Month: July 2022

A metaverse fashion show could show models walking on water. In the background, one can put star-studded skies. The outfits are digitised. These are used by the avatars of the models. The celebrity models chosen take their fees, and their permission is obtained. Even a showstopper could be chosen. There is freedom to create the background you like. It is laborious to arrange a show in metaverse. Each outfit is scanned and then digitised. The cost of the show is reasonable, but the use of technology escalates the cost. Still there is no 5G network and many would not be able to watch the show. Individuals could be given a link or private key to access the show. If an outfit is altered, it has to be altered digitally too. There is software for metaverse but the hardware is not widely available. In a couple of years, India will catch up with others. Audience seeing the outfits virtually, and expressing their preferences makes the designer’s job easy because of the feedback.

AI/ML has found applications across different organisations. However, AI is a double-edged sword. AI could be poisoned or there could be data poisoning.

Such poisoning occurs in the ML sub-set of AI. Here the information that is used to train the machines is corrupted. It then misleads the ML algorithms.

Computers are trained to categorise information from voluminous data, say images of animals from which it has to recognise a rabbit. The system might not have seen a picture of a rabbit. However, when it is given enough images of different animals, it gets the capability to recognise a rabbit’s image.

An accurate prediction relies on huge number of samples. The volume of data is diverse. It increases the chances of correct prediction.

Professional hackers manipulate the data by labelling it incorrectly. This tricks AI/ML. Such tampering of data used to train machines cannot overcome the AI-powered defences.

The threat actors corrupt the data by introducing a malicious code. It labels the data incorrectly. Organisations must use clean data by checking that all labels being fed into the machine are correct. There could be a second layer of AI/ML algos to detect errors in data training. One should be careful about the sample size. The fewer the samples, the more are the chances of the data being clean.

AI cybersecurity is an important area and organisation must be proactive in pursuing it.

Currently, the revenues of M&E industry stand at Rs.3,141,847 (2022) or Rs.3.1 trillion (Global Entertainment and Media Outlook, PwC, 2022-2026). The revenue is likely to grow at CAGR of 8.8 per cent and would reach Rs.4,304,011 (or Rs.4.3 trillion) by 2026.

OTT revenues currently stand at Rs.130512 crore in 2022. It is likely to grow at 14.1 per cent CAGR to Rs.210,32 crore in 2026. subscriptions will account for a major portion of this revenue — 95 per cent in 2026.

TV advertising is likely to grow at 6.3 per cent CAGR to reach Rs.43,410 crore by 2026. By then, India will be the fifth largest TV advertising market globally, after US, Japan, China and the UK.

Among all the segments, cinema will grow fastest at a staggering growth rate 38.3 per cent CAGR to reach Rs.16,198 crore by 2026.

The internet advertising market is set to increase at 12.1 per cent CAGR to reach Rs.28,234 crore by 2026. Mobile advertising will account for almost 70 per cent of this market. Display advertising dominates the mobile sector (say 90.7 per cent). By 2026, the share of display advertising on mobile will fall to 88.9 per cent.

The music, radio and podcast is expected grow at 9.8%. CAGR to reach Rs.11,536 by 2026. The recorded music industry is making steady progress. The live music industry remains small.

Newspapers and consumer magazines have advertising revenue of Rs.26133 crore in 2022, and this is likely to reach Rs.299,45 crore in 2026.

The epicentre of finance these days happen to be the new breed of neobanks which operate with digitally managed bank accounts. They do not have brick-and-mortar branches. These days they partner with licensed banks and offer an array of financial products — savings, lending and long-term investments such as FDs and mutual funds.

These can be distinguished from the traditional banks by superior user interface (UI) and user experience (UX) together with a faster, paperless onboarding experience.

Internationally, neo-banks focus on underserved categories such as blue-collared workers and businesses. In India, their clientele consists of a mix of both the regular customers and sub-prime customers. Millennials and prime users gravitate to these banks because of vastly superior banking experience.

These make their services economical by charging minimal banking and transaction fees.

The neo-banks operating here are Razorpay, Open, Fi, Freo, Niyo, Flobiz, Zolve and others.

In 1991, we commenced the use of Internet called Web 1.0 which was static read-only internet. There were static web pages with a passive one-way engagement. It continued till the end of 2004. Its next version was Web 2.0 which we use currently. It is interactive read-and-write internet. Web 1.0 was for passive content delivery. Web 2.0 is interactive, and has led to the emergence of the social media. Here the users engage flexibly with the servers and other users, leading to the social web. It has been a user-friendly net, and with increasing speed, it has allowed the sharing of complex information. Web 3.0 is still in the making. It is being built on blockchain technology, and follows the dictum of read-write-execute. It aims to remove the intermediaries such as ISPs, Big Tech and governments. The data will be distributed across networks and no one entity will own the data. Users thus will own and control their online data.

Jack Dorsey, the founder of Twitter has misgivings about Web 3.0. He prefers a leap forward to Web 5.0 through his cryptocurrency based company The Block Head (TBH). Dorsey calls Web 5.0 a combination of Web 2.0 and Web 3.0. Web 5.0 will be built on Bitcoin. It will be a democratised web giving users direct control over their identity and data. In Web 3.0, the data being controlled currently by Big Tech, will pass on to venture capitalists who finance it. In other words, Web 3.0 could turn out to be a centralised entity. Still Web.5 remains just a favourite project of Dorsey, and has little chance to translate into reality anytime soon.

As we know already, banking software being used widely is core banking platform. At times, this core banking platform is not available, and it thus affects payments. In order to modernise its core banking legacy system, a bank can follow a ‘hollow the core’ strategy. A startup well-versed in core banking technology could be used to create new core banking modules. It facilitates the setting up of a fully-resilient active payments architecture. It ensures minimal payment downtime, even if core banking is not available.

On hacking the system by ransomware, the hacked party is asked to pay to get the decryption tools to unlock the system and have access. However, there could be an error within the code of ransomware which centres around randomness. As we know. encryption-decryption keys rely on being almost impossible to guess — these are mathematically linked pair. Digital passwords are long and could not be deciphered by forced scrolling through each possible combination to detect if it works. If the tools are not used properly, say coding one part and using computer clock time for another, the coded part could be uncovered and computer running time could be calculated before the malware is deployed. There could be intelligent guesses of the set of numbers to create a cryptographic key that could match.

Modern hacking is being used by the vast community of hackers, many of whom do not understand the tools they use. In addition, hackers and malware writers are two distinct groups. They are not experts in their fields. They are likely to repeat the flaws and provide clues to the researchers. It is not true that all hackers are geniuses.

In this digital age, there are fintech firms which offer small ticket personal loans (STPLs) to smart consumers. Mostly these loans are under 1 lac rupees, and are a sub-set of the personal loan market. There are also instant loans against credit card limits. Majority of borrowers are millenials. Such quick gratification loans are around for years, but have become very popular now. Established banks offer such loans, but are cautious, as these are unsecured. Mostly this is the turf of non-banking financial companies (NBFCs). Fintechs are new players in this field. They have better ability to profile the customers and crunch the credit rating data. They also offer BNPL loans — buy now, pay later loans. These are facilitated by the use of AI and ML softwares. They are used for medical emergencies, as advances on salaries, and towards paying rentals.

Delinquency on small ticket loans is between 7-12 per cent and with better profiling reduces 8-9 per cent. Later it could stabilize at 7-5 per cent.

There are peer-to-peer lending platforms — P2P. They, however, have a minuscule share. Many digital apps for loans started around 2015-16. There is e-KYC. However, there are many fake apps. They misguide consumers on interest rates, charge high processing fees, misuse KYC data, change their names or disappear. These commit frauds. However, even legal apps can be used for fraudulent practices.

Cockroach theory literally means that if a lone cockroach is seen scrrrying on the floor, it indicates a possibility of many more concealed behind a fridge or under the sink.

Traders often dispatch bots to prowl blockchains to detect highly leveraged positions in danger of liquidation. The collateral that backs this up is not sufficient to cover the loan. When successfully detected by the bots, the traders get a commission of 10-15 per cent of collateral sale. These are protections from insolvency. Cryptos were immune to all these fluctuations. Not any more. Cryptos have been hit and gone under $20000. The investors fear the counterparty announcement –‘ We regret that we can’t return your money right now. It is time to find the roaches and make a meal.’

Peter Higgs (84), a Scottish scientist was awarded a Nobel in 2013 in Physics which he shared with the French physicist Francois Englert. In 1964, he had predicted the Higgs boson, also called the God particle. Higgs theory belongs to a fundamental question: Where does the mass of universe come from? Higgs used the known rules of physics, from electromagnetism to quantum mechanics. Higgs raised the possibility of an unstable sub-atomic particle which could lend mass to other particles through a series of fizzing interactions. He predicted this unstable particle would be a boson, a notably massive subatomic particle that holds matter together. Boson would exist in an energy field that enabled the interactions. Boson could be confirmed for which Higgs suggested a path to confirm boson’s existence and measure the products of its decay.

Ultimately, the Large Hadron Collider (the LHC) found confirmation for the boson’s decay products in 2012. It has solved at least some of the mysteries of the universe since mid-20th century. There are many more mysteries of the universe the answers of which are still out of reach or elusive.