 on May 23, VXV price surged 2.267% to a record high of $19.47 on September 16, before seeing a significant drop along with the rest of the price. Cryptocurrency market.
VXV/USD 1 day chart. Source: CoinGecko
The price trend on VXV is up again this week as the 24-hour trading volume on November 11th increased 380% to $9.37M, taking the overnight price by 32.42% to an intraday high of $16.18.
The sudden rise in price and trading volume stems from the fact that VXV is listed on KuCoin, the sixth largest cryptocurrency exchange by trading volume.
On this topic: Digital intelligence must overcome problems in solving cryptocurrencies
flying under the radar
Aside from the above tweet announcing the KuCoin roster, the Vectorspace AI team maintains a fairly low profile when it comes to project advertising and marketing. Much of the project’s Twitter feed contains some of the latest developments and discoveries in data analysis and the life sciences.
With a focus on “context-based NLP/NLU (natural language processing/understanding)” and using AI to “discover hidden relationships in diamond science data,” Vectorspace lacks a lot of attention-grabbing bells and whistles. Average holder of cryptocurrency.
But for anyone who understands the growing value and importance of data in the digital age, the ability to connect and analyze large amounts of data to create solutions that will take years to analyze manually is the holy grail of the world. data analysis.
For example, at the start of the COVID-19 pandemic, Vectorspace was able to analyze years of medical research and results to recommend a short list of drugs that could be used as treatments and help researchers narrow down their search and save valuable time.
The ability to generate on-demand NLP/NLU correlation matrix datasets is a much-needed feature for researchers, especially when it comes to finding a way to “make machines communicate with each other or exchange data and transactions in a way that minimizes the loss of selected functionality.”
According to the project website, the current list of partners and partners includes PubMed.gov, the US Department of Energy, the National Library of Medicine, the European Laboratory of Molecular Biology, Lawrence Berkeley National Laboratory, and CERN.
