Author: TJ Ravishankar

The real change in IT services businessNew 

IT firms never had to confront the question of technology, with their worlds largely revolving around application software. Until now. In an era of proliferating software, including apps, the big IT service companies built a huge business out of system integration. Now for the first time they need to confront technology/technologies but their trajectory or trajectories. It is anybody’s guess which path they will traverse.

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Rising above the (skills) mismatchNew 

There are problems that are indifferent to the level of economic advancement of a country. It was at once both a relief and a shock to learn that the problem of skills mismatch troubles not just India but advanced economies as well. However, this ‘common ground’ should not lull us into treating the problem as not deserving of immediate attention.

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The curious case of corporate brandsNew 

Building a corporate brand other than based on a family name is a different challenge. We have seen in India over the last 2-3 decades the emergence of successful corporate brands built out of a single business with a product/business brand that does not mention a family name. Some of them rose above their origins by reducing themselves to a set of alphabets. Slippery and nebulous and constantly reminding you of the six visually impaired men and an elephant, brands are an alluring field of exploration, especially corporate brands.

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Agentic AI model: foundational problems

Model development was always a challenge in any subject but is more so in an area where abstraction is the foundational attribute: AI. I have written earlier also that abstraction is the first step to building great software and especially in AI, because AI works on abstraction, which depends on mathematics of the highest level. Most people will say data but what they forget is that the model needs data and vast amounts of it, precisely because it has to abstract from it so as to work effectively whatever be the data. The model abstracts from the data so that it can work on any data! This is the crux of any model.

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Piercing the veil

RLHF – reinforcement learning through human feedback. This fanciful and seemingly innocuous phrase used in GenAI to moderate the output it generates hides a dark truth. GenAI needs content-moderation on a massive scale, because its inputs are the ‘vast corpus of humanity’, making it impossible to control. Some writers glibly talk about how such moderation, practised through the use of third parties, bring about ‘ethically aligned’ output, completely ignorant, wilfully or otherwise, of a vast environment of clearly unethical practices. We owe this revelation to an old institution: good journalism.

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