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A TV channel receives feedback from the viewers, but it is not continuous. There is a time lag of three months and thus the ratings get affected and in turn the advertising revenues. Zee, therefore, decided to leverage the capabilities of its Technology and Innovation Centre in Bangalore.

Zee developed ScriptGPT in collaboration with OpenAI using 1.3 million variables. These variables include character archetypes, plot twists etc. It was trained on 42000 episodes from channels across Hindi General Entertainment landscape. By April 2024, it would have ingested 100,000 episodes. It also received BARC data, brand track data, content and audience research. Its forecast accuracy is 90 per cent. It has achieved this after multiple iterations.

While it is a challenge to source copious amount of data to build its intelligence, there is an issue of the copyright of the data. They have a team of lawyers to vet the stuff they feed to the model. Of course, the IP rights of the output of the model is still a moot point. The jurisprudence is still evolving.

After a serial gets screened for a few episodes, ScriptGPT can be questioned about the suggestions to alter the show so as to improve its ratings.

ScriptGPT facilitates the understanding of characters, stories. plots and twists that the audience seeks.

There are efforts to use the model to generate a full movie script. That is worrisome for the script writers. However, they can upskill themselves in AI technology so that their jobs do not get affected.

ScriptGPT makes you alive to what works and why it works. It brings the organisation closer to the audiences.

Media firms can use AI tools to edit and dub the videos and films.

It is difficult to predict the time when artificial general intelligence or AGI will appear to match the cognitive function of the human beings or even to surpass it.

Sam Altman of OpenAI, however, feels that even before the advent of AGI, AI has the capability to influence the human mind. This influence could be superhuman persuasion leading to some strange outcomes. He has, however, not elaborated on these outcomes.

We can imagine how ChatGPT and other bots can establish a bond with the users. Such a bond can be highly emotional. It is not unusual for stressed individuals to seek relief from internet. At times, such users can be taken for a ride.

At times, there is no emotional connect with a bot, but the system has earned a lot of trust. AI may have hallucinated. It can create a serious problem.

AI can persuade individuals into unethical behaviour. It is for individuals such as Altman to clear the ambiguity about the strange outcomes, given their standing in the profession.

What has taken the world by storm is the arrival of ChatGPT in late November, 2022. In the development of artificial intelligence, this is a seminal moment. OpenAI introduced GPT series, where GPT stands for Generative Pretrained Transformer which seems to guide the AI domain.

In a recent interview to a German newspaper Handelsblatt, Bill Gates, 67, founder of Microsoft who backs OpenAI feels that the GPT technology has plateaued. He, of course, added that this could be a wrong belief. His main contention was that contrary to popular opinion about GPT-5, he believes that the current generative AI has reached its zenith. The progress between GPT-2 and GPT-4 is incredible.

The next few years will be for consolidation of AI, increasing its accuracy, and reducing its cost. He does not see a breakthrough between GPT-4 and GPT-5. Of course, in the short-term, AI is full of potential, and will tremendously benefit the developing nations. There could health counselling online and on smart phones. AI can benefit healthcare, new drug development and vaccine making.

He spoke about GPU chips costing high — say $30000 a piece. These chips consume lot of electricity and large amount of computing power. There is reduction in cost per query — from ten cents previously to 3 cents now. The costs of computing power and chips, however, remain high.

Bill Gates spoke about the blackbox whose inner workings are not known. There are many individuals who try to decipher AI’s internal workings. Bill Gates is not sure about the arrival of AGI, but agreed that it can have profound effect on humanity.

Moore’s Law stated doubling of computational growth every two years, but this was true before 2010. With the arrival of neural networks early 2010s, the computational resources utilisation doubled almost every six months. It is a paradigm shift.

With the surge in demand for compute power, the role of semiconductors becomes more significant since they are the backbone of compute processes.

The manufacturing of semiconductors is a complex process.

Chips are designed, to begin with, using electronic design software which is automatic.

There are 500 plus steps in making of chips. It takes 4-6 months to complete these processes.

After designing, there is fabrication in specialised units. It is a capital intensive process — it may cost up to $20 billion.

Lastly, there is chip assembly, testing and packaging (ATP). It involves cutting silicon waters into chips and adding connectors to chip frames.

Semiconductor market in 2022 stands at global valuation of $574 billion, and is forecast to grow to $1381 billion by 2029, witnessing a CAGR of 12.2 per cent

The development of AI at a rapid pace is so unrestrained that humanity’s future is endangered. An MIT professor of physics Max Tegmark calls this a ‘race to the bottom’ and urges us to stop this race. He has drafted an open better with several celebrated signatories, and tech industry stalwarts asking industry to halt AI experiments for sometime, say six months. Tegmark asks for AI safety standards to convert what is ‘race to the bottom’ into ‘race to the top’. Of course, AI with an oversight has incredible benefits to offer. No oversight, and we are exposed to perils of AI. Governments can think of licensing the AI models.

AGI is equal to human level intellect or above human level intellect. AGI calls for tighter regulation.

To deal with climate change, there is an international body — Intergovernmental Panel on Climate Change (IPCC). On similar lines, to deal with AI, Eric Schmidt of Google, Mustafa Suleyman of Inflection and DeepMind and Demis Hassabis, co-founder of DeepMind advocated a body at international level.

Demis Hassabis recommends greater regulation of AI since it will pose an existential crisis once it acquires intelligence beyond humans. The earlier the world responds, the better it is. Among other dangers of AI, Hassabis is also concerned about bio-weapons.

Still, it is not entirely a gloomy picture. AI has the potential to do a lot of good.

Nuclear research has oversight of CERN and other bodies such as International Atomic Energy Agency. Such equivalents can be conceived for AI too.

November 1 and 2, 2023. UK is holding an. AI Summit on AI governance. They want to arrive at a consensus about the dangers of AI.

AI will be of great help in medicine and science. Hassabis is clear that the more serious apprehensions are about artificial general intelligeble (AGI). AGI possesses intelligence equal to human beings or surpassing human beings. The world is divided about AGI. Some call it a crisis situation, whereas others see it as the most important invention humanity would have made.

Interestingly, Sam Altman predicts the arrival of AGI in the next ten years. Altman, however, feels AGI will be of great help to humanity.

Microsoft is doing well with revenues of $56 billion, and profits of $23 billion in 2023. In a letter released on LinkedIn Satya Nadela, CEO tells shareholders and other stakeholders about the big bet they take on AI. So far, the industry used some platforms, whereas AI is a platform shift. It creates maximum enterprise value. Microsoft has spotted an opportunity which it intends to exploit, and has done risk analysis. Microsoft has invested $10-$13 billions in OpenAI. Microsoft infuses AI into everything it sells.

Of late, industry witnessed shifts such as blockchain technology and metaverse. They invested hugely and quickly. AI is another cup of tea. It will replace some of the existing technologies. AI may replace the browser we use today. Co-pilot can shop, code, analyze, learn and create. Maybe, AI will continue to grow, or it may have plateaued. But Microsoft is in a comfortable position, as Satya Nadela has put MS in the best possible position.

University researchers and Eleuther AI introduce LLEMMA as an LLM for problems in mathematics. It is an open source model. It surpasses Google’s Minerva in performance.

It is based on code Llma, adopted after Facebook’s Llma 2 model duly fine-tuned. There are two versions of the model — one with 7 billion parameters and the other with 34 billion parameters. The models are fine-tuned on Proof-Pile-2, a set of scientific papers, web-data featuring maths and mathematical code.

LLEMMA is pre-trained on diverse maths data. It can use tools and can prove theorems without additional fine-tuning.

It can leverage Python interpreter and formal theorem provers to solve maths problems.

Google’s Minerva is not open source model. It is based on PaLM model.

This is a subject-specific model and not a general model.

Whether LLMs are suitable for problem solving is a matter of debate. Some scientists argue that LLMs are stochastic in nature and not suitable for math. Training data includes benchmark examples. There are efforts towards enhancing the reasoning and planning capabilities of language models. Maybe, they are not ultimate tools, but are the first step for further research for other types of models.

Masahiro Hara, a Japanese engineer invented the QR code or quick response code. He did so while working for a Japanese automotive technology company Denso. To begin with, the company used the invention for inventory management. Although Hara retained the patent for the code, he did not exercise his rights as a patent owner. He wanted the code to be used by as many people as possible. The usage did not attract any charges. The code thus became popular all over the world.

In 2002, the code gained acceptance across industries in Japan, and since then it has spread all over the world.

The information carried by the code was initially read by an electronic reader. Later, dedicated apps downloaded on devices could read the code. The reading became a child’s play with mobile cameras scanned and read the code. During the pandemic, it provided a convenient mode for payment. Post-pandemic the use increased many fold as it was convenient, contactless payments payment mode.

QR code is now combined with AI. It makes it more useful and easy to adopt. AI makes it secure and improves images. It can personalise codes.

Smart computer vision (CV) algorithms help to identify and locate a QR code within a larger image.

In retail, healthcare, consumer goods, it has emerged as a convenient mode of payment.

In India, the National Payments corporation of India in collaboration with International Card Schemes (ICS) has developed a common standard to launch Bharat QR. This is a digital payment mechanism used by merchants and e-commerce portals. QR code is likely to evolve further. Security aspects will be addressed. There could be micro-codes in future not visible to the human eye. There could be addition of colours to accommodate more data.

It is believed that generative AI soon will lead to artificial general intelligence (AGI). It will so happen that the future artificial intelligence models will need lesser data for training. Instead, these models will focus more on reasoning abilities. In other words, AI will resemble human intellect based on logic and intuition. The changed AI will have components adaptability and common sense. Sam Altman calls it a system that can generalize across many domains.

As we advance in research, the gap between what AI and humans can do is narrowing.

LLMs are not the last word. They are just stepping stones. They will acquire intuitive understanding in future. AI will master abstraction and will hold opinions about men and matters

It was so far thought that intelligence is backed by a soul, by a consciousness. Still, the chatbots show sparks of intelligence.

Since data privacy is being valued in modern age, the new platforms of AI trained on massive data are under scrutiny.

Still the potential of AI raises hopes. AGI will create a symbiotic world of humans and machines. AGI will be the ultimate tool created by humanity. Some researchers are optimistic. Some take a dismal view, e.g. Paul Christiano and Geoffrey Hinton.

As AI advances by leaps and bounds, there are ethical and philosophical issues. Altman expects AI to be a collective endeavour with participation of various stakeholders. Of course, the philosophical issues are weighty enough, because these machines might overshadow biological intelligence. Machines may make the minds obsolete.

GPT-4 has cognition resembling human beings. The real issue is ‘ghost’ inhabiting the machine and the way the machines are becoming soulful.