VEGA AI

[00:00]: Uh today uh our our first uh person is

[00:05]: Py Pish. I'm just going to bring you

[00:06]: straight in cuz I hope I'm bring I'm

[00:08]: hope I'm pronouncing your name right. Is

[00:10]: Pish?

[00:11]: It's Pumad.

[00:13]: Push. Push. Sorry. Push. Uh it's great

[00:16]: to have you here. Um and I'm really

[00:18]: excited for this because um I've been

[00:20]: following Vega AI for for a while now

[00:22]: and and just that ability. I think

[00:25]: sometimes teachers see those tools like

[00:27]: Dolingo and think, "Oh, I wish I could I

[00:30]: wish I could like give that to my

[00:32]: students, but it's but it's what I

[00:34]: teach, not not languages." And and I

[00:37]: think Vega AI really opens the door to

[00:40]: give that capability to our educators.

[00:42]: So, I'm just going to hand straight over

[00:44]: to you and um looking forward to to your

[00:46]: presentation. Thank you.

[00:48]: Yep. Thank you. Thank you, Dan, for the

[00:50]: opportunity. So, hi everyone. I'm push

[00:52]: co-founder of Vega AI and as you see let

[00:55]: me go towards the presentation

[00:58]: so we started building Vega AI with one

[01:01]: sole purpose of quantifying learning and

[01:04]: making learning datadriven as well as

[01:06]: teaching datadriven right so we started

[01:10]: to understand and analyze that there are

[01:13]: few problems on the educator admin side

[01:16]: and few problems on the student side

[01:18]: that needs to be solved. So when you

[01:20]: talk about educator side uh when

[01:23]: teachers let me move to the next slide

[01:27]: when the teacher basically spent a lot

[01:30]: of time in creating content as well as

[01:33]: it's not just content maybe you create a

[01:35]: digital content in the form of PDF but

[01:37]: you cannot track data and insights from

[01:40]: there like in this day and age where we

[01:42]: quantify our health steps our daily walk

[01:45]: steps using our smartwatches we use uh

[01:48]: insights from uh say finance market to

[01:52]: invest in shares in real time. But in

[01:55]: real time we are not able to track what

[01:57]: our student is doing, how much time they

[01:59]: are spending, what's their accuracy,

[02:01]: whether they have studied or not at the

[02:03]: very first place, practiced or not at

[02:05]: the very first place, right? And we and

[02:08]: my background also goes for a decade or

[02:11]: teaching last decade. I used to be a

[02:13]: teacher. So maybe you all can agree with

[02:16]: me or disagree how much effort we put as

[02:20]: a teacher until a student doesn't

[02:21]: practice you cannot expect an outcome

[02:25]: desired outcome right so practice is the

[02:28]: key so we started building a platform

[02:31]: which enables a educator or a school to

[02:34]: build any courses when I say any courses

[02:38]: right from building a taxonomy to uh

[02:41]: creating quizzes over there or learning

[02:43]: material materials or even uh video

[02:46]: spaces where you can interact and learn

[02:48]: becomes very easy a modern way to build

[02:51]: things in a day in minutes using Vega AI

[02:55]: right and once the student takes any

[02:58]: action the insight is populated on your

[03:00]: dashboard so that you can take

[03:02]: datadriven decisions and at the same

[03:05]: time students who are self motivated

[03:07]: they can use your AI aft to get your

[03:10]: doubts cleared etc Right.

[03:13]: And as I mentioned in starting like our

[03:15]: mission is to quantify and personalize

[03:18]: learning thus making teaching and

[03:20]: learning truly datadriven.

[03:22]: When we say we are truly making learning

[03:26]: and teaching datadriven we are covering

[03:28]: entire spectrum of teaching and

[03:30]: learning. Hence we call oursel as a

[03:32]: fullstack AI powered education platform.

[03:35]: We allow you to build any datadriven

[03:37]: courses which you can track and analyze.

[03:40]: on a click of button you can deploy it

[03:43]: uh to the student portal. Once it is

[03:46]: deployed on your student portal they can

[03:48]: take actions on it. They can practice on

[03:50]: it and whatever they do we capture

[03:52]: insights that is shown to you as well as

[03:55]: students and thus you take action and

[03:57]: based on those actions our AI engine

[03:59]: personalize the learning experience and

[04:01]: not just AI only personalizes even human

[04:04]: teachers we can personalize our next

[04:07]: class actions. Suppose you get an

[04:09]: insight that okay out of this 10

[04:11]: students frequency of error on a

[04:13]: particular topic say in linear algebra

[04:16]: it's quite high. So you can go in the

[04:18]: next session for that particular topic.

[04:21]: Okay

[04:23]: let me go to the first spectrum or the

[04:25]: first pillar of Vega AI build. You can

[04:28]: build, you can create modern courses in

[04:29]: minutes like course taxonomy is decided

[04:33]: right in the starting on a click of

[04:34]: button that helps you to capture

[04:36]: structured insights. You can generate

[04:38]: autotag content in seconds. When I say

[04:41]: in seconds, you don't even have to worry

[04:43]: about latte coding special symbols. You

[04:46]: just upload it. Our system handles

[04:47]: everything. Classify things and make it

[04:50]: ready to use in a test. And you can

[04:53]: generate also practice test and

[04:55]: resources instantly.

[04:58]: Once things are built, you want your

[05:00]: students to take it, right? You can

[05:02]: click on a click of button. You can

[05:04]: deploy it on your student portal where

[05:06]: they can see the courses that you have

[05:07]: deployed, the test assigned to them. And

[05:10]: once they take action, you capture

[05:12]: insights and also we provide G label

[05:14]: student portal for schools and

[05:16]: educators.

[05:19]: Once it is deployed, they take actions.

[05:23]: Once they take actions, we capture

[05:24]: insight as I mentioned earlier as well

[05:26]: like frequency of error analysis, time

[05:28]: management analysis. Okay, we we allow

[05:31]: also automatic grading of different

[05:33]: question types be it MCQ, short answer,

[05:35]: long answer, passages and in fact

[05:38]: listening and speaking. Suppose you want

[05:40]: to create a course on Spanish speaking

[05:42]: or English speaking courses or for is

[05:44]: TOFL our system can listen to what they

[05:48]: are speaking grade them and that too in

[05:51]: your own rubric. the rules that you set

[05:54]: and not just grade they also give a

[05:57]: immediate they also get immediate

[05:58]: feedback

[06:02]: and once the AI system the AI

[06:04]: infrastructure understands where a kid

[06:07]: is missing what are the strengths and

[06:08]: weaknesses it makes them a personalized

[06:11]: learning path okay so we allow every

[06:14]: educator to create their own AI aftar

[06:17]: which is there for students 24 + 7 to

[06:19]: support them and not just create uh we

[06:21]: allow you to train your own aftar in

[06:23]: your own domain of area of expertise and

[06:27]: not just you can train it because once

[06:29]: you train yourself you need to take any

[06:31]: exam to see where you stand. Similarly

[06:33]: you can evaluate your own aftar compared

[06:35]: to chpds or perplexities of the world so

[06:38]: that you can see b in your domain how

[06:41]: your aftar is performing better than any

[06:43]: top model lms in the world. Okay. And as

[06:47]: the last point mentioned, personalized

[06:48]: practice path tailored to each student

[06:50]: updated every week because learning is

[06:53]: not linear. You do actions, you improve.

[06:57]: So the system keeps on adaptive ad

[07:00]: adapting based on the students progress,

[07:02]: how they are progressing and it gives an

[07:05]: adaptive next actions.

[07:09]: When I say why AI stands out uh compared

[07:12]: to any top LLMs,

[07:14]: LLMs stop just at creating resources

[07:17]: like suppose if you want 10 questions

[07:19]: from a topic it can create but to get

[07:22]: into a system is a lot of manual work.

[07:25]: Forget uh like about copying a special

[07:27]: characters or equation. It takes a lot

[07:30]: of time and again you cannot track a lot

[07:33]: of data. So we handle right from

[07:36]: learning creating learning resources or

[07:37]: content you can build structure courses

[07:40]: not just build and you can just deploy

[07:42]: it give it to your students and they can

[07:44]: take actions

[07:46]: based on the learning data

[07:49]: also uh we have worked with a lot of

[07:53]: schools test prep companies so which has

[07:56]: helped them grow their revenue as well

[07:57]: using our uh field lead generation tool

[08:00]: using our insights their conversion

[08:02]: rates improved u a lot of school

[08:04]: scientist companies have launched

[08:06]: multiple course right from digital SAT

[08:08]: to ACT to TMUA to all the AP courses

[08:12]: within weeks and months.

[08:16]: Uh I would love to show you guys a demo

[08:19]: video what our product can actually do.

[08:27]: As you can see the first step building

[08:31]: courses

[08:32]: you just have to put the course name and

[08:35]: our system will start giving you the

[08:38]: taxonomy for it. If you have any

[08:40]: suggestions you can prompt again then

[08:42]: again you can edit from here which shows

[08:44]: you the tree structure of the taxonomy.

[08:46]: Once you are finalized mark and you can

[08:48]: start creating your question bank. For

[08:51]: example, if you want to create a

[08:52]: question bank with handwritten notes,

[08:55]: just upload it, click on the question

[08:57]: type and extract it. See what's our

[09:00]: system does in seconds.

[09:03]: It has handled all the latte coding at

[09:05]: the back. Okay. Not just this, it has

[09:07]: classified what are the concepts checked

[09:09]: in this question right from differential

[09:11]: calculus to chain rule.

[09:13]: So that in long run we can build a

[09:15]: knowledge graph.

[09:20]: Next thing if you want to create a

[09:21]: entire assignment or a quiz simply you

[09:24]: have to prompt it or you can upload your

[09:26]: PDF that just make a digital quiz on

[09:29]: this okay where you can capture all the

[09:32]: insights right from time management to

[09:34]: accuracy and mastery.

[09:39]: As you can see you can preview this and

[09:41]: once it is previewed and saved you can

[09:42]: deploy it or publish it to your student

[09:46]: portal.

[09:47]: Once you click on deploy, boom, you can

[09:51]: directly go to your student portal as

[09:54]: well.

[10:00]: Okay. On the admin side, you can capture

[10:03]: frequency of error analysis on different

[10:04]: different topics on different topics

[10:06]: where they are spending more time. There

[10:08]: is no point of just accuracy if you're

[10:10]: taking more than the average time. So we

[10:13]: can we show you all the vital analytics

[10:15]: and insights of a single student to a

[10:18]: group of students so that you can save

[10:20]: your time as well. And this is how the

[10:22]: student portal looks. Uh kids can go and

[10:25]: take a fulllength test or a quiz or

[10:27]: resources. If you have any lesson plan,

[10:30]: works card or flashcards as well you can

[10:32]: create. Okay. And once a student starts

[10:35]: taking a test, this is how the portal UI

[10:38]: looks.

[10:41]: So we capture all the insights like how

[10:43]: much time spent on the screen per

[10:45]: question

[10:48]: and once they click on submit

[10:50]: our system generates the report and

[10:53]: analysis immediately. The AI also

[10:55]: generates a feedback which area doing

[10:57]: they are doing good or where they needs

[10:59]: attention. Okay.

[11:03]: And as you scroll down you can review

[11:05]: the test with AI aftar. It can be your

[11:06]: day after and kids can ask question like

[11:10]: hey where did I go wrong or can you

[11:12]: explain the solution better and once you

[11:14]: understood where you went wrong okay you

[11:17]: can ask for a similar question to

[11:20]: practice again to check whether now you

[11:21]: have understood the concept or not okay

[11:24]: so this is how the entire

[11:27]: uh portal looks like there's more to it

[11:29]: you can build your own AI agent

[11:31]: yeah I think no it was a great overview

[11:33]: and I think um I think a lot of people

[11:36]: who are watching are going to want to go

[11:37]: away and try that. Thanks for thanks so

[11:39]: much for showing us that. And um do go

[11:42]: have a look at because when you say full

[11:44]: stack, you literally mean that as well

[11:46]: uh in what educators can do there in

[11:48]: terms of bringing their their courses to

[11:51]: life. Uh go check them out myvega.ai. Uh

[11:55]: thanks for joining us and sharing uh my

[11:57]: Vega with us.

[12:00]: Yep. Thank you. Thank you Don for the

[12:01]: opportunity and uh look forward to

[12:04]: speaking to you guys. You can book a

[12:06]: demo with us or you can mail me

[12:08]: directly. Would love to present you the

[12:10]: product oneonone as well. Thank you

[12:12]: everyone.

[12:13]: Thank you. Take care. Okay, we

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💡 Explanation

JavaScript Fundamentals Quiz

Test your knowledge of JavaScript basics

180s

Question 2 of 5

Question 2

Which method is used to add an element to the end of an array?

A. push()

B. add()

C. append()

D. insert()

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