Hi Friends,

Even as I launch this today ( my 80th Birthday ), I realize that there is yet so much to say and do. There is just no time to look back, no time to wonder,"Will anyone read these pages?"

With regards,
Hemen Parekh
27 June 2013

Now as I approach my 90th birthday ( 27 June 2023 ) , I invite you to visit my Digital Avatar ( www.hemenparekh.ai ) – and continue chatting with me , even when I am no more here physically

Tuesday, 6 April 2021

DIGITAL BIOLOGY – PETER BENTLEY




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When I read any book, I scribble my comments / notes in the margins


These reflect my views / opinions about what the author is saying – including my disagreement

Often, my comments are in the nature of telling myself :

Hey ! We should try out this idea in our own business ( Head-hunting / Online Recruitment )

Following are my comments re :


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Page No 16       

·         This is how Hindu Vedas deceived, both the universal & the “Atma “-Anadi [without a beginning] [shashwat=permanent]-Anant [withontan end]

Page No 18

·         This two has been proved wrong a few months ago!

Page No 19

·         Matter & Anti-matter/Dwait& Adwait [Two-ism] & [unit-ism] of Vedanta.

·         Maya wad=Illusion-ism

·         It is Anadi [without a beginning!} without an origin.

Page No 22

·         Hindu scriptures also describe “Atma “as being “Nirguna” [I, without any “properties]

Page No 23

·         What caused this chaotic universe to come into existence?

Page No 24

·         Already disproved

 Page No 44

·         Just “different”

Page No 46

·         So does business.

Page No 55

·         From 50,000 resumes we need to compile 500,000 Keywords and “evolve” co-relation between every unique set of keywords with “salary levels”& “Designation levels “which are the results of “SELECTION “by the Businesses evolution process 21/04/02.

·         This can be made into a predictive technique-whether an executive will fail or succeed in his next job.

Page No 56

·         Or “keywords”-belonging to a “language universe’?

·         Employee does not trust an unpredictable boss!

·         Software’s with a capacity to “learn”

Page No 75

·         Neural network software works on this basis.

Page No 76

·         Post experience

Page No 81

·         Also an illusion?

  Page No 83

·         Feedback loop.

Page No 87

·         Hardly a day passes without some Japanese/Korean company coming out with new model of voice-activated robots & toys, who seem to “learn” 

Page No 91

·         By this token, I suppose, one day neural network software would be able to study / examine” keyword in a resume than compare with keyword specified by client and okay or reject a resume.

·         Collection of good & bad resumes?

·         Brand new resumes arriving daily in our office.

·         To-day our consultants are spending 2/3 hours daily “reading a set of resumes, to decide which are good & which are bad. Their [biological]

·         Brain is “processing “resumes & giving “weightages”

 Page No 92

·         In our case when we tell the network “this resume is good it will look-up & record & remember what KEYWORDS it contained [i.e. what makes it “good].

·         We could also give the neural network on puts such as how often this expansive gets short listed or gets an intewiew calls.

·         Cyril wrote such software in 1995/96 & ran it for several on his computer. The software gradually learned to identify “address “in only resume.04/05/2002

Page No 93

·         Con text cartridge “software [now a part of ORACLE 8i database is supported to be working on neural network.

·         Does “resumix software use this we can treat in coming resumes? As product”

·         In our case, we would have to “train “our neural network software, on

·         Thousands of resumes, which our, consultants [human experts] have, earlier, categorized as “GOOD “or “BAD “depending upon, the [highlighted] KEYWORDS, contained in resume.

Page No 94

·         Resumes, too, contain lot of “i.e.superfluos/unrated words.

Page No 100

·         Maya Vad OF ancient India [illusionism] 05/05/2002 Anokhce’s 16th birthday. 

·         Somewhat like magician kill’s [the wet of illusion]

Page No 101

·         Perhaps, we do “sense “but jail to “interpret”

Page No 112

·         Like dot –com companies which suddenly cropped up during 1994/99

·         And then died equally suddenly? But not trying in a “state of chaos”.

Page No 124

·         Some 10/15 years back an India scientist at AT&AT, found an algorithm for talcum scheduling.KARMARKAR ‘S’ ALGORITHM
Page No 125

·         In one aquarium. A very small electrical current in this reversed, making a school of fish to reverse direction.

·         Like people sitting in a small group-in an otherwise empty bus, but if is otherwise “full, a person tries to find farthest empty seat!

Page No 129

·         We will be able to build net when we list 300,000 keywords in 10,000 resumes belonging to 100,indrstries/ 50 functions / a designation-level/10 educational levels & co relate [give weightage]with up got appointed who got short-listed &how many times 05/05/2002

Page No 140

·         If we treat each resume [-and job a vat] as an “organism “and if we study thousands of resumes we will discover elefionite “patterns” of. Keywords, in each”type”of resume. Keywords are DNA to resumes.

Page No 141

·         May be, we too will discover that no two resumes have precisely the /identical set of keywords although these may be very very similar.

·         To test this by hypotheses, we need millions of resumes!

 

Page No 144

·         Is it likely? That we will find same / similar “keywords” [DNA] in, say job destination or Experience parts of resumes of executives form similar”

·         Industry & function”?

·         Each unique combination of “ind.”& funs is like a plant “species we will uncover the similarly of keyword in each such species.

·         We will find these obvious patterns pattern in resumes too!

·         Page No will this be somewhat like saying: “give me a person’s INDUSTEY & FUNCTION, and I can construct his resume. 

Page No 146

·         We will need to establish our own “rules by figuring out the co-relation

·         Between Keywords [found] on one hand and the age /sex/eduqnali/Ind./funs/Designation etc. On other hand.

·         Obviously these rules are built the resumes. We need to figure these out.

Page No 150

·         Resumes are like melodies structures [of paragraphs & their arrangement/order]

·         Repeating elements [keywords]]

·         Symmetries [phrases & sentence employed]

Page No 151

·         Pro extending this logic we may soon be able to” see”muscic-smell “image eats. 

Page No 159

·         E.g.: neural net software’s that mimic the “learning “of a human brain. Page No 164

·         We keep coming back to neural net software’s that “learn.

Page No 171

·         Let us analyses “keywords “contained in the resumes of all the candidates that we succeed in placing [appointing]end see if any particular “pattern/behavior”emerges.in reverse can we predict “success-rate “for a given patten?11/06/2002

Page No 173

·         Can we boost the “success-rate of a candidate by planting in his resume, the “missing “keywords?

Page No 186

·         Winning Keyword patterns=patterns of keywords contained in resumes of “successful candidates.[success “can be defined as those who got shortlisted or got an interview –call form client.

·         So during our search it we find such a pattern in a given resumes we may have found a winner”!

Page No 190

·         How do keywords in thousands of resumes mutate with higher Edu/age/exp/canwe d’état a pattern? Like GM foods, can we grow’ genetically Modified Resumes, which have much better”chance”of getting “shortlist”-and ‘selected’-and “and appointed”?

Page No 192

·         I suppose programs have been writer which would remove from a resume all proper nouns/verbs/prepositions etc.-so the only words left are keywords”

·         Once this is done it would be very easy for a human expect to defeat& highlight “keywords using our “highlighter “software.

Page No 200

·         What “Nrefeeional bodies” we are member of what “bosses “we worked under. What “training courses “we underwent.

·         It we were to examine, points mentioned on top in the resumes of “successful” executives, would we see some “pattern” [genes] emerging.14/06/2002

Page No 201

·         What schools /colleges /universities we studied in what cities we lived in what companies we worked for.

·         But who is a “successful’-[a well-developed] executive? Shall we arbitrarily define an executive as being “successful “if he became-a-vice-president “in 15 year from date of graduation a gen.mgr’in 10 years.

Page No 202

·         Same can be said about our “keyword project”thre is a long journey ahead.

Page No 207

·         What patterns of “development-stages “can we expect to find if were to examine the resume of young executive after every 5 years? Then divide them into successful “&non-successful” executives.

Page no 217

·         Using “keywords” ”tiles dishes, we can produce an infinite patterns resumes using a grammar rules! 24/06/2002

·         Page No yesterday on TV [robots ump 2002 I saw two human looking rollout’s pay football!

Page NO 233

1.    Once we are able to disc   to discover the “pattern of keywords key phrases/key sentences/key pares] followed in resumes, we

2.    May discover their “golden mathematic. Millions unique resumes bill/butut together from.

3.    Permutation / combination of a few hundred keywords following

4.    Following single grammatical rules.

Page No 235

·         Neural net software’s oiled up on feedback in order to leam/to improve more &more complex.  

Page No 243

·         Someday we will a periodic cube whose 3 sides are industry /function/Designation level 210x120x10] and populate each cell with profanity of  this cruel with,probality of occurrence of keywords “what will it predicd.03/07/02

Page No 249

·         Already out in market. We are into this.

·         Tower of babel   language translator brat-in.

Page No 520 

·         Vedas on puranas have described the capabilities of Anima [to become smaller than an ANU-or atom grime a [to became bigger than a mountain a GIRI].

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