🧠🌐🤖 【ICO】 First Decentralized Machine Learning Blockchain - GNY.IO ��🌐🧠

[John_Muck]

Introducing Peter Davies, Chairman of GNY's Board of Directors

The entire team at GNY is thrilled to introduce our non-executive chairman, Peter Davies.  Peter Davies is a barrister who has held senior legal positions in a number of technology  companies, including Microsoft, IBM and Apple Computers. During his 30+ years of working in technology law and for some of the most impactful tech companies in the world, Peter has developed a refined perspective on the role of patents in emerging tech  environments.  It is precisely this expertise that made us so excited to welcome him to our team as Chairman of the Board.  We hope to be introducing Peter to the blockchain community more thoroughly in the coming months, but for now we wanted to let him introduce himself in his own words.

"I’m incredibly excited to join GNY.IO  as non-executive chairman of its board of directors. I’ve held senior legal positions in some of the biggest tech businesses on the planet and  top executives in each of these giants would often urge their teams to retain the energy, quick reactions and hunger for results of a start-up  company. Well, now I really know what that means!"

I  was very interested to read about the Internet Archive’s Decentralised Web Summit that took place last month in San Francisco. At events like these, we’re starting to see some radical re-imagining of the online world, so that innovation in AI and blockchain applications is speeding up at the same time as social pressure is growing to use the huge potential of these technologies in responsible ways. We need to keep this in mind even as we grasp the fantastic opportunities that are out there.

Any IP lawyer will tell you that tracing patterns in patent applications is a pretty good way of identifying future directions in tech innovation.  A couple of numbers tell the story: Bloomberg Law data reported on cointelegraph.com  shows that nearly 700 blockchain-related patent applications were  published in the US between January 2011 and April 30 of this year, with 70 patents on blockchain technology granted during that time. The  Financial Times cites World Intellectual Property Organisation (WIPO) data revealing that China filed 225 blockchain patents in 2017 alone, almost half of all the 406 blockchain-related patent applications made  around the world that year according to the WIPO database.

These  numbers might look intimidating but in fact they’re extremely encouraging. This is where inventive, creative energy is now being directed. This is where the opportunities are to be found. So energy, quick reactions and hunger for results are still clearly what it’s all  about. That was true when I joined my first tech company employer in  1988 and so far as I can see that much at least hasn’t changed. "

[BLOQspace]

The GNY community is now locked and loaded.  Check out Bob Anglin, with our power banners in tow, look out for our BLOQspace weekly meetup series that will be starting soon, being spearheaded by our tech evangelist Javier Guerra of BLOCquarry.

[BLOQspace]

Machine Learning summarized in one picture:

[wattson]

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?

[John_Muck]

[John_Muck]

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

[John_Muck]

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

[John_Muck]

What is Machine Learning?.......... ELI5

[John_Muck]

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

[BLOQspace]

It is always paramount to give credit where it is due. I would like to thank the GNY team for being shining example of how to engage with and respect their community. The GNY team sponsored these shirts for some of their early grassroots supporters. We really appreciate it and will proudly wear them as we represent such an admirable platform not only in tech, but culture. GNY to the MOON!

[BLOQspace]

GNY IN ACTION — GNY has consistently doubled the viewing traffic of website publisher recommendations compared to personal editors curating each article. Since it is possible for an intelligent employee to write "if this, then then this" rules.

[BLOQspace]

GNY swag was on display at the BLOQspace meetup we had tonight!

[BLOQspace]

We even had some community members standing guard over the GNY banner! 
We are members of the Sherwood Pool as a Lisk Delegate and some of our guests were having a great time at out community event!

[BLOQspace]

Lisk Sidechains were everywhere at our BLOQspace Community  event, can you spot the GNY banner?

[John_Muck]

Raport z LISK Londyn - moje osobiste odczucia.

Obejmuje również sidechains MADANA i GNY. LISKロンドンの会合レポート - 私の個人的な気持ち。また、MADANAとGNYのサイドチェーンも含まれています。

LISK London meetup report - my personal feelings. Includes the MADANA & GNY sidechains.

https://medium.com/@LiskHighlights/lisk-london-meetup-report-8ad0c7862469

[John_Muck]

During the duration of Phase 1 (now coming to a close), GNY Tokens are sold for $0.08 (US Dollar, Eight Cents).
This phase 1 of the sale includes a 20% discount on the price per token.

During Phase 2, GNY Tokens will be sold for $0.10 (US Dollar, Ten Cents).

GNY will peg the price of Phase 2 GNY Tokens in BTC, ETH, LISK and XAS immediately prior to the start of Phase 2.
The peg will last for the duration of Phase 2.

The GNY token sale Phase 1 is currently still open.

[John_Muck]

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.





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.

[John_Muck]

Advances in Machine learning and the proliferation of generative design with ReThink! Tile Studio .


The GNY IO team are pleased to bring forward the first enterprise group who will be using the LML Lisk machine learning platform and bring you a statement from the studio.





La Nova Tile Importers (http://www.lanovatile.com), in collaboration with ReThink! Tile Studio (http://lanovatile.com/tag), and GNY LML Machine Learning Platform (http://gny.io) using the LISK blockchain (http://lisk.io) will collaborate on a project that will utilize artificial intelligence technology to algorithmically generate realistic images of common materials such as natural stone, cements, or even wood varieties. The intent is to provide the manufacturing sector a deterministic and non-repeating image base to print onto products such as ceramic tiles, fabrics, vinyl, etc.

Once the computer learning algorithm has been successful in recreating a particular type of product, for example a specific type or marble, the team will utilize Interface Tokens (http://interfacetoken.com) and the Art Blocks platform (http://artblocks.io) to manage the purchasing and ownership of the generated graphical outputs. The entire ecosystem will operate on blockchain technology in a price agnostic ecosystem intended to disrupt legacy manufacturing processes that use pre-defined image sets printed repeatedly over the course of large scale manufacturing cycles.

GNY IO looks forward to bringing you interviews from the Rethink! Studio and welcome the first enterprise group to our ecosystem.

[John_Muck]

Lisk Machine Learning. Listings update.

Hello folks, just bringing you a minor update to the LISK Machine Learning token listing on behalf of the GNY - LML Team. Although this might actually be a major update for those of you based in the US.

As GNY HQ brings forward a series of announcements on our token trading dates, our first update is for the 'LML' token.  
 
In response to requests from the public, GNY have explored every avenue to allow US entrants to acquire LML and we are pleased to be releasing a temporary ERC20 token to ICO entrants from the 12th November, which will be listed on a series of exchanges from early December 2018.
 
Details of the swap from ERC20 token to Lisk sidechain will be announced early 2019 and we look forward to bringing the community more enterprise partners prior to that date.

Best Regards, GNY - LML Team.

Handy resources for you.

Our latest Cointelegraph coverage.

Our first Social Impact Partner, Child Rescue Coalition.

Our first Enterprise Partner, La Nova Tile Importers, in collaboration with ReThink! Tile Studio.

Interview with GNY.io CEO Cosmas Wong.

First to Launch a Utility Token ICO In Jersey, Channel Islands.

Some company history.

Lisk blockchain explorer snapshot of our current Lisk holdings to show our commitment to Lisk.

[John_Muck]

LISK sidechain project seeking positive delegates!

GNY HQ has issued a call for all contributing and positive Lisk community members to consider becoming a delegate on the LML network (LISK Machine Learning).
GNY are building a typescript based machine learning blockchain project, and if you invest in their ICO with LISK then they will also supply you with tokens on their Javascript-based Lisk Machine Learning blockchain.
The network will match the number of tokens 1:1. You will be receiving two sets of tokens; one set for use in the “Lisk Machine Learning” (L.M.L) blockchain, and the other set for use in the Typescript-based GNY blockchain.
The first Dapp that uses LML tokens has already been announced here.
The number of forging delegates on each chain is expected to be 101.
Delegates will be required to signal ownership of 187500 GNY tokens in their wallet and on confirmation of making voting position the tokens will lock.  Delegates can unlock tokens at any time instantly removing themselves from delegate position.
​Voting weight on the LML system will only count votes from locked wallets on the system. This reduces voting weight coming from exchange hot wallets.
Future delegates who are interested in receiving delegate information packs about the network can send an email requesting to be on the list. Please send emails to this address: [delegates@gny.io](mailto:delegates@gny.io)