Industrial Revolution, to begin with, affected the jobs of the horses. In 1901, 3.25 million horses were at work. By 1924, there were fewer than 2 million working horses. Of course, at low level of wages, they could have remained at work, but that wage is so low that it could not pay for their feed.

These days generative AI has raised the concern about what Keynes called ‘technological unemployment.’ It is the inability of the economy to create new Jobs faster than jobs lost to automation.

AI could lead to automation of a quarter of work done in the US and Eurozone. It exposes 300 million full-time workers.

In previous disruptions, the blue colllar workers bore the brunt. However, the effect of AI is on while collar jobs as well. At least 10 percent of the tasks could be performed by AI of 80 per cent of workforce.

Bill Gates calls AI a white collar worker available to assist the working population to perform various tasks.

Human skills of understanding, translating and pattern recognition are being taken over by the machines. Automation has moved from the shop floor to offices.

Of course, AI augments human intelligence and does not replace it. Clerical and secretarial work will be most affected. There will be new occupations. People should adopt the new technology.

AI has its limitations. It has theoretical understanding of an adult, but real life judgement of a child. It follows instructions, but finds it difficult to figure out the right thing to do. It is poor at grasping the context. There cannot be automation of soft skills, e.g. empathy, relationship building, social intelligence. It can be biased. It is thus necessary to have human oversight.

AI will improve productivity. It will not replace humans. On the contrary, humans using AI will replace humans not using AI.

EU’s parliament has approved the world’s first comprehensive regulation on cryptos on April 20, 2023. There are issues with cryptos on account of their anonymity because of which they are not traceable. It encourages tax evasion, money laundering, financing of illicit trade and activities, including terrorism. At the same time, there has to be protection of the consumers as far as crypto dealings are concerned. The FTX exchange tragedy calls for attention to this aspect. Volatility of crypto assets does affect the stability of the financial system. Thus all this calls for regulation of cryptos.

Europe approved Markets in Crypto Assets (MiCA) legislation to ensure that crypto transfers are always traceable and suspicious transactions are blocked. These are applicable to Crypto Asset Service Providers (CASPs). The transfer of crypto assets should be accompanied by information on the originator (name, wallet address/crypto asset account, address, country), official personal document number, customer identification number or date and place of birth.

At the beneficiary end, information to be disclosed includes name, wallet address/crypto accounts.

If the transfer is not from account to account the originator should ensure that the transfer of cryptos is accompanied by unique transaction identifier (UTI) and records originator and beneficiary address identifiers on the distributed ledger.

Crypto asset transfers should rely on suitable technological tools which facilitate identification of individual transfers.

CASPs should be incorporated within the EU as a legal entity.

Thus the travel rule of traditional finance will apply to crypto transfers. There is record of the transaction at both the sides — originator as well as beneficiary side.

There are measures against market manipulation and curb the dubious activities in the law. It envisages a public register under the European Securities Markets Authority for non-compliant asset providers (operating without authorisation).

Service providers must disclose their energy consumption. It would also cover transactions above 1000 euros from self-hosted wallets when they interact with hosted wallets of CASPs.

CBDCs are not covered under this law.

Accounting and audit firms such as Deloitte, Earnst and Young (EY), Pricewaterhouse Coopers (PwC) and KPMG have added several other professional services, say management consultancy, corporate finance, legal services and technology services.

Deloitte and EY has almost a lac of employees in India, of which 30000 are in tech practice. Of the 50000 employees of PwC, 27500 are techies. KPMG has a manpower strength of 40000, of which 13,500 are in tech practice. In a sense, these Big Four accounting firms directly compete with the IT services firms.

These accounting firms facilitate the transformation of the organisation. The tech team works on addition of systems. They see the design and maintenance of these systems.

There is an issue of integration. IT staff helps in this integration. The tech staff has specialists from the fields of data science, cloud, application development, automation, AI and DevOps. They provide solutions of SAP, MS, Salesforce, Oracle, Workday and ServiceNow.

KPMG expanded in India as banks were being computerised. The firm took advantage of the demand for cybersecurity. They also focused on customer-facing technology, rather than backend.

These firms also use their experience in product development. They are looking forward to working with future technologies such as metaverse, Web 3.0, 5G, edge computing, quantum computing and generative AI.

Endel is Berlin-based audio technology company. It trains its sound engine on thousands of in-house stems (stem-tracks) to create customised ‘soundscapes’ for the listeners by adjusting to external environment, say rain or sunshine, or the cardiac pace of the listeners or the temperature at the time of listening. It is called ‘functional music’. It plays in the background and collects billions of streams per month. In fact, here human beings listen to the machines.

Endel has released an AI lullaby with Canadian artists Grimes and has tied up with Amazon for playlist partnership.

So far, so good. However, in future an AI-generator chatbot could produce music like Reshamiya or Vishal-Shekhar from scratch. AI has already created snippets in various genres, and imitated the style of lyricists, and adopted vocal chords and timbres of various singers.

Music companies have taken steps to prevent the streaming platforms to scrape the back catalogues of artists to train their machines. In the past music was disrupted by MP3 file sharing some twenty years back. Now this new disruption has come from AI.

Top artists who are stars account for 90 per cent of streams. They are future-proofed. An artist-centric payment model could be developed to favour the music people listen to in the foreground. The real issue is for those who are the runners up.

Music companies should also distribute the proceeds of the streaming music in a fair manner so as to encourage new talents.

Quantum technology is based on the principles of quantum physics which studies matter and energy at the most fundamental level. In this study, the classical laws of physics do not apply. It is the study of the behaviour of the building blocks of nature.

Quantum physics has facilitated innovation and we have got devices and applications such as laser and transistors. Quantum physics has paved the way for quantum computing.

Quantum computers just like classical computers use chips or processors, circuits and logical gates. The operations too are governed by the algorithms. Data transmission is through binary codes of 0s and 1s. However, quantum computers differ from the classical computers in the fundamental unit of data — in classical computing a bit can either be 0 or 1 exclusively. In quantum computing the unit data is quantum bits or qubits. It shows super position — an object exists as the combination of multiple possible states in a simultaneous manner. A qubit is superposition of both 1 and 0 simultaneously until its state is measured.

Qubits are made by manipulating normal atoms or even electrons. They can be made by nano-engineering artificial atoms or semiconductor nanocrystals. These are made with lithography, a method of printing.

The states of different qubits showing superposition can get entangled — they are linked to each other through quantum mechanics.

Quantum computing offers unprecedented speed of computing. The quantum computers we have now are nascent. Still they achieve mind-blowing speeds. What could take the fastest supercomputer ten thousand years, Sycamore (Google’s 54-qubit quantum computer) takes 200 seconds.

IBM too is working on quantum computing projects. It is a costly and cumbersome technology. Qubits are kept in chambers that chill them to near absolute-zero temperature.

The technology will be useful in quantum cryptography and quantum sensing.

Several billion dollars have been released by nations for R&D in this area. India has earmarked Rs.8000 crore in 2019. Of late, India kept aside Rs.6003 crore for the National Quantum Mission.

The biggest and best corporates in the world are in the race for AI. Microsoft has backed OpenAI, the company that has launched ChatGPT and GPT4, financially. Google has merged Google Research and DeepMind to compete ably and has made AI its top priority. Amazon has jumped into the fray with its cloud division. Microsoft with its investment in OpenAI wants it to build server farms to accommodate Nvidia’s GPU processors to train them in AI.

Where is Apple in the scene? We do not have an inkling of Apple’s strategy regarding Generative AI. To begin with, Apple in its early days introduced a chatbot Siri. Apple, however, has focused on hardware. AI just facilitates its hardware to function for better customer experience.

Siri, a voice-assistant chatbot was a step in this direction. However, Apple did not build upon it. Siri looks ancient by the standards of ChatGPT. Of course, historically Apple established its lead over Nokia and Blackberry not by improving upon the physical keyboard but by eliminating it altogether.

In the new AI race, companies need massive investment in computational clusters. Cloud services are not Apple’s forte. Instead of iCloud, the company is investing in AR.

Apple is not in the fight of generative AI. Apple expects other Apple AI companies to deliver their apps to Apple’s Store. Apple’s competition is not with Samsung or Xiaomi but with cloud-based AI services with their data troves for training and improving AI capabilities.

ChatGPT is a formidable competitor for Google in AI space. Google is interested to strengthen Bard since ChatGPT is challenging the premier position of Google search engine. There is so much catching up to do for Google to be on par with ChatGPT.

Google Brain is a team working on software. DeepMind is another Google organisation dedicated to deep learning. Google wants to create a new merged entity called Google DeepMind. Demis Hassabis, CEO, Google DeepMind is assigned to bring out the next generation of Google products. Google is gearing up to face the challenges in science and engineering to build more capable AI. Google has already produced AlphaGo, Transformers and Word2vec. Jeff Dean now of Google research would also serve as chief scientist to Google DeepMind. He reports directly to CEO.

Google is not alone to compete with ChatGPT. Elon Musk too has entered into the fray by setting up a new company called X.AI. which would develop TruthGPT. Alibaba, a Chinese company too has started working on generative AI.

Microsoft Stole the show by integrating ChatGPT into its Bing search engine. Microsoft is backing OpenAI financially Samsung might make Bing of MS its default search engine ditching GoogleSearch.

Google, California-based, is in the process of developing and implementing AI across all its services, but still it deploys the technology at slow pace and with circumspection. On the other hand, OpenAI has accelerated its AI implementation with ChatGPT and GPT4.

Sundar Pichai, Google CEO, says that we do not know many things about the new technology and the technology is advancing very fast. Google is catching up by infusing its products with generative AI. Dall-E, the image generating product of OpenAI has shown a lot of potential, and many businesses from Silicon Valley and China would like to offer similar products.

Pichai is concerned about the risks of AI, especially deep fake videos. This may require regulation. It has the potential to harm the society. AI teaches itself things, independent of the programmer. One of the Google’s AI systems taught itself Bengali. It can translate all of Bengali composition. This surprises the experts. It is called Black Box, which is not fully understood. There are some ideas as to why this happens, but still it needs more research. We also do not understand how human mind works completely.

AI brings glaring flaws such as fake news, deepfakes and weaponisation. These are hallucinations. All these hallucinations have not been fully solved. All models have this as an issue.

In future, there could be wide ranging global regulation for AI. Technology has to be deployed so that it benefits the society. However, wrong deployment could harm the society. EU law makers urged the world leaders to discuss the guiding principles for the control and deployment of AI.

As we know, Elon Musk was co-founder of OpenAI in 2015 but left the Board in 2018 amid clashes with its management. Of late, he raised an alarm by signing a petition along with others about the safety of generative AI, especially GPT4, the latest release of OpenAI. According to him , it has the potential to spew falsehood and exhibit political bias.

Since then, Musk has decided, it seems, to set up an AI company that can rival Open AI. He has started, it is reported, to assemble a team of AI researchers and engineers. He is said to have roped in Igor Babuschin, a former DeepMind employee. In the team, there are half a dozen other engineers.

He has incorporated a company called X.AI on March 9, 2023. He is the only director and ex-Morgan Stanley banker is the secretary.

To build up the hardware-software for AI, Musk has acquired thousands of high-powered GPU processors from Nvidia. These processors or chips are necessary to build a large language model (LLM). LLM is an AI system that can ingest enormous amount of content and then produce human-like writing and realistic images. The equipment matches that used by OpenAI’s ChatGPT. Elon Musk would like to create TruthGPT to counter ChatGPT bias. He is worried that ChatGPT is being trained to be politically correct.

Elon is now in diverse fields — electric cars (Tesla), microblogging (Twitter), space (Space X) neuro technology (Neuralink), tunneling (The Boring Company). He has merged Twitter into X Corp as a part of his plans to create an everything app under the brand X.

Computers with AI have sneaked into the society. OpenAI’s ChatGPT and GPT4 and Google’s Bard have created a great impact. They can generate a combination of text, images and videos. There is some misgiving about such stand-alone intelligence since the machine may not perceive the surrounding the living beings do while using intelligence. AI has its limitations. Human intelligence is housed in the physical body. There are experiments to pair the large language models with a body, say a robotic body. The processor converts sound into text and the text is fed into LLM. It then responds verbally and physically. Such a robot can offer condolences on the death of your loved ones. It uses sensors to respond to the physical cues and to bodily gestures. Such a robot learns from the behaviour of the people around it. It also mimics them. It is akin to wireless communication.

Google too is integrating its LLM models and physical machines. They developed a robot called PaLM-E in March, 2023. This robot can assimilate visual features of the environment. It also absorbs information about its physical position. All this is translated into natural language. The robot in fact conveys its own space relative to other objects. It can open a drawer and pickup a pack of Schrewburys. Such robots are capable of performing basic tasks without special programming, say making you a drink or picking a fallen object while responding to simple commands.

However, living beings have a mind that is inextricably integrated to body’s actions and reactions happening in the real world. These interactions have been shaped over a long period, say of millions of years.

While AI-assisted machines respond to language, living beings performed the basic tasks even when they had not learnt language. Robots thus lack a deeper connect between the real world and theoretical world. Intelligence emanates from the living body.

Scientists have developed small robots out of live cells, say of frogs. They are called xenobots. They can do basic tasks and do move around. They are not as creative as ChatGPT, but in a sense they resemble human intelligence.