The Promises & Drawbacks of

The Promises & Drawbacks of Blockchain

By: Abdur Raffey Tariq

The blockchain technology might come off as a highly efficient way to share information; however, this is not always true.

If you’ve had an eye on the latest finance and investing trends, you must have come across the term ‘blockchain.’ Blockchain technology has been around for over a decade now, and has been catching a lot of steam in the business world lately. The way it has enabled fast and secure transactions, without the involvement of any middlemen, makes it of great use for business people worldwide. Let’s dig deeper into the topic to see what it is, how it works, and how it can be beneficial for your business.

Blockchain 101: What is Blockchain?

Simply put, Blockchain is an automated way of passing information from point A to B in a completely safe manner. All in all, it consists of small blocks of digital data stored in a public database, spread across a decentralized network of computers. Each block contains information about the transaction and has a unique identification code. The transaction is initiated by creating one such block, which is then verified by thousands, perhaps millions of computers distributed across the net. Once verified, it is added to an already existing chain (database) and hence gets associated with a unique history.

Since the chain (database) is spread out across many computers, it is virtually impossible to tamper with a block, hence making the Blockchain an extremely secure method of sharing information.

immutable”.

A simple example to understand this whole process could be that of a train ticket station. Each ticket could be considered a block containing all the information about the departure time, price of the ticket, etc. In contrast, the chain could be the entire train network comprising of every ticket ever sold to each person in the system. Each ticket is uniquely associated with the chain and is only accepted when verified by the entire system.

The Promise of Blockchain

The blockchain technology has the revolutionary potential to transform how businesses operate and collaborate. It has found its applications not only in the banking and finance sectors but also across the corporate world, enabling information sharing, digital contracts, processing payments, and tracking client information. Some of the leading businesses around the globe have been using Blockchain to speed up their everyday tasks, with minimum middlemen costs. VISA and HSBC could be simple examples of their use in the finance sector, whereas Walmart and Unilever have been using it in their supply chain to track the physical movement of goods. It does not stop here. The healthcare industry has extensive use of Blockchain, where companies such as Pfizer and GlaxoSmithKline have been us-

“Most of the data store in a blockchain is

ing it to manage digital inventories for various pharmaceutical products. Since the transfer of information is fast and completely secure, it has also found its way in international trade and travel. Market giants such as British Airways, Singapore Airlines, and Lufthansa have been using it extensively. The concept of ‘Blockchain for Aviation (BC4A)” was born through this industry. Every stakeholder in the value chain, including aircraft manufacturers, logistics providers, software developers, on-field staff, has been involved in the process. In this sense, Blockchain has been a disruptive force in the industry that no one can tame. It has disrupted marketplaces across the world and has proven its utility in almost all industries.

How the Blockchain Fell Short

With such a promising potential for the corporate world, there are also some areas the blockchain technology falls short in and hence takes it far from perfect for use in every industry. Here are some disadvantages of using blockchain technology.

Not as Efficient

The blockchain technology might come off as a highly efficient way to share information; however, this is not always true. As the number of participants in the network increases, the process gets slower as it requires 100s of GBs of space and too much energy to process the transactions.

Data is Immutable

Most of the data store in a blockchain is immutable. This means that once it is written, it cannot be removed. While this may help in fraud prevention, this can also raise many privacy concerns for the users.

High Implementation Costs

The implementation of a blockchain can sometimes be costly. The costs are mainly associated with hiring developers and experts to operate the whole system, while there are some fixed licensing costs as well.

Security Concerns

Blockchain may be relatively safer than the conventional transactional procedures, yet there is some vulnerability attached to the data stored. If an attacker gets access to 51% or more of the network, all of it is lost.

The Birth of Private Blockchains

Blockchain technology does spread the data across a broad set of computers across the network, but this does not have to be this way. This is where private blockchains come in. Private blockchains develop a closed network of transactions that operate within restricted parameters. Some basic access controls limit the people who can participate in the network, which leads to reliance on third parties for enabling transactions. Some providers offering private blockchain networks include Ripple, Hyperledger Fabric, and R3’s Corda. Companies such as Comcast and the streaming giant Spotify have been using private blockchains to cater to different privacy concerns while still keeping the transactions transparent.

Unique Blockchain Use Cases

There are several ways Blockchain can be useful for your business. Here are some use cases you should try out.

Financial Transactions

If you still haven’t tried out cryptocurrencies, you’re lagging way behind your competitors. Blockchain allows you to transact without any additional costs, whether the payments are international or local.

Fraud Prevention

Since tampering with a single block in the chain requires tampering with the whole network, which is almost impossible, there are zero chances of fraud. Implement Blockchain to take care of

Smart Contracts

Smart contracts present all the terms of the parties involved in the form of a code. These self-automated programs run without any downtime and make sure you get paid once you’ve held your end of the deal.

Tracking Client Data

Blockchain provides a unique connection to each block in the chain, making it easy to track where specific data is coming from. This could be implemented in marketing campaigns to see what customers are purchasing what items, and hence the campaign can be personalized.

Where does Blockchain go next?

While no one knows what the future holds for Blockchain, one thing experts agree on is that the disruptive effect it has had on the world economy is not going away anytime soon. Two industries that will be the most affected by Blockchain soon are International Trade and eCommerce. And this is not only limited to financial transactions. New and innovative use cases will completely transform every aspect of the value chain from manufacturing goods to stocking, supply chain, marketing, and customer care. Furthermore, since a significant part of the world economy will be affected by Blockchain, the governmental regulations will be high. From taxation policies to the rules of international trade, everything will be completely transformed - Abdur Raffey Tariq”.

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A GUIDE TO GANS (GENERATIVE ADVERSARIAL NETWORKS)

Generative adversarial networks (GANS) are machine learning approaches that utilize two convolutional neural networks. These networks contest to generate new data instances similar to the training set. Deep learning experts, Ian Goodfellow, together with his colleagues, were the first to propose GANS in the 2014 NeurlPS paper.

GAN is structured into two: The generator that learns to produce plausible data and discriminator that distinguishes fake data from real data produced by the generator. The discriminator also penalizes the generator for generating implausible results.

Use cases of GANs

Generative Adversarial Networks (GANS) has both positive and negative uses as they can learn to imitate any data distribution. They are widely used in video generation, image generation, and voice generation. In the real sense, GANS are robotic artists with impressive outputs that are usually taught to strangely create similar stuff in almost all domains, including images, speech, prose, and music. GANs can also be used in the generation of fake media content, and they are the technology supporting deepfakes.

1. Image to image translation. Generally, GANs are a perfect solution for the image to image translation problems. They usually learn the input to output image mapping with also the loss of functions for the mapping training. Conditional GANs are used in the generation of photorealistic images from inputs of sketches or semantic images. Many image-to-image tasks such as translation of photos from Google maps to satellite photographs, translation to color photographs from sketches, and translation of cityscapes semantic images to photographs; use the pix2pix GANs’ approach

2. Text to image generation. The automatic generation of real images from text is very useful and interesting. For instance, the stackGAN is used to produce accurate images relating to the textual description of objects such as flowers and birds.

3. Increasing the resolution of images. GAN can produce high pixel resolution output images with the Super-Resolution Generative Adversarial Network (SRGAN). This involves the creation of high-resolution images such as street scenes, human faces, and other objects.

4. Predicting the next video frame. Internal models designed with deep neural networks use a loss-based approach in predicting the future frames of synthetic video sequences with the use of CNN-LSTM—deCNN framework. This aspect is designed for the static elements of video scenes, which can be predicted up to a second.

Christie’s AI Artwork Selling At $432,000

Christie’s became the first auction house to sell an AI portrait of Edmond Belamy generated by a GAN for $432000 (almost 50 times its high estimate). The GAN was open sourcebased, which was written by Robbie Barrat of Stanford. What makes the artwork unique is that it was created through artificial intelligence by three French students who used a code from the 19-year old programmer, Barrat. The AI community has had a major step through the development of this AI portrait. Image generation with GANs is a multistep process that involves the collection of training data (scraper) that enables your network to replicate, construction of the generative algorithm. Then you begin running the algorithm and sorting out the outputs to pick the best out of the many generated results. From the Belamy story, in combination with their motto, we can truly attest that “creativity is not only for humans” with the creation of art through artificial intelligence.

Advantages and Disadvantages of Using GANs

z GANs are learning methods that require less or no supervision; they usually don’t need data to be labeled as they are trained to use unlabeled data in the process of learning the internal data representation. This is more efficient when compared to the manual process of acquiring labeled data which is time-consuming.

z GANs make the modeling of data distribution better by the generation of clearer and sharper images.

z GANs are capable of training all forms of generator networks that are required by other frameworks to attain some specific forms of functionality.

They can produce data similar to the real one, which is widely used in the real world in the generation of images, audio, videos, and texts. The images produced by the GANs are mostly used in marketing, advertisement, e-commerce, and games.

They are also useful in machine learning approaches as they can easily interpret data into various versions by going into the details of the data. The combina-

Christie’s became the first auction house to sell an AI portrait of Edmond Belamy generated by a GAN for $432000 (almost 50 times its high estimate).

tion of GANs and ML makes it easier to recognize people, cars, trees, and streets and can also determine the distance between different objects.

Disadvantages of GANs

z GANs are hard to train; they usually need different types of data repeatedly to check if it functions accurately or not.

z Generally, GANs handle a single task at a time, which makes it difficult to accomplish tasks of guessing the values of a single-pixel given another pixel. This can be fixed by the use of BiGAN that enables you to guess the missing pixels by the use of Gibbs sampling.

Other Potential Uses of GANs:

GANs are used in image editing. For instance, changing the appearance of an aged individual by changing their hairstyle cannot be accomplished with just the normal image editing tools. Still, with the use of GANs, you will drastically reconstruct and change the appearance of the image.

· Application of GANs for security purposes. Cyber threats are one of the major concerns revolving around the AI world, where even the deep neural networks are prone to hacking. GANs are in the front line to directly address the issues of adversarial attacks, which uses a variety of methods for fooling deep learning architectures. On the other hand, GANs increase the strength of the existing deep learning models against those methods through the creation of similar examples and training the models to detect them.

· GANs are used in cloth translation as they can produce photographs of similar clothes as they appear in online stores.

· They can also be used in photo inpainting (hole filling). This involves repairing and filling a missing section of an image that was reasonably removed with the use of created content.

· Generation of 3D objects such as cars, chairs, etc. with the provision of 2D pictures. Game designers also use GANs to generate 3D backgrounds and avatars to develop realistic appearances”.

Geoffrey M.

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