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#Blockchain benefits for Innovation: Disintermediation, Security, Autonomy

The Blockchain brings together three innovative technologies: decentralized architecture, cryptographic protection, crypto-currency issuance.

 

What is the Blockchain?

Literally, a blockchain designates a chain of blocks, digital containers on which are stored information of all kind: transactions, contracts, property titles, works of art … All these blocks form a database resembles to pages of a big accounts book. This book of accounts is decentralized; that means it’s not hosted by a single server but by a part of the users. The information contained on the blocks is protected by several innovative cryptographic methods, so that it is impossible to modify them. Finally, the Blockchain creates a crypto-currency that allows it to remunerate certain nodes of the network that support its infrastructure.

 

1st Innovation – DISINTERMEDIATION: Consensus replaces centralized validation

The first innovation of Blockchain is to generate the confidence necessary for agents (users) to exchange without control of a trusted third party.

Example – The banking system

International transfers are expensive and require several days of processing to be done. In contrary, a transfer with a crypto-currency like Bitcoin is almost instant, secure and free.

Technical explanations

– In order for a transaction to be carried out on the Blockchain, its information (volume of available funds of the issuer, recipient, volume transferred) must be integrated into a block.

– To do this, the transaction must be validated by several nodes of the network (called “miners”) that verify its conformity by solving a complex cryptographic problem (and IT power consumption for Blockchain energy impacts). This result is certifiable thanks to “Proof of Work”. The whole operation, and this is the key word, is called “mining”.

– Once all the minors agree on the validity of the “Proof of Work”, the transaction is integrated into a block. This is added to the “chain of blocks”.

Political Property

The addition of new blocks is the result of an agreement among the actors of the network, which makes the control obsolete by a reference institution. This agreement is the vector of disintermediation and it is incarnated by the collective validation of the “Proof of Work” or “Proof of Stake”.

                                                                                                                        

2nd Innovation – SAFETY: The decentralized architecture and the code block guarantee the inviolability of the information

Two mechanisms guarantee the structural security of the information recorded within a blockchain: a cryptographic process and a decentralized architecture. I’ll explain them separately.

Example 1 – Time-stamping

The proofofexistence.org website demonstrates this inviolability “by design”. It allows to save documents on the blockchain of Bitcoin network to justify its possession at a given moment. Because the document is written on the blockchain, this is enough to prove that the document exists at time T and has not been modified in T + n.

Technical explanations

The code of each new block is built on their previous block in the chain of blocks, so that modifying a block would involve changing all the blocks in the cord, which is impossible.

 

Example 2 – Wikileaks

Before their broadcasts in the press in the summer 2010, Wikileaks has recorded US State Department’s confidential documents on a multitude of worldwide servers. Instead of a single “cookie jar”, the decentralization of hosting makes it virtually impossible to delete all copies of documents. The same logic works for Blockchain.

Technical explanations

Within a blockchain, all the blocks are replicated in the nodes of the network, not in a single server. This decentralized architecture acts as a structural defense against the risks of data theft.

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Political Property

These two mechanisms guarantee the security of the information recorded on a blockchain. The strength of the Blockchain allows its use for sensitive information.

 

The Blockchain and privacy

The list of blockchain transactions can be consulted by all: this transparency is necessary so that the members of the network validate the inscriptions on the blocks and makes it possible to fight against the fraud. However, the identity of each user is concealed behind a pseudonym of 27 to 32 characters. A blockchain is not anonymous but pseudonymous.

 The transparency degree of a blockchain can be adapted to very high confidentiality requirements, which are then referred to as opaque blockchains. Conversely, if necessary, the identification may require several proofs of identity and must be completely transparent: the Blockchain is a modular technology.

 

3rd Innovation – AUTONOMY: The creation of a crypto-currency recompense the infrastructure costs

Today, online services (social networks, payment, hosting, etc.) are backed by platforms that assume the infrastructure needs. In the case of Blockchain, the computing power and the hosting space are provided by the nodes of the network themselves. The physical investment, the computing power and the storage space consumed by the mining are compensated by the emission of bitcoins (or other crypto-currencies).

Computing Power Example: BitShares.org

BitShares is an exchange and service platform backed by the Bitcoin blockchain. In June 2015, BitShares managed to execute more than 100,000 transactions in a second, a performance at global stock markets.

Technical explanations

– “miners” allocate a part of the computing power of their personal machine to solve the cryptographic problems necessary for the validation of transactions (“mining”). This is a remunerated activity.

– The first “miner” to validate a block (set of transactions) wins “tokens” whose nature differs according to the concerned blockchain.

– This opportunity for financial gains leads to a competition between “miners” to be the first to solve the problem and to suggest a “Proof of work”. This competitive situation is pushing the “miners” to invest in powerful machines and thus increase the computing power of the blockchain.

Moreover, as seen in the previous point, the blockchains are housed by the nodes of the network: some of them have a local, exhaustive and identical copy of the whole concerned blockchain. Hence the analogy with an account book shared with the actors of the network.

Political property

Within a blockchain, the infrastructure is no longer concentrated in the hands of an organization but is, on the contrary, broken out in all the points of the network. De facto, a blockchain is self-supporting and independent from third-party services.

 

Understanding the debate between public blockchain and private blockchain

Explanations

Blockchain technology is adaptable: the degree of blockchain opening can be limited to create a so-called “private” or “association” blockchain. This model is different to so-called “public” blockchains, such as the one behind Bitcoin, which anyone can consult and use. Within a “private” blockchain, block validation is performed by a more limited number of nodes on the network. As a reminder, only these nodes have access to all the information.

Example

Financial institutions are preparing for the deployment of a “private” blockchain where the validation of blocks requires only the approval of 10 institutions, as opposed to validation by the entire network. If the majority consensus idea is undermined, this model has advantages in terms of timeliness and infrastructure costs.

Issues

The situation is similar to that of the Internet network where private intranets coexist with the public Internet: the public / private blockchain debate is ideological and technical issues. Some members of the original Bitcoin community have a negative view of the privatization of a technology thought and designed to be open.

Understanding the #Blockchain Economic Revolution

The Blockchain is a revolution that is undoubtedly leading to a complete overhaul of economic activity. It’s not a simple geek trend but still most people have absolutely no idea what the blockchain stands for. It’s essential to distinguish clearly the differences between bitcoin, crypto-currency and the breakthrough of technology underlying below the nameà the #Blockchain. You must know that there are several types of blockchains on the market, and bitcoin is another version of it which got huge success in recent years.

 

To be short, #Blockchain is an information storage and transmission technology that is transparent, secure and operates without a central control unit. Transactions between network users are grouped in blocks. Each block is validated by the nodes of the network called “minors”, according to the techniques that depend on the type of block. This process puts everything on trust between the market players without going through a central authority. It’s an open source system where each link in the chain offers autonomous legitimacy. The decentralized nature of the chain, coupled with its security and transparency, suggests a revolution of an unimaginable enigma. The fields of opportunity open far beyond those who have access to the monetary sector.

 

In fact, it is a revolution, as has been in human history, the advent of commerce. When individuals bought and sold their products face to face, with the handshake, the trust was established. Second, globalization has created new needs. Entities have been set up to protect sellers and buyers. Laws and legal services have developed around financial exchanges. Each market had to have intermediaries at the grass-roots level, without it being possible to assess or quantify a degree of trust between people. What changes with the blockchain is not only its decentralized aspect, but also absence of intermediates. Blockchains could replace most “trusted third parties” centralized by distributed computing systems. More than that, many observers highlight the blockchain as an alternative to any back-office systems in the banking sector. It would also help eradicate corruption in global supply chains.

 

The boom of the Internet offers some good indications on how the blockchain could develop. The Internet has reduced communication and distribution costs. For ex, the cost of a WhatsApp message is much cheaper than an SMS. Just as the cost of a software or an online platform is cheaper than having to sell its products through a physical store. The marginal operating costs, thanks to the Web, have been reduced to almost zero. This has caused profound changes in the telecommunication, media and software markets. The Blockchains result allowed to limit all marginal transaction costs close to 0.

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Blockchains are a low-cost market disruptor for any business that acts as an intermediate in market. They allow things that have never been possible by using existing infrastructure and financial resources. We can exchange things that were not previously considered assets. It can be data, our reputation or unused power. The possibilities are as vast as they are unimaginable, but that does not mean that each type of element will be profitable for a company.

 

It is preferable not to dwell first on the technological aspect. It is much better to focus on the root of your customer’s problem. Successful businesses know how to identify, what is missing or a concern to their prospects, and know how to solve it. Blockchain technology is valuable in a setting where data has to be shared and edited by many unapproved parties. That is the infrastructure. The added value comes from the services that are built around it, with applications or modules.

Currently we are in the infrastructure market phase, there are still standards or platforms to democratize blockchain technology. In the near future, thanks to the crazy pace of development of this system, it will be easier for developers and entrepreneurs to use the blockchain on a daily basis. As easily as the MySQL or MongoDB databases we use today. Once the infrastructure stage is over, the evolution of blockchains will really become exciting. The infrastructure will be a huge database on which companies will be able to operate all kinds of connected objects or devices. The connected devices will collect data, blockchains will ensure, shear and process data; Artificial intelligence applications will automate activities.

 

Just imagine these farms where the product is grown and picked up by robots, delivered at home via drones, with a connected refrigerator that alerts us when we need something from there. An artificial intelligence system manages presets objectives to perfectly match the supply and demand. Blockchains are much more than just a bitcoin. They are the real building blocks of our future world.

Managing Data Traceability: Impact and Benefits

Data is at the heart of digital transformation. A company can’t support data lacking integrity if they aim to advance in their digital transformations initiatives.  The integrity of the data lies primarily in the confidence that users can have in the latter. Most of this trust rests on the traceability of data. In the absence of traceability, it is not possible to know if these data are trustworthy.

 

Data traceability is a concept that companies have been trying to understand for some time.  You might be asking for which reasons do today’s companies need more traceability? Well with a large amount of data from unmanaged external sources (sensors, data streams, Internet of objects), it is essential, for companies, to monitor these data when they are collected, processed and moved to be able to use them effectively. Digital transformation requires higher levels of data integrity. Indeed, companies need to have better data, which can be a basis they can trust.

 

Previously, data traceability was based on two dimensions: “where” and “how”. The need for better analysis and exploitation of the data leads to new demands and extends the definition of data, adding the following dimensions: “what”, “when”, “why” and “who”. Faced with these new requirements, it is necessary to master the bases of the primary components of the type: “where” and “how, especially as regards the impact and the value to be realized.

 

The “where” component of traceability focus on the origin of the data. The “how” component focus on how the data source was manipulated to produce its result. It is also possible to refine these two types of dimension via their level of granularity: “low” granularity and “high” granularity. The “where” component at the “low” granularity level focus on defining an upstream output dataset at the point of consumption to understand which dataset have been used to produce a result. The “how” component of the “low” granularity level focus on the transformations applied to the set of data source to produce the output dataset. On the other hand, “high” granularity level of traceability is concerned with the values ​​of data in the “low” level granularity: instead of where they were created and how they were modified to produce the result.

 

An example will better illustrate the types and granularities of traceability. Let’s take an accounting report, showing the total amount paid to suppliers over a given period. The “where” component of the “low” granularity level would trace all output data from the source invoice to the supplier tables from the accounting application. The traceability component “how” of “low” granularity level would look at how the supplier and billing tables were linked together with the calculation functions that were performed on the billing table to produce the total amount paid to each supplier. Traceability “where” at the “high” granularity level could (to search for the amount paid to a vendor) trace back to the invoices provided by the supplier. In order to take interest in the entire process, traceability at the “high” granularity level could also link to the original request: the purchase order, the receipt operations, in addition to the payment approvals.

 

Benefits of using data traceability

 

Declined in many forms, traceability can provide many benefits in terms of impact and added value to the companies that implement it. Such as:

  • Governance: Ensure the traceability of upstream data to provide owners and data sources with quality and access control results. This will allow data owners to manage their procedure in addition to downstream traceability (integrated with a corporate glossary, data traceability can allow data managers to control current definitions and understanding of terms and fields of data).
  • Conformity: Provide regulatory authorities with information to govern data sources, users and their behavior.
  • Change Management: Enabling users and developers to understand the impact of modifying certain data on downstream systems and reports.
  • Development of Solutions: Improve design, testing and deliverables of better quality. This is achieved through the sharing of traceability metadata, glossaries, and relationship among distributed development teams.
  • Storage Optimization: Provide as an input to archive decisions and provisions, an overview of the data being accessed and indicate where, how often and by whom access is permitted.
  • Data Quality: Improvement of the quality scores defined by the application of business rules and standardization on data, added to the metadata population as input of algorithms and decision making.
  • Problems Resolution: Helps in the analysis of root causes in repair-type processes.

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Traceability also brings a deeper advantage such as focus on the changed values ​​of the basic data entities that are shared between processes, services, and applications. For example, the impact that a change in, position, service, address or even the employer of a contact might have on the marketing, business or maintenance service of a business. According to the “U.S. Bureau of Labor Statistics,” an employee has on average 11 different employers throughout his career. Taking into account the speed at which US residents move and change their professions each year, the potential change in baseline data may be important in light of the adequacy of these statistics to the population of basic data within a company. The ability to collect, validate, distribute and track these changes in a timely manner could lead to better protection of existing revenue streams and the ability to capitalize on new revenue in B2B or B2C business relationships.

So, the companies which take advantage of traceability, are able to find data faster and are better able to support security and privacy requirements.

The Impact and Challenges of Artificial Intelligence for Next-Gen Enterprises

Artificial Intelligence (AI) is not a new phenomenon. It continues to develop and its applications are already very present in our personal daily life (gaming, robotics, connected objects …), arousing as much enthusiasm as fear. This complex concept gained its success in the science fiction world. Although AI is still calling for a more or less fantasized imagination, it is an integral part of reality, and it can be found in many services, systems and applications.

 

What can be the role of artificial intelligence in the enterprise of the future? Will AI make organizations smarter? These are the main questions that have motivated big companies, with the objective of analyzing and anticipating the impacts of this revolution in progress. In this post, I’ll be discussing organizational, legal and ethical issues related to the governance of artificial intelligence in large enterprises.

 

A critical factor in adapting the company to the evolutions and challenges of AI environment is to rethink relationship with the company’s stakeholders, and in particular with the customer. It doesn’t mean that one must highlight that “the customer is important” but to emphasize the interaction with the customer. With that being said, client exists only through the interest and interactions developed with them.

So, the question companies should ask is how can they develop a successful interaction with the help of artificial intelligence? What does this mean concretely in terms of channels, content, customer knowledge and, above all, commitment to the customer?

 

Some companies have “Innovation and prospective” unit to carry out an analysis and a reflection of AI impact within the company. This is to take the step without neglecting the employees who are at the center of the subject. These cells allow the sharing of ideas. As the applications of artificial intelligence within the company are diverse, such as increase of human expertise through virtual assistants; optimization of certain products and services; new perspectives in research and development through the evolution of self-learning programs. The objective of this unit is to exchange in order to make the prospective, in a participatory way, through conferences, roundtables, written reports or scenarios, depending on the choice of the structures.

 

The Impact of Artificial Intelligence for Enterprises

 

Artificial intelligence technologies are already anchored in our daily lives. These technological advances intensely question the managerial and organizational practices around innovation in large companies. Many conducted surveys demonstrate that in general, companies do not have a dedicated budget for artificial intelligence. Nevertheless, there are either investment projects or resources that can be allocated to artificial intelligence teams integrated into the wider data teams. Be that as it may, the subject of artificial intelligence is present in large enterprises; It may remain theoretical but may also be the subject of initial experiments, notably concerning the predictive algorithms. Artificial intelligence does not fundamentally change everything in the company, it will rather “increase” performance, automating or perfecting certain processes and / or operations.

 

Benefits for organizations:

 

Today, artificial intelligence already generates many benefits for organizations, notably by:

  • Responding to Big Data issues; Artificial intelligence relies in large part of the search and mass analysis of data from which it can learn;
  • Increasing human decision-making expertise, online help assistant: a Hong Kong-based company, Deep Knowledge Venture (DKV), possesses, for example, artificial intelligence at its board of directors. Vital (Validating Investment Tool for Advancing Life Sciences) who makes investment recommendations and is also entitled to vote;
  • Optimizing services and products: improving customer knowledge, decision-making and operational processes;
  • Strengthening systems security: in the area of ​​cybersecurity, artificial intelligence becomes a structuring element of IT infrastructures, in order to secure networks. Automatic recognition is well established for the detection of fraud, and experts are under way to create algorithms that will identify threats that human brains and traditional security mechanisms fail to recognize.
  • Helping to make discoveries: some companies in the field of health analyze all the scientific publications related to a particular area of ​​research, which allows them to look for new properties, new molecules.

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Challenges:

 

The challenges for large companies are numerous. Starting with cultural and organizational changes. As noted in the Telecom Foundation’s Watchbook No. 8: “The craze for artificial intelligences has been accelerated by the availability of AI capabilities in the form of APIs (on the one hand, Vision or predictive), and the source code of the platforms of Machine Learning released by major Internet operators, on the other hand “.

These technology facilitators will keep pushing companies to become APIs (APIs) in order to optimize their resources. It is therefore necessary to understand the world of APIs in this transversal, cross-enterprise approach, which is not without posing a number of challenges for large companies. To succeed one must develop the fallowing roadmap strategy:

  • Build stronger relationships with clients;
  • Optimize internal processes;
  • Accelerate the development of new developments.

 

To conclude I’ll say that we live a golden age of artificial intelligence, boosted by the increasing interest of web giants for the stakes of Big Data. The first AI investors are indeed the pure players of the internet and the main players of the software. The movement is launched, and it is our responsibility to anticipate the effects of this revolution on large companies.

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