kellatirupathi

[00:16:31]  Hello.
[00:16:33]  Hello, sir.
[00:16:35]  Hi, Tripoon.
[00:16:36]  How are you?
[00:16:37]  I'm good, sir.
[00:16:38]  How are you, sir?
[00:16:39]  All good, all good.
[00:16:41]  Where are you right now?
[00:16:42]  Which city?
[00:16:43]  I'm at Hyderabad, sir.

kellatirupathi

[00:00:08]  Next candidate, please.
[00:00:39]  Ja, und das ist ja ganz schön gut so.
[00:04:32]  Yeah, but the second student has joined.
[00:04:37]  Yeah, please turn on your camera.
[00:04:45]  Babajit, can you turn on your camera?
[00:04:49]  Hello, your mic is moved.
[00:04:55]  Yeah, good afternoon, sir.
[00:04:57]  Open the camera.
[00:05:04]  Where are you?
[00:05:07]  Sir, right now I'm out of my house.

kellatirupathi

[00:00:00]  Sir, I'm not able to find it.
[00:00:02]  Can you align the
[00:00:06]  candidates as women as per their name that you have signed with.
[00:00:23]  Same to you.
[00:03:37]  Yeah, Pratham.
[00:03:39]  Pratham has joined.
[00:03:56]  Yeah, Amit, tell me about yourself.
[00:04:04]  Yes, sir.
[00:04:05]  Good evening, sir.
[00:04:10]  Tell me about yourself.

kellatirupathi

[00:00:00]  What are LLMs?
[00:00:02]  Yes, sir.
[00:00:03]  I have just an idea about it.
[00:00:05]  So just explain me what are LLMs, why it is used?
[00:00:10]  So LLMs are large language models.
[00:00:13]  So it was like a
[00:00:17]  charge GPT for example we can take a charge GPT so if we give any prompt to that it will it will take the words as a tokens
[00:00:28]  first it will convert into tokens and it will next it will convert into positional embeddings like it will convert into binary numbers and then based on the vector representation it will predict the
[00:00:41]  like output and it will give back to us so I know that how it works
[00:00:47]  Okay.

kellatirupathi

[00:01:22]  Sanchit Pratham will be joining in a while.
[00:01:25]  We'll just wait for him.
[00:01:28]  Oh, perfect.
[00:10:38]  Hello.
[00:10:43]  Good afternoon, sir.
[00:10:45]  Good afternoon.
[00:10:46]  How are you?
[00:10:47]  Fine, sir.
[00:10:50]  Okay.
[00:10:52]  So...

kellatirupathi

[00:00:10]  Hello Deepraj.
[00:00:13]  Good evening sir.
[00:00:14]  Good evening, very good evening.
[00:00:18]  So where are you from, Vipra?
[00:00:23]  Basically, sir, I am in village.
[00:00:26]  Sorry?
[00:00:28]  Basically, sir, I am from in my village.
[00:00:33]  I mean, I know, but where are you from?
[00:00:38]  I mean, I am from Devariya, Uttar Pradesh.
[00:00:42]  Okay.

kellatirupathi

[00:02:22]  Yeah, Robert.
[00:02:25]  Yes.
[00:02:26]  We'll wait for two minutes.
[00:02:28]  Okay.
[00:03:10]  Hi, Shubham.
[00:03:11]  This is Mohan from Nixie.
[00:03:19]  I am Mohan from NextWave.
[00:03:21]  So I will be coordinating with the students.
[00:03:24]  We have Rohit, our first candidate.
[00:03:33]  Hello, Vivi.

kellatirupathi

[00:05:05]  What else can I say?
[00:05:09]  Good afternoon, Naresh.
[00:05:12]  Please turn on your camera and PVs will be joining in a few minutes.
[00:05:22]  I'm going to send this in.
[00:05:54]  No need to share your screen as of now.
[00:05:56]  When a POC joins, you can...
[00:09:05]  Hi.
[00:09:09]  Hi.
[00:09:11]  I am Mohan from NextWave.
[00:09:13]  I will be coordinating with the students.

kellatirupathi

[00:00:00]  de un testudo.
[00:04:38]  And it will be joining in two minutes.
[00:04:42]  Yeah, okay, no worries.
[00:08:27]  The candidate has joined.
[00:08:36]  Just a second.
[00:08:55]  So, how do we...
[00:09:01]  Your mic is mute.
[00:09:07]  Sorry.
[00:09:09]  Hello.
[00:09:14]  So let's start with your introduction, including academics and everything.

kellatirupathi

[00:00:00]  Can we ask the next candidate to join?
[00:00:02]  Yeah.
[00:00:03]  Next candidates are, you know, they have native Hindi speaking.
[00:00:08]  Sorry?
[00:00:10]  Next one?
[00:00:11]  Next one, like, has native, his mother tongue is Hindi.
[00:00:16]  Mother tongue is pure?
[00:00:17]  Hindi, Hindi.
[00:00:19]  Okay.
[00:00:22]  Okay, we can proceed with him.