There are advances in computer hardware and algorithms in the last twenty years. In addition, there is availability of data. This has led to breakthroughs in AI. The more the data is available, the better is the AI, since it learns from the data.

There are improvements in algorithms too. It has created an infrastructure, called neural network, which allows computers to simulate data and train themselves using billions of parameters and trillions of tokens. This way the computers assimilate all the data available on the internet and train themselves. They feign to be human beings.

It was thought that AI is artificial and not creative. This is no longer true. AI can push creativity forward.

Though AI-assisted bots are fast to respond, they are not emotional or culturally sensitive or intuitive like human beings.

It is not possible for human beings to scan all the information available and produce a report. AI has this capability. ML (Machine Learning) facilitates gathering, distillation, sharing and presentation of information. The whole thing becomes faster and better.

Journalists write articles, most of which carry information that is shared. Even this blog that you are reading shares information for you. Of course, there has to be interpretation of this information and its finer analysis. Let us assume it is 20 per cent of the task. It could expand or shrink a tad. It could expand when journalists write original stories and present different perspectives.

What is happening is that information sharing is being taken over by algorithms. ChatGPT generated copy in journalistic circles is called ‘smart automated content.’ Thus information sharing will be mostly done by AI. Human beings will have to interpret and analyse this information. Already, in automated manufacturing, the product is finally examined by human beings critically. Book-keeping in accounting is now redundant. It has become non-existent, after computerisation of accounts. However, auditing is still driven by human beings.

Thus, we envisage a future environment that is collaborative — a partnership of machines and men. Computers provide lot of information and men put it into perspectives. Machines help you develop critical thinking, argumentation and throw up ideas for consideration. Overall, it facilitates decision making. Both AI and humans can co-exist.

The world is fascinated by the generative AI chatbot ChatGPT from OpenAI and backed by Microsoft. Though Google too is working in AI, Google has also chosen quantum computing, the holy grail of scientists and researchers as another field that is equally exciting. As we know, binary information is stored as 1or 0 or in bits whereas qubits could store information in 1 and 0 at the same time. In a given amount of time, quantum computing can process large information. However, qubits exist at super-cold temperatures — just above zero degree K. Besides, qubits are susceptible to minutest interference, say light. As these are error-prone, they are problematic in computing.

Google has made a breakthrough in quantum error correction. Here instead of relying on physical qubits on individual basis, information is stored across many physical qubits and then treat this a single logical qubit. This minimises the error rate. In their research, they found that a logical qubit with larger number qubits reduces the error. It is, however, inefficient. It could be treated as a baby step.

A quantum computer will be a reality by the advancing research in material science, maths and electrical engineering. What could take a traditional computer thousands of years, could be solved by quantum computers in a matter of seconds. It is called quantum supremacy.

AI chatbots such as ChatGPT have worked only on one part of the puzzle. There should be high accuracy and error-free working. The chatbots are prone to committing errors. Improvements here is the concern for both the technologies — generative AI as well as quantum computing.

As we have already observed, quantum computing is based on quantum mechanics — superposition, entanglement, numerical and statistical algorithms and so on. There are quantum algorithms such as Simon’s, Grover’s, Shor’s. Deutsch-Jozsa and Quantum Phase Estimation. Those who are interested in quantum computing must learn the theory and concepts first and quantum computer programming next. The leading companies make available platforms/SDKs to give a start. Mostly quantum software development languages are open source, e.g. Qiskit from IBM. Qiskit is based on python, and with it we can work at the level of circuits, pulses and algorithms. Qiskit is a game changer. It is useful to have the skills.

Currently, India has only a few people who have expertise in quantum computing. India needs to upskill engineers to get this expertise.

Microsoft and AWS have platforms similar to IBM ready to be leveraged.

Certain simulations, searches, ML and optimisation calculations were intractable previously, which can now be tackled easily and quickly with quantum computing. Real life problems from these areas are converted into quantum circuits to solve the problems. The problems are solved with real data. Both a classical solution and quantum solution can be arrived it, and can be compared.

A learner in this field must have an aptitude for math and problem solving. He should be proficient in quantum logical circuits and logical-physical architecture. It is necessary to map a classical AI/ML app quantum architecture or circuits.

Certain expertise of domain, say pharmaceuticals for new drug discovery, is an added advantage.

We cannot work on quantum computers directly. We have to access them via the clouds. There are companies like Boson which work in this area.

Can you imagine life without YouTube? It found its feet soon enough by making a start in 2005 when three Confinity ex-employees decided to create it. There was another similar site in those days called stupidvideos.com. The names of the founding ex-employees of Confinity were Chad Hurley, Jawed Karim and Steve Chen. Confinity was known for its PayPal payment service in Silicon Valley. PayPal was pioneered by Elon Musk, Peter Thiel and Max Levchin. PayPal team was considered A-team, whereas the YouTube was perhaps the B-team at Confinity. Comparatively the B team was easy going and ‘not out to conquer the world.’

YouTube had its ups and downs. In early days, it started Flickr, a photo uploading site, which was later taken over by Yahoo.

Karim left YouTube early. The other too nurtured it. They rapidly tested one idea after the other. It was an easy platform. However, it discouraged porn. Videos were being uploaded by people with a desire to exhibit or be be in self-love. The audience too had similar sensibilities. YouTube made a mark with its user-generated content. The expenses of running the site were put on Hurley’s credit card. There was money crunch. Hurley roped in Roel of Both, a former colleague in PayPal. He was then working for Sequoia Capital. Sequoia invested $3.5 million which stabilised YouTube.

Google video was a rival video sharing platform. It was not picking up. Google put the videos on Google.com, but still could not catch up YouTube.

YouTube had become an attractive business and it waited for offer from Google and Yahoo. Google ultimately acquired it, despite its own video offering.

There were integration issues initially. Google brought its algorithms and revenue ideas to strengthen YouTube. Google had fiefdom culture. Ms.Wojcicki could not add flair to YouTube. YouTube was maturing and a cash cow. Still, there were no major innovations. The short video format creators diverted to TikTok and Instagram. Still YouTube continues as a behemoth .The lady stepped down from YouTube.

YouTube is an important offering from Silicon Valley.

As it stands today, metaverse represents multiple technologies. It will lead us to a future metaverse. Microsoft proposes to invest in Activision Blizzard to seek footing in the metaverse by enhancing its gaming portfolio. Microsoft will gain depth in many metaverse paradigms and technologies. Nivida and Qualcomm too are interested in metaverse.

Apart from what the tech companies do, what is more important for building metaverse is its adoption by consumer products companies.

These are early days, and wide-scale adoption has to wait for some time. There is issue of the intuitive devices for the metaverse. The current devices are intrusive. The device should take us seamlessly from the real world to the metaverse. Then there are issues of security, privacy and threats. There is a search for a game-charger application or use case that will draw a large number of users.

Diamonds are desirable, have special meaning and are a store of financial value. Natural diamonds appreciate in value over a period of time. Lab grown diamonds or man-made diamonds production reached 6-7 million carats, and about 50-60 per cent of the production happens in China. One carat is equal to 200 mgs of diamond bricks. When these bricks are cut and polished, they yield 30,000 carats of glitter.

Internationally, diamonds are grown by two methods — High-pressure, High-temperature ( HPHT) method and chemical vapour deposition (CVD) method. China has adopted HPHT method, whereas India produces man-made diamonds by CVD method. Even the US uses this method.

China produces 3 million carats of rough diamonds a year, India produces 1.5 million carats a year.

The production cost of a CVD diamond has fallen from $4000 in 2008 to $300-$500 per carat right now.

India’s LGD: Lab Grown Diamond business is concentrated in Surat, Mumbai, Ahmedabad and Jaipur.

These diamonds are used as jewellery. There are applications in electronics, thermal management, quantum technology and magnetometry.

HTPT machines are imported in India.

IIT, Madras facilitates the research in this area.

There could be an increase in misinformation after the advent of AI chatbots such as ChatGPT and Bard . It will be difficult to identify genuine content and fake content. India is already facing a surge in misinformation. In addition this gets complicated as India is a multilingual country. Generative AI aggravates this issue.

The language models of AI are not designed for factual accuracy. They are basically conversation models. AI models fail to distinguish between evidence-based information and pure fiction. There is scope to amplify hate speech, political ideology, toxic content, racism and violence — and these could be false and biased.

As we have already observed, big tech Chinese company Baidu is likely to launch soon its AI-based chatbot Ernie Bot and Baidu would integrate its existing products to it.

Opera as a browser ranks in terms of popularity. It wants to add AI-generated content services to the sidebar on the lines of Edge from Microsoft.

Tencent is present in China everywhere — in search engines, in gaming and in social media. It proposes AI-based content and generative AI services. It is now conducting research and is investing in language models.

Alibaba too is working on AI-based technology for the past six years. It is testing its product internally and might commercialise them soon.

JD.com. an ecommerce firm can launch ChatJD confined to B2B interactions.

TRAI will open up spectrum in the 95 gigahertz (GHz) to a 3 tetrahertz (THz) frequency range for allocation. It would help develop new technologies such as 6G-driven products and solutions. 6G technology would be based on the same 5G infrastructure. It will provide ultra high speed internet connectivity. The use cases for 6G would be similar to those for the 5G, e.g. healthcare, logistics, process automation or robotics. 6G will be faster. Telecom companies would welcome the access to 6G bands. As soon as 5G coverage reaches the optimal level, the companies can start preparing for 6G trials and roll out.

The airwaves could be availed of by academic institutions, research organisations and the industry.

Telcos are not in favour of administrative allocation of 6G band, and feel that the band should be auctioned. The roll out could happen by the end of the decade.

6G could converge satcom and terrestrial networks. The innovation group would identify the technological and industrial opportunities.