Ap_Web_Cm_Chandrababu_Naidu_Live_19-16-18

ETVBHARAT

1/6/2025

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00:00networks to generate new information.

00:03We don't get gibberish.

00:05We don't get gibberish.

00:07Especially under conditions of extreme events,

00:12climate change events, hazards and so on,

00:15we want to make sure that it's not sort of,

00:18because it's an unknown event,

00:20it doesn't sort of start manufacturing new information.

00:23So it's based on existing information.

00:25And when it doesn't know, it will say it doesn't know.

00:28There's limited information.

00:29But there are also monitoring and feedback mechanisms

00:32where we have human agents.

00:34So computational agents and human agents

00:36will sort of use the information together.

00:39So in a pilot case that we are planning to do,

00:41we want to sort of try and sort of test this framework

00:45because we want to make sure that there is

00:47repeated robust results coming out.

00:50It is AI.

00:51And then when users interface with it,

00:54they will use generative AI tools

00:56because that will help with natural language processing

00:59and things like that,

01:00so that people can use, ask questions in ordinary...

01:03No, are not in a position to do.

01:06Historical knowledge, everything you are putting there.

01:09Yeah.

01:10AI tools you are putting here.

01:13Real-time data feedback you are getting from...

01:17The field.

01:18The field.

01:19Yeah.

01:20Through data feedback collection, through manual,

01:25then reporting challenges, reporting requirements,

01:28geotagged local conditions, everything you are doing.

01:31Yeah.

01:32Even through cell phone.

01:35Yes.

01:36Photos, all these things.

01:37Yes.

01:38Then you can capture everything

01:40and at the same time you can give the outcome

01:44or write a solution for the problem.

01:48That is a hope, sir.

01:49That is a hope.

01:50But we want to proceed very cautiously

01:52because there is so much of an ability

01:55to sort of move too fast with generative AI tools.

01:58Right now you can go to chartGPT,

02:00you can go to various other LLM tools

02:02and ask questions about Andhra Pradesh natural farming.

02:06That we will ask,

02:07but only problem is here,

02:10real data, dynamic data, if you feed,

02:15then find a solution through AI.

02:18Yes, that is something that we are definitely...

02:21That it will help.

02:22Yeah.

02:23That is where I am thinking.

02:24Yes.

02:25What are all the tools available for us,

02:27if you can apply.

02:28Yes.

02:29Then solution will be

02:30or accurate solution,

02:36nearer to 95%, 90% accuracy.

02:39Then it is a game changer.

02:41Yes.

02:42Especially if there are,

02:43in the pilot phase if we have human agents

02:45who are sort of verifying that.

02:47Yeah, pilot project, both you can do always.

02:50Ultimately human angle will be subjective.

02:57Mission and accuracy will be more objective.

03:00Yes.

03:01That is the stage you have to reach.

03:03This is Harsha from Producers Trust USA, sir.

03:06Yes, sir.

03:07They are also meeting us in Davos.

03:08In Davos.

03:09Salesforce is one of the world's largest IP.

03:12Harsha, can you...

03:13Yes, sir.

03:14We are Producers Trust, sir.

03:15We developed a new data technology platform called LRM, sir.

03:18Based on Salesforce's CRM existing platforms.

03:20The idea, to put it in simple words,

03:22it is like to create a version of RTGS for agriculture, sir.

03:26So when created,

03:27the model would look somewhat like this, sir.

03:29Existing supply chain is very simple, sir.

03:31We have something like a producer,

03:33a trader, wholesaler, retailer.

03:35But if you can reimagine supply chain

03:37and think of it more dynamically, sir.

03:39And this is a technology platform

03:41which helps data intelligence

03:44and data coordination between all the actors.

03:46So we know where things are missing,

03:48what is the actual need of a brand,

03:50what is the actual produce of the consumer, producer.

03:53And then we can connect.

03:55And then we know where to invest,

03:56where to develop infrastructure,

03:58what are the critical missing gaps, sir.

04:00We'll have more precision.

04:01And one interesting area is carbon credits, sir.

04:03Just like in energy,

04:04we're talking about PM Suryagar,

04:06where the consumer can gain money by producing energy

04:11or by the root of solar.

04:12We can similarly give revenue through carbon credits

04:15by growing green cover on the farm.

04:18Because, sir, just in modular,

04:20we have this research for this green cover.

04:22That will lead to carbon credits.

04:24But to get that, we need data.

04:25So this is like creating an ecosystem.

04:27If you create an ecosystem,

04:29then carbon credits, money will come?

04:31Yes, sir. The idea is to do that, sir.

04:33No, earlier they used to give.

04:36Now they are going differently.

04:38But what is your assessment today?

04:40We are actually doing a pilot, sir,

04:42with the agriculture department, POC for...

04:44No, no, no.

04:45What I'm saying,

04:46government, overall global experiences,

04:48are you confident to get carbon credits?

04:51As of today,

04:53originally thermal plants,

04:55people used to buy carbon credits.

04:59Then they will produce...

Ap_Web_Cm_Chandrababu_Naidu_Live_19-16-18

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