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In near future, India could emerge as a key market for data centers. It could face competition from countries such as Malaysia and Vietnam.

It is estimated that this sector would attract a capital investment of $100 billion in this region over the next five years. There are some factors to spur this growth — strong growth of data, the rise of AI, cloud computing and digitalization.

Indian government is looking to subsidize the setting up of data centers to avail of the AI boom. There should be ready infrastructure to avail of computing power for startups, small entities and research workers. AI system depends on compute (computing capacity), algorithmic innovations and datasets.

The lower costs make the Asia-Pacific markets attractive for setting up such infrastructure. India’s current leased data center capacity is 1-3 GW. It is the highest in the emerging markets. Malaysia may overtake India, though India has an edge with strict data sovereignty requirements.

India is already home for Big Tech data centers of companies such as Microsoft. Google and Amazon.

India will face competition from both emerging markets and developed markets. The government in India should create an enabling environment.

Johor Bahru in Malaysia has become destination for new data centers.

It is a fact that operators in established market face lower operational risk than that faced by them in emerging markets.

India is promoting the setting up of semiconductor industry in India. It is going to establish an infrastructure of 10,000 GPUs. There would be public-private partnership with 50 per cent viability funding. The private partner will add more computing power if the GPUs price come down.

As a concept, Agentic AI combines language models, custom code, data and APIs to create intelligent workflows capable of solving business problems.

It represents a shift towards more autonomous decision-making systems. Here an agent is a piece of code capable of perceiving its environment. It could be done through sight, sound or text. The decision is based on such inputs.

It could be applied to simple code generation on WhatsApp to complex functions such as SCM- supply chain management or customer engagement enhancement.

An agent takes the initiative and makes decisions to solve problems autonomously.

AI agents will be the next big thing. Zuckerberg said recently there could be more AI agents in the world than humans. Google too is fiddling with AI agents. Kyndryl is a tech player who is going big on this. It is a spin-off from IBM in 2021.

Generative AI is being used in production. Agentic AI will bring about a significant shift in how things work. Agentic AI is used when there is mixed problem solving.

The queries are directed to the most suitable agent. One agent might resort to RAG. Another accesses real-time data. The former uses internal data and the latter external data (through APIs). What results is a collaborative workflow. Multiple agents work on different aspects of a problem based on a query. Agentic AI is the future.

Agentic AI is designed to run specific functions within an organization without human intervention. Agentic AI technology is gaining traction as businesses look to automate business workflows. It also augments the output of human workers.

Some organization try to build Agentic AI alone. Most of them fail. They then turn to outside firms to build these agents for them. Or else they use embedded agents from their vendors.

Building agents is a complex process. Organization may lack this expertise in-house.

Agentic AI facilitates the use of generative AI from basic tasks to more complex actions.

The architecture is convoluted. It requires multiple models — RAG, advanced data architecture and specialized expertise.

It is a nascent field. In a couple of years, it is likely to mature.

There are some open-source models too. These models could be linked to turn them into agents. They will then perform their assigned tasks without human prompts. Building on open-source model is more efficient than creating AI agents from scratch.

There should be MLOPs plan in the organization. It was aspirational technology a few years back. It is now being realized.

Though these agents run autonomously, building successful Agent AIs requires human supervision.

Many in-house projects spiral out of control in terms of cost and complexity.

Some companies train their own Agent AIs, but many lack this expertise. In addition, there are maintenance costs in future. It is complex and resource intensive.

When outsourced from suppliers, we get ready-made agents which have been tested and refined by thousands of users. This process is faster too.

In an agentic AI system, there comes the management of robust memory management.

Building Agentic AI from scratch involves designing data structures, implementing search algorithms and fine-tuning its ability to interpret and prioritizing information. It calls for ML, NLP and data engineering expertise.

By outsourcing, we are leveraging the experience and expertise of others who have navigated such systems.

An employee has to attend his official duties. At the same time, an employee has his own family and social life. If an employee is overburdened at the workplace, this may affect his life at home. To overcome this anomaly, there are week-offs, casual leaves, and vacation leaves. The idea is to have a balance between work and life.

The employment scene has become competitive. Even C-Suite executives at corporates are expected to show results in terms of healthy bottom lines. They try to cut costs, and at times eliminate costs. In order to achieve the so called ‘best’ results, they try to extract the work of 2 employees out of one employee. The working hours are extended — some remain in office from 9.30 am to 9.30 pm and may be more. It is 12-15 hours a day at times. Some superiors ask employees to attend duties on weekends. There is so much of multi-tasking. There is reduced variable pay and there are lower entry-level salaries.

There is some fear psychosis in office.

Younger employees become a victim of such toxic environment. These younger employees may be living away from their homes. They are cut off from families and friends.

There is lack of job security. If the employees cannot fall in line, their appraisal becomes negative, and they may be sacked.

In fact, the crux of the problem is the management — the superiors who take credit for the results, and who ignore the social needs of the employees. They burden the subordinates with too many tasks with impossible and constantly changing deadlines. These bosses never stand up for their staff.

It is for the HR to see that the company has the right managerial manpower. At times, an exceptionally performing subordinate is promoted to a managerial post but may lack managerial qualities. He becomes a mediocre or substandard manager. Every good salesman cannot become a good sales manager. HR must spot the candidates with the right mental abilities, personal interests and personality traits to become a leader.

Even an ordinary technical person can be promoted as a project manager, provided he has the right managerial abilities. And an outstanding technical person cannot always become a good manager.

An employee should not feel disrespected at the workplace. It has the highest negative impact on corporate culture. Managers cannot have a sustained hostile behaviour towards their teammates.

Work culture should be inclusive, respectful, ethical, collaborative and non-abusive. The company can incorporate these in their core values.

Work stress is inevitable. There should be positive stress, that inculcates achievement motivation in employees.

Anna Sebastian Perayil, a young CA, working for EY India died and her mother wrote a moving letter to the CEO attributing the death to overwhelming workload and toxic work environment. Health costs of stress is much more. There is anxiety, depression and burn-out.

There is a necessity of good communication channels in the organisation, grievance redressal mechanism, addressing grapevine communication. A company’s management should be candid and open. Just a sugar-coated letter of a CEO is not enough. There should be communication between different levels of employees. Everyone has a vital role to play to make the organisation successful.

OpenAI has launched a new model OpenAI o1 with advanced coding capabilities. Advances in AI and the availability of such models may make traditional coding dead. It has struck the final nail in coding’s coffin.

OpenAI o1 is an advanced model with reasoning capabilities across coding, math and science. Its another version OpenAI o1 mini is also good at coding. Both cracked the recruitment interview for coding at a 90-100 per cent rate. It was an interview to recruit research engineers.

These latest models increase the risk of AI being used for the creation of biological weapons. These models have abilities to reason, solve hard math’s problems and answer scientific research questions.

It is a real breakthrough towards the creation of artificial general intelligence (AGI) enabling machines with human-level cognition.

OpenAI’s system card, a tool to explain how the AI operates, labels the new models as medium risk models as far as weapomisation is concerned. In future, such models can pose increased risk when they fall into the hands of bad actors. Youshua Bengio says the medium risk models do necessitate the urgency of regulatory framework.

Mira Murati, OpenAI CTO, says the company is cautious with how bringing o1 to the public on account of its advanced capabilities. The product will be accessible to ChatGPT’s paid subscribers and to programmers through an API. Murati informs that the current models performed far better on overall safety metrics than the previous ones.

The o1 model is trained with reinforcement learning (RL) to perform complex reasoning. OpenAI previously used transformer technology, and is now using reinforcement learning of DeepMind.

OpenAI o1 model has been code-named Strawberry. Though it is capable of reasoning, OpenAI has tried to keep how its thought process works off-limits. It has its ‘chain-of-thought’ reasoning and it arrives at an answer step-by-step. Mira Murati, the CTO, OpenAI calls this a ‘new paradigm’ for the technology.

A user invites trouble if he/she tries to get the reasoning trace. By not revealing, its raw, thought-process, the company maintains its competitive advantage. That robs the process of democratization of the language models. It is a step backwards. This way AI models remain more like an opaque blackbox.

Microsoft CEO, Satya Nadella, expects Microsoft employees to possess not only the technical skills but also the soft skills, say good communication, the ability to empathize, the ability to motivate, the ability to lead etc. He wants employees to focus on adaptability and versatility.

As an IT company, Microsoft attributes its recent progress to cloud computing through Azure.

Since environment is fast changing, employees must have strong grasp over AI and its applications.

You remain relevant in technical industry if you keep learning continuously. It requires dedication and commitment. You should update yourself on the latest developments to keep growing professionally.

Consumers are the be-all and end-all of every organisation. They should be given necessary support and assistance.

Employees must be proactive, should take initiative and work diligently. They should build relationships based on trust with teammates and consumers. They should stimulate growth in colleagues.

People are fond of conspiracy theories, e.g. Covid pandemic was a deliberate attempt to control population or 9/11 attempt was executed by the US itself. Artificial intelligence (AI) can dissuade people of their beliefs in conspiracy theories.

There was an experiment to prove that strongly held beliefs can also change when convincing evidence is presented. Some 2000 volunteers asked ChatGPT4 Turbo to test their conspiracy beliefs. Volunteers were to rate their beliefs on a scale of 0 per cent to 100 per cent. They asked volunteers to substantiate their beliefs. The researchers asked the LLM to persuade people to reconsider their beliefs. Surprisingly, this worked. There was a drop of 20 per cent on an average of their faith in false beliefs. Some 25 per cent volunteers dropped their belief level to less than 50 per cent. The results were an eye-opener. The main reason to detach from their beliefs was the availability of more information, thus diluting their steadfastness in the veracity of their beliefs. It was a competition between evidence and counterevidence. The results have been published in Science in September 2024.

There are beliefs about alien life on the earth, the sighting of UFDs and assassination of political leaders. There are reporters who present their guess work as facts. There are rumours of people eating their pets.

Logic and evidence are powerful enough to dissuade people from holding such beliefs.

Under the oversight of the RBI, SRO-FT is established as an industry-led entity to enforce regulatory standards, ethical conduct, ensure market integrity and resolve disputes. The overall idea is to foster transparency and accountability amongst the member fintechs.

Ideally, it should collect data and share it with member organisations.

SRO-FT balances the creative potential of fintech and the risks they pose to the financial system. Fintechs can rapidly adapt to technological advancements and evolving market dynamics.

The first SRO-FT is FACE or Fintech Association for Consumer Environment. It is an association of fintech lenders. It has 50 members. It has been recognized by the RBI on August 28, 2024. It promotes responsible lending and borrowing.

SRO-FT formulates standards — code of conduct, benchmarks, documentation, ad guidelines, baseline governance standards, data protection, and statutory compliance.

It monitors the activities of the members and takes actions such as counselling, cautioning and reprimanding. It can impose fines also. It can expel members. It can bar fintechs from membership — temporarily or permanently.

Deep tech refers to pathbreaking scientific research and technology. It empowers its users. It fosters new designs, algorithms, techniques and intelligence.

Here the researchers navigate the unchartered waters. India’s software power could be harnessed to accept challenges in the field of climate change, healthcare, sustainable energy and so on. It is a shift to deep tech. There is an eco-system of startups to stimulate deep tech. These startups work in the areas of AI, robotics and biotech. Some startups work in the field of rocket science and unmanned aerial vehicles (UAVs), popularly called drones. These drones could be used in defence. homeland security, logistics and other industrial applications. So much research is going in the field of quantum computing, e.g. computational fluid dynamics simulation.

Deep tech brings with it deep tech entrepreneurs. They are not pursuing profits alone. Their mission is to improve life.

The government indulges in providing a conducive environment for the growth of deep tech startups, e.g. National Mission of Quantum Technologies and Applications, National Deep Tech Startup Policy, 2023, Anusandhan National Research Foundation.

Venture capitalists finance deep tech. Their contribution is rising over a period of time.

India has a talent pool of STEM graduates. India will assume leadership in deep tech in years to come.

There are longer gestation period and higher costs for deep tech companies. There is a need for sustained investment and strategic partnerships, e.g. Microsoft and OpenAI.

Generative AI has influenced the way we seek information and interact with brands. It also affects the process of opinion formation. The portals to the digital world so far were the search engines such as Bing, Google and DuckDuckGo. These days the conversational chatbots such as ChatGPT and Gemini occupy the centre stage while retrieving information.

In past two decades, we relied on search engine optimisation (SEO) to know our visibility online. These days there is a shift to AI optimization (AIO), a new paradigm where answers are provided in natural language. Thus, we often bypass the traditional search results.

While adopting SEO, we were tweaking websites, creating key-word rich content and building authoritative backlinks. These methods facilitate the climb up the ranks of search engines. AI-generated responses present users a single synthesized response or may be two responses. These responses are accompanied by an opinion or explanation.

The aim is to be shown in the best light in an AI-generated response. AI tools we know rely upon vast amounts of data from websites and databases, social media and news articles. AIO tries to influence the data being selected and the way it is interpreted. It should be consistent with the image we intend to project.

It all starts with the training of AI models. The data floating around must be corrected if it is inaccurate. AI models can draw less-than-flattering data from different sources or may draw outdated information. The communication department of the company must be constantly on its toes to curate the data available digitally. This ensures that AI draws its data available from the right sources. AI chatbots should reflect the organisation’s preferred narrative. AIO services should always be alert to incorrect or misleading information online. They should contact the websites to update the data and should push for correct information.

Generative AI relies more on structured data. Companies should focus on such structured data so that AI-generated content reflects the preferred narrative.

AI tools should discuss even individuals and brands the desired way. Through monitoring tools, it should be seen whether AI is producing positive, neutral or negative content.

AI may give incorrect information or may offer options based upon the data the model was fed. AIO-services should offer sentiment analysis tools — to assess what is being said and how it is being said. It helps business understand AI-driven reputational risks. The marketing strategies should be tuned accordingly.

The AI-assistants must provide accurate, on-brand and helpful responses to customers.

As we know, Google was found guilty of illegally dominating online search in August 2024. Google in September 2024 is facing allegations of manipulation of display advertising in violation of antitrust laws. The market size is $677 billion. The Department of Justice and a coalition of eight states accuse Google of acquiring over years the tools used to buy, sell and serve ads. It locks up the technology behind website ads. This harms the publishers and advertisers.

There are two sides in digital ads. On the supply side are the websites soliciting ads by offering ad space. Google acquired DoubleClick for $3.1 billion in 2007. It offers the entire tech stack underpinning the chain of bidding, selling, user targeting and placement. The bid request from website passes through Google Ad Exchange. On the demand side are the advertisers who use tools that help them to place ads across the Web. Their placement availability bid too goes through the Google Exchange. The supply side tools from Google account for more than 90 per cert market share. The demand side tools from Google account for 80 per cent (Google Ads) and 40 per cent for Google Display and Video 360 ads.

Today it is rare to visit a website without seeing an ad that has not been handled by Google at some point in the chain. Google controls the entire chain — a tool for publishers to sell the space, a tool for advertisers to buy that space, and the software in the middle to mediate. Thus, Google dominates both supply and demand side of the ad tech market.

The trial will take place at Alexandria, Virginia. Microsoft was charged for anti-trust activity more than two decades ago. Thereafter Google was declared as an illegal monopoly in internet search. This advertising monopoly is the third case against Big Tech.

Google denies the charges and asserts that its tool work seamlessly with products made by competitors. It also further asserts that the case is based on misunderstanding of digital ads.

Though advertisers or publishers can choose alternative services to do each of these things, Google has the power to give better deals alluring users to use Google tools for all or most of the steps. Google owns highly valuable properties such as Google Search and YouTube, and advertisers must go through these. That further strengthens Google’s hold.

The UK’s Competition and Markets Authority (CMA) too is investigating those charges.

The Justice department backed by some states in the US is calling for a forced divestiture of Google’s ad tech stack. These companies should be separated into individual companies. The EU too is calling for the same.

Google may argue that its advertising market share is overstated. It may ask for protection of its proprietary ad tech.

Whether any such future divest of its parts will dent Google’s business is not clear. Google’s competitive advantage of user data, web analytics and browsing habits will be left untouched.