Why Vectorspace.ai?
Because language is the next frontier in technology — it is the next big breakthrough for AI.
Vectorspace’s datasets power the ability for artificial intelligence to identify, learn, and predict behavior.
These datasets are about discovering hidden relationships in and between data.
Their technology is based on datasets that use experimental and formal language models including well-known models such as OpenAI’s GPT-3 (2020), Google’s BERT (2018), word2vec (2013) combined with experimental methods developed at Lawrence Berkeley National Laboratory (2008).
Vectorspace’s innovations are patented and their team has invented variants including a System and Method for Generating a Relationship Network — K Franks, CA Myers, RM Podowski — US Patent 7,987,191, 2011 with Lawrence Berkley’s National Lab.
Vectorspace indices are built and the relationships are calculated with resulting datasets available via an API.
I’d like to highlight one of their goals stated directly on their website
…to provide retail traders and investors with advanced tools used to trade the financial and crypto markets in new ways. Vectorspace context-controllable correlation matrix datasets can be used to create what we call ‘Thematic Baskets’. These are groups of assets such as equities or cryptocurrencies that share known and hidden relationships with one another in the context of a global event, theme or topic. Detecting hidden relationships between equities, entities and global events based on sympathetic, symbiotic, parasitic or latent entanglement can result in unique opportunities connected to ‘information arbitrage’.
Their platform powers research groups, data vendors, funds and institutions by generating on-demand NLP/NLU (Natural Language Processing/ Understanding) correlation matrix datasets.
Allow me to repeat: datasets are the refined gasoline that powers every Machine Learning (ML) and AI operation.
Vectorspace.ai is essentially going to make human traders extinct. The datasets will produce the best possible trades for companies, and they will all be battling for the best datasets — the smartest AI.
Vectorspace.ai is seemingly the leader in NLP/NLU and this learning will provide various institutions with the technology to maximize profits.
Currently their partners are the U.S. National Library of Medicine, U.S. Dept. of Energy, and CERN and I expect that as datasets become prevalent in trading, VXV will become utilized exponentially.
Institutions, and especially financial institutions, will not want to be left in the dust and their leaders will be adopting and adapting to this technology. They will be learning where NLP/NLU will work best or where it doesn’t work at all.
Those that get a head start on adapting AI language will be ahead on redesigning entire industries. Privacy, security, and social responsibility all surround AI and I believe that it will end up becoming the future of our civilization, for better or worse.
This is transhumanism in the making. Though I have my own personal opinions on the matter, that is not the content of this piece.
Essentially, I believe that Vectorspace.ai is a crypto gem because,
- Their datasets can be used to find hidden relationships across basically every industry.
- Their findings and technology are backed by patents.
- There is a low circulating supply and very low market cap (as of writing) and has a lot of room for growth. Though, low liquidity.
- The users are incentivized to hold because the datasets are accessed via subscription and paid in VXV.
- We are moving into the fourth technological industrial revolution based AI and the next frontier is language. Vectorspace.ai has been a leader in machine learning and comprehension.
- Though, they don’t have much of a social presence and seem to lack marketing efforts — I believe they’re focusing on tech.
Simply put, according to Vectorspace.ai,
Datasets are real-time and designed to augment or append to existing proprietary datasets such as gene expression datasets in life sciences or time-series datasets in the financial markets. Example customer and industry use cases include:
Particle Physics: Rows are particles. Columns are properties. Used to predict hidden relationships between particles.
Life Sciences: Rows are infectious diseases. Columns are approved drug compounds. Used to predict which approved drug compounds might be repurposed to fight an infectious disease such as COVID19. Applications include processing 1500 peer reviewed scientific papers every 24hrs for real-time dataset production.
Financial Markets: Rows are equities. Columns are themes or global events. Used to predict hidden relationships between equities and global events. Applications include thematic investing and smart basket generation and visualization.
Data provenance, governance and security are addressed via the Dataset Pipeline Processing (DPP) hash blockchain and VXV utility token integration. Datasets are accessed via the VXV wallet-enable API where VXV is acquired and used as a utility token credit which trades on a cryptocurrency exchange.
Obviously, this is bigger than just trading.
NLP/NLU is about understanding global movements and behavior. When global movements and behavior are understood, they can be not only predicted, but they can be controlled.
NLP/NLU is Vectorspace’s game. VXV is their token’s name.
Though, this is not financial advice. This is just my opinion on an interesting company and their native VXV token.