Topic: Certain cryptos to experience significant upside due to the following news (Read 61 times)
July 10, 2018, 03:12:26 PM
I have been reading such news from quite a while now but we are here and still waiting for the institutional money and big volumes to come into the market which is obviously badly needed by the market in the current situation, i know market sentiment can quickly change but we need some action now i guess.
July 10, 2018, 01:10:13 PM
"In May, the Swiss bank UBS said it was moving 80 staff into a new artificial-intelligence division, dubbed the Strategic Development Lab, which is dedicated to defending its fixed-income trading turf against hungry fintech startups.
Later the same month Deutsche Börse, the German stock exchange, said it had earmarked €270m for investment in big data analysis, blockchain, robotics and AI.
Meanwhile, the City Corporation’s top envoy to the EU, Jeremy Browne, said late last month that he thinks AI will be more disruptive to UK financial firms than Brexit, in the long term.
Quant Insight and its backers are betting that banks and asset managers will also tap into new tech by buying in services like the one it offers. The analytics firm said it has grown customer numbers by 50% this year, and has added new staff to sell its services in Asia and the US.
It is also working with “major banks” on creating bespoke indexes and equity baskets — groups of stocks that share certain characteristics and are likely to move in a similar way in response to given macro events."
Full article: https://www.fnlondon.com/articles/alan-howard-backs-artificial-intelligence-data-venture-20180705
Alan Howard backs artificial intelligence data venture
Founders of Brevan Howard and Stone Milliner put their names behind Quant Insight, which uses machine learning for macro insights
European hedge fund managers Alan Howard and Jens-Peter Stein have put their money behind a startup firm promising to use artificial intelligence and machine learning to analyse macroeconomic events.
Quant Insight, founded in 2014 by a pair of former hedge fund portfolio managers, Mahmood Noorani and Krishnan Sadasivam, working with astrophysics professors at Cambridge, uses algorithms to crunch vast amounts of data.
Its analytics software aims to predict the effect of macroeconomic trends — such as currency moves or new government regulations — upon security prices.
Howard, the founder of $13bn macro hedge fund Brevan Howard Asset Management, is a user of Quant Insight’s service. He said it “helps untangle complex markets and identify what is driving asset prices. I can see many applications for Qi’s technology and am pleased to support them in their expansion”.
Jens-Peter Stein, the founder and co-chief investment officer of Stone Milliner Asset Management, a UK-Swiss macro fund running about $6bn, said: “With so much attention on alternative data sources, Qi focuses on better understanding the data we already have — the data that really matters for markets.”
Quant Insight declined to say how much it has raised in the cash call, which is its second, beyond describing it as a “multi-million dollar” fundraising. Eighty percent of the money came from users of the service, the company said.
The hedge fund financiers backing QI are far from the only City bigwigs putting cash behind AI and related fintech projects.
In May, the Swiss bank UBS said it was moving 80 staff into a new artificial-intelligence division, dubbed the Strategic Development Lab, which is dedicated to defending its fixed-income trading turf against hungry fintech startups.
Later the same month Deutsche Börse, the German stock exchange, said it had earmarked €270m for investment in big data analysis, blockchain, robotics and AI.
Meanwhile, the City Corporation’s top envoy to the EU, Jeremy Browne, said late last month that he thinks AI will be more disruptive to UK financial firms than Brexit, in the long term.
Quant Insight and its backers are betting that banks and asset managers will also tap into new tech by buying in services like the one it offers. The analytics firm said it has grown customer numbers by 50% this year, and has added new staff to sell its services in Asia and the US.
It is also working with “major banks” on creating bespoke indexes and equity baskets — groups of stocks that share certain characteristics and are likely to move in a similar way in response to given macro events.
Add to this “We believe that just as the last three megatrends — mobile, social, and cloud — intersected and reinforced each other, so will the next three megatrends — next-gen computing devices, AI, and crypto.” andreessen horowitz
Full article: https://medium.com/@lazslotatherton/three-artificial-intelligence-cryptos-ef1b4a88156d
When the internet first made it’s presence known to the masses in the mid 1990’s, the public was understandably skeptical. Sure, people understood intuitively that computers were going to change the world, but up until that point the average person was not interacting with, or being effected by them on a daily basis. Or at least so they thought. The reality is that computers and the proto-internet were already streamlining aspects of the military, government, and mercantilism starting by the 1960’s. But despite those early use cases, in the 1980’s the majority of us were still not using computers for work nor did the majority of us have them in our homes. At most we had a Texas Instruments calculator to balance the checkbook or a Commodore 64 you could use to play games on a monochromatic screen like The Oregon Trail or Lode Runner.
But gradually developments in personal computing allowed lay people to do more things with these mystery boxes composed of hydrocarbon plastics and filled with circuit boards and wires. Bulletin boards accessible via modems had strictly been the domain of “computer nerds” and those mysterious teenaged “hackers” that could effortlessly start WWIII as depicted in the film War Games. But when companies like AOL and Netscape made the worldwide web more easily accessible to the average consumer via their home telephone lines, the drawing of a new era with incalculable civilizational ramifications was unquestionably upon us. Of course, it didn’t look that way at the time. And to a large extent, it never really does except in hindsight. Even technologists and otherwise experts in the field cannot predict how and at what pace a technology will develop and create ripples of change throughout the world and in our day to day lives. At the time, that GeoCities Dave Matthews Band website wasn’t exactly setting the world on fire. What exactly did it do? What problems did it solve? How was it going to change the way we live? Well, it wasn’t. But early iterations of personal computing and the internet had enough of a hook to grab the public’s imagination and their desire to know more, to interact more, and to experience new things. And of course, there was money to be made. And that capital investment allowed these technologies to be further developed into whichever now nearly ubiquitous device you’re using right now to read these words.
In discussing the crypto space and blockchain, AI, VR, and next-gen computing, it’s often been a reiterated truism that we are in a stage analogous to those early dial-up days of the internet where future use-cases were unclear but adoption seemed like an inevitable outcome to all but the old and visionless who had lived their lives in an analog world and assumed it would therefore always be as such. The quote from a16zcrypto at the beginning of this article asserts that the trifecta of blockchain, AI, and quantum computing will work synergistically to create use-cases and applications that will change our lives in ways so potentially disruptive and liberating that we simply cannot conceive of them. As these technologies go forward, particularly in the case of machine learning and autonomous machine interaction, the telescopic and exponential growth curve in both applications and related markets is probably limitless. In fifteen years time our future selves will look back upon contemporary cryptocurrency exchanges and cloud computing in the same way our present selves experience a floppy disk drive. We will wonder how we ever managed without advanced robotics, artificial intelligence, virtual reality, and completely decentralized peer to peer mediums of exchange. Hopefully, we will also have availed ourselves to invest in these technologies and to be the ones that got in early on what everyone else will be using tomorrow. Below are three examples of companies that represent just such a future synthesis of blockchain and AI technology.
Matrix
Designed to be the new generation blockchain, MATRIX leverages the latest artificial intelligence technology to resolve the aforementioned challenges. The fusion of blockchain and AI technologies enables MATRIX to build a revolutionary cryptocurrency, which support significantly boosted transaction speed, superior accessibility to general users, enhanced security under malicious attacks, and highly flexible operations.
The challenges facing today’s blockchains have to be resolved before the ideal of cryptocurrency can really become reality. We believe the artificial intelligence technology, which has received an unprecedented growth in the past decade, provides out-of-box solutions to address the challenges. MATRIX is designed to be an intelligent chain to unleash the potential power of the blockchain technology. In this section, we briefly review the objectives of MATRIX.
Although smart contracts give blockchains the essential capability to handle scaled commercial behaviors, they need the users to be able to write programs in a given programming language. With MATRIX, no programming expertise is needed any more for designing smart contracts. The unique code generation technique of MATRIX allows automatic conversion of an abstract description of a smart contract into an executable program. Matrix only requires users to input the core elements (e.g., input, output, and transaction conditions) of a contract with a scripting language. Then a code generator based on a deep neural network is able to automatically convert the script into an equivalent program.
Smart contract programs may call functions offered by the host system and/or third-party libraries. Also, programs running on different computers in a distributed framework do not provide any guarantee for execution time. Such openness and decentralization are the reflection of the essential spirit of blockchains, but give birth to various sources of security threats. In fact, the lack of security is plaguing the smart contracts. The MATRIX blockchain is equipped with a power AI security engine consisting of four major components, 1) a rule- based semantic and syntactic analysis engine for smart contracts, 2) a formal verification toolkit to prove the security properties of smart contracts, 3) an AI-based detection engine for transaction model identification and security checking, and 4) a deep learning based platform for dynamic security verification and enhancement.
Today all public chains are suffering from the problem of long transaction latency and low transaction throughput. Specifically, it takes over 30 minutes for Bitcoin to finish one transaction, while the transaction throughput of Ethereum is only 10 Transfer Per Second (TPS). In fact, a blockchain depends on a P2P network to validate transactions. Since a transaction needs to be broadcasted to all nodes in a network, the overall latency has to increase as long as more nodes are joining the network. MATRIX resolves the problem by dynamically selecting a delegation network in which all nodes are voted as delegates of others. All Proof-of-Work (PoW) processing is only allocated inside the delegation network, which only incurs a much smaller latency due to the smaller number of nodes. The selection process is random in the sense that a node is selected with a probability proportional to its Proof-of-Stake (PoS). The online version of MATRIX will support a throughput of 100,000 TPS.
MATRIX is designed to be a highly flexible blockchain. The flexibility is twofold. First, MATRIX offers access control and routing services so as to allow seamless integration private chains into a common public chain. Such a feature meets the requirements many industry and government players for authorization, while at the same time allows necessary information flow from a public chain to a private one and vice versa. Second, MATRIX uses a reinforcement learning framework to optimize its parameters (e.g., consensus mechanism, and transaction configuration) in an evolutionary manner. The optimization paradigm ensures dynamic updating of parameters for near-optimal performance without the risk of incurring hardfork.
Perhaps the most criticized part of cryptocurrency is the “waste” of energy in the mining computations. Although it is essential to attach physical value to the cryptocurrency, the mining process does not make any sense out of the world of digital currency. The problem is even worse when now over 70% of the total computing power around of world is dedicated to mining Bitcoins and others. MATRIX introduces a new mining mechanism in which miners perform the Markov Chain Monte Carlo (MCMC) computation, which is an essential tool for Bayesian reasoning. MCMC based Bayesian computing plays a fundamental role in numerous big data applications such as gene regulatory network, clinical diagnosis, video analytics, and structural modeling. As a result, a distributed network of MCMC computing nodes provide the power for solving real-world compute-intensive problems and thus build a bridge between the values in the physical and virtual worlds.
Vectorspace
The Vectorspace AI [link]platform enables ‘Smart Basket’ (token baskets for traders, funds, ETFs) generation based on user-selected trends that exist in search, social media and news. Their ‘Smart Baskets’ are based on the ability for these baskets to determine for themselves whether or not to include additional cryptocurrencies or components from related baskets that may increase overall returns. Baskets that interact this way with one another will conduct these kinds of transactions between one another using the Vectorspace utility token VAI, which is also required to dynamically generate baskets.
Vectorspace is designed as a tool for discovery as well as a suite of sophisticated tools to help you increase your profits with other cryptocurrencies by reducing risk and maximizing your gains. Their focus is on “Advanced Natural Language Processing (NLP) & Sentiment Analysis for Smart Cryptocurrency Basket Trading” and they have live products any crypto trader can use today. Their site updates every few minutes powered by their algorithms.
[ Link to Smart Baskets ]
According to their whitepaper: “A growing number of organizations offer the ability to trade a basket or group of cryptocurrencies with a single transaction. Similar to a traditional ETF (Exchange-Traded Fund), “token baskets” as they’re more commonly called, enable a fund or individual investor to spread their risk, diversify and lower volatility while maximizing gains with more safety and stability. This approach is valuable but incomplete. For example, taking the top 20 best performing cryptocurrencies and placing them in a basket or fund minimizes gains compared to enabling fine-grained custom creation of token baskets. Which groups of cryptocurrencies are beating the market? Why? What do they have in common? How strong are those relationships? Are those relationships well known and obvious or are they hidden relationships? Are the relationships numerical or nonnumerical, based on concepts, context and sentiment, or a combination of both?”
These are the questions Crypto Discover is designed to answer. Vectorspace AI’s Crypto Discover platform is an advanced cryptocurrency discovery engine that enables a user to automatically generate a token basket or “mini-index fund” made up of cryptocurrencies that are related to trends in news, global and local searches, concepts, context, keywords, hashtags, social media, URLs and other “dynamic content.”
Join the Vectorspace Telegram group for more information on the project here.
Singularity
The value and power of Artificial Intelligence is growing dramatically every year, and will soon dominate the internet — and the economy as a whole. However, AI tools today are fragmented by a closed development environment; most are developed by one company to perform one task, and there is no way to plug two tools together. SingularityNET aims to become the key protocol for networking AI and machine learning tools to form a coordinated Artificial General Intelligence.
SingularityNET is an open-source protocol and collection of smart contracts for a decentralized market of coordinated AI services. Within this framework, the benefits of AI become a global commons infrastructure for the benefit of all; anyone can access AI tech or become a stakeholder in its development. Anyone can add an AI/machine learning service to SingularityNET for use by the network, and receive network payment tokens in exchange.
SingularityNET is backed by the SingularityNET Foundation, which operates on a belief that the benefits of AI should not be dominated by any small set of powerful institutions, but shared by all. A key goal of SingularityNET is to ensure the technology is benevolent according to human standards, and the network is designed to incentivize and reward beneficial players.
The concept of a Technological Singularity is increasingly widely accepted throughout the technology and business worlds. More and more, it is realized that within the next few decades there will be a transition to a new society and economy in which machine intelligence is the dominant factor; and novel digital and organic technologies acting on multiple scales will network together to produce emergent “global brain” dynamics of unprecedented complexity and sophistication.
Humanity faces many challenges on the path to a positive Singularity; among these is the contemporary global economic system. In numerous respects, today’s standard financial mechanisms and institutions are not up to the task of serving as the economic engine of a smooth transition to a broadly positive Singularity. New, more flexible, open and rapidly adaptive economic structures and dynamics are needed.
Blockchain provides a powerful tool for managing transactions in a Singularity- era economy; but blockchain is just a tool, and it must be used in the right way. A blockchain-based framework designed to serve the needs of AI Agents as they interact with each other and with external customers can enable the emergence of a collective intelligence. And it is critical that this framework be designed with positive principles in mind:
Democratic governance on specific issues — giving the community a voice in the system will tend to make the system act for the benefit of the community;
Encouraging innovative new Agents to enter the network, and creating the conditions for Agents to act in a manner that feeds the collective intelligence;
• Directing a significant percentage of the network’s efforts toward causes of broad benefit.
SingularityNET has been designed to meet these requirements, via
Delivering intelligence services to corporations, individuals and organizations;
Fostering the emergence of increasingly powerful distributed general intelligence;
Deploying artificial intelligence for ever-increasing benefit of as many humans and other sentient beings as possible.
SingularityNET is explicitly designed both to be highly valuable in the current context, and to lay the groundwork for the emergence of a future self-modifying, decentralized “artificial cognitive organism” with the eventual potential for general intelligence and beneficial ethical characteristics beyond the human level. It is a practical design inspired by long theoretical thinking and prototyping on the part of the founders regarding concepts such as Artificial General Intelligence, Open-Ended Intelligence and the Global Brain.
What’s your opinion on AI and cryptocurrencies exploiting AI for great benefits?
Later the same month Deutsche Börse, the German stock exchange, said it had earmarked €270m for investment in big data analysis, blockchain, robotics and AI.
Meanwhile, the City Corporation’s top envoy to the EU, Jeremy Browne, said late last month that he thinks AI will be more disruptive to UK financial firms than Brexit, in the long term.
Quant Insight and its backers are betting that banks and asset managers will also tap into new tech by buying in services like the one it offers. The analytics firm said it has grown customer numbers by 50% this year, and has added new staff to sell its services in Asia and the US.
It is also working with “major banks” on creating bespoke indexes and equity baskets — groups of stocks that share certain characteristics and are likely to move in a similar way in response to given macro events."
Full article: https://www.fnlondon.com/articles/alan-howard-backs-artificial-intelligence-data-venture-20180705
Alan Howard backs artificial intelligence data venture
Founders of Brevan Howard and Stone Milliner put their names behind Quant Insight, which uses machine learning for macro insights
European hedge fund managers Alan Howard and Jens-Peter Stein have put their money behind a startup firm promising to use artificial intelligence and machine learning to analyse macroeconomic events.
Quant Insight, founded in 2014 by a pair of former hedge fund portfolio managers, Mahmood Noorani and Krishnan Sadasivam, working with astrophysics professors at Cambridge, uses algorithms to crunch vast amounts of data.
Its analytics software aims to predict the effect of macroeconomic trends — such as currency moves or new government regulations — upon security prices.
Howard, the founder of $13bn macro hedge fund Brevan Howard Asset Management, is a user of Quant Insight’s service. He said it “helps untangle complex markets and identify what is driving asset prices. I can see many applications for Qi’s technology and am pleased to support them in their expansion”.
Jens-Peter Stein, the founder and co-chief investment officer of Stone Milliner Asset Management, a UK-Swiss macro fund running about $6bn, said: “With so much attention on alternative data sources, Qi focuses on better understanding the data we already have — the data that really matters for markets.”
Quant Insight declined to say how much it has raised in the cash call, which is its second, beyond describing it as a “multi-million dollar” fundraising. Eighty percent of the money came from users of the service, the company said.
The hedge fund financiers backing QI are far from the only City bigwigs putting cash behind AI and related fintech projects.
In May, the Swiss bank UBS said it was moving 80 staff into a new artificial-intelligence division, dubbed the Strategic Development Lab, which is dedicated to defending its fixed-income trading turf against hungry fintech startups.
Later the same month Deutsche Börse, the German stock exchange, said it had earmarked €270m for investment in big data analysis, blockchain, robotics and AI.
Meanwhile, the City Corporation’s top envoy to the EU, Jeremy Browne, said late last month that he thinks AI will be more disruptive to UK financial firms than Brexit, in the long term.
Quant Insight and its backers are betting that banks and asset managers will also tap into new tech by buying in services like the one it offers. The analytics firm said it has grown customer numbers by 50% this year, and has added new staff to sell its services in Asia and the US.
It is also working with “major banks” on creating bespoke indexes and equity baskets — groups of stocks that share certain characteristics and are likely to move in a similar way in response to given macro events.
Add to this “We believe that just as the last three megatrends — mobile, social, and cloud — intersected and reinforced each other, so will the next three megatrends — next-gen computing devices, AI, and crypto.” andreessen horowitz
Full article: https://medium.com/@lazslotatherton/three-artificial-intelligence-cryptos-ef1b4a88156d
When the internet first made it’s presence known to the masses in the mid 1990’s, the public was understandably skeptical. Sure, people understood intuitively that computers were going to change the world, but up until that point the average person was not interacting with, or being effected by them on a daily basis. Or at least so they thought. The reality is that computers and the proto-internet were already streamlining aspects of the military, government, and mercantilism starting by the 1960’s. But despite those early use cases, in the 1980’s the majority of us were still not using computers for work nor did the majority of us have them in our homes. At most we had a Texas Instruments calculator to balance the checkbook or a Commodore 64 you could use to play games on a monochromatic screen like The Oregon Trail or Lode Runner.
But gradually developments in personal computing allowed lay people to do more things with these mystery boxes composed of hydrocarbon plastics and filled with circuit boards and wires. Bulletin boards accessible via modems had strictly been the domain of “computer nerds” and those mysterious teenaged “hackers” that could effortlessly start WWIII as depicted in the film War Games. But when companies like AOL and Netscape made the worldwide web more easily accessible to the average consumer via their home telephone lines, the drawing of a new era with incalculable civilizational ramifications was unquestionably upon us. Of course, it didn’t look that way at the time. And to a large extent, it never really does except in hindsight. Even technologists and otherwise experts in the field cannot predict how and at what pace a technology will develop and create ripples of change throughout the world and in our day to day lives. At the time, that GeoCities Dave Matthews Band website wasn’t exactly setting the world on fire. What exactly did it do? What problems did it solve? How was it going to change the way we live? Well, it wasn’t. But early iterations of personal computing and the internet had enough of a hook to grab the public’s imagination and their desire to know more, to interact more, and to experience new things. And of course, there was money to be made. And that capital investment allowed these technologies to be further developed into whichever now nearly ubiquitous device you’re using right now to read these words.
In discussing the crypto space and blockchain, AI, VR, and next-gen computing, it’s often been a reiterated truism that we are in a stage analogous to those early dial-up days of the internet where future use-cases were unclear but adoption seemed like an inevitable outcome to all but the old and visionless who had lived their lives in an analog world and assumed it would therefore always be as such. The quote from a16zcrypto at the beginning of this article asserts that the trifecta of blockchain, AI, and quantum computing will work synergistically to create use-cases and applications that will change our lives in ways so potentially disruptive and liberating that we simply cannot conceive of them. As these technologies go forward, particularly in the case of machine learning and autonomous machine interaction, the telescopic and exponential growth curve in both applications and related markets is probably limitless. In fifteen years time our future selves will look back upon contemporary cryptocurrency exchanges and cloud computing in the same way our present selves experience a floppy disk drive. We will wonder how we ever managed without advanced robotics, artificial intelligence, virtual reality, and completely decentralized peer to peer mediums of exchange. Hopefully, we will also have availed ourselves to invest in these technologies and to be the ones that got in early on what everyone else will be using tomorrow. Below are three examples of companies that represent just such a future synthesis of blockchain and AI technology.
Matrix
Designed to be the new generation blockchain, MATRIX leverages the latest artificial intelligence technology to resolve the aforementioned challenges. The fusion of blockchain and AI technologies enables MATRIX to build a revolutionary cryptocurrency, which support significantly boosted transaction speed, superior accessibility to general users, enhanced security under malicious attacks, and highly flexible operations.
The challenges facing today’s blockchains have to be resolved before the ideal of cryptocurrency can really become reality. We believe the artificial intelligence technology, which has received an unprecedented growth in the past decade, provides out-of-box solutions to address the challenges. MATRIX is designed to be an intelligent chain to unleash the potential power of the blockchain technology. In this section, we briefly review the objectives of MATRIX.
Although smart contracts give blockchains the essential capability to handle scaled commercial behaviors, they need the users to be able to write programs in a given programming language. With MATRIX, no programming expertise is needed any more for designing smart contracts. The unique code generation technique of MATRIX allows automatic conversion of an abstract description of a smart contract into an executable program. Matrix only requires users to input the core elements (e.g., input, output, and transaction conditions) of a contract with a scripting language. Then a code generator based on a deep neural network is able to automatically convert the script into an equivalent program.
Smart contract programs may call functions offered by the host system and/or third-party libraries. Also, programs running on different computers in a distributed framework do not provide any guarantee for execution time. Such openness and decentralization are the reflection of the essential spirit of blockchains, but give birth to various sources of security threats. In fact, the lack of security is plaguing the smart contracts. The MATRIX blockchain is equipped with a power AI security engine consisting of four major components, 1) a rule- based semantic and syntactic analysis engine for smart contracts, 2) a formal verification toolkit to prove the security properties of smart contracts, 3) an AI-based detection engine for transaction model identification and security checking, and 4) a deep learning based platform for dynamic security verification and enhancement.
Today all public chains are suffering from the problem of long transaction latency and low transaction throughput. Specifically, it takes over 30 minutes for Bitcoin to finish one transaction, while the transaction throughput of Ethereum is only 10 Transfer Per Second (TPS). In fact, a blockchain depends on a P2P network to validate transactions. Since a transaction needs to be broadcasted to all nodes in a network, the overall latency has to increase as long as more nodes are joining the network. MATRIX resolves the problem by dynamically selecting a delegation network in which all nodes are voted as delegates of others. All Proof-of-Work (PoW) processing is only allocated inside the delegation network, which only incurs a much smaller latency due to the smaller number of nodes. The selection process is random in the sense that a node is selected with a probability proportional to its Proof-of-Stake (PoS). The online version of MATRIX will support a throughput of 100,000 TPS.
MATRIX is designed to be a highly flexible blockchain. The flexibility is twofold. First, MATRIX offers access control and routing services so as to allow seamless integration private chains into a common public chain. Such a feature meets the requirements many industry and government players for authorization, while at the same time allows necessary information flow from a public chain to a private one and vice versa. Second, MATRIX uses a reinforcement learning framework to optimize its parameters (e.g., consensus mechanism, and transaction configuration) in an evolutionary manner. The optimization paradigm ensures dynamic updating of parameters for near-optimal performance without the risk of incurring hardfork.
Perhaps the most criticized part of cryptocurrency is the “waste” of energy in the mining computations. Although it is essential to attach physical value to the cryptocurrency, the mining process does not make any sense out of the world of digital currency. The problem is even worse when now over 70% of the total computing power around of world is dedicated to mining Bitcoins and others. MATRIX introduces a new mining mechanism in which miners perform the Markov Chain Monte Carlo (MCMC) computation, which is an essential tool for Bayesian reasoning. MCMC based Bayesian computing plays a fundamental role in numerous big data applications such as gene regulatory network, clinical diagnosis, video analytics, and structural modeling. As a result, a distributed network of MCMC computing nodes provide the power for solving real-world compute-intensive problems and thus build a bridge between the values in the physical and virtual worlds.
Vectorspace
The Vectorspace AI [link]platform enables ‘Smart Basket’ (token baskets for traders, funds, ETFs) generation based on user-selected trends that exist in search, social media and news. Their ‘Smart Baskets’ are based on the ability for these baskets to determine for themselves whether or not to include additional cryptocurrencies or components from related baskets that may increase overall returns. Baskets that interact this way with one another will conduct these kinds of transactions between one another using the Vectorspace utility token VAI, which is also required to dynamically generate baskets.
Vectorspace is designed as a tool for discovery as well as a suite of sophisticated tools to help you increase your profits with other cryptocurrencies by reducing risk and maximizing your gains. Their focus is on “Advanced Natural Language Processing (NLP) & Sentiment Analysis for Smart Cryptocurrency Basket Trading” and they have live products any crypto trader can use today. Their site updates every few minutes powered by their algorithms.
[ Link to Smart Baskets ]
According to their whitepaper: “A growing number of organizations offer the ability to trade a basket or group of cryptocurrencies with a single transaction. Similar to a traditional ETF (Exchange-Traded Fund), “token baskets” as they’re more commonly called, enable a fund or individual investor to spread their risk, diversify and lower volatility while maximizing gains with more safety and stability. This approach is valuable but incomplete. For example, taking the top 20 best performing cryptocurrencies and placing them in a basket or fund minimizes gains compared to enabling fine-grained custom creation of token baskets. Which groups of cryptocurrencies are beating the market? Why? What do they have in common? How strong are those relationships? Are those relationships well known and obvious or are they hidden relationships? Are the relationships numerical or nonnumerical, based on concepts, context and sentiment, or a combination of both?”
These are the questions Crypto Discover is designed to answer. Vectorspace AI’s Crypto Discover platform is an advanced cryptocurrency discovery engine that enables a user to automatically generate a token basket or “mini-index fund” made up of cryptocurrencies that are related to trends in news, global and local searches, concepts, context, keywords, hashtags, social media, URLs and other “dynamic content.”
Join the Vectorspace Telegram group for more information on the project here.
Singularity
The value and power of Artificial Intelligence is growing dramatically every year, and will soon dominate the internet — and the economy as a whole. However, AI tools today are fragmented by a closed development environment; most are developed by one company to perform one task, and there is no way to plug two tools together. SingularityNET aims to become the key protocol for networking AI and machine learning tools to form a coordinated Artificial General Intelligence.
SingularityNET is an open-source protocol and collection of smart contracts for a decentralized market of coordinated AI services. Within this framework, the benefits of AI become a global commons infrastructure for the benefit of all; anyone can access AI tech or become a stakeholder in its development. Anyone can add an AI/machine learning service to SingularityNET for use by the network, and receive network payment tokens in exchange.
SingularityNET is backed by the SingularityNET Foundation, which operates on a belief that the benefits of AI should not be dominated by any small set of powerful institutions, but shared by all. A key goal of SingularityNET is to ensure the technology is benevolent according to human standards, and the network is designed to incentivize and reward beneficial players.
The concept of a Technological Singularity is increasingly widely accepted throughout the technology and business worlds. More and more, it is realized that within the next few decades there will be a transition to a new society and economy in which machine intelligence is the dominant factor; and novel digital and organic technologies acting on multiple scales will network together to produce emergent “global brain” dynamics of unprecedented complexity and sophistication.
Humanity faces many challenges on the path to a positive Singularity; among these is the contemporary global economic system. In numerous respects, today’s standard financial mechanisms and institutions are not up to the task of serving as the economic engine of a smooth transition to a broadly positive Singularity. New, more flexible, open and rapidly adaptive economic structures and dynamics are needed.
Blockchain provides a powerful tool for managing transactions in a Singularity- era economy; but blockchain is just a tool, and it must be used in the right way. A blockchain-based framework designed to serve the needs of AI Agents as they interact with each other and with external customers can enable the emergence of a collective intelligence. And it is critical that this framework be designed with positive principles in mind:
Democratic governance on specific issues — giving the community a voice in the system will tend to make the system act for the benefit of the community;
Encouraging innovative new Agents to enter the network, and creating the conditions for Agents to act in a manner that feeds the collective intelligence;
• Directing a significant percentage of the network’s efforts toward causes of broad benefit.
SingularityNET has been designed to meet these requirements, via
Delivering intelligence services to corporations, individuals and organizations;
Fostering the emergence of increasingly powerful distributed general intelligence;
Deploying artificial intelligence for ever-increasing benefit of as many humans and other sentient beings as possible.
SingularityNET is explicitly designed both to be highly valuable in the current context, and to lay the groundwork for the emergence of a future self-modifying, decentralized “artificial cognitive organism” with the eventual potential for general intelligence and beneficial ethical characteristics beyond the human level. It is a practical design inspired by long theoretical thinking and prototyping on the part of the founders regarding concepts such as Artificial General Intelligence, Open-Ended Intelligence and the Global Brain.
What’s your opinion on AI and cryptocurrencies exploiting AI for great benefits?
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