Register for free to join our community of investors and share your ideas. You will also get access to streaming quotes, interactive charts, trades, portfolio, live options flow and more tools.
Deal with S&P Global and now QuantCloud
VXV is primed for big run into 2021
https://www.coingecko.com/en/coins/vectorspace-ai
Vectorspace AI & CERN Create Natural Language Processing (NLP) Datasets in Particle Physics with Applications in Artificial Intelligence (AI) for Every Industry
https://www.prnewswire.com/news-releases/vectorspace-ai--cern-create-natural-language-processing-nlp-datasets-in-particle-physics-with-applications-in-artificial-intelligence-ai-for-every-industry-301138576.html
Vectorspace AI and LCX Announce Partnership to Enable Event-driven Smart Baskets for Cryptocurrencies
https://medium.com/@492727ZED/vectorspace-ai-and-lcx-announce-partnership-to-enable-event-driven-smart-baskets-for-2cf18baea418
Dexamethasone Announcement Could Have Made Hedge Funds A Fortune — Alpha Week
https://medium.com/@492727ZED/dexamethasone-announcement-could-have-made-hedge-funds-a-fortune-alpha-week-313abb218a64
Comparing RPS (Revenue Per Share) between Cryptos & Stocks
https://medium.com/@492727ZED/comparing-rps-revenue-per-share-between-cryptos-stocks-f2aecc4fef1b
Predicting Future Correlations between Equities
https://medium.com/@492727ZED/predicting-future-correlations-between-equities-8a0fcf302ce6
Real Due Diligence (DD) Guidelines for Crypto Companies in 2020
https://blog.goodaudience.com/real-due-diligence-dd-guidelines-for-crypto-companies-in-2020-fce9794e1bbd
Generating Alpha from Information Arbitrage in the Financial Markets with NLP Datasets: ????
https://medium.com/hackernoon/profiting-from-information-arbitrage-in-the-financial-markets-3abfca9806d8
VXV News - AMZN and MSFT!
Vectorspace AI Datasets are Now Available to Power Machine Learning (ML) and Artificial Intelligence (AI) Systems in Collaboration with Elastic
SAN FRANCISCO, CA -- January 22, 2020 -- InvestorsHub NewsWire -- Vectorspace AI (VXV) announces datasets that power data engineering, machine learning (ML) and artificial intelligence (AI) systems. Vectorspace AI alternative datasets are designed for predicting unique hidden relationships between objects including current and future price correlations between equities.
Vectorspace AI enables data, ML and Natural Language Processing/Understanding (NLP/NLU) engineers and scientists to save time by testing a hypothesis or running experiments faster to achieve an improvement in bottom line revenue and information discovery. Vectorspace AI datasets underpin most of ML and AI by improving returns from R&D divisions of any company in discovering hidden relationships in drug development.
"We are happy to be working with Vectorspace AI based on their most recent collaboration with us based on the article we published titled 'Generating and visualizing alpha with Vectorspace AI datasets and Canvas'. They represent the tip of the spear when it comes to advances in machine learning and artificial intelligence. Our customers and partners will certainly benefit from our continued joint development efforts in ML and AI." Shaun McGough, Product Engineering, Elastic (NYSE: ESTC).
Increasing the speed of discovery in every industry remains the aim of Vectorspace AI along with a particular goal which relates to engineering machines to trade information with one another connected to exchanging and transacting data in a way that minimizes a selected loss function. Data vendors such as Neudata.co, asset management companies and hedge funds including WorldQuant, use Vectorspace AI datasets to improve and protect 'alpha'.
Limited releases of Vectorspace AI datasets will be available in partnership with Amazon (Nasdaq: AMZN) and Microsoft (Nasdaq: MSFT).
About Vectorspace AI (vectorspace.ai)
Vectorspace AI focuses on context-controlled NLP/NLU (Natural Language Processing/Understanding) and feature engineering for hidden relationship detection in data for the purpose of powering advanced approaches in Artificial Intelligence (AI) and Machine Learning (ML). Our platform powers research groups, data vendors, funds and institutions by generating on-demand NLP/NLU correlation matrix datasets. We are particularly interested in how we can get machines to trade information with one another or exchange and transact data in a way that minimizes a selected loss function. Our objective is to enable any group analyzing data to save time by testing a hypothesis or running experiments with higher throughput. This can increase the speed of innovation, novel scientific breakthroughs and discoveries. For a little more on who we are, see our latest reddit AMA on r/AskScience or join our 24 hour communication channel here. Vectorspace AI offers NLP/NLU services and alternative datasets consisting of correlation matrices, context-controlled sentiment scoring and other automatically engineered feature attributes. These services are available utilizing the VXV token and VXV wallet-enabled API. Vectorspace AI is a spin-off from Lawrence Berkeley National Laboratory (LBNL) and the U.S. Dept. of Energy (DOE). The team holds patents in the area of hidden relationship discovery.
Source: vectorspace.ai
A Deep Dive on the Data-focused Crypto, Vectorspace AI (VXV)
https://medium.com/@492727ZED/a-deep-dive-on-the-cryptocurrency-vectorspace-ai-vxv-5fae8f53c11d
AI Venturetech to Utilize VXV Smart Tokens
AI VentureTech To Collaborate with VectorSpace AI to Develop Smart Applications for Finance And Medical Industry
(NEW YORK)– AI VentureTech, Inc., the parent company of Data Elf, announced plans to collaborate with Vectorspace AI (VXV) for the development of applications within the finance and biomedical research sectors.
Vectorspace AI Platform is powered by context-controlled Natural Language Processing (NLP) and facilitated by cryptocurrency transactions. A single trend represented by a concept, keyword, hashtag, URL or news story can represent a network of cryptocurrencies or stocks based on their relationship to one another and surrounding context or concepts. This relationship network can represent a tradable token basket of closely related group of stocks that have known and hidden symbiotic, parasitic, and sympathetic relationships. They may trade in a group and fluctuate together being impacted negatively or positively by outside events and sentiment.
Medical Research
VectorSpace may also provide a useful tool for our new healthcare data science division, Deep MedTech, in finding new and novel research paths in biomedical research. The ability to find hidden correlations could be a useful tool within the biomedical and drug development industry. Deep MedTech will look to build applications that could be marketed to developers, and other drug and pharmaceutical companies seeking new approaches in novel drug and gene therapy development.
Deep Fakes and Cybersecurity
VectorSpace technology may also be useful in hashing out fake news and content online, and in cybersecurity in finding hidden relationships online to root out unscrupulous activity. With ‘deep fake’ content expected to explode in the coming years the ability to hash out ‘good’ data from bad will be in high demand.
Market Use of Smart Basket Tokens
In addition to utilizing their platform, Data Elf will help in marketing VectorSpace technology to its growing community of data science developers. This will include marketing their NLP/NLU technology to developers and financial institutions, as well as their crypto token (VXV) to cryptocurrency traders, and potential investors.
How to Acquire VXV Tokens for Research
https://medium.com/@492727ZED/vectorspace-ai-vxv-customer-on-boarding-instructions-61aff13b66a9
Current Quote on VXV Token:
https://www.coingecko.com/en/coins/vectorspace-ai
Thomas Bustamante, the Founder & CEO of AI VentureTech, Inc. commented, “We are very excited to be collaborating with VectorSpace AI in utilizing their platform to develop new machine learning applications. VectorSpace Natural Language Processing/Understanding (NLP/NLU) can enable pathways for generating new insights, hypotheses or discoveries, which could prove very beneficial for such industries like finance, and biomedical research.”
To request an investor packet on this project please register to our AI investor network at https://aiventuretech.com/investors/
About VectorSpace AI
Founded 2018 in San Francisco California and headquartered in Valleta, Malta, the team consists of scientific and technical founders with a well-known track record in Silicon Valley. Vectorspace AI maintains a deep understanding of the financial markets having developed algorithms for quantitative information arbitrage opportunities along with running public companies as well as advising hedge funds. Vectorspace AI holds a number of patents in the area of context-controlled Natural Language Processing (NLP) in collaboration with Lawrence Berkeley National Laboratory along with academics that have contributed to leading Google’s AI efforts. The platform has been registered by 300 enterprise customers that include Machine Learning (ML) companies, hedge funds, trading desks, asset management companies, technology partners and data vendors. All customers consume Vectorspace AI’s alternative dataset building and ‘feature engineering’ platform which provides on-demand datasets and features for NLP, ML and AI operations. www.vectorspace.ai
About AI VentureTech
Located in New York City, AI VentureTech, Inc. is a data science research lab focused on providing technology solutions in the areas of biomedical, robotics, and cloud application development. Our team of data scientists and engineers can customize AI-powered software and technical solutions for both companies and institutions looking to leverage data and machine learning algorithms for greater business value. The Company seeks growth through both collaboration and acquisition of dynamic new start-ups in the areas of business analytics, machine learning, natural language processing (NLP), visualization tools, predictive modeling, and cloud advanced analysis. We also leverage our expertise and extensive network of professionals specializing in all disciplines required to build a successful company including legal, finance, marketing, operations, business development and HR. www.aiventuretech.com
Data Elf Facebook Group: https://m.facebook.com/groups/523900388341864/
Share Your Comments Below
https://dataelf.com/vectorspace-01228/
VXV+Elastic (ESTC) Generating and visualizing alpha with Vectorspace AI datasets and Canvas https://www.elastic.co/blog/generating-and-visualizing-alpha-with-vectorspace-ai-datasets-and-canvas
Articles on VXV including how to acquire and trade it https://medium.com/@492727ZED
3 AI + Crypto companies, VXV described
Followers
|
0
|
Posters
|
|
Posts (Today)
|
0
|
Posts (Total)
|
15
|
Created
|
12/27/19
|
Type
|
Free
|
Moderators |
About Vectorspace AI
=================
Name: Vectorspace AI
Symbol: VXV
Site: https://vectorspace.ai
Team background, experience and track record:
We’re a team with a deep background in science, technology and the financial markets.
We're veteran software engineers, scientific and technical founders. We work in the area of specialized algorithms in ML/AI for Life Sciences and the financial markets.
Here are a few references that might help during any due diligence process on Vectorspace AI:
- We've done an AMA on AI in reddit.com/r/AskScience with 16M subscribers: https://www.reddit.com/r/askscience/comments/9k5i8u/askscience_ama_series_were_team_vectorspace_ai/
- We've been in the AI industry since 1994 at Genentech executing on pattern recognition algorithms. Before that, we built search engines which have their roots in AI. Ref: "Overlooked No More: Karen Sparck Jones, Who Established the Basis for Search Engines" https://www.nytimes.com/2019/01/02/obituaries/karen-sparck-jones-overlooked.html "Ideas she wrote about are now being put into practice as artificial intelligence research becomes more prevalent."
- In the bioinformatics industry, we invented new systems and patented commercial products that assisted in finding hidden connections between human genes right after the human genome was sequenced. This involved pattern recognition and prediction (a pillar of AI/ML). This was when the term 'Data Science' did not exist when we everyone called it 'Data Mining' and 'Knowledge Discovery' aka AI.
- In the bioinformatics industry, our group worked with Rob Tibshirani and Trevor Hastie, both top level figures in statistics, data mining (AI):
https://en.wikipedia.org/wiki/Robert_Tibshirani
https://en.wikipedia.org/wiki/Trevor_Hastie
- Based on our work, we were invited to Lawrence Berkeley National Laboratory/DOE/DOD to work on 'special' projects 10-20 years ahead of their time related to developing systems to find hidden connections between genes that extended human lifespan and chromosomal damage related to LET Radiation (space radiation) for the purpose of space bioscience and extended space travel related future population of habitable planets. We continue work in the area with Mina Bissell, Life Sciences division director at Lawrence Berkeley Lab for 14 years and distinguished scientist: https://youtu.be/xukDIWFMU9Y
- While at the Lab, we had the privilege of collaborating with Michael I. Jordan (teacher of Andrew Ng who built Google's AI foundation which all others sit on top of today) and David Blei, 'grandfather' of LDA (topic modeling, AI related to predicting topics in human language) Ref: Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span - Blei DM, Franks K, Jordan MI, Mian IS. - http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1533868 - Min: 1:01:51 https://www.youtube.com/watch?v=28TefyYoAm4&t=3711s
In the past, we’ve raised capital for more than one startup including $7.4M for our largest startup with 50M MAUs and 250M searches per month along with successfully disrupting the music market related to Apple, Warner and EMI based on our work above and described here:
https://medium.com/startup-frontier/steve-jobs-made-warner-music-sue-my-startup-9a81c5a21d68
More on our work:
'Word2Vec is based on an approach from Lawrence Berkeley National Lab'
https://www.kaggle.com/c/word2vec-nlp-tutorial/discussion/12349
Products:
The easiest way to understand what Vectorspace AI does would be jump right into it by observing a real life event that resulted in an opportunity to profit based on our NLP/NLU real-time datasets and connected to what's called 'information arbitrage'.
Our platform, which includes datasets and products that can built on top of them, enable known and hidden relationship detection in data. Our datasets can be used to cluster entities that have known and hidden relationships to outside events, global trends or news. These clusters can represent networks of suppliers, companies working on similar drugs or any entity that might have symbiotic, parasitic or sympthetic latent entanglement with another entity, event or global trend.
Examples and case studies are located here:
https://vectorspace.ai/examples
Create your visualization from one of our datasets:
http://vectorspace.ai/vis/relationship-network
Real-time heatmap clustering:
https://vectorspace.ai/vis/heatmap/stocks-by-drugs.html
Hidden relationship network clustering:
https://vectorspace.ai/vis/clusters/v2/
More details on our products:
https://vectorspace.ai/vis/heatmap/
An example of how our customers make money with our product, an equity-based case study of the Celgene (CELG) acquisition:
https://vectorspace.ai/assets/Vectorspace-NLP-Dataset-Use-Cases-v03.1.pdf
Revenue model:
VXV Revenue model (with mathematical proof), slide 14:
https://vectorspace.ai/assets/VXV_Deck_External.pdf
( Revenue calculation breakdown: https://vectorspace.ai/assets/the-math.txt )
The VXV utility token network diagram is described in detail here, slide 11:
https://vectorspace.ai/assets/VXV_Deck_External.pdf
The value of the Vectorspace VXV utility token:
What is the network worth?
- Billions. This is because we are a data company with a focus on revenue generating customers which are trillion dollar asset management companies, funds and other financial institutions. Our job is to help them make money by providing them with an edge. This happens based on our product, NLP/NLU on-demand datasets that are updated every minute and based on any data they choose. Our revenue model, described, includes related details.
- You'll also find our token transaction network diagram in that deck which illustrates how our VXV token is utilized. This includes transacting dataset updates along with our Data Pipeline Provenance (DPP) hash which controls data lineage (aka provenance). Knowing where your data comes from and knowing how reliable it is, is extremely important to financial institutions that rely on it to make billion-dollar decisions everyday. We give financial institutions an edge that to them, is worth billions.
Why is the token valuable?
- Value created by our community which includes the core team, the outside team and contributing members of our global community, translates directly into the value of the VXV utility token and as a global public trading vehicle.
- VXV utility tokens do not function like a security or currency and share only minor similarities with e.g. Google Cloud credits, AWS credits or WeWork utility credits due to VXV doubling as a public trading vehicle in a global public marketplace.
- Our top-tier proprietary datasets and algorithms deployed in the financial markets that enable asset management groups, hedge funds and institutions to generate and capture alpha, can only be used by a limited number of customers. In this business, it's a common requirement from our top-tier customers to prevent saturating the market. It's like giving everybody the exact same weapons. This means the value of VXV is controlled by our customers, who will also be taking long term positions in VXV. It only makes sense and it's out of our control.
- In order to serve our customers properly, we've carved out a public marketplace which allows them to acquire blocks of VXV and out-bid other customers if they'd like to 'corner the market' on particular proprietary datasets. This happens when they sign-up for top-tier services and pay for them by acquiring and bidding for VXV on the open market. Once acquired, their wallet address can be used inside the VXV network to access top-tier services based on the VXV wallet-enabled API key. These services also include tracking of data lineage via the Data Provenance Pipeline (DPP) hash.
- The VXV utility token credit also doubles as a global public trading vehicle available to be transacted, acquired, bought and sold between anyone, including speculators, in the global public crypto markets via the ProBit exchange and soon to be, one or two other larger exchanges. This means a farmer in Kenya or a villager in Borneo can acquire VXV to access a dataset one minute and resell VXV to a trillion dollar asset management company the next minute in exchange for "JPM coin" for example. This is completely out of our control.
- We have plans on enabling machines (data engineering pipelines onsite at customer locations) to transact VXV with one another for the purpose of 'minimizing loss' which is at the core of effective ML/AI.
- In the case of an M&A event or strategic investment by one of our customers, or outside companies or investors, the VXV utility token will be the most valuable asset they acquire related to this company based on the above. This is if we allow any M&A in the first place of course. This is how we've financially engineered, structured and positioned Vectorspace AI.
Reddit:
https://www.reddit.com/r/VectorspaceAI/
Telegram:
https://t.me/joinchat/GrCYjA8rPgD8coAiEhRuBA
ERC20 etherscan and contract address:
https://etherscan.io/token/0x7D29A64504629172a429e64183D6673b9dAcbFCe
How to acquire & trade VXV on exchanges:
https://medium.com/@492727ZED/vectorspace-ai-vxv-customer-on-boarding-instructions-61aff13b66a9
Chinese: https://vectorspace.ai/assets/VXV-IDEX-on-boarding-CH.pdf
Partners & Collaborators:
WorldQuant
https://www.worldquant.com/home/
Elastic (ESTC)
https://finance.yahoo.com/quote/ESTC?p=ESTC
Lawrence Berkeley National Laboratory
National Library of Medicine (NLM)
https://www.nlm.nih.gov/pubmed
The European Molecular Biology Laboratory (EMBL)
Selected Patents, Papers & Awards:
Articles authored by the founders:
Winner R&D100 Award - Lawrence Berkeley National Laboratory
http://newscenter.lbl.gov/news-releases/2008/07/09/berkeley-lab-wins-four-2008-rd-100-awards
System and method for generating a relationship network - K Franks, CA Myers, RM Podowski - US Patent 7,987,191, 2011
http://www.google.com/patents/US798719
Inter-term relevance analysis for large libraries
https://patents.google.com/patent/US20030204496A1/en
Matching and recommending relevant videos and media to individual search engine results
https://patents.google.com/patent/US8037051B2/en
Media discovery and playlist generation
https://patents.google.com/patent/US8117185B2/
System and method for summarizing search results
https://patents.google.com/patent/US20080154886A1/en
Discovering and scoring relationships extracted from human generated lists
https://patents.google.com/patent/US8108417B2/en
Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span - Blei DM, Franks K, Jordan MI, Mian IS.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1533868
A Search Engine that Thinks, Almost
https://newscenter.lbl.gov/2005/03/31/a-search-engine-that-thinks-almost
Upcoming news and announcements: Coming soon!
Volume | |
Day Range: | |
Bid Price | |
Ask Price | |
Last Trade Time: |