Bitcoin Forum

Hello, GNY staff here to assist with questions and the thread. We have an important information drop coming on Monday for an industry first announcement.

Hello, everybody.
My name is John_Muck, and I will be helping the GNY staff out with this thread.

I have question about this project, since this project is all about the machine learning , my question is you planning to make your own chain? or this project will depends only in the ethereum blockchain?

The system will open using an erc20 token to power its access through a universal api system. Then GNY will migrate to its own dpos network, the code is developed by Leo Liang, engineer of Asch coin. It will offer full decentralised machine learning sidechains.

Thanks for a quick response, GNY used a DPoS consensus algorithm that will be a great choice :D  , GNY will be a the next Lisk ;D

I would like to ask the developers. And on which segment of customers do you expect when creating your platform? For private or commercial use within organizations?

GNY's Machine learning technology was built by Grey Jean technologies, they are our US retail non-blockchain company.  It was built to predict consumer behaviour and answer business problems.

Let me give an example we created:

---------
Let’s say Beyonce wears a stylish leather jacket her latest video. A skilled marketer of that jacket knows to start promoting sales of that jacket to segments of Beyonce’s fan base on social media based on historical segmentation (location, age, income bracket, past purchase history). Individual results from this marketing push may be analyzed individually; say women in their 30’s purchase more than those in their 40s, but the correlations between trends remains unutilized.
GNY's comprehensive management and manipulation of 100s of factors (tracking sales, social media shares, press hits, online queries) allow it to “see” 1000s of new patterns and correlations that are too subtle and complex for a human to see and then be able to track and improve their translation to marketing recommendations.
For example within 10 days Genie learned that women aged between 23-35 in Houston responded more to Facebook Advertisments, and women aged between 28-35 in Los Angeles responded more to Instagram. Recommending the jacket for purchase to young women is easy for marketers, but GNY empowers them to find the optimal message, for every customer, in every market in real time
--------

Gny has built a test model looking at fraud detection of opioid misuse, to prevent abuse.  Insurance fraud detection is just one of infinite industries you can apply our system toward.

You can see history of the team working in the machine learning space in these articles:

https://www.businesswire.com/news/home/20161024005125/en/Pure-Green-Selects-Grey-Jean-Technologies’-AI
https://www.businesswire.com/news/home/20160516005269/en/Grey-Jean-Technologies-Launches-AI-Powered-Personalization-Retailers
https://artificial-intelligence.cioreview.com/vendor/2017/grey_jean_technologies

GNY also wants to highlight the great work being done by the Bloqspace team for the Lisk community, so a big thank you to all the team.  We have grown close to the group and looking forward to the co-projects we are preparing together and presenting in the near future.

https://twitter.com/bloqspace?lang=en

oh, this is really interesting. very nice and friendly type of project which i hope could succeed, but for now i'll just be cheering from the sidelines since i don't have much knowledge about it.

Cheer away, Behiri, and if you have any queries, just ask.  :)

Very grateful for the recognition. and every more humbled to be involved in the community of such a community-centric platform.

Even one partnership with CRC is enough, if this platform will be successful in implementing their objectives thru blockchain, this project would be commendable.
And if another area is tackled like this opioid crisis, it's like a big bonus already.
I hope your ICO will be successful, and if not, I do hope that you will continue this amazing project.
Everyone knows that most projects with noble missions are only after the money, I hope it's not the case here.

Hi TimeTeller, an important point you bring up and we also do not want to fall into the "gesture only" category, so how can we address that.

Zachary Barnett our head of social enterprise is a Founder and Executive Director of Abzyme Research Foundation (ARF), a group with a clear mission of fighting to End HIV. We have the staff to tackle real issues and progress.

CRC already work with tech as part of their operational function, we can add to that, we can provide a machine learning element to improve the information sets they have and we can expand.

The Opioid issue we have built a blockchain model on which is already functional test model, it was created on ASCH chain and is the result of GNY being approached by a group in healthcare for a novel solution to reducing Waste, Fraud and Abuse in this sector.

One thing we must be clear on is what is for profit and what is non profit.   Our work with CRC is purely non profit and will never cross into that area.

Our work in the Opioid issue is for profit, there is a great opportunity for tech companies in this area that can solve these issues that will improve lives and also save insurers money on fraudulent claims and cities dealing with expensive abuse epidemics.

We will be clear which of our work falls into which category so our business model looks achievable.

https://i.imgur.com/jbFN8qp.jpg

GNY will also be bringing a Lisk SideChain for those entrants who use Lisk to enter into our ICO.  This sidechain will offer the full functionality designed by the team to allow developers to deploy directly on Lisk and use Machine Learning (ML) in their network design. We hope to see many large projects on Lisk that use our algorithms to push the boundaries in our industry.


For those entrants who use Asch to enter our sale we will be providing a unique set of Dapps powered by GNY ML and that feature a cross chain transaction protocol for in App payment and settlement.  Leo Liang has joined our team and is a developer from the Asch network, we are very proud to have him working with GNY and will provide great value to the ecosystem.

For entrants joining our token sale using Ethereum and Bitcoin, we have lined up a unique set of bonuses and Dapps to be announced shortly.

I am very sympathetic to your project and I support its idea. I would like to know if there is any information when you roughly plan to continue the presale?

Starting on 3 September 2018, Phase 1 of the GNY sale begins, Jocolyn.
It will include a 20% discount on the price per token.

THE COUNTDOWN IS OVER — The GNY ICO has begun. The $GNY utility token will enable holders to power the machine learning ability of the GNY network prior to migrating to their decentralised sidechain platform

🚀 https://www.gny.io/ico (https://www.gny.io/ico)

https://pbs.twimg.com/media/DmLRj4YU8AEUWc9.jpg

It's an interesting project! GNY. The movie is also easy to understand. I have just started, so I look forward to his future success. At this stage, I can only cheer but I would like to participate if there are bonus events etc. I'm sorry I had already finished.

When will the sales start? And what cryptocurrencies accepted to  buy u tokens?

Sale starts today,  very excited to open our website up   https://www.gny.io/ico

About to start uploading an information drop of announcements!

Good reaction so far to Richard, Co-founder of GNY's special message to the Lisk community from GNY.io.
I have a copy of it below....



This special message was originally posted in this reddit thread (https://www.reddit.com/r/Lisk/comments/9cnn6v/a_special_message_to_the_lisk_community_from/)
 

Great day yesterday for GNY.IO HQ, Summary of the highlights:

Decentralized Machine Learning Platform, GNY, Is the First to Launch Utility Token ICO In Jersey, Channel Islands

Saint Helier, Jersey-  GNY achieved two firsts today as it becomes the first decentralized machine learning system on the blockchain as well as the first utility token ICO to launch in Jersey, Channel Islands. The machine learning platform has been refined and extensively tested over the last two years with top insurance, retail, and publishing companies in the US. The launch of GNY’s utility token centers on its technical solution for how to decentralize its machine learning platform, and embed it directly into the blockchain. Now businesses of all sizes can take advantage of GNY’s state of the art analytic and predictive power by purchasing and using GNY utility tokens.

Feature spotlights in Cointelegraph

https://cointelegraph.com/news/blockchain-based-machine-learning-platform-to-help-businesses-predict-consumer-behavior

Update from the international legal firm representing GNY

https://www.careyolsen.com/news-and-deals/carey-olsen-advises-latest-jersey-ico-launch-gnyio-limited


Important news regarding the GNY Network design

GNY will be launching as an ERC20 token, using a pay as you go model to power its machine learning system. GNY will then migrate in March over to its own DPOS network. A blank slate design that inherits no code from other chains and allows users to build in Typescript.  This brand new code base is in its design phase headed up By Leo Liang, known from his work on the Asch network. This new network will allow sidechain deployment with inbuilt machine learning ability.


GNY LISK SIDECHAIN UPDATE
Lisk community will be getting a full GNY Sidechain that allow developers to deploy Javacript based chains that can access the Machine Learning capability built by the GNY IO Team. The Lisk sidechain will feature 400million tokens and participants who use Lisk in the GNY.IO token sale will receive both sets of tokens from GNY at a 1:1 ratio.  


ASCH Community update
Today on the 4th of September the GNY team will be in the ASCH telegram system, updating the community on the unique Dapp built by the GNY team using the network. Also posting all the relevant ICO material so members of the group can join in our ICO.  

Plenty more to come, next up is youtube filming and more press releases!  

www.gny.io

 An amazing project! I really like the community in the project. A project without drawbacks, everything is done simply and easily.

I'm excited about this new project!
I support you from vietnam, please let me succeed!

this is a promising area for development. I think you should do it. if of course you believe in your project and want to succeed. are you planning a bounty company? I think you need to advertise your project well.

A newly released infographic by Callaghan Innovation breaks through the hype and intrigue around artificial intelligence to raise awareness of the opportunity this extraordinary technology is creating.

Hello,
   
GNY IO ICO has been listed on UnboxICO (link: http://unboxico.com/ico_detail.php/734/GNY-IO/ ).
   
Feel free to contact us via unboxico108@gmail.com , if you have any questions.
   

Adding translations of our Cointelegraph article:

Italian
https://it.cointelegraph.com/news/blockchain-based-machine-learning-platform-to-help-businesses-predict-consumer-behavior
Portugese
https://br.cointelegraph.com/news/blockchain-based-machine-learning-platform-to-help-businesses-predict-consumer-behavior
Spanish
https://es.cointelegraph.com/news/blockchain-based-machine-learning-platform-to-help-businesses-predict-consumer-behavior
German
https://de.cointelegraph.com/news/blockchain-based-machine-learning-platform-to-help-businesses-predict-consumer-behavior

A little bit of General History.
A Machine Learning Evolution Infographic showing a brief Timeline.


http://www.smdi.com/sites/default/files/Evolution%20of%20Learning%20Machine-01.png

Bringing up some important company history to the thread:

Grey Jean technologies built the machine learning technology GNY is using for its blockchain platform.

Grey Jean has plenty of recorded history in the public space:

https://artificial-intelligence.cioreview.com/vendors/most-promising-artificial-intelligence-solution-providers---2017.html

of the the 20 Most Promising Artificial Intelligence Solution Providers - 2017

https://artificial-intelligence.cioreview.com/vendor/2017/grey_jean_technologies


https://www.businesswire.com/news/home/20160516005269/en/Grey-Jean-Technologies-Launches-AI-Powered-Personalization-Retailers

https://www.businesswire.com/news/home/20161024005125/en/Pure-Green-Selects-Grey-Jean-Technologies’-AI

GNY feature in German news:
https://www.btc-echo.de/projekte-auf-lisk-was-geschah-nach-dem-relaunch/

Translation:
GNY
The blockchain project GNY started already in 2015 under the name Grey Jean Technologies. The aim of the project is to build a platform for machine learning and artificial intelligence. As a cross-blockchain project, GNY not only wants to set up its own blockchain, but also to insert its elements into various existing blockchains, thus adding new aspects to them. In addition to a Lisk sidechain, the project also builds on Ethereum and Asch.
GNY wants to find a blockchain solution for processing the huge amounts of digital data in order to make them commercially usable. GNY recognizes recurring patterns and learning components that adapt to the behavior of users. GNY wants to develop its own blockchain ecosystem on Lisk. With the GNY token, the holders will be granted access to the platform's learning tools.

Machine learning could really take big-data and reduce human dependence from it and as data volume, velocity and variety is increased machine learning will have a better chance to cope up as Moore's law makes their system faster, cheaper and smaller.
So, we should keep our hopes up and radar on in adopting machine learning in our corporate DNA.
So, we could cope up with changing world with increasing complexities and scale.

Read the full article here - https://www.linkedin.com/pulse/20140417121158-1853953-the-silent-rockstar-of-bigdata-machine-learning

also interesting articles and I became convinced that in the future this project will increasingly support it, good luck and projects can be realized.

Japanese language translation of the cointelegraph article on GNY is out now.
Here is the link.....   https://jp.cointelegraph.com/news/blockchain-based-machine-learning-platform-to-help-businesses-predict-consumer-behavior

excellent work guys in japan is very often browsing this site for investment and it can attract new investors to your pool. the main thing is to continue at the same pace and develop.

While Tomb Raider Underworld is largely forgotten in the ongoing adventures of Lara Croft, the impact this game had on the emerging game analytics field (and AI research as well) is hard to ignore. In much of the contemporary research literature on game analytics, Tomb Raider: Underworld is celebrated as one of the seminal bodies of work that established what we can learn from even the smallest amounts of data and paved the way for more exciting projects in the future — some of which I already covered here on the channel. It’s fair to say game analytics are only going to increase in scope moving forward, so who knows, maybe we’ll find out in a couple of years whether players fare better in the more recent entries of the franchise.

https://medium.com/@t2thompson/tombraider-60682f8fe36f

https://thefintechtimes.com/carey-olsen-advises-latest-gny-ico/

The Fintech Times @thefintechtimes:

Carey Olsen’s corporate team in Jersey has acted on the launch of the GNY Token by GNY.IO Limited – one of the first initial coin offerings (ICOs) to receive consent from the Jersey Financial Services Commission (JFSC) since the publication of the JFSC’s ICO Guidance Note.

The GNY Token is a cryptographic utility token that enables its holder to gain digital access rights to a decentralised machine learning predictive platform for the blockchain. The GNY platform combines cutting edge machine learning with state-of-the-art algorithms to forecast user behaviour and to provide business, marketing and social impact solutions that are predictive, adaptive and responsive.

The Carey Olsen team, which was led by partner Chris Griffin and included associates Joseph Barker-Willis and Filip Kwilinski, advised Philean Trust Company Limited, GNY.IO Limited’s administrator in Jersey, on the token generation event and worked closely with the JFSC to obtain the JFSC’s consent to GNY.IO Limited’s ICO.

Cosmas Wong, founder and CEO of the GNY platform, said:

“It was important for us to not just work with a team who understood the formal guidelines established by the JFSC, but also how it dovetailed practically into our technology and our business. It was a pleasure working with Chris and the rest of the Carey Olsen team, who understood both.”

Mr Griffin said:

“The launch of the GNY Token as one of the first ICOs to utilise Jersey’s formalised ICO regime is another really exciting development for the Island in the cryptocurrency space, and Carey Olsen is delighted to once more be at the forefront of this evolution.

It’s important to stress that JFSC consent does not give the GNY Token or GNY.IO Limited ‘regulated’ status, but it does mandate a set of conditions designed to ensure that GNY.IO Limited meets specific standards in terms of governance, investor disclosure and AML/CFT compliance. These conditions should give token purchasers a degree of reassurance that may not be available in other jurisdictions.”

A gratitude for me. For being the first supporters of GNY project. I hope you can achieve all your mission to achieve!

"Your artificial intelligence network"
LISK MACHINE LEARNING
(L.M.L)

Take one Lisk Hub...add One GNY sidechain...combine industry leading ML...provide unique Lisk open toolsets

Wth 400 million tokens the Lisk Machine Learning sidechain will match the token supply of the GNY Network. Entrants into the GNY ICO who use LISK to enter our sale will receive an equal numbers of LML tokens. The network will allow the Lisk ecosystem to add Artificial intelligence capability to sidechain deployment. GNY's tested ML system has been used in Commercial US industry and will bring consumer behaviour prediction. Developers will have the tools to reach consumers with better and more genuine interactions. The network will lock up tokens being used to access this machine learning ability as more developers in insurance, medical and a near limitless combination of Dapps build on the platform.

https://pbs.twimg.com/media/DmphV54WwAA_uB0.jpg

this project is indeed very interesting and has a team that is experienced in their field, hopefully, the ICO will run according to plan.

.  Thank you !

https://www.gny.io/lisk

Website now updated with all Lisk sidechain branding updated!  Please visit the site to be included in the ICO, Phase 1 only
100m tokens.

The project associated with the development of artificial intelligence with the help of blockchain technology - looks very promising and in demand! Do you have a bounty campaign? I would like to take part in it.

Bounty information to follow soon,  we are just reviewing currently.

Hey guys. How do you guys compare to Nudge (nudge.io) (https://www.nudge.io)? They've been around the AI space for a while now and are also working on a blockchain offering.
Nudge's BitcoinTalk Link (https://bitcointalk.org/index.php?topic=4755321.msg42950056#msg42950056)

For me, plan it’s a good choice for investment. Check wp and price on market and all will be clear for you.

https://www.manufacturing.net/article/2018/08/mixing-ai-and-machine-learning-business-processes#.W4btxk5gonk.twitter

From the above article......  What you need to do to adopt AI and machine learning..........

📌  Make sure the data is clean.

📌  Find the low-hanging fruit where AI capabilities can make an immediate impact.

📌  Find the right vendor for the AI-based business process project.  

📌  Remember that AI and machine learning algorithms are tools, not magic bullets.

but this idea is similar to some of the same ideas in other projects. I believe that there should be something special in order to stand out among others. the team has to show its advantages over other projects that also have a similar idea. Of course the competition is good.

Hey Matt! I spoke with Co-Founder Richard from GNY and he gave the following analysis (he did not use the GNY AI or Machine learning algos to come up with this response): "The difference between us and nudge is that they have no members of staff. No detail of machine learning in their whitepaper. No history in the domain. And one follower on twitter."

I'm a sucker for everything related  to machine  learning, I really do believe that's the way of the  future. Honestly, your project sounds  incredibly  interesting to me, what's the  best way to learn more details  about it?

The GNY.io telegram group would be a good place to start, wattson  :) .................  https://t.me/GNYioBlockchain

How Artificial Intelligence Can Influence Governance, Risk, and Compliance.

Artificial Intelligence (AI) offers enormous opportunities to businesses. Given the correlation between risk and an organization's objectives, one could easily extrapolate how AI can help bring insight to Governance, Risk, and Compliance (GRC) activities as well.

But, what is AI? As a working definition, AI is the science and engineering of making intelligent machines and computer programs to achieve a goal. It's about creating a computer mind that can think like a human. It's about machines taking action.

One of the most important technological advances of our time is artificial intelligence, and, in particular, machine learning, which is the ability for a machine to keep improving its performance without human involvement to accomplish tasks. Systems can now be taught to perform activities on their own.

The transformative effects of AI will be felt across nearly all industries. The impact on core processes and business models will be enormous, placing further strain on management and implementation.

Known Unknowns
Probably one of the best cases is fraud detection. Algorithms can be written using various stochastic modeling techniques, coding, and data testing. Of course, for machine learning to be successful, it must have quality data. As a result, there is a premium on structuring risk data in such a way to use it as AI input. Conversely, a challenge implicit in machine learning is substantiating its outcomes. As machines "learn," their conclusions may not always yield the desired result. This conceivably makes it difficult for a risk manager to explain the machine's conclusions to executives or a regulator difficult. For example, there may be issues with multicollinearity, lack of data, as well as how the machine deals with outliers, which is common with many risk data, especially if the organization uses external data.

GRC and AI Image 2 This example applies to a typical risk management anecdote of "driving by looking through the rear-view mirror." The shear amount of data aids in the confidence (not just the statistical significance of a model) of AI's output. This is beneficial to many high inherent, intrinsic risks that organizations experience. Malware is an example.

AI can also be used to substantiate conformance. For example, one large financial services company uses AI to help prevent money laundering, thereby assuring AML/BSA compliance.


Read the full article here.... https://www.nasdaq.com/article/how-artificial-intelligence-can-influence-governance-risk-and-compliance-cm894603

The piece below does not factor in the GNY or LML projects as they are still in development, but nevertheless the piece is an interesting read.  




Do you need custom development, API software, or startup acquisition?


Companies can't turn a blind eye to machine learning anymore, as it is so powerful at certain tasks. Answer these four questions to understand whether your business needs machine learning, and, if so, how you can adopt this technology.

AI and machine learning are making a significant impact on multiple industries and changing the landscape of our society. These are not just hot trends; they are here to stay.

Still, machine learning is not a magical solution that applies to every single use case. So often companies embark on an AI development journey without a clear understanding of the value it should bring to their business. As a result, many data science and machine learning projects don’t have clear KPIs and simply drain R&D budgets.

That’s why managers have to ask themselves four key questions to justify the need for machine learning development.


There are three strategies for companies to adopt machine learning.

1. Build a machine learning solution from scratch.
This is probably the riskiest option, as only an estimated 10 percent of machine learning R&D projects succeed. It is still the most viable option for some narrow machine learning cases in specific domains.

2. Explore machine learning with cloud engines from Google, Amazon and the like.
This is the easiest way to gain access to machine learning technology. On the downside, you cannot freely configure system parameters. For instance, Amazon uses only logistic regression models, so is practically useless if you need to use different models for a particular project. That means, more sophisticated machine learning projects require custom solutions development. Furthermore, 80 percent of machine learning development is still about big data engineering. This is something you cannot delegate to Amazon.

3. Buy a machine learning startup.
This is the most expensive option that suits only big companies.

Data science and machine learning often produce unexpected results and give invaluable insights. This technology is here to stay, and it’s going to evolve at an extremely fast pace. Answering the above questions will help you start your machine learning development journey.


Read the full article here.... https://www.business.com/articles/machine-learning-project-questions/?utm_campaign=coschedule&utm_source=twitter&utm_medium=bigthinkingio

How Artificial Intelligence Estimates Obesity Levels From Google Map Photos.


The research suggests that the predictive power for obesity rates came from the presence of natural features such as lakes and parks detected by the neural network.


https://thumbor.forbes.com/thumbor/960x0/https%3A%2F%2Fblogs-images.forbes.com%2Fwilliamfalcon%2Ffiles%2F2018%2F09%2Fobesity_preds.jpg


In the study, the features extracted by the neural network were able to explain around 60% of the variation in obesity levels for the ground-truth obesity data from a survey known as Behavioral Risk Factor Surveillance System data.

Analysis of satellite imagery using modern deep learning techniques is an exciting path of research which can help save billions in census expenses. More importantly, it can help sociologists remove implicit biases from sampling techniques which may disadvantage minority communities.

William Falcon.

Read more here. (https://www.forbes.com/sites/williamfalcon/2018/09/04/how-artificial-intelligence-estimates-obesity-from-google-map-photos/#275de80d3a41)

Wow this is extremely intriguing. extremely pleasant and inviting kind of task which I expectation could succeed, yet for the present i'll simply be cheering from the sidelines since I don't have much information about it.

Is LML token going to be added onto Binance?  I just saw the market watch listing thing on there.  Probably hush hush to say I guess but maybe someone in here can chime in on that.

Hope this was a joke. Do you even know what parameters are asking for finance to fill the project on listing? Many bitcoins as a payment for a market maker and listing+a large community of active developers+transparent actions. All this is not in this project, which means one can only dream of major exchanges.

AlgaeaFrampton, The "market watch listing" from Biance is added for way of clarity.


As to a Bianance listing I very much doubt such sensitive information would be disclosed on Bitcoin talk/telegram/reddit in such a way by GNY HQ.
NDA's would probably be in force and even if there were no NDA's staff members would not say anything until the deal was sealed for fear of looking like they were pumping the token.

I will say however that the next exchange to list the LML token (Lisk Machine Learning) is incoming shortly.
Stay tuned.....

I understand correctly that there should have been cooperation with a fox, but in the end nothing happened? Or does it still work and the gateway is in order?

Cooperation with a fox?

I am afraid I am not following your drift here, starkovblue.
Could you explain further.

Lisk Machine Learning now at coinmarketcap
https://coinmarketcap.com/currencies/lisk-machine-learning
great work team  ;)

Does your LML coin have any direct relation to the LSK coin? How can I use LML tools for my purposes? There is a great future for artificial intelligence.

Quote : Does your LML coin have any direct relation to the LSK coin?

LML and the token it hosts will be built as a sidechain of Lisk.
The team behind the LML sidechain will be working closely with Lisk HQ on this project to ensure the highest levels of quality and value are added to the Lisk projects mainchain.
Below see an image showing members of the LML team meeting with the Co-founder of Lisk, Max Kordek, in London a short while back.




The aim is to add machine learning to pre-existing blockchains, so we are offering a smart API that bridges to Lisk.
A tool that will allow developers building side chains on Lisk to access the power of machine learning and integrate it into their Dapps.


Quote : How can I use LML tools for my purposes? There is a great future for artificial intelligence.

There is indeed a great future for artificial intelligence.
While code and exact intergration has yet to be revealed for LML I can tell you that it will deliver a unique learning capacity, superior processing of market segments, all with decentralized blockchain integration.  
So, commercial grade machine learning through a decentralised blockchain to create a unique product with considerable application.

Leveraging data sets from the hits and misses of past communications to build a predictive model for each person and each action.
Responding In Real-Time
Conventional techniques are extremely limited in their ability to adjust to real-time needs and in today’s landscape of viral content and interconnectivity can have negative consequences.
LML considers many more factors then possible for humans
LML also Looks at Data Many Different Ways
Communicating securely with the blockchain is another great advantage and something the compertitors do not have.
LML leverages its power to securely record and maintain consistent data.
This encourages secure data sharing, so data does not leave the security of the chain.

So if you need to see new patterns in your data, drive higher clickthrough rates, or predict sales and efficiencies within supply chains, then LML can help
For larger businesses and select social impact organisations, it can offer a full service consultation, business analysis, and custom application creation service.
From initial analysis of business goals, to standardisation of data sets, and delivery of metrics and reporting.

Don't forget our TELEGRAM GROUP covering all the machine learning capabilites offered by the GNY.io group including Lisk Machine Learning........  https://t.me/GNYioBlockchain

The following article was first published by William Ryan on his medium blog account on the 18th December 2018.... https://medium.com/@FinTechWill/gny-machine-learning-a-deeper-look-f92683b9f2b2
William has formally announced his intention to signal as a @gny_io delegate as GNY.US on his personal twitter account here.... https://twitter.com/fly_nryan/status/1058546941708054528 (https://twitter.com/fly_nryan/status/1058546941708054528)

Lisk Machine Learning (LML) (https://cryptochartindex.com/currency/lisk-machine-learning) Token is on CryptoChartIndex (https://cryptochartindex.com), Showing marketcap and prices.

GNY Project's Co-Founder Lays Out the Development Plan for the Week Ahead.

Yesterday, Chief R&D Officer and Co-founder of GNY, Richard Jarritt (bringing Machine Learning to Lisk) revealed the tasks for the week to the projects followers on the GNY telegram (https://t.me/GNYioBlockchain)  

1. Analysis.

The team will undertake a comprehensive analysis of the solutions other Machine Learning developers have offered within the DPOS space. This to ensure their efforts are above current industry standards. Dissection, comparison, and learning for the team this week so.

2. Internal Education.

The heads of team are creating guides to the projects Machine Learning in Python and Javascript. This is to ensure all team members not only understand the concept but also the code. Internal education cannot be underestimated and is vital to keep all team members aligned.  

3. Timeline.

Drafting a completion timeline for the GNY Machine Learning operating within the codebase that Leo Liang (https://vimeo.com/309873352) (known from the Asch decentralized application platform) has created. This will be made available to the public.

The GNY universal Beta Api plug-in update is out now and testing is welcomed for commercial developers aiming to work with Machine learning and blockchain. You can visit Github to view the steps to run it here....  https://github.com/GNYIO/GNYPLUGIN/blob/master/PlugincodeV098 (https://github.com/GNYIO/GNYPLUGIN/blob/master/PlugincodeV098)

 




         

 
 









 
 

At the beginning of the topic, it was wrote about the migration of LML tokens to Lisk at the beginning 2019. Do you know anything about this?

I saw a change in roadmap the Testnet in May, not March. Are going works well? Because I can't see updates on GitHub.

   
   

 
 
   

 




 

 

 

 

 

 

 

new result achived by this project, now all of us can see this project at coinmarketcap
https://coinmarketcap.com/currencies/gny
congratulations  ;)

The volume of trade is only 0.25 BTC per day, but this is at least something.
There are no successful companies in this format of artificial intelligence. So the team can take a good place and make a profit to investors.

Friends are you going to add new exchanges? What you have now on https://exrates.me/ is a shame. There bots trade only and without volume you will not be able to attract traders.

GNY listed on LATOKEN soon!
https://latoken.com/

LATOKEN is a rapidly growing Top-30 crypto exchange focusing on providing liquidity for new tokens:
●   $300+ million daily turnover
●   150,000+ registered traders
●   350+ crypto pairs available for trading
Besides crypto trading, LATOKEN users can participate in selected Tokens Sales at pre-sale and crowd sale stages.

 

Full text.


Cosmas Wong is a tech entrepreneur and investor who created companies for more than 20 years. He is the founder of Grey Jean Technologies; the genesis of the GNY platform, and also of other strong technology companies. I had the opportunity to make that interview with him, and we discussed the problems of AI, blockchain, and crypto adoption as well as his business ideas.
Andrey: Let’s meet with the Hacker Noon community. What is your background?

Cosmas: I’m a corporate lawyer by training. I spent over 13 years in mergers and acquisitions, private equity, corporate finance and venture capital investments before I started my first company in New York in 2010 with a few other co-founders.

Andrey: What companies were built under your management?

Cosmas: The company, Enso Financial, is a financial services data analytics company, and it was sold in 2016 to a financial services group in the UK. In 2015, I started Grey Jean Technologies in New York, and we started to build the Genie machine learning platform.

Andrey: Why machine learning?
Cosmas: The main catalyst for Grey Jean was to find a way to organize the large amounts of unstructured and semi-structured digital data that we produce every day and see if we can find repeatable patterns that might predict our next actions. This depended on having a process that can find correlations in the datasets that the human mind or eye cannot detect; correlations that don’t sit within an X:Y or X:Y:Z, but a multi-dimensional axis, and one that changes all the time. Only a machine can see and track that.

Andrey: What are the challenges of blockchain adoption?

Cosmas: Not enough people understand blockchain, how it’s different and better than what we currently have. Our opportunity is to show the implementation of blockchain technology more widely and provide more useful real-life use cases.

Andrey: What place blockchain will take in everyday life?

Cosmas: Many large institutions — banks, insurance companies, governments — are testing blockchain and cryptos. When we see the training wheels come off, adoption levels will skyrocket. When that happens, and comfort levels increase, blockchain technology will simply be another technology that operates in the background of everyone lives.

Andrey: What are the barriers to AI adoption that the tech community should overcome?

Cosmas: The biggest barrier to AI adoption is cost. Cost of implementation and cost in time to implement. All too often AI technologies like machine learning are seen as “cure-all” panaceas for every single data problem; companies think they can throw all the data they have at a solution and expect to get every question answered. We have seen that that is a sure way to failure. AI solutions are intelligent, but they are artificial, and they require training and they need to be tuned to answer more specific questions. They need to have the right data sets. That is our approach; define the question to be answered, test the right data sets, and expand from there.

Andrey: Elon Musk said that AI can be a fundamental risk to the existence of human civilization. What do you think about his warning?

Cosmas: I admire Elon Musk for everything he’s done, but I think that’s a complete overstatement. The late Stephen Hawkins had the same opinion.
We equate AI to some all-knowing all-doing mega computer brain like “Skynet” from Terminator. I’ll agree that “Skynet” is a fundamental risk to the existence of human civilization, but we’re far from it. Having said that it is true that AI solutions are a fundamental risk to certain types of jobs — jobs that are repetitive, certain jobs that require immense quantitative requirements, jobs that require better efficiency — but that’s also what they said about algorithmic trading platforms.
Although certain types of jobs will be eliminated by AI solutions, the human functions for those jobs will also change. The people who succeed are the ones that train themselves to master the machine, and let the machine do all the heavy lifting.

Andrey: There is a lot of buzz in the media about Facebook’s new currency Libra, but many consider it wrong use of blockchain because it’s not decentralized. What are your thoughts on Libra and the use of centralized blockchain?

Cosmas: I think the launch of Libra just catapulted the awareness of cryptos into the mainstream, and that’s a good thing. We can debate whether it’s a real crypto because it’s not decentralized. As I said earlier, blockchain technology needs to be more accepted, and the technology needs to morph and change and go where it’s needed, and we need to let that happen. If some want to use it in a way that’s more centralized, then it still serves that purpose.

Andrey: What is your main business and leadership target right now?

Cosmas: In September 2018, we launched GNY.IO with new investors and partners, in order to decentralize and distribute the machine learning platform on the blockchain; we called it GNY.

Andrey: And how is it going on?

Our first major milestone this year was the GitHub release of the core GNY code. The next target is scaling GNY’s capability on a chain with a release this month. Developing the scope and capability of GNY will be in constant evolution along with heading towards our sidechain solution for token deployment and onboarding partners and developers to the system.

Andrey: How did you come up with an idea to combine machine learning and blockchain?

Cosmas: The idea to combine both cutting edge technologies came out of necessity. We saw that some of the challenges in machine learning could be overcome by the blockchain.
A typical machine learning platform relies on being able to churn a huge amount of data, and all that data needs to live in one place. That’s why many large enterprises are building data lakes. With the increasing push towards data security and ownership, we believe the opposite will occur — that people’s appetite for their data to be shared and collected, especially personal data — will not be centralized, but distributed.
We’re also seeing that although machine learning solutions are becoming more popular, and more people are testing them, they are also less likely to want to give their data to a third party to be processed. Centralized data and transferring sensitive data to be processed, means a higher risk that a security breach of that database will compromise the security and privacy of more people.
By distributing the machine learning system on the blockchain, we are letting a company or a group or consortium of companies that normally share data, to build a GNY side chain so that the necessary data is shared and used securely within that group, and all processing is done on-chain. Nothing leaves the security of the chain.

Andrey: Machine learning system requires reliable and consistent data, how will you ensure this?

Cosmas: Data entering the blockchain will be verified and exist in a form that the machine can learn to read from the beginning.

Andrey: A typical machine learning platform requires millions in investment and a long integration period, can you solve that problem?

Cosmas: A distributed system like GNY can be deployed much more quickly and run more cheaply. This is extremely important for us as it promotes the use of the technology and “democratizes” it so it can be used by not just the very large corporations.
And by making GNY lightweight in order to sit in the blockchain nodes, we are amplifying its power by using the blockchain’s natural distributed infrastructure as a neural net.

Andrey: Did you test GNY somehow? Do you have use cases?

Cosmas: We’ve had the privilege of testing the predictive powers of our platform with some large retailers and publishers and have consistently showed very impressive results. For example, we compared our predictive platform’s ability to predict a publisher’s website users’ interest in certain articles versus their own editors, and found that we were consistently between 90% and 120% better. We could also predict a large US retailer’s customers’ next day purchases at over 70% accuracy. We will be releasing more detailed use cases later this year.

Andrey: Are there any unique technologies that your company uses in your neural network?

Cosmas: GNY’s recurrent neural network deals with sequence problems because our blockchain connections form a directed cycle. In other words, GNY can retain state from one iteration to the next by using our own output as input for the next step. In programming terms, this is like running a fixed program with certain inputs and some internal variables. The GNY recurrent neural network can be viewed as a fully connected neural network if we unroll the time axes. We’ve filed a provisional patent for this technology in the US.

Andrey: And the last question. We can see that cryptocurrency little by little fight their way to everyday life. What is your opinion, crypto community and ordinary people are ready now for a global adoption?

Cosmas: I actually think that blockchain technology will integrate into everyday life. Certain blockchain products and operations will soon rapidly demonstrate their superiority to the established best practice in technologies.
Similar to how the internet increased digital interconnectivity, blockchain will elevate digital ownership, activation, security, and optimization rapidly. This will force new standards in an already competitive digital marketplace.
Currently, we are onboarding our first beta-commercial partners and it is incredible to see how quickly they are moving from, “How can this technology improve my business?” to, “What else can GNY do to unlock value and meaning in my existing data operation?” We are most excited to see how small to mid-sized enterprise use GNY to build new and improved digital operations. We can’t wait to see what people come up with.
I’m also excited about the greater and more widespread adoption of cryptocurrencies in everyday life. A decentralized “store of value” is crucial in our current trade and political climate. Having said that, we also need a much more stable cryptocurrency, and bitcoin’s wild daily fluctuations don’t help. I believe as more people adopt cryptos, they’d stabilize, but again, we’re a long way off.

The full text of the Retail Sales Machine Learning Prediction demo can be read here..... https://www.gny.io/post/retail-sales-prediction-demo
Within it Richard Jarritt, Co-Founder and Chief R & D Officer of GNY walks you through the step by step guide for how you can run the demo on a GNY server.



Text description of some of the elements of the meetup.


Lisk Meet-Up Utrecht - Alpha SDK Updates and New GNY Demos.




The Time: from 18:00 onwards on the 24th of July 2019.

The Location: The Netherlands; home to bulb fields, cheese markets, the Old Masters, millions of bicycles, canals, and innovative water-management.

The Venue: The Lisk Center Utrecht; quickly becoming "the" blockchain hub of the Netherlands and the place to find the most interesting talks, networking, and activities around blockchain innovations for that region and further afield.

This is where GNY.io decided to unveil their Retail Prediction Demo ( https://www.gny.io/post/retail-sales-prediction-demo ) . It was quite fitting, as this reveal was part of a blockchain get together that featured quite a number of innovative blockchain projects. For example Rachel Black, the Lisk project's tech evangelist started off the presentations on the night with an introduction to Lisk's Alpha SDK and a demo proof-of-concept invoicing app titled "Lisk bills". This was built by the Lisk team over a number of days using the hot-off-the-presses Alpha SDK and is exciting for the GNY.io team as it begins to open the way for them to start the initial phases of building their LML (Lisk Machine Learning) project also.  

Other hot blockchain projects on the night included EDEX, a DEX build on Lisk, and described on the night by Haidong Liu from Elitex.io, a currently centralized exchange which services the Lisk ecosystem.

Also on stage was Larry Pang of IoTeX, a silicon valley based privacy-centric blockchain platform aiming to power the Internet of Trusted Things

The night was rounded out by a presentation from Eugen Salkutzan of MADANA.io, a platform for data analysis that uses Blockchain technology allowing participants to get in on the data market with their own data and simultaneously preserving their privacy by design.

So in the midst of all this, and following a word from the Lisk Co-Founder, Max Kordek, this is where GNY.io took to the stage and shone. Presenting on the night for GNY.io was long-term supporter of Lisk and GNY, John Muck. He provided an intro and some context for the blockchain enthusiasts present as to the goals of this innovative decentralized machine learning on the blockchain. What followed this was a series of videos linked with intros by John Muck.

https://static.wixstatic.com/media/cddf32_dd0d92af9a8b4438a674066b995c2ce5~mv2.jpg/v1/fill/w_740,h_412,al_c,q_90,usm_0.66_1.00_0.01/cddf32_dd0d92af9a8b4438a674066b995c2ce5~mv2.jpg

John Muck leading the GNY presentation. Photo courtesy of Telegram User Lemii

First up in video form was Zachary Barnett, Head of Social Impact for GNY.io, offering good wishes to all those in attendance at the Lisk Center Utrecht. This then led into Richard Jarritt, Founder, Chief R&D Officer of GNY.io providing an overview of the potential use cases for the GNY technology with regards to a users historical data, for example how patterns can be uncovered that can predict your next top seller, identify which district you need to canvas in order to win your election, or which routes are being overfished and are in danger of collapse. Identifying these patterns, with hundreds of variables, and millions of data points, is too complex for the human mind. Tasks of this complexity require machine learning and this is where GNY.io and it's decentralized advanced machine learning software secured across the nodes of a blockchain will be of great benefit.

To round out the presentation Richard Jarritt then took all there present step-by-step through the GNY Retail Prediction Demo. This entailed generating a new account, visiting the GNY Faucet to collect 1000 demo GNY Coins, uploading the historical data set, clicking the “Get Prediction” button, which will then reveal the prediction for the next day’s top 5 sales items as it loads directly into your wallet. The full instructions and sample GNY data file to allow you carry out this demo yourself are also available here on the GNY.io blog..... https://www.gny.io/post/retail-sales-prediction-demo.

John Muck gauged the response on the night following the GNY presentation and it was felt that the combination of spoken word, video clips, and product demo was a big hit. This mix of elements was essential with to hold the attendees attention especially considering the array of projects that had already come before on the night, and the decision taken on this media mix is a testament to the forward planning of the GNY.io team.

 

 

 
 









 
 








 






  

 

   

Cryptobridge is delisting GNY coin on the 25th of november along 50+ more coins. I can help you out withdraw your coins from CryptoBridge for a fee through another solution. Minimal trust involved, not full trust of your assets. Same for everybody else that has problems. As they are delaying KYC's and doing everything in their power to keep the coins so they can dump after that. All I ask is a fee and a review so I can help more people. I will provide my social media accounts also in case you want them, but for this solution you will see it's not truly necessary.

You can contact me on discord : Equilibrium#1004  or  telegram : @Equ1Librium