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.

When OpenAI was founded in 2015, it had 11 founding directors. Out in 2015, of these 11, OpenAI retains just two directors now, owing to an exodus after Sam Altman’s short-lived quit.

In 2024, three founders have departed, including John Schulman, who joined rival Anthropic. Greg Brockman too intends to take long leave from the company.

It is not unusual for a startup the churn of manpower. However, the exodus of senior management can lead to a leadership crisis.

OpenAI operates in a competitive field with strong rivals such as Google and Anthropic. Elon Musk, the earliest founder is a critic of OpenAI.

OpenAI had recruited top researchers as its founders when it was founded in 2015.

Let us see where these 11 founders are right now.

Gerg Brockman is on leave of absence since August 2024. John Schulman has joined Anthropic in August 2024. Ilaya Sutskever left to found Superintelligence in May 2024. Andrej Karpathy founded Eureka Labs in February 2024. Durk Kingma left for Google Brain in June 2018. Elon Musk resigned from the Board in 2018. Pamela Vagata joined Stripe in 2016. Vicki Cheung joined Lyft in 2017. Trevor Blackwell left in 2017.

The founders who remain with OpenAI are Sam Altman and Wojciech Zaremba Zarema, a Polish computer scientist and researcher.

Generative AI has created a buzz for AI-powered tools that can create content such as text, images and computer code. Since the launch of ChatGPT in November 2022, generative AI occupies the center stage.

This narrative has taken a dent on account of two issues — the realization that the technology is overhyped and absurdly expensive.

We know that chatbots still struggle to answer fundamental questions and hallucinate with flawed information. In addition, the models are hungry for humongous data and compute power. To remain afloat, the companies in this space must have massive funding. Many business enterprises still have to put the technology to use. Initial expectations reached sky high. There is trough of disillusionment now.

However, soon there will be realization that generative AI is not the entire spectrum of AI. There are components of AI called ML and predictive AI. In fact, these have preceded the arrival of generative AI. The whole AI is a broad toolkit. It is an issue of the use of right technology for an appropriate case.

Generative AI is not going anywhere. It has already become a part of our lives. It can give us productivity as well as efficiency. As we have become used to Google searches, so we will also get used to easy-to-read summaries of work meetings, composing of e-mails and office memos and creating images and presentations by uttering a few words.

Generative AI has attracted massive investment — say up to $1 trillion. It has to pay off. Its use must give us healthy bottom lines. Early adopters have passed on the technology to mainstream users, who find that their expectations are not being met. The process of resetting the expectations begins. There could be incremental benefits in applications. Industry has to work for monetization of AI technology. The sector as a whole has still to prove.

There is a history of AI Tecnologies being stimulating for other newer technologies, say computer vision has become a great contributor to multimodal generative AI. Similary generative AI can receive a push by technologies such as agentic AI — AI systems designed to act like autonomous agents to pursue complex goals and workflows. Such symbiotic relationship can help the technology to reach its full potential.

Please do not think that this is an AI winter. It is time to do the right tinkering of generative AI so as to get the work done.

In 2022, Noam Shazeer and Daniel De Freitas left their jobs at Google as Google was too slow and set up their own AI startup Character.AI which develops chatbots. In August 2024, Google struck a deal with them. They rejoined Google, together with 20 per cent manpower of Character.AI and provide Character. AI’s technology to Google. In fact, it is not a buy out of Character.AI, but involves licensing the technology, and recruiting the top employees. It is a swallow up of the startup, and its most precious assets — the manpower, without becoming the owner of the firm. The licensing fees agreed are $3 billion, Character.AI’s shareholders including Shazeer with a stake of 30 to 40 per cent stands to gain $750 million to $1 billion. The remains of Character.AI will continue as an entity without its founders and investors.

Such unusual deals are happening in Silicon Valley recently. Big Tech resorts to such complicated deals for acquiring startups. The idea is to obtain licensing technology and poach the top employees. It is a way to sidestep regulatory scrutiny, especially the FTC. It is non-traditional deal.

Microsoft started the trend by agreeing to pay the startup Inflection more than $650 million to license its technology and hire almost all its employees, including its founder Mustafa Suleyman. Suleyman now heads the consumer AI business of Microsoft.

Amazon similarly acquired Adept.

There is surrogate advertising — the advertising pertains to alcoholic drink Kingfisher, but what is advertised is Kingfisher mineral water, club glasses are advertised to promote Carlsberg, music CDs are advertised to promote Seagram’s Imperial Blue. ASCI guidelines distinguish between surrogate advertising (prohibited by law) and brand extension advertising (legally permitted). ASCI reports the cases of surrogate advertising to various authorities for appropriate action. There are loopholes here. If a brand extension product is available in at least 10 per cent of the stores as does the leading product in that category or if its sales reach Rs.5 crore annually or Rs.1 crore in the state it is sold, they are deemed to be in order. The well-funded liquor and tobacco lobbies take advantage of this provision.

The government intends to bring new regulation that will outlaw advertising for non-alcoholic items (mineral water, club glasses, soda, music CDs) if they display the same logo or branding as does the alcoholic brand. The violation of the rule would entail fines of up to Rs.50 lac, while the celebrity ambassadors promoting such brands could face an endorsement ban of up to three years. Thus, both the celebrity and the marketer will be held accountable.

Brands will have to take customized and targeted approach to reach the customers. Digital platforms will be crucial to enable campaigns to engage with targeted audience. There will be personalized ads. Thus, digital media will be the unintended beneficiary of all this. Companies can take social responsibility initiatives and community engagement to build brand loyalty.

Generative AI has a great market potential. It can account for 33 per cent of the global AI market by 2027. The total AI market is expected to reach $320-380 billion, growing at a compound growth rate (CAGR) of 25-35 per cent.

In Indian tech industry, women make up 36 per cent of workforce. There is a significant gender gap at executive level. Generative AI could transform the tech sector by reducing the disparity between men and women in the tech sector.

It is reported that 45 per cent women in the tech roles feel that generative AI can boost their perceived competence. One in five women use generative AI on a daily basis. Amongst the senior management women, the daily usage of generative AI tools is nearly 35 per cent.

Still, the usage is lower at the senior levels. This could be attributed to limited knowledge, lack of trust, restricted access to these tools and fear of competence scrutiny. The knowledge gap must be addressed to get greater adoption. The enabling environment should be created to make women comfortable while using generative AI.

Some measures to boost adoption among women are to provide clear career pathways, mentorship programmes, flexible work schedules, providing training, building a suitable work culture and fostering networking opportunities.

Many women have shown willingness to invest more time to achieve professional success in generative AI.

In order to leverage a huge opportunity of $320 billion market, India must have gender diversity.

John Schulman, one of the founders of OpenAI, quits to join rival Anthropic. Schulman had joined OpenAI in December 2015, just before his doctorate in electrical engineering and computer science at UC Berkeley. He announced his exit on Tuesday, August 6, 2024. He is making the move ‘to deepen his focus on AI realignment and to resume technical work, thus opening a new chapter of his career’.

Greg Brockman, OpenAI’s cofounder, has announced his sabbatical till the end of the year. He intends to relax and would like to work for achieving AGI goal.

Schulman at OpenAI has led the team of reinforcement learning that developed ChatGPT powered by GPT-3, a language model.

After the departure of Schulman, only three of OpenAI’s eleven original founders remain in the company — Sam Altman, Brockman and Zaremba.

Ilaya Sutskever, another founder, left the company in May 2024. Andrej Karpathy, another founder left in February 2024.

The most notable early exit was that of Elon Musk on the ground that OpenAI is deviating from its public good priority to commercial priorities.

Peter Deng from Product Management area who joined in 2023 also exited this year.