Vectorspace AI

Vectorspace AI

VXV
$0.776530884%-8.93

Key Metrics

Price$0.776530884
Real Volume (24H)$126,930.8
Marketcap$38,762,134.17
Fully Diluted ValuationN/A
ATH$19.19
ATH Date9/16/2021, 9:55:16 AM
ATL$0.01289305
ATL Date11/12/2019, 5:38:55 PM
Circulating Supply38M
Total Supply50M
WebsiteN/A
WhitepaperN/A
Popularity Rank768
Chart
What is Vectorspace AI?

Vectorspace AI is a cutting-edge blockchain-based cryptocurrency designed for software development in the areas of space biosciences and financial markets. With a focus on natural language understanding and processing, Vectorspace AI helps research groups, data vendors, institutions, and funds save time by improving signals and precision in their work. The platform is designed to allow machines to transact and exchange data in a way that reduces loss, with the ultimate goal of improving innovation and making scientific breakthroughs.

The Vectorspace AI network uses advanced approaches in machine learning and artificial intelligence, merged with experimental methods developed at Lawrence Berkeley National Laboratory Bioscience Division. The team has a deep understanding of financial markets and has created algorithms for quantifying data arbitrage opportunities. The platform also allows for deep analysis of global trends in scientific papers, news, patents, and internet data, providing unique analysis opportunities for continuous information arbitrage.

VXV is the native and utility token of Vectorspace AI and is used as a public trading vehicle. The value of the VXV token is controlled by users who aim to take long-term positions in the asset. Vectorspace AI also provides a public marketplace where users can acquire blocks of VXV and bid for proprietary datasets.

Vectorspace AI was founded by Kasian Franks, a 25-year Silicon Valley veteran and pioneer in digital data streaming, with experience in machine learning, artificial intelligence, natural language processing, and data science strategies. The founding team also includes Mike Muldoon and Caleb Pate.

Vectorspace AI tokens are created and earned by enabling machines to transact VXV tokens, with 50% of the revenue used to buy VXV tokens on the open market. Users can earn yield, funding, and revenue through subscriptions, licensing, revenue sharing, and transaction fees. The VXV token does not function as a currency, but rather serves as a mechanism for accessing data sets, data provenance, governance, and on-chain activities.

Vectorspace AI also places a strong emphasis on data reliability, recognizing the importance of understanding the source of data, especially in the field of bioscience. With a focus on context-controlled natural language understanding and feature engineering, Vectorspace AI is able to detect hidden relationships in data related to space biosciences.

The Vectorspace AI platform is designed to be highly scalable, allowing for growth and expansion as more data and participants are added to the network. The platform also has a strong focus on security, utilizing blockchain technology to ensure the safety and integrity of data and transactions.

In addition to its focus on machine-to-machine data transactions, Vectorspace AI also allows for human-to-machine interactions. The platform provides a user-friendly interface that enables users to easily interact with the network and access data sets, while also allowing for the creation of custom data sets tailored to the specific needs of individual users.

Overall, Vectorspace AI is a cutting-edge platform that is revolutionizing the way that machines interact with data in the fields of space biosciences and financial markets. With its focus on natural language understanding, scalability, security, and user-friendliness, Vectorspace AI is poised to become a leading player in the world of cryptocurrency and data transactions.

Disclaimer

The investment information, comments, and recommendations provided here do not fall under the scope of investment consulting. Therefore, making an investment decision based solely on the information and comments provided here may not yield results that meet your expectations.

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