Emails (Others): RE: NICE TO HAVE MET YOU

Rohit ,

As discussed over phone , we look forward to your visit to our office on 2^nd May , at 9 am for demo of your product

In the meantime , following will interest you

Warm Regards,

Hemen Parekh

+91 98675 50808

3P Consultants \ Strategic Human Resources Consultants

{ My Comments in RED }

When artificial intelligence evaluates chess champions

April 25, 2017 by Alexiane Agullo

The ELO system, which most chess federations use today, ranks players by the results of their games.

{ Headhunting is a kind of “ game “ in which several “ players ( candidates ) “ compete against each other , in order to “ Win “ ( get selected= result ) for a given position }

Although simple and efficient, it overlooks relevant criteria such as the quality of the moves players actually make.

{ Moves = Job Changes during the course of the career / some GOOD and some POOR }

To overcome these limitations, Jean-Marc Alliot of the Institut de recherche en informatique de Toulouse (IRIT - CNRS/INP Toulouse/Université Toulouse Paul Sabatier/Université Toulouse Jean Jaurès/Université Toulouse Capitole) demonstrates a new system, published on 24 April 2017 in the International Computer Games Association Journal.

Since the 1970s, the system designed by the Hungarian, Arpad Elo, has been ranking chess players according to the result of their games.

{ Results = In how many GAMES ( interviews for different positions ) , did a candidate manage to cross each step of “ Elimination “ , to reach the final interview ? or “ get selected by different companies for appointment }

The best players have the highest ranking, and the difference in ELO points between two players predicts the probability of either player winning a given game.

{ Difference in the NUMBER of “ Elimination Stages “ that each candidate managed to cross ? }

If players perform better or worse than predicted, they either gain or lose points accordingly.

This method does not take into account the quality of the moves played during a game and is therefore unable to reliably rank players who have played at different periods.

Jean-Marc Alliot suggests a direct ranking of players based on the quality of their actual moves.

His system computes the difference between the move actually played and the move that would have been selected by the best chess program to date, Stockfish.

{ “ What / which” are those BEST MOVES that a executive could have , ideally made , to reach / qualify for a GIVEN POSITION ? }

Running on the OSIRIM supercomputer, this program executes almost perfect moves.

Starting with those of Wilhelm Steinitz (1836-1900), all 26,000 games played since then by chess world champions have been processed in order to create a probabilistic model for each player.

{ Among the 1275 positions that we have filled over the past 6 years , each IDENTICAL position , may be only 20 / 30 in number . But , if we ignore that , we have put through the process ( all stages ) , some 25,000 executives for these 1275 posts . And if there are ( say ) 5 stages of elimination for each post , on an average , these 25 , 000 executives may have gone through ( say ) 3 stages . That would make for 25000*3 = 75,000 INSTANCES of eliminations }

For each position, the model estimates the probability of making a mistake, and the magnitude of the mistake.

These models can then be used to compute the win/draw/lose probability for any given match between two players.

The predictions have proven not only to be extremely close to the actual results when players have played concrete games against one another, they also fare better than those based on ELO scores.

The results demonstrate that the level of chess players has been steadily increasing. The current world champion, Magnus Carlsen, tops the list, while Bobby Fischer is third.

Under current conditions, this new ranking method cannot immediately replace the ELO system, which is easier to set up and implement. However, increases in computing power will make it possible to extend the new method to an ever-growing pool of players in the near future.

From: Rohit Verma [mailto:rohit.v@ipredictt.com]
Sent: 26 April 2017 18:43
To: Hemen Parekh
Cc: Nirmit Parekh; Mitchelle; Prashant Sharma; Manoj Pandey
Subject: Re: NICE TO HAVE MET YOU

Sure,

Proposing either 2^nd or the 3^rd May, 9 -11 AM

Let me know which date works

Thanks,

Rohit

From: Hemen Parekh <hcp@recruitguru.com>
Date: Tuesday, 25 April 2017 at 1:13 PM
To: Rohit Verma <rohit.v@ipredictt.com>
Cc: Nirmit Parekh <nirmit@3pconsultants.co.in>, Mitchelle <mitchelle@3pconsultants.co.in>, Prashant Sharma <prashant@3pconsultants.co.in>, Manoj Pandey <contact@3pconsultants.co.in>
Subject: RE: NICE TO HAVE MET YOU

Rohit,

I had a meeting with my colleagues, this morning

Let me know your convenience next week when you could visit our office for a demo of your current products and for discussion on your proposed “ elimination algorithm “

Warm Regards,

Hemen Parekh

+91 98675 50808

3P Consultants \ Strategic Human Resources Consultants

From: Rohit Verma [mailto:rohit.v@ipredictt.com]
Sent: 24 April 2017 10:08
To: Hemen Parekh
Cc: nirmit@3pconsultants.co.in; Mitchelle; Prashant Sharma; Manoj Pandey
Subject: Re: NICE TO HAVE MET YOU

Thanks for the update.

Here are some platform websites and documents as prereads/precursor to the meeting.

While we will be discussing much in detail on our data science based recruitment intelligence platform for Enterprise (aka B2B platform),, we are seeing great adoption of our B2C platform which you may visit to experience.

B2C – www.careerletics.com

Access details

Password – ipredictt

(or you may create new account by submitting details)

B2B – Click on enterprise button on right panel of www.careerletics.com or visit enterprise.careerletics.com

Access details

Password – ipredictt

(or you may request for a new account by submitting details)

Also attached please find presentation for reference

Look forward to meeting.

I am reaching Mumbai on 27^th, so anytime after that.

Regards

Rohit

From: Hemen Parekh <hcp@recruitguru.com>
Date: Sunday, 23 April 2017 at 11:09 AM
To: Rohit Verma <rohit.v@ipredictt.com>
Cc: <nirmit@3pconsultants.co.in>, Mitchelle <mitchelle@3pconsultants.co.in>, Prashant Sharma <prashant@3pconsultants.co.in>, Manoj Pandey <contact@3pconsultants.co.in>
Subject: RE: NICE TO HAVE MET YOU

Rohit,

I plan to discuss this with concerned colleagues , on Tuesday

By end of the week or early next week , we can look at your demo ( current product ) and finalize the requirements for the “ Elimination Algorithm “

Warm Regards,

Hemen Parekh

+91 98675 50808

3P Consultants \ Strategic Human Resources Consultants

Nirmit / Mitchelle / Prashant :

Pl take a look at www.ipredictt.com

https://enterprise.careerletics.com/

From: Rohit Verma [mailto:rohit.v@ipredictt.com]
Sent: 23 April 2017 09:38
To: Hemen Parekh
Subject: Re: NICE TO HAVE MET YOU

Sir, Just wanted to know if you were able to have an internal discussion around data feed for creating “elimination algorithm”. It would be great if we can get started anytime soon, if approvals are in place.

Many thanks

Rohit

From: Rohit Verma <rohit.v@ipredictt.com>
Date: Thursday, 13 April 2017 at 5:15 PM
To: Hemen Parekh <hcp@recruitguru.com>
Subject: Re: NICE TO HAVE MET YOU

Thanks Mr Parekh for your time.

I am deeply enlightened to meet you. I am also very enthused to be aligned to your prophecies in some ways.

Thank you for the codes. We will review the same.

It would be great if you provide us opportunity to work on the “elimination algorithm”, and we will certainly build a Free of cost use case for P3 Consultants.

Look forward,

Regards,

Rohit

From: Hemen Parekh <hcp@recruitguru.com>
Date: Thursday, 13 April 2017 at 2:11 PM
To: <rohit.v@ipredictt.com>
Cc: <hcp@recruitguru.com>, Sachin Olkar <systemadmin@3pconsultants.co.in>
Subject: NICE TO HAVE MET YOU

Rohit,

It was nice to meet you this morning

Sachin is forwarding to you , source codes for :

www.GlobalRecruiter.net

www.IndiaRecruiter.net

www.RecruitGuru.com

Resume Rater ( tool )

When he finds , he will send you source codes for,

“ My Jobs / Resume Blaster “ mobile apps

Find below the link to my blog :

https://myblogepage.blogspot.in/2016/07/share-your-soul-outsourcing-unlimited.html

With Regards,