In direct-to-mobile technology, the television content is streamed directly to mobile phones without an internet connection. The challenge is to integrate smart phones that support D2M and digital terrestrial TV to mobile devices (DTT2M).

There should be nationwide network for indoor coverage for quality services.

The implementation means higher costs for smartphone makers. The sets will be costlier.

There should be a standard compatible with existing mobile handsets. Smart phones can be designed and manufactured to be ready for receiving broadcast signals directly.

This technology seeks convergence of broadband and broadcasting services. It enables users to receive terrestrial digital TV directly on their handsets. It is similar to the concept of FM on the handsets.

The service can be used to spread citizen-centric information, say emergency alerts, public safety messages, social services etc.

The technology is in its early stages.

Once, there was a distinction between online gaming and gambling platforms. Of late, both these platforms have converged. A substantial portion of India’s online gaming involves gambling. There is a campaign to call these as a game of skill whereas gambling is a game of chance. These days every game is being played for stakes. Self-regulation has been proposed but there has not been any progress here. The crux of the matter is what is going to be regulated and how it will be regulated.

There could be regulation of gambling, sporting, or entertainment companies. Or will it be just a regulation of internet intermediaries? Internet companies tend to avoid regulation, e.g. e-commerce, social media, communication apps, super apps. First step of regulation could be licensing these companies.

There are unregulated pool or purse collections, and GST has been levied on them.

China has been strict with such companies.

Medical profession so far acknowledged only substance abuse addiction. It has now acknowledged non-substance behavioural addiction including online gaming and gambling. South Korea has identified online gaming as the largest health problem.

Many have been laid off in technical companies. At the same time, tech businesses have made significant investments in AI. The model that is emerging is of shedding headcount and hiring talent with AI skills. It is estimated that in the next five years, 30 per cent of entry-level coding jobs would be replaced by AI.

AI and ML has changed coding which has become speedier. Software development uses AI in development, testing and maintenance. Programmers should use AI tools to their advantage. A programmer can complement his own skills and can overcome his weaknesses by leveraging AI. AI can enhance the capabilities of programmers.

AI generated content is not always accurate, and hence manual monitoring to check the codes would be essential. There should be sufficient safeguards before proprietary codes are shared with generative AI tools for decoding.

Human ingenuity is required in the system design and software architecture. It is necessary to know where to use AI and where human intervention.

Investor expectation from AI has reached sky high. These expectations are hard to meet. Microsoft, Google and AMD are working hard to infuse AI into their products. Still their stocks decline in value.

AMD’s new processors will capture market. Microsoft declares that users are taking to its AI assistants. Google expects to enhance its searches and cloud computing services.

Investors took the shares to dizzy heights since they expected AI to be magical. Results do not satisfy them.

Microsoft, in fact, is doing very well. AI products help drive the adoption of its data center services. Revenue from Azure cloud has shown a 30 per cent jump.

Wall Street wants clarity about what AI will contribute to financial performance. Investors want companies to quantify the AI potential over the next couple of years.

While dealing with computers for the last 70 years, the dream, according to Satya Nadella, has always been — making computers that we can understand versus making computers that can understand us. He was addressing a crowd of developers in Bangalore on Thursday, February 8, 2024. The theme at this event was democratization of artificial intelligence (AI). AI thus becomes accessible and transformative power for the society.

Developers are inclined to digitize people, places and things. AI changes this. There are data models. We can query them. They act as neural reasoning engines. These can find patterns and that gives us predictive power.

There is a platform shift. That is the key to drive the economic growth. It can contribute 10 per cent to India’s GDP. That empowers people at large.

India is only second to the US in terms of total number of developers on GitHub, and by 2027, India may cross this to emerge as the hub of greatest number of developers. India puts generative AI projects on GitHub next to the US. India has achieved creditable momentum here.

There are AI transformation opportunities in India. AI can facilitate employee experience, customer engagement, business processes, and can bend the curve on innovation.

Microsoft has 60 Azure regions, 800 data centers. There can be breakthroughs through AI in science. Microsoft has global AI footprint. It believes in equitable AI.

Microsoft’s CEO Satya Nadella in a talk with the Indian CEOs in February 2024 said that it is for the first time that India’s fast growth in AI is bridging the gap between India and the rest of the world.

Since Nadella joined the industry, he has seen four big shifts in technology — PCs, client servers, web, mobile and cloud. AI is the first revolution where India is keeping pace with the world. There is no gap. India is not just talking about AI, but it is scaling AI.

He calls this ADVANA(I)GE. INDIA. He calls the AI engineers in India second only to the US. A technology is real if it can have real impact on the growth of an economy. In a growing economy that India is, a significant percentage of growth is going to be driven by AI. According to Nadella, AI’s contribution by 2025 would be worth $500 billion to GDP when India’s GDP is expected to reach $5 trillion.

It is necessary for India and the US to cooperate on the norms and regulations, instead of fracturing them.

If AI diffuses faster, it could be an ‘equal distributor of growth.’

Microsoft intends to train 5 lac students and job seekers in AI skills. It will provide AI technical skills to 1 lac young women. Microsoft will help equip 2 million Indians with skills in AI by 2025.

Deloitte has rolled out a chatbot for its 75000 employees across Europe and Middle East so that they can do PPTs and write emails and code. This will boost their productivity.

First, they launched a precursor to a full-fledged chatbot called PairD in the UK in October 2023. It was an indication that the full thing is work in progress and the employees were cautioned that the tool may go wrong, and they should exercise due diligence.

Other competitors tied up with existing AI firms for their chatbots, while Deloitte developed it internally through its AI institute.

It shows how professional service providers are automating their tasks. PwC is using chatbots in its legal and tax divisions. Allen & Overy, a law firm, uses it for drafting agreements subject to amendment and acceptance by lawyers.

Deloitte employees will take a training module before using the AI tool.

Mustafa Suleyman, a cofounder of DeepMind with Hassabis and Shane in 2010 is an AI heavyweight. DeepMind was later taken over by Google in 2014. Suleyman continued with the new company for five more years, but left Google to form a new company Inflection AI that offers personalized AI assistants.

Suleyman, though optimistic about AI’s efficiency increasing capability leading to increased productivity, is also apprehensive about its job replacement potential at the workplace. It is estimated that almost 47 per cent of jobs could be at risk of being automated by mid-2030s. According to a Mckinsey study, there would be 12 million job switches as AI takes over their roles by 2030.

Suleyman calls AI a truly transformative technology and not just a hyped concept. However, it can displace workers, if not regulated.

In LLMs, we come across inaccuracies and hallucinations in what they generate. We have previously discussed the concept of Retrieval Augmented Generation (RAG) where the LLM is integrated to relevant external knowledge in the generation process.

Though this addresses the problem to a large extent, there is an issue here. RAG’s success depends on the accuracy and relevance of the retrieved documents. If the retrieval process fails, we face the inaccuracies in the generative process.

Researchers have devised a pathbreaking Corrective Retrieval Augmented Generation process (CRAG). Here a lightweight Retrieval Evaluator is introduced. It assesses the quality of retrieved documents. The documents could be correct, ambiguous or incorrect. They are subjected to knowledge refinement. They are subjected to knowledge refinement and knowledge searching if they are ambiguous. They are subjected to knowledge searching if they are incorrect. Thus, the documents are corrected to x. These are then generated. This is the dynamic approach of document retrieval. It uses a decompose-recompose algorithm if the documents are sub-optimal. Thus, the generative process gives most relevant and accurate information.

CRAG surfs the vast web resources to augment its knowledge base. It goes beyond static corpus of data.

This is a significant leap forward for the LLMs. It sets a new standard for integrating superficial knowledge in the generative process.

There is fluent text with factual integrity.

Google maps are popular for navigation. However, organizations such as HERE offer maps with detailed mapping attributes, say for example ‘bridge attributes’. It tells the truck drivers the location of the bridges, their height, their load bearing capacity, and alternative routes if it is a low bridge and so on. Google maps are good, but the kind of detailed mapping HERE provides makes it suitable for autonomous driving.

Here is also developing 3D models for 100 cities. They are working on indoor mapping. They would map the height of the buildings and power lines. It will facilitate drone deliveries. They will prepare indoor maps of buildings. It will make easier to locate your parked car. At the same time, you can locate a spa or a restaurant in a big hotel easily. There are no flying cars now, but they are preparing routes for flying cars.

HERE is backed by Audi, Mercedes-Benz, Intel, NTT, Robert Bosch, Continental and Pioneer. It is a location tech platform.

In Germany, BMW’s Personal Pilot Level 3 automated driving function will be available in March 2024. HERE HD Live Map plays a central role here. In 2021, the same maps assisted Mrecedes-Benz Level 3 autonomous driving. Uber chose HERE maps to aid its geolocation functionalities and improve its pick-up and drop-off locations.

HERE has on its payroll 6500 employees, of which 3700, almost half, are located in India. Data processing, crunching and managing is done in India.

Though backed up by nine corporations, they have full operational autonomy. Over time, it will be an independent company. The three German companies will be their biggest customers, instead of owners. Though Audi BMW and Mercedes are the owners now, they do not get any preference over other customers. Mike Nef Kens is the CEO of HERE Technologies.