Advertising has promising opportunity in CTV market. It is a fast growing space. The cost of streaming is reducing. The quality of content on streaming platforms is way ahead of what the broadcast TV offers. Jio pushes digital penetration with the IPL. CTV thus gets an impetus.

The growth of AI is a good trend. Advertising would be data-led. It would be more impactful with AI. Over the next three years or so, AI will definitely play an integral role in digital advertising.

Apart from connected TV, we expect other connected devices to emerge. Most of the devices that a consumer uses will eventually be connected to the internet, from refrigerators to wearables. These are new touch points for the brands.

Programmatic advertising makes precise targeting possible.

Google utilises supercomputers to train its AI models. Google’s systems are faster and more power-efficient than those used by Nvidia. Google has designed its own customised chip called Tensor Processing Unit (TPU). Google now runs its fourth generation of TPU.

Google has strung more than 4000 of the chips together into a supercomputer by using its own custom-developed optical switches.

Digital advertising is today far more measurable than it was a few years ago. The old world metrics were impressions and clicks. These days the measuring standard has changed to conversion led model. It is called cost per converted user (CPCU). This is completely ROI-focussed. It requires a strong data management platform. It enables the agency to make predictions about the kind of product a consumer may be interested in purchasing. Thus only the most relevant ads can be shown to a user, making the chances of conversion far greater. The advertiser pays the agency only when the conversion happens.

Advertising is no longer seen as a cost to the company but rather as a revenue line item. Affle uses this innovative CPCU model.

Indian is known for arranged marriages, and for a low divorce rate. Dating is a new phenomenon in India. Residents of smaller towns seek long-term relationships out of dating, rather than a one night stand. They are not averse to having a long distance friend. Daters in India have older age profile, and are ready to part with a subscription for a dating app. Sure, they should learn how to chat with the opposite sex online. The average age of the users of dating apps is 26 and above. There are MNC apps such as Tinder and Bumble. They offer extra features and have a subscription. They also earn from advertising. Subscriptions rule out the non-serious users. It invites trust in small town users. Tier 1 cities have users for both Tinder and Bumble. US based Tinder has a user base of 40 million in India (2021).

Smaller town users go in for made-in-India apps such as QuackQuack, TrulyMadly and Aisle. They are in the process of building a subscription-based model, rather than an ad-based one. Big cities seek relationships in a proximity of one kilometer, whereas small town users do not mind cultivating remotely placed relationships. They would like to connect with people all over India. They would like to sustain the friendship.

Subscription for QuackQuack starts at Rs.299 per month, and reaches to Rs.6400 a year. It boasts of 22 million users, and more than half the users were added in the last two years. It has 25000 downloads a day.

TrulyMadly has close to 14 million users. There are repeat downloads — users end up downloading the app twice or thrice. Then the downloads are 20 million plus.

What has invited the attention of the whole world is the emergence of AI models ChatGPT and its versions. It has led to a need for data annotation or labelling of the data. Data annotation is the process of labelling individual elements of training data to facilitate the understanding of machines about the nature of the data and the significance to be attached to the elements. Such annotated data is used for model training. In other words, we curate the data that goes into the training of models. Of late, data annotation has seen exponential growth. Data annotation will be an industry worth $12 billion by 2030.

Two things are necessary for data annotation — trained manpower and efficient annotation platform.

These are the days of commercialisation of AI. Some annotators are supervised. AI is being applied to different levels of production. There is an explosion of data. There has to be sifting and triaging of data. It is fed into time and test cycles. It involves considerable amount of work. This requires talented manpower trained in data annotation. In addition, there is unsupervised learning in this ChatGPT days. There is also semi-supervised learning. In such situations, there should be people in the loop.

In automobile industry, there is vehicle-to-vehicle communication and connected car technology. There are areas of speech recognition and NLP. Data annotation thus becomes an integral part of this industry.

RWS, UK-based company, has introduced TrainAI. It is an end-to-end data collection, data annotation and data validation service for all types of AI data. It employs a pool of 1 lac annotators who provide AI services in 400 plus languages in 175 countries. They collect, annotate and validate any type of AI data. These annotators must have diverse talents. A part of the work focuses on visuals. The next leg of AI machines will have big focus on visuals. Soma, a US-based non-profit organisation, focuses on visuals.

Goldman Sach made a study of the impact of AI and consequent automation in 30 countries, with eight developed countries included. According to this study generative AI could expose over 300 million full-time employment (FTE). The FTE is calculated by the scheduled hours per week an employee works divided by employer hours for full time work. To illustrate, if the employer’s full time work week consists of 40 hours a week, employees who work for the same are 1FTE. If they work for 20 hours, they are treated as 0.5FTE.

The lowest impact of AI including generative AI is in countries such as India, Kenya, Vietnam, Nigeria, Mainland China, and Thailand. The impact ranges from 13-16 per cent. In India, it is the lowest, say only 11-12 per cent.

The highest impact on work will be in Hong Kong, followed by Israel , Japan, Sweden, the US and the UK. Here the percentage of jobs which could be automated range from 25-30 per cent.

AI, on the positive side, would raise productivity by a global average of 1.4 per cent points over a ten year period. It amounts to a $7 trillion increase in global GDP over the ten years.

According to Goldman Sach’s estimate, the impact of AI on jobs will be more perceptible in developed economies.

The Consumer Protection (Direct Selling) Rules have been notified by the Government in December, 2021. These rules aim at protecting the consumers from fraudulent schemes. At the same time, these also protect the interest of direct sellers and their companies. The Indian Direct Selling Association (IDSA) has welcomed these rules. In the Rules, there is a provision to set up a monitoring committee by the state government to supervise the activities of direct sellers and direct selling companies. So far, eight states have set up such committees. IDSA is following up this with the remaining state governments.

According to IDSA, the country’s direct selling industry is worth Rs.19,000 crore in 2022. India has still a vast untapped market potential. The Act also prescribes the appointment of Grievance Redressal Officers for addressing consumer grievances within one month from the date of receiving the complaint.

After assuming office as the CEO of Google in 2016, Sundar Pichai announced that Google is the first AI tool, and predicted that AI’s effect will be greater than electricity and fire. Microsoft-backed ChatGPT has been launched, and it has flashed in headlines. There is debate about ChatGPT’s capabilities and limitations.

Google launched its AI-backed Bard on 21st March, 2023 on experimental basis, and naturally it was compared to ChatGPT and was criticised. There were issues about its capabilities. Of late, more than 1000 plus researches, scientists and industry leaders have expressed concerns about AI.

In fact, as we have already observed, they have requested to put a moratorium of six months on AI research. Google wants to strengthen Bard, and Pichai is of the opinion that the concerns about AI cannot be neglected, but at the same time AI cannot be abandoned. It has the potential to make the world a better place to live in. Google feels they have a better product, and it could be upgraded as potential pathways language model (PLM) which will give it added capacities. It is good at maths, reasoning and coding. Google is moving ahead with caution about the limited capabilities of Bard.

Pichai is in talk with Larry Page and Brin Sergey, the co-founders of Google. AI is advancing by leaps and bounds. Perhaps, it could be a threat to the society. It requires debate. No one knows all the answers. Google will continue to move ahead with its AI project.

No company would like to miss the generative AI bus. As we have already observed in a previous blog, Air India uses AI to summarise pilot briefings and to respond to frequently asked questions from the customers. Pocket FM uses AI tools, and has invested in Large Language Models (LLMs). Pocket FM wants to empower writers to produce quality audio series by using generative AI, e.g. climax of an episode could be made more peppy or a series from one language can be adapted to another language. AI can facilitate brainstorming of ideas among the writers, so as to produce great content. The writers can create thumbnail through these tools. A model can be chosen by a fashion garments company by paying fees, but photo shoots of the model would not be necessary to display the garments. The same will be managed with AI.

Google and Microsoft embed AI across their offerings. AI could be used for content creation , writing code and education.

ChatGPT is available for around $20 a month. A few users from a company can start fiddling with it. ChatGPT collected 100 million users as soon as it was introduced towards the end of November, 2022. There is wide application in content generation, visual generation and promotional message generation. Generative AI-based content itself fetches millions of dollars of revenue. Code writing is another widely used capability. As it is Co-pilot made on GPT on GitHub of Microsoft can write a good part of the code developed by a regular programmer. GPT 4 has been used by Khan Academy to help the students clear competitive tests.

Scripting should be accurate. Any wrong scripting could take a site down. Scripting is manually verified, though there is automation. AI tools are being developed that will facilitate scripting, that too with accuracy. MakeMyTrip uses generative AI.

Cutting edge AI have been developed by Deep Mind (London-based) and OpenAI (San Francisco-based.) There are other four tech giants in this field. Chinese company Baidu too is working in this field. Next to the US, China happens to be in a second position. All others are scrambling for the third position.

India too is working on indigenous version of ChatGPT. India could make headway in climate technology and biotechnology. India can concentrate on cyborgs and longevity techniques.

AI is everywhere, still it requires ethical guardrails. It is not just a substitute for search engine, but a tool to develop new things.

what3words has been founded in London in 2013 by Chris Sheldrick. It has divided the world into a grid of 3 metre by 3 metre squares. There are 57 trillion such squares. It has given each such square a unique combination of three words — a unique address assigned by a mathematical algorithm.

Customer discover their what3words address through their application both for Android and iOS devices or on their site what3words.com. India Gate, Delhi has what3words address — /// warmers.shunning.head. Gateway of India, Mumbai has what3words address — /// lampost.label.stand.

what3words communicates exact locations. It is accurate to a three metre square. These addresses are fixed and never change. These addresses are in 54 languages to date.

Indian operations started in 2019.