02:01It will be even like housemates, houseworks, and that stage is going to be done.
02:10So, in future, we will join here, and we will be able to do the same thing, and we will be able to do the same thing, and we will be able to do the same thing.
02:19We will be able to do the same thing, and we will be able to do the same thing.
02:35Now we have a generative large language model.
02:38We have a quen model.
02:40This model is used to use a byte or a moment.
02:47We also have a neural network classware.
02:50The classware is used in small questions.
02:55Move right, move forward.
02:57I detect that this classware is separate.
03:00I have to use a scientific-state classware.
03:06I have a current classware,
03:07but I am a state-classware.
03:10Of course, I had a local school and was able to use this class.
03:13I have an assistant.
03:15I have to use this classware.
03:18Each classware is used to use this classware.
03:20It's hard to use this classware.
03:23I can't read a paper.
03:24I can't read these�ans.
03:26We have it in a very posse.
03:28automation
03:29saskethi qathatho apaginchuna pana ni
03:31iti swaya ng gha ches thun di
03:32neural network kubayaginchudam vallaa
03:35bhavi shatthu lho manishi chees e
03:36marennu pannu ni e robot chees e la
03:38tteerjee dhidthu tundnaru
03:39iti robot gen e robot normal
03:42a a a vada ches thar
03:43a a vada ches e
03:45Johnson Motors vada yam
03:46torque eku kawal gavatti
03:48Johnson Motors vada yam
03:50normal motors vada yam
03:51load eku padese sarki
03:53moment uundakkuenna akkannu
03:55motors kalipodhe gavatti
03:56I am going to get a laptop in the future.
04:00We will get a light weight model in the future.
04:04We have a high-end program, and RAM is going to get a lot.
04:09We will get a lot of motors.
04:12We will get motors.
04:14We will get a lot of running.
04:19The case is about 2-0 in the future.
04:23In the future, the team has travelled to be a business model.
04:30I am going to take a lot of our projects.
04:33This is a cheeser cycle.
04:34I am going to get a lot of practice.
04:36We will get one year to prepare.
04:39We will get a lot of time.
04:41I am going to be doing it.
04:43We have to do it.
04:44The problem is that we are not doing anything like this.
04:49We are doing a lot of things in the future.
04:52We are doing this project in the future.
04:58We are developing a lot of technology in this project.
05:05We are doing AI models as a GPU.
05:11We are doing a lot of technology.
05:16We are doing a lot of technology.
05:19Retrieval augmented generation.
05:21We are doing a lot of technology.
05:26The real-time projects are made.
05:29The university is a part of the classroom.
05:32Classroom is a part of the project.
05:35It is a part of the project.
05:37The project is a part of the project.
05:40Especially if we were robots, first we started moving forward to the left.
05:43Then we thought that the intelligence will create.
05:46Generator A concepts have worked for almost 6 months.
05:50They built their own model.
05:52Available models are used to try and do it.
05:54Next, we have internet dealers.
05:55Then we go for a local try and do it.
05:58Suppose on the internet, we are the president of the US.
06:03But in the KELU, we have local data.
06:05We are such an area.
06:06They may not know.
06:07So, I would say, what are the specialization available in the university?
06:10So, they want to know about the university.
06:12Suppose there are a thousand pages of information on the university.
06:15We feed it everything.
06:16If a person can see it, they can forget it.
06:19But if everyone knows, they can learn, they can understand about the university and everything
06:23by interacting with this robot.
06:24That is creating an intelligent.
06:26Well, we have to share the information on their lives.
06:28Click on the next talk.
06:31Now, you can see the sailor, residing, and the next time.
06:33This is the T拜拜.
06:34Later, you will see the moon's trip.
06:35The moon's, the moon's, the moon's.
06:37They will see the moon's, the moon's.
06:40The moon's, the moon's, the moon's.
06:42These moon's, the moon's, the moon's and the moon's.
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