Nvidia, the chip supplier, mainly to the AI sector confirmed in September 2024 that its new Blackwell chip had faced some production problems, affecting Nvidia’s shares which fell by 8.4 per cent. It happens to a company that has shown spectacular growth in past. And its growth forecast too beats expectations. This justifies the adage in Silicon Valley that hardware is hard.

The Blackwell delay is a temporary hitch. The overall margins are enormous. The surging demand for its chips will continue for many more quarters. That Blackwell is a little late is not an issue. The existing products sell like hot potatoes. The production issue is sorted. It was an issue related to operations rather than the chip design. It was not an issue where the product will be back-to-the-drawing-board type. The company has streamlined its operations. It pledges to update its flagship hardware at least once a year. They hope to have a great next year.

Investors should better be concerned about the biggest buyers of Nvidia chips making their own components. They contribute 45 per cent to Nvidia’s revenues.

The issues may not become obvious in a couple years. Even if AI is overhyped, it will be detected after many more billions being spent on Nvidia chips. Till then, there is no cause for investors to overreact.

Of course, hardware is hard. Keeping Wall Street happy is even harder.

AI is transforming our world. ChatGPT and Gemini are known for generating human-like text.

Researchers have come across AI models trained on data that is generated by previous versions of the models. It is moving away from the original data distribution. The output could be distorted and unreliable. It is called model collapse.

As we know, AI models are trained vast volumes of data. It has data scraped form internet. The data is, to begin with, generated by humans. The model learns patterns from this data. The future generations of the model use data from two sources — human-generated data and data generated by the previous models. There is degradation in the output as the data quality successively goes down. Each version dilutes the original detail. The final output is a hazy and less accurate description of the world around. It is a slow process, but it happens. It is like making a copy of a copy, and so on. There is a loss in output. It is inevitable.

The content is less creative, more stereotyped and less useful.

It is not a limited problem. It has far-reaching impacts. There is decline in the efficiency of the model. The model becomes less reliable. It may commit costly errors. The issue of bias raises its ugly head.

One solution is to restrict the model’s training on human-generated data. However, of late, much of the internet content is model generated. And there is an issue of distinguishing human-generated content and AI-generated content.

At times, AI-generated content mimics human-generated content.

The use of human-generated data has its own problems — there are ethical and legal issues. The first-mover advantage is enjoyed by the pioneering models, as there is less contaminated data for training. Thus, early adopters are at an advantageous position.

It is crucial to have access to human-generated data. This has to be balanced with the rights of those whose data is being used. There should be cooperation at the industry-level. Models should be continuously exposed to fresh human-generated data.

Though AI models are powerful, they are still dependent on the quality of data they are trained on.

Though model collapse poses a problem, we can overcome it by implementing the right strategies.

Telegram founder and CEO Pavel Durov was detained at an airport near Paris. It has repercussions all over. Some called it an assault on free speech and innovation.

There are nuances here. Telegram has been ultra-lax about the content oversight. There are allegations of child sexual abuse (CSAM) material on the platform. Other social media platforms spend considerable time and resources to ban such material. There are alleged drug trafficking and money laundering issues.

Telegram is a powerful platform with 900 million monthly users. There is no overseeing worth the name. It has minimum intervention policy (resulting into low operational costs). Undesirable groups may be using the platform not for its secrecy but for its ‘anything goes’ approach.

Telegram calls it absurd that the owner of the platform is held responsible for the abuse of the platform. It says it abides by the EU laws, including the Digital Services Act. Many others do not see any absurdity if someone is held accountable for criminal activity. Telegram is not end-to-end encrypted. Most chats on the app use client-server encryption. If it chooses, Telegram can access message contents. Much of the content is on public channels. Telegram’s ‘secret chat’ feature is end-to-end encrypted. It is not active by default. It is not used for regular communication. Telegram does not offer real privacy, but only creates an illusion of it. It has technical means to monitor content. It chooses not to use this capability.

Telegram has allowed a free rein to all kinds of activities on its platform and is not immune to its consequences. Digital world is too subject to regulation, just as the physical world is. There cannot be a regulatory vacuum for social media platforms. Europe and Britain are on the right track by either enacting or proposing to enact regulatory laws.

Telegram CEO Druv has been charged with multiple criminal offences. Though it is unusual to target executives for crimes committed on their platforms, Paris prosecutor noted the platform’s ‘near complete’ lack of response to legal requests for cooperation. The 39-year-old CEO posted bail of 5 million Euros after being questioned by a judge on 28th August 2024 and following four days of police custody.

The founder-CEO has acquired multiple citizenships. Druv has dual citizenship of Russia as well as France. His arrest has upset Russia. France treats his as a part of investigation, and not as a political move. When Telegram was run as a free speech absolutist, these passports protected him. Once he wrote in Instagram, ‘To be really free, you could be ready to risk everything.’ That risk appears to have caught him up (despite the passports from Russia, France, UAE, Saint Kitts and Nevis.)

The French charges are against the platform, and not against Durov personally. It serves as a warning to other Big Tech companies. So far social media enjoyed protection across jurisdictions called safe hurbour. Its basic premise is that platforms cannot control the posts on their site. They should not be held legally liable for any objectionable content they host. The only condition is that they should be ready to take such content down when flagged by the government or various courts. Safe harbour is viewed as a basic text of allowing freedom of expression. In the US, this special protection is available to social media under Section 230 of the US Communication Decency Act on par with Section 79 of India’s IT Act, 2000 which classifies social media as intermediaries, and shields them from legal action.

In India, certain officials of social media can be sued if their platforms violate the norms. Under the Rules of the IT Act, 2021, social media companies with more than 5 million Indian users have to appoint a chief compliance officer who could be held criminally liable if the platforms do not adhere to the government’s take down requests or violate other norms. However, the government has not exercised this power so far.

The IT Act will be followed by the Digital India Bill. The government is expected to consider whether safe harbours should be available to the social media.

There is data flood on internet. It becomes difficult for organizations to sift the data that is useful to transform their operations from a huge pool of data. Generative AI has made the data available on internet even bigger, though much of the data is useless for any organization trying to address a specific problem.

Of course, there is a need for big data for business analytics and to get AI solutions. Still, the data inundation in this digital age is fearsome. It becomes difficult to keep the company afloat in this data deluge. Larger storage is made available to deal with the deluge. There is lot of cold data not immediately required for data modelling. It may be used in future to build more efficient AI learning algorithms.

Internet produces several zettabytes of data, and the capacity to store these zettabytes falls short. Data increases at a CAGR of 25 per cent, causing a larger deficit in storage space. In the coming three years, the data could rise to 175 zettabytes. One zettabyte is equal to one billion terabytes. A terabyte is 1000 gigabytes (GB).

How to make sense of this data? Organizations use analytics. The team has experts in statistics, data science and number crunchers. They search for a pin in a haystack. Maybe, they deal with junk, and more junk is likely to be added as time rolls on. Data cleaning has become a humongous task. Much data remains floating on servers without being put to any use. It is not that the data is dirty. The issue is that the data is old. And data ages quickly.

Data storage requires mega data centers. This approach is not sustainable. There are high costs, and there is power consumption.

It is necessary to delete data that has not been used for several years. Let useless photos, files, conversations go offline forever. It is data purging. It requires corporate courage to purge data that is too old to be used. It limits useless computing and storage. The focus is on using relevant and real-time data. The analytical conclusions reached on the basis of such data are actionable immediately.

Indian fashion is being reinvented. There is democratization of design. In past, designs were for the elitist but are now wearable and simple silhouettes.

Indian fashion designers from the 1980s such as Tarun Tahilani (now 62) and JJ Valaya (now 56) have adapted Western couture to Indian sensibility and craftmanship. Tahilani is a Wharton School business graduate and Valaya, a CA. Tahilani set up Ensemble in 1987 in Mumbai and Valaya an eponymous store in 1992 at Sultanpur, Delhi. Much water has flown through the Ganga and the Jamuna since then, and we are on the cusp of another change.

Both these designers gathered like-minded friends — Rohit Khosla, Abu Jani and Sandip Khosla (who costume designed for Umrao Jaan, 1981). There was Anuradha Mafatlal, Anita Shivdasani, Sunita Kapoor and Neil Bieff. They chose a colonial building at Lion’s Gate, Mumbai to showcase about 80 outfits in December 1987. They utilized the services of weavers and embroiders of Mohammed Ali Road. Anarkalis were inspired by Mughal miniatures. French designers thronged there to buy the clothes. These events were closed-door, with no invites sent to buyers.

Valaya was a pioneering batch student of NIFT, New Delhi. He is the founding member of the Fashion Desigh Council of India (FDCI). It was set up in 1998. He is the first to break ice at Paris Haute Couture Week, 2001. He had a solo show at Delhi in early 1990s. He took it to Dubai, Hong Kong, Singapore and London. By 1996, they had a luxury store that went beyond women’s wear and men’s ware. It showcased home decor, furnishings and artefacts. There was an art gallery too and a fine-dining restaurant.

India Couture Week, 2024. Tahilani broke the shackles of elitism by doing a repeat show for those who missed it in the overcrowded hall.

Valaya feels there is no room for resting in the field of fashion. He reset his vision to contemporary trends.

Fashion cannot serve only the rich and elite. It must find a younger voice. Tahilani now experiments with dhoti-saris and button-downed collared cotton shirts. Fashion labels can sustain only if they find a wider market.

There was liberalization in India in the 1990s. It gave full rein to the imagination of designers. Bina Ramani did her first show with cow heads on sequined dresses. Fashion has become a spectacle. It was playfulness. It was frivolous. However, in order to qualify as an industry, it must be more than a culture club.

When Valaya started, menswear stagnated to bandh-galas, sherwani and churidar. There is steady progress towards ready-to-wear and accessories. Social media guides the youngsters. Though technology arrived in fashion design, it brought an element of homogeneity. It is necessary to change the design philosophy.

Tahilani mingled with the Kumbh crowds to get fresh ideas to shape his fashion philosophy. He observed the draping styles of the pilgrims. There were ideas for slip-ons, zip ups and trouser, sari and skirt wears. There are myriads of ways of folding the cloth. In the sameness too, people are distinctive. The villagers of Kutch region too provide a lot of ideas. Valaya travelled along the silk route to get new ideas. He brought the collections inspired by Iran, Turkey and Delhi. Valaya is now controlled and minimalist.

There should be balance between tradition and modernity in fashion. Never commit the sin of bastardizing the design. But it should be blended with the language of the day.

Tahilani says he has evolved a new grammar of fashion design. One has to make a statement by a light and minimal design. Yet, it should be classical and should also go beyond the event.

Corporate tie-ups help you scale up and stay relevant. There should be workshops in the villages. India has just scratched the surface of its vast retail market. There are segments such as pret, luxury, ready-to-wear and mass. Those inspire us to carry on.

Both Tahilani and Valaya do not use showstoppers. They are confident that there are enough takers available, on the ramp and off it for what they design.

We are fascinated by clairvoyance. However, there is another tribe of futurists who see into the future, based on the status the world is in today. And there are two types of futurists — those who draw a rosy picture of the future and those who raise an alarm.

Ray Kurzweil is a futurist who predicted in 2005 that smarter machines by 2045 will lead us to an infection point which he calls singularity. As it is Kurzweil has tracked AI since 1960s. Kurzweil has preponed the arrival of singularity — from 2045 to 2029. He attributes this to algorithmic innovations and big data.

Apart from other mundane things, he expects the medical science to extend human life by several decades.

Futurists draw their power of looking ahead from their insights into looking back. To several futurists, life will be brighter ahead than ever before. And the advent of singularity will make life exponentially better.

However, all this ignores the several other trends on the horizon.

There are issues of climate change, economic inequality, polarization, misinformation. There is rise of big tech feudalism. We can ignore these issues at the cost of deterioration of life.

Kurzweil talks of nanobots in medicine which will convey drugs, genes and other payloads in the body. He visualizes a brain that will interact with the web automatically. Are we ready to ingest such nanobots? Can we conceive of computer chips inside our bodies?

There is a limit to understanding of futurists.

China has made advances in getting patents in the AI field. All over the world, there is a monumental wave of innovation. Between 2014 and 2023, 54000 generative AI related patents were filed (patent families). There are 75000 scientific publications in this field.

TenCent leads the generative AI patent applications with 2074 applications, followed closely by Ping An Insurance with 1564, Baidu with 1234, the Chinese Academy of Sciences with 607, IBM with 601, Alibaba Group with 571, Samsung with 468, Alphabet with 443, ByteDance with 418, Microsoft with 377. Out of these top 10 highest patent filers, six are Chinese. (Patent Landscape Report on Generative AI, WIPO Report, 2024).

China dominates this field — it commands 38,210 generative AI inventions, whereas the USA commands only 6276 inventions, followed by Korea with 4155 inventions, Japan with 3409 inventions and India with 1350 inventions.

Chinese universities too file generative AI patents with the Chinese Academy of Sciences.

China plans to establish over 50 AI standards by 2026. Though a regulation-free environment fosters innovation, regulatory frameworks analyze innovations by providing a structured environment. The regulations should be stringent, yet flexible. Clear regulations reduce compliance costs and uncertainty. What is needed is regulatory clarity and consistency. These make the environment predictable legally. It facilitates standardization of technologies.

Chinese government too encourages AI development through strategic planning and significant investments. They have developed substantial AI infrastructure — high compute resources, data centers, cloud computing.

There is an ecosystem of startups, tech giants and academic institutions.

A talent pool of AI researchers and STEM graduates is available in China. It also attracts international talents.

China concentrates on hardware too. They have developed powerful chips — Ascend series of Huawei, Hanguang of Alibaba, custom AI accelerators.

Humanity has always valued natural diamonds. These diamonds are mined from the earth where they are formed over a period of time if the conditions are conductive. As an alternative, these days synthetic, man-made and lab-grown diamonds are available. Lab grown diamonds (LGDs) are just like natural diamonds and are grown in a reactor using a thin slice of high-quality diamond that service as a seed for growing them.

Diamonds need specific temperatures, environment and gases to grow. These conditions are replicated inside the reactor exposing the seeds to carbon-rich gases and carbon deposits. The process mimics natural conditions but occurs in less time. The process is called Chemical Vapour Deposition (CVD). It produces CVD diamonds.

The largest LGD manufacturers account for 25 percent of India’s production. There are several manufacturers in Surat. Kira Diam, one such prominent manufacturer has 7-lac square feet facility with 2500 machines, and it produces around 1.5 lac carats of polished diamonds per month.

The whole cycle from seed to diamond takes 25-30 days, followed by 45 days of cutting and polishing.

The lab-grown diamond jewellery market has been valued at $264.5 million in 2022. It is expected to grow at a CAGR of 14.8 per cent over the next decade, so as to reach $1.9 billion by 2033. The spike in demand is driven by millennials. The rising demand led to higher prices and margins. It has attracted more players. This influx has resulted in oversupply, and a consequent fall in prices. What was selling at Rs.60000 per carat is now available at Rs.20000 per carat. The LGD production units operating in India are 10000.

Though India is one of the leading producers of LGDs, the biggest consumer market for LGDs is the USA. LGDs in the USA account 60 per cent of the market.

Indian retailers resist the presence of LGDs, but this resistance is decreasing.

Though LGDs are price competitive, the consumers do not find them as good investments. They lack the resale value. As it is, diamonds, whether natural or lab-grown, are not ideal investments. Unlike gold, they do not guarantee price increase.

Traditional mining involves the abuse of human rights. Thus, youngsters find the LGDs a guilt-free use item. Besides, we can make many designs out of LGDs, which we cannot from natural diamonds on account high losses.

Natural diamonds are within the reach of 1 per cent affluent people. LGDs can be afforded to the next 15-20 per cent of consumers.

While speaking at Stanford University, Schmidt, former Google CEO boldly advised young and aspiring entrepreneurs to create a replica copy of TikTok stealing copyright music. If the video does not become viral, try your hand on an alternative video. This is the approach of a Silicon Valley entrepreneur. If per chance, they are successful, they hire a battery of lawyers to clean up the mess. However, if the product is a flop, who bothers about copyright violations? This is the modus operandi in Silicon Valley. It raises the issues of ethics and IPR. There are discussions about the work culture of tech industry. This comment adds to such discussions. He also held the work-from-home policy tells upon the results of the startups. Later he diluted the remarks about work hours.

It is argued that IPR creates a monopoly. Knowledge is not created in isolation. It has links with existing body of knowledge. Monopolising it creates a calamity. The counterargument is that it takes a lot of capital and mental investment in creating innovation, and hence these costs must be recovered, and must accrue to those who facilitated this process. However, in medical emergencies, such as the Covid pandemic, we can think of relinquishing the IPRs for the broader good of humanity.

Big Tech are planning to make large investments into Nvidia-based data centers, which may cost as much as $300 billion to build. The data center with in-demand AI chip H 100 will make a winner.

In future, big tech plans to make their own chips — Google making TPUs, Microsoft Azure Maia 100, Amazone Trainium chips and Facebook Artemis (surpassing their previous Meta Training and Inference Accelerator — MTIA).

Broadcasting, either through radio or TV, goes much beyond entertainment. Broadcasting could be a source of information, knowledge and education. The governments all over the world thus take advantage of broadcasting to reach the public.

India is considering the National Broadcasting Policy. The government has proposed the Broadcasting Services Regulation Bill (which it has withdrawn). India should produce broadcasting content not only for domestic consumption but for international audiences. We should develop technical skills in production — animation, VFX and other emerging areas.

Apart from broadcasting, the audiences receive content through the OTT (over-the-top) platforms such as Netflix, Amazon Prime and Hotstar. OTTs are functionally different from traditional broadcasting. TV and radio have a dedicated infrastructure of cable or satellite. OTTs send data over ‘ the application layer’ in IP networks, just like any other information transmission over the internet.

Traditional broadcasting and OTT markets are at different stages of development. Traditional broadcasting celebrated its golden jubilee whereas OTTs are only a decade old. It is a sunrise sector.

TV is a family bonding device, whereas OTTs cater to individuals enjoying content on their smartphones. OTTs could be seen at any place and time of their choice. TV has appointment viewing. Since their maturity levels are different, the regulatory approaches too should be different.

OTTs benefit network operators and telecom by providing valuable data traffic. In fact, they strengthen the operators financially.

Digital media falls under the Ministry of Electronics and IT. The IT Act, 2000 and IT Rules, 2021 govern the intermediaries. OTT platforms inclusion under broadcasting is uncalled for.

There is carriage regulation for content delivery, and there is content regulation. It protects public sensibilities and values. Both these require different approaches. There should be separate regulations for each area. The Ministry of Information and Broadcasting too reaffirmed this point.

The Indian OTT market is expected to reach $3.22 billion by 2025. The video market will grow to $13 billion by 2028. There is capital investment in this area. India should emerge as a digital media powerhouse.