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Mystery surrounds the identity of Satoshi Nakamoto, the founder of Bitcoin. We cannot say with surety whether Satoshi was a single person or a small team. If he were a single person, it opens up the possibility of future innovations. It also indicates there are more unknown geniuses out there. When treated as a team, it proves that secrets are easier to keep than people think. That gives rise to conspiracy theories.

What is widely believed is that Satoshi Nakamoto is a pseudonym used either by a single creator or a group of creators who published the original white paper in 2008 and released the Bitcoin software in 2009.

It is a matter of speculation whether Satoshi is dead or alive. He has not been heard since 2011. They stopped communicating with Bitcoin community since then. It is natural to be curious about who could have created more than $1 trillion in market capitalization. If we presume, he passed away, it is logical that no longer we hear from him. Bitcoin’s ‘origin block’ is less likely to be sold. It might be frozen for ever, with its current valuation in tens of billions of dollars. It puts a stop to creation of bitcoin. Even rules of Bitcoin cannot be changed.

A living Satoshi could have exercised more sway over Bitcoin users and institutions. It is in the interest of Bitcoin if Satoshi is no longer alive.

If the original block has not been moved, there are questions about human motivation. Does it mean that people do not want to be billionaires? Why has it not been encashed? Does it mean Satoshi’s sudden death? However, even a dying person thinks of allocating funds for a cause, relative or charity. Could it be that Satoshi destroyed password?

It is an interesting story. Satoshi, if alive, thinks that aggrandizement must be avoided. Someday, we may learn about his identity. And that will affect our views.

A recent HBO documentary names Peter Todd, along with Adam Back. It is an open question. Why one should care? There is a great deal at stake — intellectual, financial and political. He could a product of a movement obsessed with e-cash or e-gold.

Thus, potential Satoshi candidates could be Nick Szabo, Hal Finney, Wei Dai. David Chaum and Douglas Jackson among others. These are experimental movements. They suggest direction and should not be judged on the success or failure of the movements.

Since Satoshi alive could have hold over a million Bitcoins worth billions of dollars, there is no such movement from their original wallets, and hence the mystery persists. The original block is also known as the ‘genesis block’. It denotes fixed supply. It presupposes creation through the process of mining — solving complex math problems and get Bitcoins as a reward. The original block has historical significance — the timestamp, the initial block hash and a message from Satoshi. It is one-of-a-kind artifact, a cornerstone of Bitcoin’s existence.

We are at an important milestone that marks the reaching of 3000th write-up on Marketingganga. Of late, we have focused on AI, keeping with the latest development on marketing landscape. Thank you all and hope the blog will keep you updated with the latest and the best.

Microsoft and OpenAI are in partnership for the last five years. Microsoft has funded OpenAI to the extent of $13 billion. However, OpenAI is still in need of funding, and is expected to lose $5 billion in 2024. The disagreements between employees of the two companies and the financial pressure have strained their five-year-old partnership.

AI startups depend upon Big Tech for money and computing power. In addition, Big Tech controls massive cloud computing systems which small outfits use to develop AI.

The partnership has benefitted both the companies. OpenAI is negotiating again with Microsoft to secure more computing power and reduce expenses. Microsoft is reexaming its dependence for AI work on OpenAI. Microsoft would like to hedge its bet. In March 2024, Microsoft spread $650 billion for manpower needs to hire staff of Inflection, OpenAI’s competitor. Mustafa Suleyman oversees a new Microsoft group working on building AI (based on OpenAI’s software). It is a long term effort that could replace what Microsoft is getting from Open AI.

OpenAI may not like this development. Many Microsoft engineers work onsite at OpenAI’s Offices in San Francisco.

OpenAI is in a bind after Microsoft’s reluctance to fund further. It requires cash to keep things going. It negotiates with other companies to buy computing power.

We have already studied the concept of Internet-of-Things (IoT) which emerged a decade ago, and was branded as a major advance in technology. It looked promising in applications — smart cities, smart homes and smart industries.

However, today AI has been in the limelight and has taken the center stage. IoT was ubiquitous sometime back — was embedded in devices and objects so as to convert data into actionable insights. It looked promising in diverse fields — from traffic management to healthcare. AI has overshadowed IoT, especially after the emergence of generative AI.

IoT has not failed or disappeared. However, it is no longer the sole protagonist. IoT utilizes data, senses the environment and provides the raw material for decisions. These decisions are facilitated by AI which processes the data. AI facilitates real time decisions and predicts outcomes. AI also facilitates automation. Jointly IoT and AI have created Artificial Intelligence of Things (AIoT) — a new hybrid.

IoT is present in over 14.4 billion devices (2023). This growth could be attributed to advances in wireless technology, miniaturization of sensors and cloud computing. Yet this seamless integration is yet to materialize in India. On an individual level, IoT devices have integrated with our lives — smart watches. In Industry 4.0, IoT sensors allow us to exercise control over operations. Industry is adopting IoT for predictive maintenance and efficiency. However, this revolution has not proved to be transformative.

AI has tremendous ability to process data in real time. It can analyze video streams. It can crunch data from millions of sensors. Thus, it is indispensable. Investment is being committed to AI.

India lags behind in formulating the standards for IoT adoption. There is no unified global body to regulate IoT standards. This makes compliance difficult. It can stifle innovation. Instead, the system becomes vulnerable without harmonized global standards.

Both IoT and AI should contribute to the bottom line to promote their higher adoption. IoT and AI can help citizens by alleviating civic chaos. There is a need for investment to build capacity. There should be arrangements for training at all levels. There should be adoption at grass roots.

IoT, AI and cloud computing should be integrated and synergized. AI has IoT as its younger sibling. They are disruptors. Both together will shape our future. Leaders must direct these technologies for development, since technology by itself is neutral. It all reduces to the choices we make while using technologies.

Far from being a dismal science, economics is emerging as an exciting science. However, certain things come in the way of this growth of economics. It has become too insular. Majority of economics prize winners have spent half their career at just eight universities — Harvard, Yale, Princton, Stanford, MIT, University of Chicago, Columbia and Berkley. In other fields, talent is wide-spread, but in economics it has a high level of concentration.

Economic research justifies the laws of demand and supply. There are subtle innovations. Radical ideas are rare. It explains the geographical concentration. In other fields, a pathbreaking research, say of mRNA vaccine technology may not earn the researcher a professorship at the top university. Some pathbreaking research work say in antiobesity drugs has been done in Denmark, far away from the US research labs.

In economics, there are standard toolkits for economic issues, say inflation, recession, fiscal policy, deregulation etc. Economics just argue about the right mix of these policies from the toolkit. There are no novel solutions, no new drug to be discovered.

However, economics does not become less scientific in the absence of this novelty. Brazil controlled hyperinflation using economic policy three decades back. Some time-tested remedies could be tried even in contemporary scene. Many nations have achieved fiscal consolidation using standard economic advice.

In microeconomics too, there are many remedies.

Of course, breakthroughs in economics are rare, but the economists have built a protocol of solutions to the real-world problems.

By 2031, the UAE wants to become AI leader. It is leveraging its oil wealth to attract new talent and fund research in this area.

AI flourished in Silicon Valley. It is now expanding beyond it. It has reached Malta and Paris. It is spreading worldwide. The UAE wants to emerge as a key player in the middle east.

In 2017, the UAE has appointed the world’s first AI minister. They are developing AI infrastructure. The UAE has created the Mohamed bin Zayed University of AI in 2020. They have established several AI-related laws and regulations. The UAE Council for AI promotes public-private partnership.

Abu Dhabi and Dubai have been ranked as the smartest cities in the Middle East and North Africa region.

Amazon would like to expand its prime video business in 2025 by introducing advertisements in five new major markets including India. The ads in India will be limited. Already, Amazon includes ads on Prime Video in the USA, the UK, Austria, Canada, France, Germany, Italy, Mexico and Spain. There is an option to viewers in these countries to receive an ad free feed by paying. The same model will apply to the new countries being added this year. There will be an ad-free option at a price.

Netflix too is considering a free ad-supported tier in India. It is also testing pause ads. Amazon’s ad supported feed will help brands connect with new audiences.

Since streaming costs are on the rise, it was just a matter of time before Amazon Prime changed its traditional model to include ads. It is not possible to scale up subscription model beyond a point.

India has 547 million OTT users, but active paid subscriptions remain stagnant at 99.6 million (Ormax OTT Audience Report, 2024). Ad supported video (AVOD) has grown 21 per cent as compared to previous year. However, subscription-based video on demand (SVOD) has reported a growth of just 13 per cent. Growth has slowed down, since most people who can afford subscriptions already have them. To grow, companies must attract new audiences and encourage current subscribers to buy more subscriptions. On an average, a city dweller, has four subscriptions. That is a tough call.

TSMC — Taiwan Semiconductor Manufacturing Company — was established in 1987. In those days, they did not have a strong talent pool and established R&D. There was no capital to produce VLSI or very-large-scale-integration semiconductor system. Still TSMC has emerged as a leading company making world-class fab for semiconductor chips by the late 1990s.

TSMC focused on ‘fab alone’ approach. It integrated with the needs of fab-less chip designers. It evolved a good supply chain. It sourced silicon wafers from Japan and S. Korea. It sourced chip designs and lithographic machines from the USA. and Netherlands. It sourced engineering talent from India. The shipping costs were higher, but were compensated by high purity of silicon wafers, novel chip designs and error-free chip fabrication processes. It was an international sourcing strategy that worked for over four decades.

The recent legislations in the US has changed the supply chains. Chip design and fabrication has moved back to the USA. Post-fab operations (assembly, testing, packaging) are friendshored to strategic partners.

TSMC has set up a unit in Ohio, US to adopt the onshoring policy on fabs. It has included India as a service provider for outsourced semiconductor and assembly test (OSAT).

In Indian Semiconductor Mission (ISM), there is emphasis on electronic design automation (EDA) tools and GPUs.

ISM also incentivises production by production linked incentives (PLI) schemes.

India’s R&D work for high precision fabs makes it suitable to nearshore operations to India.

IPR may have challenges as India emerges as a nearshoring destination for advanced fabs from abroad. There should be strengthening of patent laws and contract laws.

In semiconductor ecosystem, there are chip yield related risks as the firms upgrade to advanced nodes. There should be revolving financing facility to cushion risks of capital loss.

Three economists based in the US have won 2024 Nobel economics prize. Simon Johnson, MIT, USA emphasizes the importance of societal institutions for prosperity. James A Robinson, University of Chicago, USA focuses on European colonialization which had divergent impacts across the world. Daron Acemoglu, MIT, USA emphasizes the need for democracies to reclaim better governance.

We see the differences between the rich and poor countries. There is persistent income inequality in these countries. Though some poor countries become richer, they still lag behind the richest countries. Of course, some inequality can be attributed to historical reasons. However, there are strong reasons to believe that institutional differences explain the disparity. This theory has been espoused by the trio to win the Nobel this year.

How do we define institutions? These are the economic and political structures that stimulate growth agenda. In short, it denotes an inclusive regime, which is largely democratic. It means a strong legal system, and judiciary. There are transparent laws of doing the business and collection of taxes.

By contrast, there are autocratic regimes where there is no rule of law. There are institutions which exploit the people.

The trio traces their theory to colonization. They examine the progress of colonies post-independence, linking it to the existence of institutions and their quality. Some colonists were exploitative and worked for their own benefit. Some built political and economic systems for the long-term benefit. This varies. Where colonists became settlers and built institutions, they contributed to development.

One important take away from their work is the importance of democratic set up. The second take away is the creation of the right institutions. Protection of private property is an important tenet of such a system. It is protected by a good judicial system.

Though China is autocratic, how it could achieve development. It should be noted that amidst pockets of development, there is immense inequality within China. Here the government owns large part of the means of production. It is not an optimal solution.

Singapore is another exception. Though it is not democratic, it has strong institutions. It can be considered an outlier.

India too happens to be the fastest growing economy and has a good institutional set up. Yet India has still to cover a long distance to become a developed economy.

Nobel laureate trio has no specific solutions and yet they have rightly emphasized a democratic regime which fosters the building of strong institutions to promote growth.

Autonomous AI functions independently without any human intervention. In traditional AI, there are pre-defined algorithms. In autonomous AI, there is ability to adapt, evolve and improve itself over a period of time. It recognizes patterns and makes decisions. In the process of evolving, it can match human intelligence and may even surpass it.

In the last seven decades, autonomous AI has continued to evolve. The early start was the Stanford Research Institute which developed a robot called Shakey in 1966. In the meantime, there was revival of neural networks. General Motors developed an industrial robot Ultimate in the 1980s. Then there was a 20-years pause. Again, autonomous AI gained momentum in the late 1990s. The concept of self-driving cars is in public domain. Tesla and Waymo are gathering data from multiple sources and are interpreting the data so as to attain smooth navigation. Autonomous robots have entered the manufacturing operations and perform repetitive tasks along with humans and sometimes they perform these tasks independently.

The increase could be attributed to the availability of large volumes of data and the computational capacity to process it and the breakthrough in deep learning. The models make decisions in real time. There is optimization of the supply chains, and financial transaction become error-free. Analytics enable faster decision making.

Of course, there are limitations of autonomous AI. Autonomous AI still falls short of comprehending nuanced context of patterns or decision making. It is good at handling specific well-defined tasks. Some tasks cut across multiple domains or relate to unfamiliar environment. Here autonomous AI does not fare well. Another limitation is its prohibitive cost. There are limitations of infrastructure, internet and sensors.

Despite the limitations, autonomous AI is gaining ground. It is being used for water distribution, electricity grids and waste management. E-commerce firms are using it in warehouse management. Banks are using it for fraud detection.

AI is advancing by leaps and bounds. In data centers, AI workload will constitute 50 per cent of infrastructure by 2025. AI can process voluminous data in real time. It relies on advanced hardware — GPUs and TPUs. These accelerate training and inference processes

Traditional data centers are modified to handle the complexities of AI workloads. It involves adaptations in network architecture, storage systems and data transmission.

The challenge is not the storage of data. It is about how fast data can be processed, analyzed and used.

There should be integration of compute, storage and networking into a single system. It is a hyper-converged infrastructure. Then there is edge computing to allow processing of the data closer to the source.

If the computational power is enhanced, there is a great demand for energy. Then there are issues of cooling — say liquid cooling to dissipate heat generated by powerful hardware.

This is about how AI is driving the demand for data centers. AI also helps in the management of data centers. It optimizes operations. Routine tasks are automated. AI is used for traffic routing and load balancing. It helps in allocating resources. It prevents hardware failure through predictive maintenance.

In future, data centers will evolve further using advances in quantum computing, new cooling technologies and more integration of AI into data center operations.