Key Events of 2022

• Russia-Ukraine War
• Covid-19 Pandemic and Vaccines
• Turmoil in British Politics
• Turmoil in Pakistan Politics
• Iranian Protests
• Global Inflationary Movements
• Energy Prices
• Climate Change Movements Intensify
• US-China Tensions
• Football World Cup
• Overturn of Abortion Rights in USA
• Queen Elizabeth II dies
• Prince Charles becomes King
• Kurdish Protests in France
• Elon Musk takes over Twitter
• UK Gets a First Indian PM
• Record breaking Heatwaves
• Droughts around the World
• Floods in Pakistan
• Cop27

Hypocrisy of Climate Change Activists

Climate change activists alert the world of the effects of having a high carbon footprint. However, one only needs to look at these activists and realize how hypocritical they really are in their own lives. Take for example Greta Thunberg. She talks about climate change and yet uses a plane, lives in a house, consumes electricity, produces waste, celebrates xmas, lights up a tree, receives gifts that use wrapping paper, while complaining on the world stage as how everyone has ruined her childhood. And, all her supporting crew had to be just as hypocritical in building their own carbon footprint just to enable her to travel via a zero-emissions sailboat and jet set around the world, provide for freeze dried meals that use plastic wrapping, the use of train, and the amount of water needed to grow cotton for t-shirts. Most climate change activists can't live without electronics and internet. She even seems to have a social media presence. One generally has to use the internet to be active on social media. According to estimates, all the gadgets, the internet, and systems we use today equate to 3.7% of the global greenhouse emissions. And, when one looks at it in realistic terms, her complete carbon footprint is greater than an average individual on the planet. And, in the time that she has taken center stage, has she provided any quantifiable and qualitative evidence with a set of constructive solutions? During conferences and summits one can see her ranting to the audience but passing on technical questions for other people to answer. Is this an indication of her being totally out of touch with reality? People that posture and rant to others while not practicing what they preach makes them rather hypocritical as they appear to have lived in a very protected environment of self-entitlement and don't seem to understand the complex social constructs and the global dynamics of the world.

How To Identify A Racist Company

• They will reject your CV even if you are appropriate for the job
• They will keep talking about skills shortage even though they keep rejecting good candidate CVs for the job
• They seem to want to give you an interview invite if the name is not disclosed but not when the name is disclosed
• They don't want to shake your hand after an interview
• They isolate you from communications so it prevents you from doing your job
• They block your bonus or pay increments
• You have to work harder than everyone else to prove your worth
• They incessantly talk about your background like you don't belong
• They try to talk to you like you have entered civilization for the first time
• They avoid going to lunch with you
• They look at you differently
• You get stared at work
• When you raise issues of racism with the company HR they deflect the topic or brush it aside
• They block you from contributing to any technical project work
• They try to put you on the spot as a scapegoat for all their politics
• They will try to blame you for all their wrongs and mistakes
• You will likely be the first person they will consider to make redundant
• They will racially profile you in the workplace
• They will talk to you like you don't understand their language
• They will talk to you like you are beneath them
• They will even talk about how they feel about 'your kind' in the workplace and you may have to put up with it as the HR don't want to do anything about it
• They will try to harass and bully you in the workplace so you end up leaving the organization
• They may expect you to put up with their verbal abuse and hostile intimidations
• They may even overly criticise you for your lack of abilities
• You might have to put up with microaggressions
• You might have to put up with your complaints being dismissed
• You might see it in the hiring and interview process
• You might see it in the lack of diversity in both the management as well as in the general workplace
• You might hear the term 'cultural fit' being used a lot by people that are mostly similar to each other
• Your ideas for change and opinions will get dismissed without much thought
• They may even try to take credit for your work
• They will avoid having a desk next to you
• They will constantly complain about you behind your back and keep tabs of your work
• You will be expected to work harder for the same level of work and put in more hours
• They will treat you like someone that doesn't have a voice in the organization
• They will avoid giving you access to things to be able to do your job
• They will overlook you from attending organizational events
• They will not be willing to pay you the same level of compensation but expect to pay you less
• They will put you in the hiring process for diversity but will not consider you for the interview or have any intention of hiring you
• They will go out of their way to keep tabs of your whereabouts and have a heightened sense of distrust for you than is normal - what time you go to lunch, what time you leave office, how much time you spend at the desk, how long you spend time in the restroom, what you are doing on the computer, what time you get into work, checks and balances for everything that you produce
• They will scrutinize your background alot more than is typical for their candidates in an interview process and likely will give you more tests to do
• They will likely consider you an outsider and not part of the team
• During the breakout periods in an organizational induction you will typically see the first signs of racist employees where they openly talk about how they hate a particular group of people, religion, etc
• Their organizational culture, marketing, and advertising campaigns are not considerate towards the protected characteristics
• The managers, co-workers, and colleagues are generally rude, unapproachable, and hostile towards you
• Many times the security will block you from entering the building and likely also do more random searches on you
• The receptionists will generally have a rude and hostile demeanor with which they greet you and how they interact with you 
• They will excessively question and scrutinize your right to work in the country even though you might have been born there, are a citizen of that country, or have already shown proof of id
• The contract will at times display signs of it in the wording and particular sections
• They make bigoted and inappropriate jokes and comments about race, color, nationality, ethnicity and other cultures
• They show favorable preference for people of a specific nationality, race, color, ethnicity, or culture
• They refuse to do business with companies that are run by minorities 
• They play down acts like slavery, human rights, affirmative action, and equality
• They use offensive terms to describe people of certain race, color, nationality, ethnicity, or culture 

Statistics is Pointless in AI

One can blame all of complexity in AI to statistics. The main reason why AI is going no where is because of statistics. Machines have no understanding of what they are learning in a statistical model. There is no formal method of testing statistical models that work in a blackbox. So, why bother working through something that can't be fixed? To explain the model, one will have to build an explainability model - uncertainty to explain the uncertainty. One is going from complexity to another form of complexity. As the old adage goes - 'keep things simple, stupid'. Even the machine needs an interpretation device to work out the statistical model which may be provided in form of a codified language. When one codifies a model they are right back to using logics and an instruction set that a machine can then understand and process. So, why not reduce the process to logical set of representations and let the machine figure out the rest of the statistical invariance through axiomatizations? After all, even when one builds a statistical model, it will eventually reduce to logic anyway. 

Brat Annotation Tool

Brat Annotation Tool

Resting Bitch Face

An interesting area to tackle with deep learning for computer vision is in psychology to discover human state of emotions. One such area is RBF - Resting Bitch Face. This facial expression is often characterised with commonality between males and females where they appear unintentionally to display feelings of anger, despair, grumpiness, annoyance, or irritability. However, the state of the individual is likely confused for relaxation or resting. There are often more underlining psychological aspects at play here both from the on looker standpoint as well as from the one projecting such a state of emotion. The phenomenon seems to be fairly a common condition. It often also gets used in fashion and lifestyle photography. Such applications can use methods of stable diffusion either to enhance the condition or further to distort such an appearance. Furthermore, one could develop an emotion model for psychology to study the various facial expressions to understand the mental state of an individual.

The plumber

theplumber

Dreambooth

Dreambooth

Avoid Pig In The Diet

Pigs are widely consumed as meat. However, there are several reasons why one must avoid the consumption of pig meat altogether in their daily diet.

• The meat contains high concentrations of saturated fats and trans fats causing the greatest risk to health
• Pigs are one of the few animals in our diets that will eat human remains
• It is dangerous when it is undercooked
• It is prone to contamination
• Susceptible to pathogens
• As the saying goes "you are what you eat"
• It porks you up with cholesterol
• Factory farming
• The meat has high levels of toxins that can make it difficult to digest
• Cheaper meat does not equate to better quality
• Make a conscious choice in what you consume
• Pigs are prone to eating their own feces, dead carcasses, and scraps
• They are prone to incest, unless consciously kept separated

Xmas Is The Festival Of Hypocrisy

Energy prices are skyrocketing. And, yet we see people putting up xmas lights everywhere. Who will be paying for the energy bill for this? There has also been much mention of climate change. And, yet we see people putting up trees inside their homes when they should be outside. And, shockingly many still decorate real trees rather than the fake ones in their houses and gardens. Even the celebration of Santa Claus is odd because in the old days he was considered to be a demon. The holiday period is the hallmark of teaching kids the value of materialism. And, all of a sudden people can be seen interested in buying turkey and drinking egg nog when they wouldn't even dare touch it at any other time of the year. We also see mulled wine only at this time of the year. We also see everyone putting up smelly socks next to fireplaces and silly wreaths on the doors. People sit around overindulging in food and drink till their bellies explode, another attribute of gluttony embraced during the festive period. We see people taking out loans to pay for gifts. One can even see vegans on holiday this festive season and embracing the dead corpse of a turkey on the table. Treehuggers and climate change alarmists are all on holiday. And, as the xmas passes on we can see trees next to rubbish bins. A temporary short run on economic growth through consumer spending. Capitalism in all its glory!

Awesome Quant

Awesome Quant

How To Identify A Racist

Racism occurs in all forms of society. Anyone can be a racist. It is a false notion to assume that only a white person can be a racist. In fact, most secular societies display the most prevalence of racism. And, societies that have caste systems and class hierarchies also display similar forms of racism. Racism helps maintain the status quo within the hierarchical class structures in societies. The following are typical aspects to identify a racist.

• They will question your background based on your skin color
• They will insult your intelligence and talk to you differently based on your skin color
• They will talk to you like you were some illiterate
• They will often use terms like "you speak english well" eventhough english might be your first language and probably speak and write better than they do
• They will often ask you to go back to your country, eventhough where you reside is your home
• They will talk to you like you have experienced civilization for the first time
• They will assume that you have never experienced things before like games, electronics, certain cuisines, travel, music, etc 
• They will treat you differently because of your skin color
• They will use stereotypical assumptions about you rather than get to know you first
• They will talk to you like you are beneath their level
• They will block you from certain aspects of society such as specific clubs, restaurants, jobs, events, sitting areas, etc
• They will try to racially profile you
• They will cut you off and dismiss whatever you say as wrong even before you have had a chance to fully communicate
• They will attempt to insult your background or use it as a form of jokes
• They will discriminate you and hold biases against you
• They will consider you an outsider and question your identity
• They will never consider you an equal member of society or in the theory of assimilation
• They will stare at you in a creepy sort of way in workplace, restaurant, supermarkets, and in every aspect of your life
• They will avoid communicating with you
• They will try to avoid serving you or providing you any customer service
• They will use terms like "you won't be able to afford this" and ask you to leave
• They will reject your job application without even bothering to read it as some names according to them are associated with a certain background
• Furthermore, medical institutions have staff often treating patients differently based on their skin color that dictates the quality of care they receive
• In places like india, untouchables are excluded from almost all aspects of society
• Investment opportunities are also forms of discrimination based on ones background
• The credit reference agencies also play their own part in racial profiling individuals
• Often the notion of cultural fit is in itself a form of bias, discrimination, and racism
• They will try to play down your concerns about racism or your experience of it
• Police brutality is another aspect of racial profiling
• They will be less friendly towards you compared to their interactions with people of other backgrounds
• They will have an extreme dislike and distrust for everything that you say or do
• They will have a threatening and rude demeanor, likely scrutinize you even more than is necessary
• They will block you from renting or even buying a property in a particular neighborhood
• They will often question you whether you know what racism is

Text2SQL

Text2SQL

ChatGPT

ChatGPT OpenAI

Heartland

Heartland is one of the most hypocritical shows. The show is based on a ranch with the center story revolving around a self-centered and cheating horse whisperer. On one hand the show displays how disturbed horses are treated while on the other end we are shown animal cruelty at the hands of cowboy and cowgirls in rodeo for which the horse whisperer is only more than willing to take part in ranging from broncos, roping calves, wrestling steers, bull riding, and other activities. We even are shown some characters that are vegans and yet willing to take part in the rodeo. It is even questionable how well the horse whisperer can communicate with horses. This is a family show that showcases the whole idea of being selectively heartless with double standards. It also has the re-runs of the same dramatic storylines of misunderstandings between characters. But, this might just be an indication of poor scriptwriting. Eventhough, life of a cowboy or cowgirl cannot be easy, one cannot but shrug in dismay at the mistreatment of animals in such communities. However, at one point it does provide an angle towards family life. But, loses its appeal by an anti-climax of killing off a crucial character. With such a long running show, it is understandable how actors would want to leave to move on to other opportunities and perhaps even encounter creative differences as their acting experiences evolve through time. This is a show that perhaps started with some good intentions and then meandered into the gravy train of greed as popularity grew through the seasons. However, one has to ask when is the right time to end the show that has been going on for so long and has lost the plot? When is the right time to end the life of a character? Or, is it a case of drawing the line as life moves on and letting the characters live on while the show reaches its end. This is a typical example of a show that has gone past its sell-by date.

Second-Hand Marketplaces

Often second-hand marketplaces sell goods that should never be made available for re-sell. In fact, most consumer items depreciate in value considerably faster. Only items whose re-sell value appreciates as time goes on should be considered. Second-Hand consumer items that are associated with cooking tend to have a health risk associated to them. Again, clothing items are similarly of health risk. Invariably, the intention of use often dictates such second-hand purchases and their long-term value.

Consumer items that should never be purchased second-hand. These items tend to lose value after each new release or after use:

• books
• electronics
• mobile phones
• clothes
• tableware
• kitchenware
• cooking utensils 
• shoes
• furniture
• toys

Consumer items that could be considered for purchase second-hand:

• Property (flat, house, office space, shop, etc - only after they have been thoroughly checked)
• Automobiles (only after they have been thoroughly checked and only if they are good as new, for some brands they can be bought directly from the manufacturer)
• Antiques (only after a valuation has been made)
• Old books (one of a kind books only after a valuation has been made)
• Paintings (only after it has been checked for authenticity)
• Autographed memorabilia (only after a valuation has been made)
• Watches and Clocks (only after a valuation has been made)
• Collection items (stamps, etc - only after a valuation has been made)
• Clothings (reuse materials to create new designer wear)
• Furniture (reuse materials to create new furniture)
• Shoes (reuse materials to create new shoes)
• Phones (reuse materials to create new phones)
• Electronics (reuse materials to create new electronic items)
• Books (reuse materials to create new books)

Psychopathic AI

Norman 

Norman AI

Debatabase

Debatabase

Why Coding Tests Are Bad

Not all roles at companies require coding tests, or even tests for that matter - so its a form of discrimination. Did the ceo of the company go through a test before they were hired to manage the company? Secondly, most interviews start with introductions where candidates share their background. So, after that if you go into a coding test, what you are doing is essentially discrediting a candidate's cv/resume, skills, experience, and education background. Not a good start at building a relationship from distrust. It also showcases how the company might treat the candidate, if they were to transition into an employee. Coding interviews can also be quite opinionated, biased, frustrating, flawed, outdated, bookish, pedantic, use buggy third-party tools, unclear instructions, and unrelated to the job. Plus, you can't really correct the interviewer during the process with best practices and the way they do things. Another aspect is it is chargeable time, the interviewer could get a free lunch without having to pay and hire you. By the time you set them through all those test stages they could have an offer with someone else. Likely, the candidate has already gone through tests at uni and most of their life, do you really want to bore them with more tests to do.

• They eat a significant part of an interview process
• They take time to do
• Often the instructions are not clear and there is no one to ask for help
• There is a chance that the organization could get a free lunch without the need to pay and hire the candidate
• There is a chance that the organization could ghost on the candidate straight after
• Doesn't accurately compare candidates
• Other roles do not require such tests
• Candidates can lose interest
• Then there is the aspect of human bias
• Test markers could be too pedantic e.g. marking down for spelling a variable either in American or British english
• Often the test is unrelated to the job e.g. asking someone to do a spring test when the job description does not even require that experience
• The test provides incorrect instructions
• The tests can be biased and discriminatory
• Often tests don't reflect the real-world
• Often tests are too bookish and an indication of how junior the role is
• People go through university and school taking tests, do you really have to then give them more tests during interview
• It is a perfect way to put off a candidate
• It can be seen as a form of insult to the candidate
• If you require tests then why do you need them to have a bachelor's, master's, or a phd
• Giving someone a test to do is in a way discrediting all the skills, education, and experience they have on the CV/Resume. Not a good way of building a relationship from distrust.
• It can be seen as a form of discrimination, especially as not all roles require tests, or even the same types of tests
• Coding interviewers can be quite opinionated and not necessarily correct in their best practices
• Correcting a coding interviewer during an interview can be tricky
• It can be frustrating for candidates as the coding interviewer has their own way of doing things
• It showcases how the potential employer will distrust and treat the candidate as they transition into an employee
• Coding tests can be outdated or use third-party tools that are buggy
• And, when the third-party testing tool gives you the message "system is down for maintenance" right in middle of a session

Programs in Cognitive Science

Cognitive Science Society

Survey of Pre-Trained Transformer Models

Survey of Pre-Trained Transformer Models

Jina

Jina

Why Metaverse Will Not Become A Reality

Metaverse is all the hype. But, it is simply just a re-brand of SecondLife which has been around for ages and never really took off as well as people had thought it would. However, it does show how Facebook likes to rip off things from others. The level of technology needed for hyperreality is going to take ages. One can see the slow pace with which augmented, virtual, and mixed reality has taken off in the mainstream. People will also have a challenging time understanding what hyperreality really means to them. And, in many cases it will become boring, not very user-friendly, and inaccessible. There is also the element of surveillance which will become a big privacy issue. In many respects, it will become another deep/dark web like the Tor/Onion privy to only a select few. Just like blockchain, Metaverse will simply not make much sense to people. And, as people find the whole idea difficult to comprehend, it also means generating ad revenue will become a complex terrain to navigate in consumer reachability. The types of consumers may just turn out to be gamers especially ones on Twitch or possibly the ones that find another outlet from Tor/Onion.

Hypocrisy of Marriage

Women want equality. And, yet they expect the man to propose to them. Rarely, does a woman propose to the man. Often, women take the last name of the man as their own after marriage. The father walks his daughter down the aisle and presents her to the groom. One never sees the mother walking her son down the aisle and presenting him to the bride. The woman dresses up in a bridal gown. The man dresses up in a suit. In certain religious ceremonies a dowry is even presented to the bride from the groom. But, not the other way around. Additional ritual ceremonies may be performed that are different between bride and groom. In some countries, the rights of a husband are different from the rights of a wife. Women don't appear to even have an issue with the reference to husband and wife. They don't even have an issue with labels of wo-man and fe-male. Eventhough, such terms are linguistic derivatives in the english language. Then after divorce the woman expects the man to give half of all his wealth. While the woman has no obligation to give anything. And, if they have kids the woman can expect financial support from the man but not the other way around. The legal rights of the mother and ex-wife are far greater than that of the father and ex-husband. What if they both work and earn an income? Women also want equal pay in the workplace. The legal system is in place to protect the rights of women but not so much for the rights of men. The ramifications of any changes towards equality impact the fabric of society in four dimensions: socially, legally, economically, and politically. These dimensions determine the way society projects the gender role disparities and differences. In fact, equal pay will have drastic effects on the breakdown of society and increase the struggles of women finding suitable men as partners in marriage and for starting a family. In most societies, women generally tend to have preference for men who provide both emotional and financial stability as well as enable them to climb the social ladder. As a result, it may have detrimental effects in the dynamics of social relationships, more likelihood of broken marriages, more children being brought up out of wedlock, and potentially more men avoiding the idea of marriage altogether. 

Fifa Qatar 2022

Fifa Qatar 2022

Draso Strum

Citation Network Analysis

Citation network analysis follows six core steps in the process:

• Collect and clean scholarly publications in a given field of study
• Identify and select a set of objects to represent the research community
• Measure the connectedness between such objects in context
• Multivariate statistical analysis
• Network analysis and visualization
• Interpret and validate the results

Citation Analysis

Scientific research is a social activity defined in a set of norms. The key norms dispel the motives behind how research activities are dispensed, shared, and evaluated.

• Universalism
• Communism
• Disinterestedness
• Organized Skepticism

Recsperts

Recsperts

Evolution of Photography

Photography has been a dark art at times. These days anyone can pick up a camera and take a snap. Even deep fakes have enabled boundless forms of creativity. The dying art of professional photography is truely over for most photographers whose struggle for work is likely to grow even more and the evolution of digital photography is eclipsed by AI and Computer Vision. Computational photography apps will likely enable any individual to have the skills at their disposal within a few clicks of a button. An agent inspired photographic lens could also be an option. However, to this day the trickiest aspect of photography has been the embodiment of colors in imagery. At times, colors can transform themselves like deep below the ocean where red color is no longer visible. Capturing emotions and imagery in the stillness of time then looking at it decades later has been the very essence of preserving memories which is very efficient in terms of storage. Perhaps, quantum information may be explored through storage of data in images that could come alive as they are explored and processed through a virtual world.

Evolution of Acting

The old days of acting are long gone where one has to be present physically on set. The Covid period has challenged the way people work remotely across industries. It so happens that virtual, mixed, and augmented reality with AI will set the scene for a more cohesive and flexible work environment for actors. One should be able to join a virtual conference call and practice their scripts. And, where stunt doubles are required they could be superimposed with computer vision models. Actors should be able to virtually connect and run their scenes under a camera without leaving the comfort of their home. All that is then required is to embelish the acting with background ambience and to set the scene in motion which could be done using editing techniques. Voice overs could also be superimposed to enable crisper sound performances. The Metaverse may itself provide an alternative virtual environment for actors. Eventually, full repacement of human actors for AI agents will completely transform Hollywood and Bollywood. Multiagents acting in a situational scene environment like a virtualized form of puppetry.  Affective Computing could set the scene for ambient emotions and sentiments. The end to human actors is in the mist.

Dokieli

Dokieli

Women in IT

The reality of hiring for diversity is that one will have to work with people who are unqualified, ill-mannered, and unprofessional. Increasingly, there are stories abound about how it is difficult to work with women in IT.  Women in workplace expect men to help them in every possible way, just because they are women. And, yet expect equal pay. More and more women are only interested in hiring women and exposing their biases. On other occasions they are rude, racist, and unprofessional to male colleagues. Women make bully bosses in workplace and they enjoy it. They even enjoy acting that way over other women. One can say that it is a touch an go. But, on most cases a woman can be a man's worst nightmare in the workplace. At times, one can even see women avoiding to talk to non-white colleagues completely to the extent that it starts affecting their work. There are cases where female interviewers just refuse to shake hands with candidates after the interview. Women harassing and abusing men and even women in workplace has been growing since diversity initiatives came into play. Manipulations through false allegations where even the use of CCTV as evidence is blocked. All this breathes toxicity and questionable ethical practices in the workplace. And, it is only going to get worse as women hide behind the victim card and play the differential gender disparity myth.

Hypocritical Practices in IT Industry

There are many odd practices in IT industry that spell hypocrisy. The following highlight a few of these practices that are not applied in other roles.

• Interview Tests
• Silly Interview Puzzles
• Pair Programming
• Using Notebooks to build models that instil bad practices
• Using lots of ceremony in an Agile team
• TDD - Test-Driven Development (what other roles expect to derive test first before development?)
• Infinite Scrolling
• Gone Fishing pages
• Software Engineering Sweatshops and Xtreme Programming
• Using statistics to explain a process or method
• Using statistics to reason about a solution that itself is seeped in uncertainty
• Avoiding everyday commonsense logic in favor of statistics to derive practical solutions
• Using statistics to increase the complexity of a solution rather than working towards simpler solution that reduces uncertainty
• Calling something deep when deep down it is just statistics
• Using statistics to build everyday things that even humans don't use statistics for
• Using all the wrong methods that a university degree teaches one not to use
• Rejecting qualified candidates in favor of unqualified Phd candidates who don't even have a formal or practical IT background
• White, black and gray hacking where they all use the zero sense of discipline of hacking
• Using racist jargon like blacklists and whitelists

Why Recruitment Tests Are Pointless

• When you hire an accountant do you test them first with sample accounts?
• When you hire a lawyer do you test them first with a sample case?
• When you hire a construction team to build you a house do test them first with a sample house?
• When you hire a plumber do you test them first with a sample water leak?
• When you hire a carpenter do you test them first with a sample woodwork?
• When you hire a bricklayer do you test them first with a sample brickwork?
• When you hire a mechanic do you test them first with a sample car fault?
• When you hire a ceo do you test them first with a sample business?
• When you hire a gardener do you test them first with a sample garden?

...

Why test candidates in IT??!!

Employers should be asked to pay candidates if they want to test them. Some hypocritical practices are simply weird in IT field. 

Metadata

• Controlled Vocabularies
• Introduction to Metadata
• Categories for the Description of the Works of Art

Transformer Model Comparisons

There are comparisons out there between various transformer models. However, such comparisons often are flawed that provide evaluations between apples and oranges. Transformers must be first narrowed down to the architecture and use case in order to compare. For example, a comparison between Bert vs GPT vs T5 is pointless. Bert has an encoder architecture. GPT has a decoder architecture. And, T5 has a balanced encoder-decoder architecture. All three have their contexts for specific use cases. One approach is better for NLU use cases. One approach is better for NLG use cases. And, one can be used interchangeably between NLU and NLG use case. There are cases for when a balance is needed and cases for when a particular architecture is required. Evaluation really should be made across similar use cases and context-specific architectures so as to provide a more meaningful comparison. Context is very important.

Project Debater

Project Debater

Project Debater Simulation

Large Corporates vs Startups

In the IT industry, there is a stark difference between working for large corporations compared to startups. The following explore a few areas of comparison.

• Startups 
• enable employees to be heard
• to be more vocal
• chance to influence a culture
• explore and exchange thoughts and ideas
• build closer relationships
• bigger sense of responsibility
• fast-paced
• proactive
• rapid learning
• can be disruptive and at the same time risky
• less stability of work
• smaller teams and even individual ownership of work
• chance to play many hats which leads to often overworked staff
• more loosening up parties and chill out times
• opportunities to explore play times and breakout periods
• equity options
• salaries can be low
• greater degree of flexibility to be creative
• limited funding budgets on projects
• small teams means cultural fit becomes important which may lead to issues with diversity, inclusion, and equity
• communication channels are often spread across a very flat hierarchical structure
• Large corporates
• one is reduced to an employee number
• lots of red tape to get things done
• chance to influence culture is minimum or difficult
• more decisions are made by management
• people become too distant
• lots of reporting functions 
• lots of internal competition
• more ceremony within team structures
• lots of mundane work as things slow down considerably
• excessive amount of politics which at some places can be toxic
• difficult to make a mark and rise up the ladder
• risk of stagnation
• can be great places for graduates to start their careers as period of learning and ramping up skills in industry
• lots of stability
• projects can be complex
• willing to take risks
• chance to do things properly
• chance to specialize in an area
• lots of benefits and perks
• salaries can be more dynamic with greater bonus options
• great when you just want to move up into management
• great to go back to when you are nearing retirement
• great to go back to when you want stability while setting up a startup of your own
• great for networking for the future
• chance for bigger project budgets
• chance to work in different countries and with distributed teams
• more structured career progression
• potentials for redundancies under bad leadership
• more consideration for compliance
• more restrictions on opensource
• unnecessarily and often long recruitment processes
• lots of pointless paperwork for filling out forms
• lots of areas of unclear, inefficient, incorrect channels of communication
• often issues relating to diversity, inclusion, and equity in the workplace

Worst Consultancies

Indian companies have the worst record of how they treat their employees both in terms of compensation and work/life balance. They also have a terrible record of having dishonest and exploitative practices both with their clients as well as with their employees. The following are some of the worst companies that one should avoid:

• Infosys
• TCS
• Wipro
• HCL
• Mphasis
• Mindtree

Although, not indian companies, mention also goes to Virtusa and NTT Data, in this category. Other multinational consultancies that are basically sweatshops and that mostly have indian outsourcing are CapGemini, Accenture, KPMG, EY, and Deloitte. Most of these companies all have dodgy practices of low pay and terrible work ethics.

The Satanic Verses

'The Satanic Verses' can be downloaded from the archive for free. Don't bother buying the book as it is not a good read. In fact, it is garbage from any sense of the word. The entire book is filled with embedded hate speech. The author dispels many of his hate through the personification of characters. Not only does he hate everything and everyone, he seems to also hate himself. The book was written to offend and provoke, much of which can be seen from the quote at the beginning of the book from Daniel Defoe. The more significant bit of hate speech is directed towards women that not only incites hate but also violence. In 1989, an incident occurred against a woman in New York where six individuals after reading passages from the book went out to put it into action that conjured up their imaginations. The book not only hates on blacks, but also jews, brits, whites, women, hindus, and across the protected characteristics. In US, hate speech laws don't really exist much outside of incitement. However, in UK/EU the hate crime law can provide a way towards censorship of the book. After all freedom of speech is not absolute. One finds it surprising that there is a lot of focus around the hate for a given religion while much of the other forms of hate in the book are completely overlooked. Perhaps, this is because of racism and bigotry shared in much of the western societies towards Islam and the book provides a weapon to incite hate towards it. But, it is shocking that many do not notice the level of hate speech mentioned in the book towards women. The author is an opportunist. Who wanted to gain notoriety by being as controversial as possible. In fact, a lot of the writing is in broken sentences and swearing that do not amplify any form of literary quality. The author cannot even make up his mind whether he wants to swear in hindi or english. It reads like an indian version of an urban dictionary. This leads one to wonder why on earth would someone want to consider it for the Booker Prize. The book sales is an indicator of how it is viewed in society. Book sales increased after the fatwa. They further increased after the attack on the author. But, in between such events book sales were virtually unheard of. Many people who support the book are jumping on the bandwagon of crowd follower mentality and have never even read the book. However, the man that attacked the author may also be exercising their freedom of speech and expression. This could be compared to the egg attack on John Prescott who returned it with a punch. Book burning is also another form of freedom of speech and expression. And, apparently, one cannot even challenge the holocaust behind the curtain of freedom of speech and expression. Or, even challenge the use of additional pronouns in freedom of speech and expression. We live in a society of hypocrites.

Extracts from 'The Satanic Verses':

• "White women -- never mind fat, Jewish, non deferential white women -- were for fucking and throwing over. What one hates in whites -- love of brown sugar -- one must also hate when it turns up, inverted, in black. Bigotry is not only a function of power." 
• "Torture. Maggie the Bitch."
• "N****r eat white shit?"
• "Black shit is bad?"
• "Sister Fucking British"
• "This country that's stuffed full of fucking old corpses"

Prologue (by Daniel Defoe, from 'The History of the Devil'):

"Satan, being thus confined to a vagabond, wandering, unsettled condition, is without any certain abode; for though he has, in consequence of his angelic nature, a kind of empire in the liquid waste of air, yet this is certainly part of his punishment, that he is....without any fixed place, or space, allowed him to rest the sole of his foot upon." 

Argumentation Reasoning with GNN

Argumentation Reasoning with GNN

Micromouse

 

Faanmg Companies

Faanmg have weird processes, lots of politics and unnecessary levels of arrogance. Fang, Faang, Faamg, Faanmg - what is it short for? It consists of Facebook, Amazon, Apple, Netflix, Microsoft, and Alphabet-Google as per their stock tickers. But, the referred acronyms can vary as per stock performances and their potential growth.

• Why do they have so many interview processes?
• Why do they ask so many dumb, irrelevant questions in interviews?
• Why do they care so much about what academic background a person has when even their founder, in most cases, is a dropout?
• Why do they have so many screening stages?
• Why are they stuck on processes when they talk about breaking barriers?
• Why do they have such a bad track record on diversity, inclusion, and equity?
• Why is working for them so mundane and boring?
• Why people that work there are bred to be arrogant pricks?
• Why do they outsource work and then bother recruiting through so many stages?
• What is the point in working for such pointless companies when there are a lot better opportunities out there at startups?
• Why do they recruit people to work on mundane and boring stuff when they can outsource it?
• Why life at such companies is not cracked up to what they say in their marketing campaigns?
• Why do majority of these companies hire for academics, especially ones that can't put theory into practice?
• Why there is so much politics and red tape in such companies?
• Why such companies like to hire dumb people and give them tasks to work on complex things?
• Why the typical employee at such companies is a high academic achiever but an inept practical problem solver?
• Why they like using theoretical puzzles in interview stages but have no skills of solving real-world practical issues?
• Why most work in such companies is compartmentalized boredom?
• Why such companies have the worst managers with terrible people skills?
• Why such companies have the worst record of sexism and discrimination against women?
• Why every such company should have a separate ethics department so they can control all the discrimination, biases, and unethical behavior rampant in the organization?
• Why do such companies have such a discriminatory policy on hiring blacks and asians?

Energy Prices

As energy prices soar, likely people will look for alternatives. Predictable things that could emerge from such an event may include:

• Demand for household generators goes up
• People will try to commoditize their use of energy for the home as a crowdsourcing initiatives emerge to compete against big businesses
• Demand for energy from big businesses will go down - supply vs demand will cause cheaper prices, but such prices will not be reflected in the market as the providers will stall via price caping and price fixing for maximization of returns, setting into action their monopoly. Since no one will want their energy, they will go out of business which will again lead to layoffs.
• Can't create or destroy energy, you can only convert and conserve it into different forms
• The govt will try to step in but will have very little effect as they work for organizations not for the interest of the public
• People get inventive and form alternative energy sourcing systems for the home
• New crowdfunding projects for energy will emerge to tackle energy prices as everyone will want to make a profit from it
• People will protest against big businesses for energy prices, but this will have very little effect on deaf ears
• Big businesses will use their lobby to hamper smaller business ventures for alternatives or try to buy them out

Economic Outsourcing to Foreign Countries

Outsourcing is the single biggest contributor to mass unemployments in western countries and an inhibitor to economic growth. One of the worst contributors to western economies is outsourcing and visa-work permit issues to indian or eastern european outsourcing companies. In fact, it promotes foreign talent, while reducing opportunities for local talent pools. While western economies have over the last few years had a dry spell in growth, they have channeled much of the growth potential into developing and emerging countries - putting private organizations before local taxpaying individuals that comprise the public. 

There are fundamentally key things that hurt western economies:

• Outsourcing to india or other eastern european countries on the cheap - when you could be recruiting, re-training, and promoting local talent
• Issuing visa/work permits - when you could be recruiting, re-training, promoting local talent
• Dodging the bullet by saving costs through foreign hires means in long-run your customers suffer from lack of quality and service
• You end up putting your customers second before costs - but it is the customer that drives revenue
• Using foreign individuals means you depreciate the value of your local currency as it gets converted more frequently into euros and rupee
• Lack of local jobs means business pack up and mass unemployments as consumers spending reduces
• Outsourcing inevitability means non-compliance, likely not compliant under local laws, likely you will have to re-build and re-design the systems again, additional costs, lack of accountability, lack of training, where the costs all add up to more complex situations, and plenty of risks not to mention of not meeting local standards of care
• Difficult to manage data transformations across countries and jurisdictions
• In many cases passing the buck for responsibility and accountability means unethical practices emerge within organizations
• Foreign individuals form a clique so they only look to hiring their own and promoting their own, which means local talent suffers
• Payscales get effected in countries as they have to constantly compete against foreign individuals who may be willing to work for less, often challenging local living costs through inflation
• Local businesses suffer who look to hiring local talent pools, while larger organizations outsource on the cheap 
• The local talent pool may also be potentially an element of the customer pool in the local markets

Countries in first instance should impose restrictions on the issuance of work visa/permits to employers where they are required to seek local talent, then have a complicated process to justify requirements for foreign talent recruitment. The same should go for multinationals who work across countries where they should be expected to source local talent pools in the first instance.

Cognitive Architecture

• Cognitive Architecture
• Common Model of Cognition
• Cross-Pollination

Graph Neural Networks

• Graph Neural Networks
• Graph Neural Networks
• Machine Learning with Graphs
• GNNPapers

Dive into Deep Learning

• Dive into Deep Learning
• Deep Learning

Why Organizational Layoffs Don't Work

Layoffs is a cyclical short-term approach to looking good to shareholders on the balance sheets. In long-term those same jobs will need to be re-filled. In end, it costs more because not only does one have to layoff people with redundancy packages, but in a few months one will have to hire people to fill those same job roles. In MBA schools, the first course of action taught is to let go of people to resolve financial issues. As a result, such degrees teach a disconnect between management and employees. An alternative approach is to selectively shrink the middle and senior management within the organization.

What this means is that:

• less people to layoff
• reduces red tape so the organization can function more efficiently, productively, and get things done quickly
• layoff people who set such performance targets for others and don't meet them in first place
• letting go of those managers in most cases will result in not having to re-hire either because it would have solved many internal issues in process and then can set more realistic targets for the future
• save on future costs where one may have to consider layoffs again
• something that acts as a quick fix in short-term is likely not a long-term solution
• better looking balance sheets as managers get paid more than employees so the sum total will reflect more in cost savings when it all adds up
• managers are also then held accountable for organizational-wide, team-wide decisions which may have collectively cost the business
• reduce the recruitment costs every year from cyclical layoffs and re-hire
• produce more stable balance sheets that are reflected in the long-term performance of the organization which means more opportunities for finance and business
• reduces employee turnover
• organizations become more responsible and accountable for people and their local communities
• not having to let go of the best people
• increases employee moral as they can maintain stability in their lives from working with a responsible organization that practices rational and strategic decision making for the long-term
• reduces the collective expense in benefits packages
• reduces the toxic culture that may be brewing in the organization through excessive and unnecessary politics
• reducing employee head count does not reflect well for the future of the organization 
• layoffs invariably are a sign of bad leadership
• laid off employees may hold resentment and ill-feelings which brews on the social media and effects brand value 

Endless Road of Tests

Life seems to be a never-ending cycle of tests. One is tested from the day they are born through the life's many struggles and obstacles. Tests in schools. Tests for uni. Tests for jobs. Tests for medical diagnosis. Tests for friendship. Tests from parents. Tests from background screening. Tests from banks. Tests from insurance. Tests of emotions. Tests in relationships. Tests of spirituality. Tests of love. Tests of blood. Tests of mental agility. Tests of behaviors. Tests of personality. Tests of psychology. Tests of languages. Tests of standardization. Tests and more Tests. It is like one can never recover from all these unnecessary tests that come our way. Academic tests measure absolutely nothing. Job tests measure absolutely nothing. The world has gone mad with testing people all the time. At times, the one testing does not even bother to even evaluate it and just goes for the score. Is life really reduced to a score and a race to the finish? Have we reduced the life to a mere competition rather than a lesson? We are increasingly living in shallowness, superficial, one-dimensional, mundane, depthless and trivialized world of cosmic energy. 

Lenskit

Lenskit

Godel Machine

Godel Machine

Society of Mind

• Society of Mind
• The Society of Mind

CRISP-DM

• CRISP-DM User Guide
• CRISP-DM Process Model

CPMAI

CPMAI

Non-Compliant Queries

Writing adhoc queries to a database is non-compliant. It is always better to formalize the queries into programmatic transformation code. Aside from that, queries should be versioned and trackable so a change data capture could be reported into a downstream system for transparency as a continuation of data lineage. Non-compliant queries not only break governance standards, but in a highly regulated sector could result in fines for an organization. 

NLP Research Journals

• Journal Finder
• Journal Suggester
• ACL
• NLP Flagship
• Sheffield Journals
• Arxiv
• NLP Conferences and Journals

What Makes an Effective Leader

From the time humans have existed, leaders have been all around us. Over time such leaders have emerged across a multitude of disciplines from religion, to engineers, to scientists, to economists, to politicians and beyond. The road they all take is an arduous one. Some came with the need for power, others came with the need to change the way things were done, while still others inherited it through family or through their scientific thought. However, in many respects leaders often struggle with popularity vs hate, all requiring a degree of security protection which makes their lives fraught with challenges from within the ramifications of society. Life is a complex road for leaders. One can question that some even chose such a path while others were simply destined for it. However, over the years there have also been many caught on corruption charges, scandal, and assassination attempts. And, yet we see an endless cycle of people with the same desires of becoming a leader one day. What attributes shape a leader is not an easy question. Many are unique and do not share the same traits or qualities. But, one thing is for sure, for an effective leader one has to inspire and trigger the very hearts of people that they want to garner support in society to fulfil their objectives. The following list some attributes of effectiveness in leadership:

• Leaders inspire and motivate others to succeed
• Leaders make sensible, timely, and impactful decisions 
• Leaders are compassionate, understand people, and their sentiments
• Leaders instill a sense of hope in others
• Leaders make great communicators and provide convincing arguments
• Leaders make great enablers and achievers
• Leaders make great visionaries and this trait often turns them into role models
• Leaders prefer to use terms like 'We' rather than 'I'
• Leaders take control but delegate when it is necessary
• Leaders empower others to be at their best, but also acknowledge their human side to making mistakes
• Leaders invests in people
• Leaders stay focused during critical situations and times of crisis
• Leaders are great influencers
• Leaders are results-oriented and open for change
• Leaders make good mentors and coaches
• Leaders are self-aware

Gender Bias Mitigation

Gender Bias Mitigation

Economic Effects of Migrant Workers

The net effects of immigration has on a local economy include the below:

• Stress and pressures on local services
• Stress and pressures on healthcare
• Stress and pressures on housing
• Stress and pressures on infrastructure
• Stress and pressures on education
• Net effects to quality of life
• Net effects to urbanization
• Net effects to environment
• Net effects to overpopulation
• Net effects to competition
• Net effects to crime and security
• Net effects to local law enforcement
• Net effects to local unemployment rates in respect of immigration
• Net effects to consumer spending behavior
• Net effects to local exchange rate
• Net effects to payscales
• Net effects to inflation
• Net effects to taxes

In many cases, this is dependent on the quality of immigration which could have positive or negative effects to the economy. Highly skilled immigrants that are stingy and work for significantly less pay thresholds may effect local consumer spending behaviors, drive supply and demand curves, cause an increase local unemployment rates, increase local competition for jobs, effect quality of housing demand, and much more. In both cases, dependent on the quality of immigrants, this may also effect other local services as well as crime and security rates, significantly changing and influencing the lifestyle over time. This may be a reason why in some countries segregation takes over so as to curb the influx of immigration taking over and influencing major aspects of society like cultural makeup and laws.

Energy Supply and Demand

Why have energy controlled by a few? Why not let everyone supply their own energy as a crowd sourcing affair and use it as a form of monetization. Households could be self-sustainable with solar power, biofuel, and hydropower. These are fundamentally the three greatest sources of abundant energy available in every densely populated society. Sunlight could be used to generate energy. Human and animal waste from bathrooms as well as plant waste from gardening could be used for biofuel. And, hydropower generated from water. Any surplus could be sold on the open market for nearby stores and businesses to consume and buy. Buildings could then buy and sell as well. Government could use such means to light up streets and public services. Overtime reaping benefits in a highly competitive world where energy prices could be sustained by supply and demand as well as create abundance of renewable energy. This might even provide an additional source of revenue for households that need an additional source of income. Mass electrical charge points could be provided by every household to build the energy supplies, no longer requiring the gas station on a street corner. Eventually, leading to a society free of dependency from hiked oil prices. And, the rise of automotive that is dependent only on renewable energy sources. These methods might further solve issues with rising waste sewage, process innovation for recycling, and more controlled use of water consumption. Houses become self-powering rather than stuck on a grid. Even the broadband access could be treated as an extension of a decentralized monetization service for supply and demand. Clean living becomes an ultimate environmental reality. The open traded market for energy could become a new ecommerce product both for C2B, C2C, B2C, B2B. As people move on towards suburbs and rural areas, with vast spaces of land people could produce even more energy. Farmers could sustain their livelihoods as an alternative to agriculture and cattle sources. No more monopolization of energy by a few capitalist ventures.

Non-Degree Finance Courses

MIT OpenCourseware:

• Behavior Economics and Finance
• Blockchain and Money
• Competitive Decision Making and Negotiation
• Early Stage Capital
• Economic Analysis for Business Decisions
• Entrepreneurial Finance
• Entrepreneurial Marketing
• Entrepreneurial Sales
• Financial Accounting
• Financial and Managerial Accounting
• Financial Management
• Financial Theory 1
• Financial Theory 2
• Fintech: Shaping The Financial World
• Investments
• Negotiation and Conflict Management
• New Enterprises
• Nuts and Bolts of Business Plans
• Practice of Finance: Advanced Corporate Risk Management
• Pricing
• Technology Strategy
• The Analytics Edge
• Topics in Mathematics with Applications in Finance
• Strategic Management 1
• Strategic Management 2
• Business Analysis and Financial Statements

Non-Degree Law Courses

MIT OpenCourseware:

• Law for Corporate Finance and Financial Markets
• Law for Mergers and Acquisitions
• Constitutional Law: Structures of Power and Individual Rights
• Ethics and The Law on The Electronic Frontier
• Introduction to Copyright Law
• Patents, Copyrights, and Law of Intellectual Rights
• Law for Entrepreneur and Manager

KG Embeddings

Bilinear:

• DisMult
• ComplEX
• ANALOGY
• SimplE

Non-Bilinear:

• HolE
• TuckER

Geometric Pure Translational:

• TransE
• TransH
• TransR
• TransD
• TransA

Geometric Translational with Additional Embeddings:

• STransE
• CrossE

Geometric Roto-Translational:

• TorusE
• RotatE

Convolutional Neural Networks:

• ConvE
• ConvR
• ConvKB

Capsule Neural Networks:

• CapsE

Recurrent Neural Networks:

• RSN

Selflessness

In modern western societies, people like to emphasize their volunteering activities. However, this entirely defeats the purpose of charity and volunteering. By definition volunteering is supposed to be a selfless act where one doesn't declare it as an achievement, take credit for it, or boast about it. By doing so, not only does it invalidate the intention, action, and effort but the whole essence of selflessness. It is about putting someone else first. In some religions it is expected that a person gives or does something of this nature anonymously without any form of recognition or reward. University applications look for volunteer activities. Resumes contain volunteer activities. What are people trying to gain from declaring such activities that they did in a selfless act? 

Future of Workforce

As AI becomes more ubiquitous in society, we are likely to see a massive shift which will be gradual in nature. More service level workers will be hired that can be replaceable for an organization when times get tough so they are easy to re-hire with rudimentary requirement of skills and in most cases this will relate to operating and managing robots. Such roles will act as buffers between management and robots to facilitate human-in-the-loop automation. The structure will become so flat that economies of scale will mean mass unemployment and degradation of the workforce at large where organizations will shrink in their hiring of human resources. Management of people will transform into the management of robots. As life becomes more simple and mundane so will it mean complexities of lifestyle and living standards between a huge rich vs poor divide. Societal class structures will inevitably mean makeshift barriers will be errected to keep the untouchable poor away from the rich resourceful. Security will take on a whole new transformation, in most cases violating freedoms and data protection rights of individuals. Education will become a widespread online learning experience for many, while lacking in quality, and the on-campus learning experience a privilege for a few. The few humans controlling the economies of the world will use robots against annihilation of the human race, what will be regarded as part of the eugenics movement. In many cases, this may take the shape of concentration camps while pandemics will be a natural course of action for population control. We have witnessed such scenes of societal destruction and urban decay play out in a multitude of movies, in most cases what is defined as sci-fi. However, as we move through the times, we come to realize that sci-fi is more and more becoming a reality for humans. It is the human that defines and creates a seed of ethics inside the artificial machine. What if this human is unethical? What if they are immoral? What if they build biases inside the programmable machine? We already see such issues of biases in machine learning models of today which are only to get more and more sophisticated. As time goes on, it is the human role that will no longer fit in the puzzle of the world. The future looks bleak for humans in the world of artificial intelligence and even superintelligence.

Qiskit

Qiskit

Nvidia Riva

Nvidia Riva

Text2SPARQL and MK-SQUIT

MK-SQUIT

Nvidia Nemo

Nvidia Nemo

Quantum Natural Language Processing

• Quantum Natural Language Processing 
• A Gentle Introduction To Quantum NLP
• Mathematical Foundations for Compositional Distributional Model of Meaning
• Parameterized Quantum Circuits as Machine Learning Models
• A Graphical Approach To Measurement-based Quantum Computing
• The Mathematics of Text Structure
• Functional Question Answering
• Quantum Algorithms for Compositional Natural Language Processing
• Kindergarten Quantum Mechanics
• Interacting Quantum Observables
• A Retargetable Compiler for NISQ Devices

YouTube:

• Quantum Natural Language Processing
• A Gentle Introduction to QNLP
• Compositional Natural Language Processing

MIT Courseware:

• Quantum Computation
• Quantum Information Science 1
• Quantum Information Science 2
• Quantum Information Science

Interview Questions

Some companies have interview processes that involve psychometric and behavioral questions. However, what is the point of such questions and how do they relate to the job? In many cases, such questions are so personal that they end up violating GDPR in the way candidate profiles are assessed, stored and processed. What is the point of mapping shapes through a hole? What is the point of so many unnecessary tests? The candidate likely already has a degree and to obtain that they likely had to also sit multitude of tests. It seems like tests are an endless cycle for people when it comes to recruitment. And, having multiple stages in an interview process not only increases the bias with the number of interviews, but also reduces the probability of someone passing all the stages. Invariably, the interview questions do not match the job, and there is only so many ways an interviewer can ask questions to a candidate. No doubt such tests are defined on the advice of Phd individuals who want to test others but are too incompetent to have practical skills of their own. In many cases behavioral and psychometric tests are flawed as statistics is used to evaluate candidate answers, and those answers are very much subjective and purely academic. Such subjective evaluation also leads to rejection to suitable roles and incorrect recommendations to roles for which the candidate may not have any prior experience. No wonder organizations struggle to hire people because for every aspect of work Phd individuals are providing and dictating incorrect guidance determined through flawed academic analysis which rarely takes into account outliers, while pigeonholing people into artificial groups of biases.  Phd individuals in the IT sector have really made a mess of the field and this is likely to grow as more and more get hired into professional workplaces in organizations with very little to offer in terms of practical returns. Perhaps, this is also a reflection of how academia is a failure to societies at large and the Phd qualification, in particular, that produces such incompetence where one percent of the population dictates to the world on how things should be done. HR processes are only going to get worse and more competitive where academic potential weighs higher than practical experiences leading to stymied organizational performance and growth. The ultimate goal of an application and interview process should not be overly complicated and academic in nature. The whole objective is to evaluate the skills of the candidate to do the job which is more practical in nature. So, what if they are not a cultural fit in their approach to life or that they can't be bothered to do silly hackerank tests. Pointless tests tell very little about candidates anyway. Not to mention they may be incorrectly worded or just expect a subjective way of doing something. Not everyone can fit neatly in a square box. The only real way to conduct interviews is to have a friendly, approachable discussion about the job and the skills required to do it, with as minimum stages as possible rather than dragging the process on an endless cycle of subjective evaluations, at the expense of using costly and implausible third-party systems.

NLP courses

NLP course

DeepLearning.ai - NLP Specialization

MITCourseware:

• Affective Computing
• Advanced Natural Language Processing
• Computational Models of Discourse
• Natural language and Computational Representation of Knowledge
• Linguistic courses

NLP with Deep Learning

CMU Natural Language Processing

From Languages to Information

Deep Learning for Natural Language Processing

Natural Language Processing

Natural Language Processing

Applied Natural Language Processing

Racist Organizations

It is true when an organization struggles to fill roles they are merely professing to the fact that their biases and discrimination are holding them back from determining the right candidate for the job. Increasingly, recruitment agencies are removing candidate background information such as name, address, and such from resumes to emphasize the fact that it is really the content of work that matches the job not what race, gender, or background someone is. In many instances, candidates even change their names to fit in with the employer ideals and stand a better chance for an interview. One only has to look at the people within any given organization on linkedin to get the eagle eye view of diversity, equity and inclusion in the workplace. In fact, an organization that rejects an asian or black for a technical role may in fact do it because most of the people that work there are white and this can be easily seen on the types of people that work there and their backgrounds. In many occasions employers may scrutinize on candidates if they are non-white especially on their education backgrounds. On other instances it is merely a case of utter racism that comes into play. Roles like natural language processing and computational linguistics are often seen as roles for white individuals especially as the employer assumes that non-whites may not know how to write and speak english. Such baseless biases are rampant in the IT industry across the sectors. Some recruiters just don't like working with non-whites. Others look at all muslims as terrorists so avoid hiring them altogether, while blacks may be seen as difficult or challenging to interact with in the workplace. All these biases are holding back the asian and black communities from jobs and quality education which may be the point all along. The lesser jobs they have and the lower standard of education they have means they can be kept in control and monitored in lower paying jobs where they are not able to hold authority, influence others, and make significant impactful decisions for society at large. This is also a mere sense of distrust and fear of the non-whites as well the need to maintain the status quo. A typical aspect that one can see transpiring is when a white person gets caught being racist they immediately release an apology. But, what good is this apology anyway when it is made only because they got caught, not that their actions were wrong. They are still likely to hold the same views unless they get caught again for some other reason. Why is it always the non-white being attacked in society? It is bizarre that the majority of wealthy economic societies are in the west dictating the terms of global supply and demand. While the countries with the richest reserves of natural resources are in the east. Is it any wonder that for the last few decades west has always had a reason to target an attack on the east which in most cases was either due to oil or some other naturally abundant resource? There has never been a time in such a long time where the east targeted the west especially in form of greed for resources. This imbalance of power has had severe ramifications across the economic divide and something seriously has to be done to level the playing field. Two fundamental factors that could reduce the economic disparity in the east is to transfer more economic funding towards sustainability and educational efforts which in both short-term and long-term could prove a surefire way of increasing the global balance. The transformation could then be made visible through job creation, reduction of debt, support for the disadvantaged, better educational institutions, more startup innovation, accountability audits for corruption, and sheer economic development for the future. This will undoubtedly create a sustainable form of enrichment to the east without being hampered by the west. Sustainability and increased educational opportunities leads to both social, economic, and environmental improvements in multiple dimensions which eventually eclipses and influences complex fabric of societal systems.

Inconsiderate Universities

The following list the types of things that make a bad university.

• Never get back to your enquiries within 24-48 hrs
• Don't prioritize or who can't be bothered about students
• Really slow admin processes you are bound to be frustrated for the entire academic period, it really is not worth it
• Terrible housing if you are looking for on-campus living
• Lecturers have no office hours and don't go out of their way to make themselves accessible to students
• Don't sympathize or show any empathy for students
• High faculty turnover
• Consistently drop in rankings each year
• Low student satisfaction
• Antiquated systems and IT
• Unhelpful staff
• Make mistakes even on academic transcripts
• Grade incorrectly
• Hold biases and discriminate on students
• Staff take kickbacks and discriminate on the admissions process
• Very low graduation rates or very high acceptance rates
• No accreditation for their courses
• Struggle to get funding for research and teaching and dependent completely on intake of students
• Probationary status or where abuse/harassment/discrimination are rampant
• Cannot separate education from religion
• Lack student services
• Driven by profits over quality of education
• No scholarship or alumni progams
• Terrible teaching methods 
• Don't have any form of recognized research program or a poor publishing record
• Poor collaborative record with other established institutions both for teaching and research
• Poor health and safety record
• Poor international recognition
• Poor job prospects after graduation
• Unrecognized credential
• Poorly rated on government metrics for teaching and research quality
• Academic programs are not designed through standardized guidelines and recommendations
• Lacks diversity, equity, and inclusion in their processes
• Graduates from the university have little change in their prospects, and often lack ethics in how they conduct themselves in society
• the institution gives nothing back to society or the local community either via jobs, funding, charity, regeneration programs, or cultivating urban improvements
• the institution has misleading and complicated processes for admissions and in most cases done on purpose to cover up for biases and discrimination
• work experiences are asked for but not used for admissions
• trying to get students to take more prerequisites in order to make more money or the fact that they don't have that many advanced courses that are supposed to make the course interesting
• most of the courses that they advertise on open days are rarely available for students

Cryptography and Machine Learning

Cryptography and Machine Learning

What makes a sucky Employer

Increasingly, in a competitive world, many organizations are becoming the worst places to work for employees and the worst places to apply for candidates. The below sheds some light on questionable employer practices.

• Employers that stress diversity, equity, and inclusion but have very little reflecting that in their management team or recruitment practices
• Employers that hide behind the facade of cultural fit to discriminate on candidates and employees
• Employers that want people from top schools but have very low compensation packages
• Employers that want everything but don't want to offer anything in return
• Employers that expect their employees to lie and cheat to customers
• Employers that have disgruntled customers and bad customer service practices
• Employers that have cheap and terrible products to sell to customers or can't be bothered to understand the frustrations of the customer, identify the gaps in market, and take the necessary steps to improve their business model
• Employers that have terrible work life balance for employees
• Employers that treat their employees like disposable goods
• Employers that care more about where you went to school rather than what you did with your degree
• Employers that are pretentious and procrastinate with employees
• Employers that can't be bothered about candidates during the hiring process and display unprofessional practices
• Employers that have terrible record of dealing with abuse, harassment and discrimination in the workplace
• Employers that are unethical and lack the sense of social responsibility
• Employers during tough times will always look to job cuts as a point of cutting costs rather than reducing red tape between managers
• Employers that have poor incentives for training and career growth
• Employers that don't appreciate good employees and overcompensate bad employees
• Employers that have high turnover as a result of bad recruitment and cultural practices
• Employers that don't realize that it is a two way street between them and customers, employees, and candidates
• Employers that don't realize their brand value can drop in a second through bad social media reviews
• Employers that don't value customers, employees, and candidates will lose business in long run
• Employers that don't make themselves accessible to the public
• Employers that are out of touch with reality and the internal issues in the organization
• Employers that don't listen to customers, employees, and candidate feedback and put it into action to improve both the product, service, and the workplace
• Employers that display a total lack of empathy towards customers, employees, or candidates
• Employers that don't take the time to quality check their products before selling to customers
• Employers that don't care about the privacy rights of customers, employees, and candidates nor take the necessary steps of care to protect their personal data
• Employers that don't have an effective health and safety induction process
• Employers that are disorganized, badly managed, and hire clueless individuals
• Employers that have core values that includes teamwork, valuing people, and integrity while not practicing any of it in the workplace, especially if valuing people involves making them redundant at the drop of a hat or not valuing customer service
• Employers that mostly have bad reviews from their customers, candidates, and employees
• Employers that have biased and discriminatory processes for employee performance reviews for bonuses, increments and promotions
• Employers that don't provide support for maternity and paternity leave
• Employers that have dodgy benefits packages
• Employers that expect employees to work during holiday leave
• Employers that provide bonuses to their mgmt for mass layoffs
• Employers that pay huge pay packages to mgmt but are stingy when it comes to paying their employees
• Employers that don't have sustainability in their business model nor take initiatives to protect the environment
• Employers that don't provide days off for volunteering to employees 

Phd Incompetence

Academia is very different from the practical world. In academia, foundational skills are measured through exams and rudimentary coursework. While in practical world, organizations want people that can do the job under uncertainty, huge amounts of complexity, efficiently process noisy data, adaptability to change, and a requirement for following best practices. At some point in a person's career, work experience far surpasses academics both educationally and in problem solving. The below points highlight the typical patterns of behavior that Phd individuals display in the work place and academia:

• Will want to command authority simply because they hold a Phd which may not even be in a technical field and totally unrelated to the job
• Will measure someone's skills by the amount of degrees they hold and where they got them from
• Will expect others to help them with 80% of their job
• Will struggle to convert theory into practice 
• Will take years to do something that could be done in months by an engineer
• Will reject perfectly good candidates simply because they don't hold a Phd like they do or went to a certain university like they did
• Will advertise for roles where job titles are miss-aligned to job descriptions to miss-lead candidates
• Will be enamored by the amount of papers they have published even though many of them are either plagiarized, summary synthesis of other papers, lack technical depth, incorrect in plausible theory, or are simply too unimportant to hold any real value to an organization
• Will ask really dumb questions to engineers and then expect them to sound deep like asking what is unit testing
• Will reject the very same people with experience in academic admissions to universities while lacking the same skills themselves
• Will try to take credit for other people's work 
• Will have questionable basic foundational skills for the job, but will call themselves as experts anyway
• Will have multiple published papers that have different topical headings but basically the same content
• Will spend majority of their time hacking through things but will expect others to think they are following a scientific method or process
• Will usually have no clue themselves as to what they are doing
• Will introduce biases into their data just because they can and no one will question them for it, they will then produce such flawed and biased results and expect everyone to call them experts
• Will have no real accountability for their work output in organizations
• Will likely make terrible leaders or managers of people
• Will struggle to teach others the very same concepts that they call themselves experts in because they don't fully understand the concepts either
• Will make silly reasons as to why they need to hire more people on the team, even when it is really part of their own job to know how to do
• Will expect anyone that doesn't hold a Phd does not know what they are talking about
• Will likely patronize and discriminate on non-Phd people in the workplace
• Will reject people if they hold a difference of opinion to themselves
• Will likely be very insecure and take offense if their skills or work is criticized or is taken into question purely because they assume they are experts because they have a Phd, eventhough that Phd could be in cartoonism
• Will likely add more cost to organization for all the help they will need to be able to do their job, and the job that they do amounts to very little in quantifiable value
• Will likely leave a forgettable mark in organization especially as most of their work would already be done by others 
• Will tend to hire people that will not be a threat to them or highlight their deficiencies in the workplace 
• Will likely not know how to read a CV/resume
• Will reject approaches that are outside of their own discipline, knowledge, or comfort zone
• Will not be adaptable to change outside of what they already know
• Will likely hamper organizational productivity and efficiencies in work output and provide incorrect recommendations to management
• Will produce incorrect models which then influences flawed strategic decisions within organizations
• Will likely only have questionable academic skills with jupyter notebooks, matlab, or tools that will require huge amount of effort to refactor and productionize
• Will likely be expected to teach what they can't put into a practical implementation
• Will likely not have basic skills in data structures and software engineering or the background of things that they will look for in admissions applications to universities
• Will focus on theory all day long but be clueless about how to apply any of it in practice
• Will likely lack fundamental work experience to put them in a position of seniority to call them experts in organizations
• Will likely struggle to take such things as uncertainty, noisy data, biases, complexity, and context into account within their work output and likely expect someone else to sort out for them
• Will likely for all the things they call themselves an expert in, they will expect someone else to do for them
• Will likely be the weakest link in organizations expected to be an expert in an area, but a master of none when it comes to practical implementations
• Will likely be unprofessional when interacting with non-Phd individuals and not value their time
• Will get easy access to funding for their research projects but the work output will not be sufficient to justify the cost, and at times a lot of that funding may be deceptively used to fund other projects in other research teams or faculties
• Will require an awful lot of mentoring to be able to do even simple tasks, making you wonder how in the world they could be called experts or have achieved a Phd
• Will act like a grasshopper with the absence of legs in the workplace
• Will use overly complicated methods rather than approach it first with the simplest solution
• Will use academic approaches to solve non-academic problems in most cases the approach they use will be inefficient and unworkable for prime time production

Ex-Googlers

It seems googlers are taught to practice arrogance as if their entire life goal was to be part of Google. In fact, working for such a large company does have its disadvantages. And, when they turn ex-googlers they become even more arrogant. So, why did they leave? Is this because they are insecure that they left the company or because they want to impress on the fact that they once were there as well? But, one thing both ex-googlers and googlers share is the fact that they find any one that did not work at Google as beneath them. This sort of sordid culture of arrogance and conceit is unlikely to be found in other companies like Amazon, Facebook, Microsoft, Apple, or even at Netflix. Perhaps, this is the way Google's internal culture brews and transforms the mentality of their employees into spoilt individuals. Either way, it projects a toxic culture. One can already see glimmers of toxicity in the way the organization forces other clients to use their cloud infrastructure which compared to AWS has a significantly long road ahead in playing catchup. Is it any wonder that ex-googlers struggle to find much success outside of Google as if to permanently lose their sense of what it means to be human. One can only anticipate that such a large company over time can only get bigger, and this perpetuated sense of complacency within Google is only bound to get worse, can only eventually lead to a corporate demise like a climactic fall of bricks.

Capsule Networks

Capsule Networks

Atticus Project

Atticus Project 

Atticus Github

Biased Practices of University Admissions

International students to USA universities from the beginning of their application submission are at a disadvantage with competition for seats that grows every year and may even be different from one term to another depending on the applicant pool. However, the biased practices don't stop there but they begin from the screening process. International students are expected stronger backgrounds, better GPA compared to local students, better essays where their english is evaluated more stringently even a grammar or spelling mistake is an issue, and many go through an FBI database profile check. Yes, there is racial profiling involved here. And, if the program is affiliated with defense or military then one can be sure to be scrutinized for religious affiliations which becomes apparent based on the application profile from such things as place of birth, name, and from essays. First amendment constitution rights don't hold any weight on an international student application screening process and affirmative action is only for namesake. And, no controls on the application for diversity, equity, and inclusion. One thing to note is that on most USA institutions the research assistants usually have very similar backgrounds. They are either locals, europeans, or asians with predominately alternative religious or non-religious affiliations. In public universities they are required to comply with anti-discrimination laws. However, in private universities this may not be the case. And, often these laws are abused by individuals under the covers of paperwork and cultural biases where it is extremely difficult to apply transparency and accountability. In fact, many admissions processes don't even provide any feedback to applicants. The academic admissions process is very much subjective. This is equally why universities need to resolve biases by introducing AI into the system of screening applications. And, not only accepting or rejecting applications but providing the right sense of constructive feedback that can help them in their future endeavors whether that be a re-application in the future, an acceptance at the university, or beyond.  The following are some suggestions on how an application could be evaluated via AI:

• Key/Value extractions in JSON form from applications, then store in a database
• Key/Value extractions in JSON form from resume, then store in a database
• Key/Value extraction in JSON form from academic transcript, then store in database
• Automated essay scoring using NLP methods
• Automated resume scoring using NLP methods
• Basic distribution curves of GPA in pool of applicants
• Basic distribution curves of standardized test scores of applicants
• Identify outlier class attributes using unsupervised clustering methods
• Building a bayesian model for uncertainty reasoning for causal inference, this could be in the form of a factor graph to identify whether this applicant will :
• struggle to maintain a 3.0 GPA, 
• whether they are likely to accept if given an offer, 
• whether resume experiences can be considered in lieu of lower GPA,
• the degree of course rigor for which they attained a high GPA,
• the overlap of courses in the alternative degree attained,
• the likelihood of meeting the prerequisites,
• whether they are likely to dropout part way through the course,
• whether they were top of their class in their respective peer group given the percentile,
• the degree of their intents, interests, experience, goals, maturity, and peers match to the program
• Produce a Knowledge Graph representation of the applicant profile that could be queried for 5W1H question/answering.
• Identify the key classification classes that every applicant must have to build a diversified pool of offers - this could be a combination of supervised regression and unsupervised clustering methods
• A graph-machine learning based recommendations system that ranks the candidates in order of priority taking into account outliers
• Build an affective computing model using symbolic reasoning to identify intents and interests then feed that back into the recommendations process
• Apply a fraud detection mechanism to identify fake application documents
• Apply a lie detection mechanism to identify whether the applicant actually did these extracurricular activities like volunteering, whether they actually did face such hardships, or whether they did have these work experiences
• Apply a financial evaluation of applicants to see whether they will be able to financially cope with the tuition and fee payments or will they struggle significantly, then look to evaluate recommendations for financial aid if they meet such criteria.
• Build a feedback loop mechanism to enhance the application structure in the way they are worded to analyze for biases and build an explainability model
• Build a criteria model for fairness then apply such transparency and accountability measures for errors in the feedback loop
• Build a constructive feedback loop for applicants identifying the class attributes that held them back and what they could do to improve their chances of future acceptance, although this may vary based on any given applicant pool for the term, at least it could be evaluated from historical trends. Most rejection letters are worded in a standard form which is unhelpful to applicants.
• For Phd applicants this may also have a separate step to evaluate the strengths of the department vs the interests of the applicant and whether an appropriate advisor could be provided.
• References could further be assessed with NLP methods of extraction, and as a feedback loop into the recommendations, question/answering, causal inference, financial evaluation, fraud, deception, quantifying biases, and other forms of assessment criteria
• Identify similarity trends between applicants using nearest-neighbor methods
• Identify regression method for whether applicants meet the relevant prerequisites
• Build a chatbot that assists applicants through the pre-application and post-application process. The objective should be of converting the applicant into a potential student and treating the individual as a customer. This chatbot should then take into account customer relationship management and affective computing for sentiments and emotions.
• Anonymization and masking of potential key attributes that could pose as an underlining bias in the decision like place of birth or name.
• Localization of applications if a threshold needs to be maintained between international, in-state, and out-of-state applicant offers.
• If there are publications they could be checked for citation scores and validated for theory correctness and coverage
• If there are any awards won they could be verified and validated
• Identify a key set of behavorial attributes that may be needed for a successful student on the course then measure against those set targets
• Making sure that correlation does not imply causation
• Convert non-refundable fees into refundable retainer fees so when an applicant is declined the application fee is refunded. Why penalize applicants that got declined, in fact it will only push more applicants to apply that would boost the ranking of the university. Why get applicants to apply if it is obvious they will be rejected at the expense of boosting university rankings. Only accept application fees from those that you have accepted to the university and let the fee go someway towards the tuition and fees.

*This does not include international credential discrepancies where different languages and grading systems would need to be translated. A separate algorithmic process would need to be defined for such functional use cases of international applications.