DKN's AI Post from DKN to L I



Introduction

By time of this writing 2025/01/30
I has been the top Post performing about AI on LI on the list below with
359 impressions  for   Item #1=Reality of AI system
251for #2=Some Critical Questions
530 for #5=A Proper Way
244 for  #4=Validation of AI
1124 for #10=Validation of AI
1036 for #7=DKN's View


  1. Reality of AI system
  2. Some Critical Questions To All Serious AI Professionals
  3. Unrealistic AI-ML
  4. A Validation of AI System
  5. A Proper Way Forwardfor AI
  6. Risky AI-ML
  7. DKN's View
  8. Very Tiny AI System
  9. Very Tiny AI System
    10. ML-AI is extremely dangerours like nuke

ML-AI is extremely dangerours like nuke posted on 2024/04


Why ML-AI is extremely dangerours like nuke ?
Dear LI Fellow First and foremost is my sincere apology to any inconvenience may cause from this post Recent I found a comment from Elon Musk from GGL in meeting with UK prime minster on 01 Nov 2023 in UK Tech billionaire Elon Musk said that AI will have the potential to become the �€œmost disruptive force in history.�€� First I just want to emphasized here I assume he meant ML-AI( Machine Learning) Not original AI( first proposed by Warren McCulloch and Walter in 1943, 80 years ago I cannot reach him for clarity I absolutely disagree if He meant AI Even with my fuzzy yeyes and head due to my 2 strokes 7 years ago in June 2016 Still fortunately my bledssed human Intelligent(BHI) still able to appreciate his sincere and thoughtfull warnnings regarding ML-AI I'm a unfortunate retiree with disability at age 69 with limited time budget left over Still worried on the well being of 3 my blessed college graduated kids( 2 Daughters Mary Helen+1 Son David) I'm prepared to shake The Lord hands I have a joke to share with You One day Head of Heaven (HofA)call Head of Hell(Hof L) for a chat HofA:"How going on down there" HoL :"It's really relaxing and comfortable down here ;-)" HoA"kidding How come ??" HoL"No idea Very 1st time an Engr get here He created a lot like Air Conditioner Electric generator Washing/Laundry machine etc" HoA"It must be a huge mistake in letting Engr to be there So I have no worry my upcomming last minute to meet HoA ha ha ha :-) I wish to present my analysis on this warning in this post As usual with my favorite divide & conquer way We have 2 part= AI+ML AI system is composed of 3 Layers (1) Input Layer ( in Training Data) (2) Hidden Layer (NOT in Training Data for number of neurons set by AI guy ) to be trained to provide our desired output (3) Output Layer (in Training Data) for desired output Each Training data set is simply composed of ONLY Input Data and our Desired Output DataThat's it Just I/O Data Nothing more or less So AI is absolutely not harmful, but helpful as it can povide our desired output we really want While the so-called ML-AI is unable to provide such simple IO Data and passing the blame to Machine These ML guys must have no idea what they're doing??! Is there any useful system providing no output Is there any system with only either input or output nut not both ??!! That is the key difference between AI and ML-AI Here is my question to ML-AI guys What such ML-AI can realy provide us Are U saying depenging on Machine ?? That is where the root cause of real danger The Machine could explode blow away all like a nuke bcz absoluely no guarantee to prevent it from happening That is why the ML-AI is absolutely not allowed to be developped at all Am I reasonable or agressive Now I challenge ML-AI to provide I/O data for a better Edu & Health Care for USA May GOD bless USA Amen DuyKy Nguyen, PhD in EE Ex Symmetricom Sr R&D Eng, unfortunate retiree with disabilty

Tiny AI posted on 202402

VTFI (VeryTiny Fractional Intelligence, VTFI) Is is just a VTFI not AI as discussed in this post
I got involved in AI in 1993( 30 years ago) when my class mate at UTS asked me to help his brother in AI prj at the end of the brother's AI class in Computer Science at Sydney Univ The brother loaned me an AI text book used in the class That's how I started my AI After my AI Research contract at UTS in 1994 I never involved in AI So I have no idea on latest AI update Correct me if this post contains my outdated AI info But I'm too sick in reading so many hoaxes on AI It's unwise to invest our limit resource time & money at something we're not sure like AI AI advocate may not agree with me So may I have their answers to my question below per my outdate AI info got 30 years ago 1)AI is a neural network similar to human brain believed to have neurons connected with adjacent ones via a weighed link and each neuron become active if incoming signal ampitude above some threshold level Is it still valid ?? 2) Just got answer to my query "how many neurons are in the brain" from Goggle a human brain has more than 80 billion neurons, all connected in a massive network that makes us who we are? My next question is can we implement our AI with such huge number ? I really don't think so 3) If not What number of neurons to be use in our AI and WHY ?????????????????? It must be a pratical small number hI AI expert, would You pz provide me number of neuron U use in your AI network I really doubt if it reach 8 million, a very tiny fractional of 80 billion 1 part of 10 million That's why I call Very Tiny fractional Intelligence It's smaller as human brain is not active 100% What are activive types in human brain processing/reasoning ??% storage??% cognitity??% what else ?? The current AI model for what brain activity is it Processing/Reasoning ? How these activities interact with each other ?? These issues could be adressed in Neuro Science, if so any new significant break thru yet?? How Neuro Science cooperate with AI to support each other for some break thru?? If we cannot answer to these questions and still to want to invest to AI We 're all guilty to our next generation in wasting our limit resource into wrong investment we're really gambling on AI upon our limit resource, myself first so I have this post Are my concerns reasonable or too conservative ?? I'm quite aware of tradeoff, no pain no gain But what we gain with AI and at what cost ?? What pain we left for our next generation is it a painful system of education and of healthcare ?? Why not stem cell R&D for cure of paiful disease like cancer, lidney heart ?? I really offer my sincere apology for any incovenience may cause from this post to any L_I member May God bless USA with right investment for healthy safety to all future USA fellows Amen DuyKy, PhD, Ex Symmetricom R&D Engr, unfortunate retiree with disability

DKN's Viewposted on 2024/01

DKN's View on AI R&D In this post I wish to present my narrow view on our current AI R&D Sincerely sorry for any incovenience may case from this post To the best of my knowledge Our current AI has been based on the the McCulloch and Pitts MCP model, named after the two scientists (Warren McCulloch and Walter Pitts) who proposed it in 1943, 80 years ago However per my control back ground and 4 years as tutor in a Control Lab for Senior EE / Master student and practicing Engineer in 1994-1997 in Instrument &Control EE at University Technology Sydney Australia All mathemacical models cannot be use before verified My note on modelling in this control lab can be found below https://lnkd.in/eqA6ugRC So my real concern is Was this mathematical 80-year AI model was ever verified ?? I could not find such info via googling If probably it's not So all our AI R&D may have been rendered useless ?? What a real unfortunate we may have waisted alot of our limit real resource on unreal and worthless work ?? In my control discipline, the followings are strictly hornored 1) system identication for a mathematical model 2) system verification for a evaluation of output of simulation of the model and output of real system using the same step input 3) once verified a system controller is developed based on the verified model As You've seen in my modelling note a mathematical was precisely derived per physic law with some assumption All system verifications were not absolutely matched but within acceptable tolerance Per my control discipline I've seen as a very productive R&D with proper working attitude There must be some kind of problem in any product Once I was reported a problem in my responsive product My first job was to verify its existence before start solving I always see my product is buggy and think seriously on its ill behavior to prepare precautious accordingly Being human being err after all The only way making no mistake is doing nothing but it's not our choice So I'm not suprised with our wrong AI approach I truely honor the job well done in creating MCP model as a mechanism to mimic human brain Regardless how accurately it behaves like human brain or not It's was a original contribution to our scientific technical socoiety somehow in stimulating new area hopefully not any harm to human kind Even it realy a correct model of human brain But it's impossible to implement such model with of 80 billion neurons as in human brain The more expecting on AI the more wasting on our scare resource Before move on with AI using this reasonable MCP model We have to set what our reasonable goal to achieve if not getting it within some resouce constraint anf time frame Forget AI once and for all and focus on urgent task in health care It's unwise to get work done at all cost Or we want challenge ourseves with AI Let's challenge ourseves with better health care for all Sincere Rgards DuyKyNguyen, PhDEE, ex Syymetricom R&D Engr, unfortunate retiree with disability!!

Risky posted on 2024/03

A risky ML/AI Dear my L_I fellow First and foremost to offer sincere apology to ML- AI professionals and I also offer my sincere appreciation to correct my outdated AI know ledge in this post based on what I got in 1994 when I first got into AI followed by my AI R&D contract at Univ Tek Sydney with NSW medical center in diabetic prediction for potential diabetic patients I've got bad feeling from all kind of AI ads whenever I surf www So if I were not put out this post I really feel serious guilty to the next generation per their unaffordable and painful healthcare as we waste our limit invaluable resource[time money]for risky ML-AI Basically AI is a network of neuron[neu-net] with connection whose weights to be determined in a training to get desired output. The neuron is activated for output if input above some level using switching function per math model known as perceptron proposed by Mc Culloch in 1943 In 1960, there was a demonstration of the �€œperceptron�€� �€“ �€œthe first machine learning,�€� by Frank Rosenblatt known as father of deep learning Traning data required to eliminate error between desired/actual output.A positive sum of squared error as multivariate function of weights used in training; ZERO is minimum of positive number hence a numerical minimal method used in this training; minimal methods are classified by 1st derivative gradient class with line search [LS] like steepest descent [SD]and gradient +LS+2nd derivative Hessian[incl curvature for better convergence quicker done] like Conjugate Gradient or no gradient at all like Nelder Mead; it is in a iteration loop requiring exit condition must be provided like error below 1e-6 [part per million] SD is the simplest and the worst widely used currently hence no converegence, no result Obviously there's no problem at all with desired output as they are what we want However the real problem is input data must be validated Even worse as input data may not guarantee getting correct weights for desired output as the training might be early terminated due to divergence of computational method [ bad data-in or round-off err in computation ?] when a max number of iteration say 100k is reached while the error above the predefined tolerance and the results are rendered useless per big difference between desired/actual outputs Getting training data is very costly and ML came to exist But this also bring a new serious problem how to validate input data So ML is not promising anything at all !!?? Data getting more complicated and huge over time so it's a real big task to get data validated So I urge not to invest in ML/AI until data validation fully addressed It appears to me we have some very challenging to deal with before AI/ML is acceptable 1) validation of input data and data distribution for convergence of numerical method 2) Efficient minimal methods for any kind of data May God bless happy healthy wealthy life for all USA people Amen Sincere Regards DuyKy Nguyen, PhD in EE

Proper Way Forward For AI posted on 2024/04

A proper way forward of AI/Ml and its usage dear my LI fellow In my most recent AI post, I did mention validate all data used and data are getting a lot more huge over time. So certainly this task is a lot more challenging As my favorite way of divide & conquer, we should look for a better DB [data base] so it'd make this task more feasible In addition DB itself can used by it self alone as AI as DB can be used to recognize or to predict like AI with appropriate DB structure to be developed I bet some AI is disguised with DB underneath Rather a true AI with neurons I overheard concern of AI would take over human and render human in redundant I absolutely disagree that negative view and I have a positive view instead AI is really just a helpful assistant to human in minimizing confusion for human in finalizing decision on action It never ever be a decision maker in place of human It's crucial to put anything in its own strength to maximize its usage for the sake of human I 'm a HW guy with no data base[DB] at all back ground and sincere appreciate if data base profs help me get started in data base in any language Java C++ I failed to do so in few attempts I asked my SW partner with me at work before and they told me no DB development in USA all outsourced to India !!?? What a short sight and narrow mind!!?? May Gods bless happy healthy wealthy lives for all USA people Amen Duy-Ky PhD EE

Validation of AI System posted on 2024/10

Dear my LI fellow First and foremost Ihave no idea why this post appear with the mileading title "new proposal of sinplified stucture of AI system"!!?? I also done such work and do have such document but not ready to post as it may cause some unwanted impact on AI community Just want more time to validate my new structure It is realy embarrassing if the new structure with bad fearure as the current one ??!! God bless USA and bless me to find new structure along with new training algorithm done in eye blink with hidden layer of 4 millions Nodes[ no Activate function per its ZERO deivative as analized in the document] the training done in 0.87 second I did try with 4 billion but Octave outof memory on my w7-64 bit with 32 G RAM !!?? So I'm more than willing to release new such structure to US AI authority for the sake of USA competitiveness in AI hopefully to make sure USA in the forefront of AI technology for national interest As a serious Control professional where system identification and validation sis the very first task required to be done this working attitude in my blood in very long time I'm glad to have done some kind of this kind of task for AI system based on my limit calculus background To the best of my knowledge It probably the very first work in this trend Hopefully it start new wave of action in this trend rather just taking for grant and start something seriously on something not validated yet . It's not professional at all in doing so I truely do offer my sincere apology if I may hurt feeling of somebody in any way But if I were not then I feel guilty to my self and also the next generation so I have 3 articles for this purpose to get around so many LI rpost estrictions I have to to put put on my personal page hopefully it's understandable https://lnkd.in/g9ivrGBv Math_of_AI dkn_optimiz04 Octave Programming Calculus My Calculus https://lnkd.in/grDCK5Sy https://lnkd.in/gEYz2ygn https://lnkd.in/gPegnCnb Octave programming should be read first as a tool to have some kind of simulation for fun Also have my note on calculus it is very old stuff but nobody care to simplify But I found some college student painfully struggling with it so I wrote this note https://lnkd.in/gkHg5Xau Absolutely nothing new but comprehensive, painless and compact presented in an unified way from limit to derivative up to Laplace transform to solve differential equation but no integral to compute volume and the such this can be easily using numerical method on Octave That's why I'm now 70 retired after 2 strokes and not fully recovered but keep study new stuff Sincerely appreciate if I got your help in showing your successful AI training using Activate function I've been quite aware it work with such function But all sudden I failed using it in my simulation of training and found the root cause is its ZERO derivative DuyKy Nguyen, PhD EE @unitedthc.com

Some Critical Questions To All Serious Ai Professionals

AI questions to serious AI posted on 2024/11/24
dear my serious great AI professionals May I have your honest straight answers on my questions below based on my 20 yrs in NPI [ New Product Initiative] and on my original contribution in my PhD works and ability in turning biz around in any work place I have been in VN Australia and USA Solution to any problem type could be of any type For example there're HW/SW component in modern equipment so product problem could be HW or SW type but solution could be HW or SW regardless problem type Unfortunately AI system is trained on some type of data input whether ML or not so it cannot provide efficient solution as expected Before really having AI commitment we should have screening evaluation in real world first and try best an existing technology 1. Is there any new breakthrough in AI recently If not We have to follow divide conquer way to look at sub AI systems like: Data/Nero Science, computational methods Otherwise AI may get stuck in a dead end 2. Have You been quite aware of any successful AI implementation in the real world ? 3. What are its structure like how many neurons input, output ? 4. How it was implemented tools library platform ? 5. Have You attempted to duplicate it ? 6. If You are ML[Machine Learning] AI professional How your ML works ? Doe it collect training data by it self and what are collecting device Are they available currently How input data are qualified/ verified or they are simply used with out any such mechanism at all ? I did have one as listed in my Experience in 1995 but in prediction of diabetic patient but unfortunately the predictions was wrong Even I really did it with MatLab on Window 3 unfortunately I could not run it successfully for some unknown reason after 29 years and thru some OS upgrade window 3 win 2000 win 7 If You cannot verify/ validate AI model At least You should do on its implementation What I'm really concerned is it's implementation was not a real AI system but something else like just data base search for their own interest nor for public AI interest For the sake to save our limit resource time money and human effort I'm more than willing to offer my free AI consulting via my email to dkn@unitedthc.com in hoping our limit resource reserved for real biz not for un real and risky biz AI Honestly speaking all automatic system like Au pilot etc can be seen as AI powered But they have no neurons at all!! ?? If You as AI professional have no answer to those question You may want to save your resource foe something real for the sake of The People We currently do have a lot serious urgent and challenging task like poor healthcare sub standard living conditions like poor health care low quality but expensive Truly and Sincerely Appreciate May GOD bless us with bright idea for the sake of happier and wealthier USA Amen

Reality of AI systemposted on 2024/12/26

Reality of AI system::2024/12/26 A qualified system must satisfy criteria below 1. theoretical/mathematical model 2. The model must be verified 3. Must be realizable and stable As specific illustration with Control technology well used in all areas in decades with features below 1. Mathematical derived on differential physic law with a transfer function composed of Numerator and enominator 2. It's back by system identication& verification as seen in this article ==> ctl_mdl 3. Realizability by controllability theorem 4. Stability by Stability theorem simply ensure non-ZERO Denominator We all are quite familiar with Wireless phone To my best knowledge with some experience at Venture Design Service in Mar 2013 - Mar 2015 For wireless operational signal from a transmit [Tx] phone going to nearby wireless towel The Receive [Rx] phone get signal from nearby towel A Tx/Rx in each Towel it has Controlled Oscillator Without it Wireless towel cannot be operational Now going back to AI Its model based on perceptron model by Mc Cullog in 1943 using Activate function However it's never been verified either using human brain or mathematical simulation current AI system appear to have no stability criterion All it has is training process of perceptron with Activate function of ZERO-gradient However the training process based on gradient-type optimal method Therefore the training ended up in failure My conclusion is current I systemappears unoperational Therefore I came up with new AI system with powerful training method done in blink of eye I wish to have a chance to validate my new AI structure Any idea truly appreciated toy email dkn@unitedthc.com ay The Lord bless You with great happy healthy wealthy life Merry Christmas and Happy New Year