The investment opportunity of Vectorspace A.I.
Updated: Aug 11
This blog is an overview covering factors that exist beyond the current market speculation that is primarily dictating the price action of the VXV token, as of the time of writing.
Vectorspace A.I. is a data orientated technology company that is situated in the field of space-bioscience, producing datasets that can be used to provide insight into different variables using machine learning techniques i.e. natural language understanding and natural language processing. These datasets are secured and powered using the VXV token. The usage of these datasets are not limited to just companies in the space bioscience industry but also those in the financial sector such as hedge funds and financial institutions.
Under current market conditions the VXV token is primarily a trading vehicle to carry speculative value amongst retail investors, however that value is just simply that. Speculative.
As the cryptocurrency market evolves from the stages of adolescence to maturity, cryptocurrencies with staying power will maintain intrinsic value that can not be denied by anyone, regardless of bias.
Before we begin I would like to share this quote that I believe epitomises why VXV is a great long-term investment and Vectorspace A.I. is a great company with good values.
"We have an ongoing relationship with the U.S. SEC and DOJ based on running a public company and defeating a $40B suit from Apple, Warner, EMI - this has equipped us with a few good law firms that work inside the SEC/DOJ and a good sense of what it means to operate a public trading vehicle. As a company in the crypto space where there is little to zero regulation, we operate by the spirit of U.S SEC regulation and U.S. securities law which includes the primary mandate of protecting mom and pop investors."- Kasian Franks, CEO of Vectorspace A.I.
The Lindy Effect
Firstly I would like to begin with the lindy effect, a theorised observation concerning non perishable items such as information or technology. The older something is, the greater the staying power it possesses and in turn the likelier it is to be around in the future. An example of the lindy effect would be world religions. Hinduism and Judaism are around four thousand years old, Christianity is around two thousand years old, and Islam is around 1500 years old. As each religion increased in age, so did the number of followers and believers, in turn whole cultures and societies were shaped around these religions, in turn further increasing their staying power. However there have been hundreds of religions that have died down in popularity such as the polythetic (many gods) religions of ancient Egypt, Greece, Rome and Scandinavia.
(The ancient pyramids have survived for thousands of years, based on the lindy effect it would suggest out of everything in Egypt, this is the thing that will live the longest, regardless of what get's created in the modern age.)
We can also observe the Lindy effect in relation to technology and media as well as art. Telecommunication devices such as the telephone have undergone innovations since it's conception in the 1800s; but the original concept of remote communication continues to live on. The automotive industry was conceived in the late 1890's and has now been a staple in modern society for the last hundred years later. Mediums of art such as music and books are persistently transcending generations in spite of being created decades and even centuries prior to the modern day reader and listener. An example of this is classical music produced by Mozart and Beethoven as well as Theological and philosophical literature produced by monks in the early 13th century i.e. Thomas Aquinas.
Currently the cryptocurrency market is in the midst of showing it's staying power to large institutions and banks who are looking to see if it is a valid long term investment. Cryptocurrencies such as Bitcoin and Ethereum have survived and continued to maintain a relatively high trading value/market cap over prolonged periods of time. With each year value is sustained, the likelier it is these cryptocurrencies will stay and be maintained.
There are 2 main factors as to why these non perishable items continue to thrive:
- They are capable of adapting to a wide number of use cases.
- They maintain a low hazard rate.
The hazard rate:
This is the belief that over time the threat to a non perishable item or concept diminishes to a lesser extent than its modern day counterpart. For example, if a book is listed on the New York Time's Best Seller list, and survives it's debut week by maintaining it's listing, it has a lower hazard rate than a new book that later enters the rankings. This does not mean it will never die in popularity, but it's chances of doing so is now less than that of a new debutant. To summarise, the lower the hazard rate the better. The higher the hazard rate, the worse.
To see how the Lindy Effect applies to VXV's current standing in the cryptocurrency market, we have to determine what constitutes a high hazard rate for cryptocurrencies in general. This is subjective as there's not a definitive standard to measure a cryptocurrencies likely hood of survival (If there was we'd all be rich), so I will outline four conditions that I personally believe will be good indicators for a high hazard rate:
1. Young Age:
The younger the project, the higher the hazard rate. This is because new projects tend to go through abnormal price action (market manipulation), and have likely not developed an ecosystem strong enough to maintain a strong price level. Furthermore, the younger the project we can assume the less time the founding members have been committed to working on it, so most young projects tend to be susceptible to un-loyal team members who leave to do their own project which makes it harder for them to develop. Finally, most young projects tend to differ from the direction and goals of their whitepaper later on in their development due to the inability to foresee problems, or the realisation the project itself is not appropriately equipped to scale or solve the problem they promised. Therefore, the longer a project stays true to it's original whitepaper and goal, and the longer it has existed with key founding members, the better.
2. Low Accessibility:
The less accessible a token is for investors or institutions to buy on the open market, the less likely that token will be able grow in relation to it's market cap and therefore the less likely it is to retain a large value over time. Therefore the less accessible a token is, the higher the hazard rate. High accessibility increases the likely hood of the token being utilised and is healthy for an ecosystem to consistently capture value.
3. Niche Target Audience:
The less companies a project caters to, the less chance for it to be adopted, thus higher the hazard rate. Projects with niche target audiences tend to be of relatively low value because unless they are catering to extremely valuable clients, they won't generate enough revenue to keep developing their ecosystem. It can be further reasoned that unless the competition is significantly weak, they must in turn capture a large percentage of the market to gain the necessary revenue to survive and grow as well as have a low error rate as the margin of success is now very slim.
4. Low Disruptiveness:
Disruptiveness in relation to innovation refers to technologies that significantly alter the way an industry or consumers produce or perceive a product or industry. It does not conform to the standards of the market, but rather exceeds them and set it's own standards. The less disruptive the technology or innovation the higher the hazard rate, this is because over the long term these technologies will continue to lose value in relation to the competition in the market as the number of competitors increases. Examples of disruptive innovations in the modern day include streaming platforms in the entertainment industry such as Netflix and HBO. Another is the invention of distrusted ledger technologies such as Bitcoin which are revolutionising the way value and data is transferred. Online search engines such as google utilise the world wide web to gather and assort information instantaneously and changed the way we are able to extract information.
How does VXV fair against the Lindy Effect?
Vectorspace A.I. was founded in January 2016, though a relatively young company, members of the team have been working in the A.I. Industry for multiple decades such as CEO Kasian franks whom since 1994 at Genentech was building search engines that were rooted with A.I; encompassing the ideas of Karen Sparck Jones.
“[The] Ideas she wrote about are now being put into practice as artificial intelligence research becomes more prevalent.”
The VXV token was created in 2018. Co-founder of Vectorspace A.I. Kasian Franks, has been working at the company since it's conception, and provides weekly voice conferences (dating back to January 2020) that are to be utilised as an updated roadmap expressing the company's progress and goals. These weekly voice conferences are clear indicators that the team has not deviated from it's goals.
Currently as of the time of writing this blog, the VXV token is listed on exchanges such as Coinmetro and LCX. ( check out my other blog to learn more about LCX here.) Both exchanges have put a strong emphasis on maintaining high regulatory compliance. Being listed on such exchanges ensures that accessibility remains relatively high in the future. The VXV token also trades openly on Uniswap- a decentralised exchange.
With many of the core founding members remaining with the company, the team continues to expand with their most recent addition being to their scientific advisory board.
Dr Mina J Bissell , the director of life science at Berkeley Labs, who garners a profound resume (here's a link- VERY MUCH WORTH THE READ) joined the Vectorspace scientific advisory board in June 2021 and will be with the company to advise on potential partnerships with other companies in the space bioscience industry such as Blue Origin, Space X, Virgin Galactic, NASA and others in regards to DNA sequencing and repair etc. (PR Newswire. article)
Vectorspace and Dr Mina J Bissell are fairly familiar with each other, with the team having been invited to Lawrence Berkeley National Lab 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..."
Being able to maintain and expand on the team and advisory board ensures that the company is able to sustainably maintain the project for the foreseeable future. Adding to their scientific advisory board, people with multiple decades of high level experience and knowledge in the field of bioscience, adds maturity to the company as they will be now prone to making less mistakes as they will have greater foresight of future events.
Vectorspace A.I. has achieved noticeable achievements partnering with a diverse set of companies in various industries.
In July 2020, LCX and Vectorspace announced a partnership to develop "event driven smart basket technologies." Smart baskets are datasets algorithmically generated based on news events, and can be used by investors who want to look into different themes.
Earlier that year in March 2020, Vectorspace A.I. announced a collaboration with industry giants, Amazon and Microsoft in connection with the United States Office of Science and Technology and Policy (OSTP), making available for free real time COVID-19 drug repurposing (adaptable) datasets.
Data was extracted in context from academic literature published in the National Library of Medicine, and other databases, to look for the hidden relationship between genes, proteins, drug compounds for infectious diseases such as COVID-19.
A quote from CEO of Vectorspace, Kasian Franks on making the datasets available:
"Our team and community are eager to join the fight against SARS-CoV-2 and any future viral threats by offering free subscriptions and VXV token credits granting free access to our wallet-enabled APIs which generate these kinds of datasets,"- Kasian Franks.
In September 2020, a PR Newswire Article was released citing that Vectorspace A.I. and CERN (European council for Nuclear Research) were creating datasets to:
"Detect hidden relationships between particles which have broad implications across multiple industries. These datasets can provide a significant increase in precision, accuracy, signal or alpha and for any company in any industry."
Attracting conglomerates such as CERN institute as partners perhaps should not come as a surprise as it is a testament to the prolonged time spent in the industry Kasian and other members of the team have worked most of their lives in.
"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 everyone called it ‘Data Mining’ and ‘Knowledge Discovery’ aka AI."
It is quotes such as this that it should be without doubt that the VXV token exudes staying power. Vectorspace A.I. continue to illustrate that there is a large iteration of companies that they are able to reach out to with their datasets. Working with CERN as well as being able to offer datasets in collaboration with Microsoft and Amazon to governmental agencies such as the United States OSTP clearly shows they're not working in a niche market as most of these companies do not interact with each other unless inadvertently through mutual partnerships. Their product (datasets) is something that caters to a lot of companies in different industries. In regards to disruptiveness, I believe the last quote highlights an important contrast between companies that have long term staying power and those that fade into the distance. Being able to innovate is great in it's own right, but being able to patent your own inventions not only limits competition, but increases the demand for your own products. The datasets and the VXV token incorporate the patented technology that the Vectorspace team have worked on throughout the last twenty years.
Tokenomics relates to factors revolving around the token supply of a cryptocurrency. In relation to Vectorspace A.I., 50 million VXV tokens were created based on (not to replace) the number of shares the company had.
In the cryptocurrency market, tokens will primarily garner value based on the supply to demand ratio. The ideal ratio is to have a low supply and high demand, however if there is not enough supply to sustain the ecosystem then the demand can not sustainably increase and will plateau or suffer a sharp decrease. This is why many tokens will be divisible into 18 decimals and will build an ecosystem that may require only a fraction of the token to be utilised.
Cryptocurrencies are assorted based on market cap. This is the circulating supply (not the total) multiplied against the current price. This metric should primarily be used to determine a cryptocurrencies market dominance. The higher the market cap, the more value within that market it can be said to have captured. The most dominant cryptocurrency on the market currently as of the time of writing is bitcoin because it currently has the largest market cap of all cryptocurrencies. Therefore when we are looking at an asset to increase in market cap, we are really saying we want it to become more dominant in the market i.e. capture more value. If a token has a low supply it will naturally have a low market cap in comparison to tokens with a larger supply as more value has to be captured to keep pace. However, because the supply of tokens are fixed for most networks, the price will have to increase to raise the market cap, and it is from this, great investment opportunities are created.
If a token can reach a very high price but still maintain a reasonable market cap, then the cheaper you are able to accumulate said token, the better.
The question that can now be posed is... how do I as a retail investor know whether the VXV token is undervalued and has a lot of room for price appreciation?
We can compare the VXV token supply and price (Currently as of the time of writing this blog) to other A.I. related tokens on the market. Side note these figures have been rounded in some aspects so they're are not completely accurate.
Fetch A.I. Token Supply : 1.1 Billion (£0.30p = 218 million market cap)
Singularity Net Token Supply: 1.0 Billion (£0.15 = 133 million market cap)
Ocean Protocol Token Supply: 600 million (£0.38 = 235 million market cap)
Numeraire Token Supply: 11.0 million (£27.00 = 150 million market cap)
Prometeus Token Supply: 19.25 million (£8.88 = 146 million market cap)
Judging by these five cryptocurrencies we can see that the 50 million supply of VXV token's is relatively low in comparison as well as it's market cap of £105 million. In just relation to other A.I. projects in the space, the VXV token has a lot of room to grow and become more market dominant.
Let's go one step further.
In relation to A.I. related companies that are outside of the cryptocurrency space, there exists companies such as Nvidia (£350 billion market cap); Palantir (£28 billion market cap); Alphabet (£1.3 trillion market cap) and SAS (£10.7 billion market cap).
VXV is grossly undervalued in comparison. Vectorspace A.I. does not see their competitors as those within the cryptocurrency market but those residing outside. It is here that we can see that the price of the VXV token has an incredible room for growth in the long term.
"This is great but what's going to cause the price to go up???"
There are two main factors that will cause the price of the VXV token to increase, and neither rely on retail demand. Institutional companies including clients and investors, and Vectorspace A.I themselves.
Vectorspace A.I. have available 100 billion datasets. These datasets are all valued differently, some could be worth millions others could be worth just a few hundred. However fees are required to be paid for certain features to create and maintain these datasets, which can be paid using the VXV token or in fiat which will be converted into VXV tokens via the open market.
Each data source used to help create these datasets will cost $0.99 cents. However there can be a maximum of 100 data source used, or a minimum of just 2.
Per Row of data used to construct the dataset it will cost $0.99 cents. However the maximum amount of rows that can be used is 1000, and the minimum 1.
Per Column of data used to construct the dataset it will cost $0.99 cents. A maximum amount of columns that can be used is 1000, and the minimum is 0.
Each dataset can be updated with new pieces of information. However per update of information it will cost $0.99 cents. There is no maximum limit of updates, however there is a minimum required which is dependent on the type of use of the datasets. Institutions in industries that rely upon real time data will be required to purchase a minimum of 100 updates. Academic institutions such as universities will be required to just purchase a minimum update of 1. These updates are all per month.
"We offer a one-month trial and to access a trial we say that you’ll need to acquire a minimum of 100 VXV utility tokens and keep in mind this is just the trial. They are provided a link to our CoinMarketCap entry and it continues: the VXV utility token is an ERC-20 token used to ensure that every change to your dataset, including each correlation score, is hashed via blockchain to provide a maximum level of dataset provenance, lineage, governance and security. The trial API uses a VXV wallet address as the API key. The VXV wallet address must have a minimum of 100 VXV utility tokens to access datasets specific to your trial."- Kasian Franks
Financial Institutions and academic companies that utilise these datasets will be required to pay fees, as well as hold VXV. As the fees will be converted into VXV this means that the circulating supply for the VXV token will decrease and therefore, as the demand to utilise these datasets increases, people will have to pay more to obtain the VXV token from the open market. This will create a price floor on the open market for the VXV tokens in the future, meaning the value of these tokens will remain consistently high.
It is in turn, in the interest of these institutions to accumulate large amounts of the VXV token whilst it is cheap, else it will cost them more in the future.
Vectorspace A.I have also stated that they will initiate buy backs (undisclosed) in regular intervals using the revenue generated from the sales of datasets and fees, to purchase the VXV token from the open markets. They plan is to initially utilise 50% of the revenue generated from the sales of datasets to purchase tokens from the open market and subsequently reduce the percentage of revenue in later years. This in turn also will create a price floor in the long term throughout bear markets, in which the price of VXV token does not undergo crashes as the scarcity of the token will drive up demand and in turn also price.
"Yep, we'll be acquiring as much as we can via buybacks. Anyone that does not like it can out bid us."- Kasian Franks
Space and Bioscience Industry
In July 2020, the global space economy was reported to be worth $420 billion. Morgan Stanley stated in the same month that the potential revenue for the global space industry could reach $1 trillion by the year 2040.
To understand why there is such a large projected value, we have to understand what made it important in the first place and where it's future value will be derived.
Space exploration originated from the fallout of World War II, in which the United States and the Soviet Union created their own missile programs. In 1957 the Soviet Union launched Sputnik 1 (first artificial satellite) into space. Four Years later in 1961 Yuri Gagarin became the first astronaut. On July 20th 1969 Neil Armstrong became the first human to set foot on the moon. In 1971 Salyut 1 became the first international space station to be launched from earth. The 1980's saw the rapid expansion of satellite communications across the world in which the average citizen was able to receive a satellite signal to their television antennas.
The space industry therefore can be said to have been conceived on a technological rivalry. The outrageous achievements made in the industry since 1969 provided a common goal for the future of humanity i.e. to explore space as well as causing many people to think about ways to ensure the survival of the human race. Through these notions different sectors of the space industry have been formulated and in turn providing potential avenues for revenue.
One such profitable avenue is in the mining of asteroids. Statista have a list of estimated values and profits of mining certain asteroids. On the list, the asteroid Anteros was valued at 5.5 trillion dollars with a profitable revenue of over 1.2 trillion dollars.
Harvard research affiliate Andy Greenspon, explained in a 2016 blog that some natural resources on Earth could be depleted in 30 years due to the need for the construction of computers and phones and other advanced technologies. He cites that neighbouring asteroid belts between Mars and Jupiter contain millions of rocks comprised of important metals such as Iron; nickel and cobalt as well as others such as platinum. He reasoned there would be asteroids worth trillions in value.
In the future data attaining to the cost of space excavation and equipment will be required to be funnelled into datasets that will discern which missions are profitable and which ones are detrimental to a countries economy. Datasets that can convey the difference between the two will be worth millions as countries will compete for long term supplies of natural resources.
Forbes in 2017 published an article explaining why Space Data is becoming mostly sort after:
"New uses for “space data” are opening up across many industries. In farming, satellite data can be used to monitor factors which influence crop yield. In real estate, areas prone to flooding or sinkholes can be more accurately identified, impacting property developments and prices. In retail, foot traffic around shopping centres can be monitored in real-time, giving an increased overview of how customers behave."
Anita Kirkovska wrote an article dissecting the importance of data analysis in the space industry for exploration and other avenues. In this article she explains that Data correlation and fast processing is critical to gain insight for critical space missions and will lead to greater rates of scientific discovery. She cities the Square Kilometre Array (SKA) project as an example of the demand for big Space Data. The SKA project is an international project in which many engineers and scientists are working together to build the world's largest radio telescope.
"From challenging Einstein’s seminal theory of relativity to the limits, looking at how the very first stars and galaxies formed just after the big bang, in a way never before observed in any detail, helping scientists understand the nature of a mysterious force known as dark energy, the discovery of which gained the Nobel Prize for physics, through to understanding the vast magnetic fields which permeate the cosmos, and, one of the greatest mysteries known to humankind…are we alone in the Universe, the SKA will truly be at the forefront of scientific research."- SKA project
(The cost of the project was estimated to be around 1.9 billion euros)
Space institutions such as the NASA and Jet Propulsion Laboratory (JPL) have utilised two applications from Elasticsearch- an open search analytic solution that aims to provide real time data analysis. It is worth mentioning that Vectorspace A.I. is collaborating with Elastic to provide consumers with near real-time data visualisation and interpretation.
Another need for datasets in the space industry is DNA analysis. In 2015 a study took place in which American astronaut Scott Kelly went to space for a year on a mission to the international space station, and his twin Mark remained on earth. When Scott came back to earth his blood was analysed as well as his physiology and behaviour. Christopher Mason, a geneticist and a team of NASA scientist, noted that there was a variety of changes:
Weight loss, lengthening of chromosomes, retina and carotid artery thickening, gut microbe shifts and more.
"Gene expression changed dramatically. In the last six months of the mission, there were six times more changes in gene expression than in the first half of the mission."- Christopher Mason.
In 2016 NASA astronaut Kate Rubin performed DNA sequencing of living organisms in space. This was a game changer in which illnesses and microorganisms could be diagnosed. The data garnered from this could allow for the identification of DNA based life forms on other planets. Datasets that could be created from this will also be of extreme value and importance for the future of space exploration.
"Azure Space will be storing datasets related space biosciences and the protection of human DNA during space exploration. We are providing these datasets. They help detect hidden relationships between genes, DNA repair genes included, proteins, plant compounds, drug compounds."- Kasian Franks
Developments such as these showcase that the space industry is indeed in demand for tools that will create datasets to help analyse data that will be important to the future of humanity. Vectorspace A.I. is working in a field that will not disappear over time but will continue to grow and invigorate public interest.
"We have been in space biosciences from the beginning. It's where we got started and continue to advise to this day. Datasets that enable new hypotheses and discoveries related to protecting and repairing human DNA and tissue while in space is the next frontier. It's going to be one of the most important and well-funded efforts in human history. Discoveries in space biosciences will benefit all industries with immediate benefits to nanotechnology and nanomedicine, a branch of personalized and precision medicine."- Kasian Franks
It's not just Vectorspace who've taken an interest in the space industry; blockchain companies have already begun entering into the space industry. In 2012, Hollywood director James Cameron and Google Co-Founder Larry Page invested into a company known as planetary resources inc, that aimed to launch satellites into space and eventually work on asteroid mining. However in 2018 the company failed to secure funding and were a year later bought by parent company ConsenSys, a blockchain technology company with very deep ties into the crypto industry with projects such as Hyperledger. They are currently opening up the patents of planetary resource for open usage to help companies in the space community.
"Hedge funds’ use of AI is accelerating and reshaping the industry, particularly in investing, cost models and recruitment." - Peter Salvage, Managing Director at BNY Mellon in 2019.
Institutional Investor published an article in August 2020 reporting that hedge funds utilising artificial intelligence had a huge competitive advantage over those that didn't.
Forbes published an article earlier that year also depicting the rapid and large increase in financial investments made in machine learning since 2017, in which the market was estimated to be $1.5 billion at the time. Tractica projects revenue from the market to be in 2025 around $100 billion globally.
Machine learning seems like the logical progression for hedge funds and institutions looking to increase their income. Naturally as retail investors we aren't able to conceptualise the financial impact that the development of machine learning algorithms have had on markets.
You're probably thinking:
1. Sure they are able to generate more money but is it that much more than they were already making?
2. Has it made it any easier than what they were doing in the past?
3. Are these hedge funds investing anything substantial that should cause me, a retail investor, to take notice?
The answer is a resounding yes to all three questions.
To give context as to the degree of difficulty and risk investors have been facing investing in their respective market of choice for the last one hundred years. In 1975 John Bogle started the first index fund. Index funds make it easier for investors to diversify their portfolio and minimise risk. It is an amalgamation of select companies in which the success of the investment is dependent upon the average of companies in the list rather than individuals. The average annual return for an investment in the S&P 500 (a specific index of the top 500 publicly traded companies on the market) is 10-11%.
This average return creates a baseline in which allows us to see if an investment has underperformed or overperformed.
Over the past 20 years, only an average of 1.5% of hedge funds outperformed the market.
For fun, (mainly because I have too much free time on my hands) to conceptualise how bad hedge funds have underperformed in the last ten years against the S&P 500, I will show you the final value of a $1000 investment using these figures. The $1000 investment based on the performance of the hedge funds over the last decade would be $1593.60 (A 59.3% increase after 10 years). However if it had just been left in the S&P500 then the $1000 investment would be worth $3646.97 (A 264.6% increase after 10 years).
Just to hammer this in, the difference between these two investments final value was 125%. If the hedge funds were to perform 3-4 times better (percentage wise) with their investment they would still come up short than someone who just did nothing and let the free markets decide.
In context to the first question an article published in Fortune looked into the performance of hedge funds which used A.I. to invest in the S&P 500. A hedge fund called Next Alpha (created by John Flowers) netted a 40% increased return between April 2019 and April 2020. During that same period the S&P 500 made a loss of 4.9%. However Next Alpha may be an exception rather than the general rule as a hedge fund called Eurekahedge A.I. only made a 6.3% return in the same period and was only up by 2% during 2020 as of the time the article was written.
This data gives us two important pieces of information. The first is not all A.I. are equal and will perform differently compared to each other. The second is that A.I. driven hedge funds can succeed in producing significantly better results than the S&P 500.
Question 2 can be answered by the thoughts John Flowers who spoke about the biggest A.I. pitfalls. He explains that the users of A.I. are their own biggest hurdle.
"They spend too much time thinking about the worst scenario they can remember, rather than the worst scenario that could possibly happen. As a result, they aren’t well prepared for black swan events—such as the 2008 financial crisis or the recent pandemic."
In a sense it is better to give the A.I. extreme random scenarios for it to test against and develop in a simulated environment. The wider the testing area the wider the scenarios it can cater for.
But are hedge funds investing serious money into the field of machine learning? IDC (international data corporation) suggested spending on Artificial intelligence is to reach $110 billion in 2024.
"Companies will adopt AI — not just because they can, but because they must."- Vice president of artificial intelligence at IDC, Ritu Jyoti.
At the end of June 2021, JP Morgan announced the launch of an A.I. driven climate fund. The fund will use natural language processing to pick stocks that are acting on climate change. It is reported to screen 13,000 companies and will narrow them down to 50-100.
But how does this all relate to Vectorspace A.I. and the VXV token?
Where some funds are utilising A.I. to generate returns of 40%, Vectorspace A.I. have produced datasets that have shown potential returns of over hundreds and in some cases thousands of percent increase in returns.
CRMTKA on twitter wrote a fascinating thread (he also has a plethora of other threads in relation to Vectorspace!) showcasing the power of Vectorspace A.I.'s datasets. Please give him a follow for more information on Vectorspace A.I.!
(click on the image for a link to the remainder of the thread!)
Vectorspace A.I. can generate over a 100 billion different datasets, whilst also giving people the option to create their own. By having a wide range of possible outcomes and access to these datasets via holding the VXV token, hedge funds and even banks will be able to look through previous events and even test out unusual scenarios. With real time data implemented available to be implemented into these datasets this provides an edge to users of the datasets as they'll be able to quickly adjust their trading strategy to sudden changes. At the heart of all of this is the VXV token.
" VXV represents the value of a given dataset. We offer over 100 billion different dataset designs and some will become very valuable. This means some individuals, groups and machines will bid on datasets using VXV as the trading vehicle. VXV operates in a public open marketplace which means everyone is a player, including ourselves, and can bid on datasets using VXV. Just like anyone else, we want the best possible price we can get for VXV because we value it as it's directly connected to the value of one of our algorithmically generated updating datasets."- Kasian Franks