7 January 2025
6 January 2025
4 January 2025
What makes a person ugly or beautiful?
Cultural Standards:
- Societal Ideals - this varies across cultures and shifts through time
- Media Influence - promotes unrealistic and narrow-minded ideals
Biological Factors:
- Symmetry - defined facial symmetry, often influenced by the golden ratio
- Averageness - closer to the average are perceived as more attractive
- Health Cues - features that signal good health
Psychological Factors:
- Personality - positive traits that aggregate into attraction
- Confidence - inclined to be more assertive
- Individual Preferences - subjectivity based on different perceptions
- Inner Beauty - positive traits that are considered more important for the long-run
Top Books on Philosophy
Classics:
- Meditations
- The Republic
- Nicomachean
- Meditations on First Philosophy
Modern/Contemporary:
- Being and Time
- The Myth of Sisyphus
- Existentialism is a Humanism
- The Ethics of Ambiguity
- The Order of Things
- The Interpretation of Dreams
- No Logo
Intros:
- Sophie's World
- The Story of Philosophy
Deep Dives:
- Critique of Pure Reason
- Being and Nothingness
- Thus Spoke Zarathustra
Ethical/Political:
- The Prince
- Utilitarianism
- On Liberty
Consciousness:
- What Is It Like to Be a Bat?
- The Conscious Mind
- Consciousness Explained
- I am a Strange Loop
- The Enigma of Consciousness
- The Astonishing Hypthesis: The Scientific Search for the Soul
- Other Minds: The Octopus, the Sea, and the Deep Origins of Consciousness
Nihilism:
- The Conspiracy Against the Human Race
- Nihil Unbound: Enlightenment and Extinction
- The Trouble With Being Born
- The Will to Power
- The Gay Science
- The Stranger
- Notes from Underground
- Thus Spoke Zarathustra
- The Myth of Sisyphus
Stoicism:
- Letters from Stoic
- Discourses and Selected Writings
- How to Be Stoic: Using Ancient Philosophy to Live a Modern Life
- The Obstacle Is the Way: The Timeless Art of Turning Trials into Triumph
- A Guide to the Good Life: The Ancient Art of Stoic Joy
- The Daily Stoic: 366 Meditations on Wisdom, Perseverance, and the Art of Living
- Meditations
Existentialism:
- Fear and Trembling
- Existentialism is a Humanism
- The Myth of Sisyphus
- Thus Spoke Zarathustra
- Being and Nothingness
- The Plague
- Existentialism from Dostoevsky to Sartre
- Notes from Underground
- The Stranger
Metaphysics:
- Metaphysics
- Critique of Pure Reason
- The Structure of Scientific Revolutions
- Being and Time
- Naming and Necessity
- On the Plurality of Worlds
- Metaphysics: A Very Short Introduction
- The Metaphysics Within Us: The Hidden Dimensions of Our Everyday Lives
Epistemology:
- The Problem of Philosophy
- Knowledge and Its Limits
- The Structure of Scientific Revolutions
- Gettier Problems and the Analysis of Knowledge
Philosophy of Mind:
- The Mind-Body Problem
- Consciousness Explained
- I am a Strange Loop
- Supersizing the Mind: Embodiment, Action, and Cognitive Extension
Ethics and Morality:
- The Republic
- Nicomachean
- Justice: What's the Right Thing to Do?
- The Moral Limits of Markets: The High Price of Putting a Price on Everything
- Utilitarianism
- On Liberty
- Groundwork for the Metaphysics of Morals
- The Ethics of Ambiguity
- Beyond Good and Evil
- On The Genealogy of Morals
3 January 2025
AI Tools for Development
- Aider: rapid prototyping
- Cline: rapid prototyping
- Cursor: refinement
- Devin: build projects and scrapers
- Copilot: quick edits
- Tabnine: integrate with IDE for code completion
- Kite: high-quality suggestions
- Codeium: autocompletions
- Polycoder: code assist in teams
- Ghostwriter: custom code enhancer
- Bolt: project starter and initialization
- AutoGPT
- Pandora
Labels:
big data
,
data science
,
deep learning
,
machine learning
,
natural language processing
,
programming
Why does the west hate Islam?
- Media perpetuates anti-Islam hate through a pre-defined mainstream narrative
- Cyclical perception influenced through negative portrayals
- Media and Entertainment industry is divisive in labels, black vs white, and demonization
- Lack of tolerance, understanding, and inter-faith dialog
- Perceptions of backward stereotypes and biases that contradict western values and beliefs (although one can question, what are western values and beliefs?)
- Fear of the unknown
- Lots of collective judgement and generalizations that breeds prejudices, biases, and discrimination
- Looking for someone else to blame or scapegoat for the issues in their lives
- Trigger of tribalism of us vs them
- Fear of sharia law (even though, this is not really a required practice)
- Extremism and terrorism which is propagated, financed, and perpetuated by the West. This is indicative of the fact that conflicts and wars are profitable to the West.
- Historical context in the crusades
- Direct financial motives connected to natural resources and religion. Many pre-dominantly Islamic countries are rich in natural resources, centers of trade routes, and rich in traditional values.
- Cultural complications with dietary restrictions, freedom of speech, treatment of women, religious attire, and many other cultural practices are seen as odd and incomprehensible
- Perceived as a threat to western cultural norms (what exactly are western cultural norms is anyone's guess where people are confused about what gender they are?)
- Bad perceptions and intolerance feeds further negative views and hate like a vicious cycle
- The fact that many muslims are fixed in their beliefs and unwilling to change makes it incompatible with modern values of social progress, democratic participation, and resistance to scientific thought
- The perceptions that Islamic societies have an intolerance for other religions
How do you counter this?
- The West likely needs to stop interfering in foreign politics, economics, and conflicts
- The West should focus on their own taxpayers
- The West should stop trying to colonize other countries that don't conform to their ideals to steal land and natural resources
- Respect other people, their cultures, and values
- Provide more objective mainstream narrative and mindful use of language with journalistic ethics and responsibility so people can decide for themselves
- The West should let countries flourish and grow
- Stop bombing their countries so they don't turn into refugees and cause a western immigration crisis
- Increase tolerance through understanding and inter-faith dialog
- The understanding that every one has the right to liberty and security wherever they are in the world
- The understanding that basic human rights are accorded to people in every civilized society
- Stop being so greedy with the colonial mentality
- The West should stop selling weapons and equipment, if there are no real conflicts, who'd need the budgets for defence?
Labels:
deep learning
,
economics
,
finance
,
machine learning
,
natural language processing
,
news
,
world events
Work Better and Smarter
Prioritize Ruthlessly
- Find your Key Objectives
- Use the Pareto Principle
- Use the Eisenhower Matrix
Optimize Your Workflow
- Block time slots
- Batch Tasks
- Minimize Distractions
- Learn to Delegate
Continuous Learning and Improvement
- Develop Skills
- Get Feedback
- Experiment and Iterate
Cultivate a Growth Mindset
- Take on New Challenges and Deal with them Head On
- Focus on Solutions
- Accept Mistakes and Learn From Them
Take Care of Yourself
- Prioritize Sleep
- Develop a Healthy Diet, Exercise, and Routine
- Take Breaks
Labels:
big data
,
cognitive
,
data science
,
deep learning
,
health
,
machine learning
,
natural language processing
,
workplace
Things LLMs Cannot Do
- Lack of True Understanding:
- They operate on probabilities and patterns based on the training data
- They have no understanding on the meaning of language
- They have no grasp of concepts on the basis of which they generate grammatically correct sentences
- Hallucination and Bias:
- They have the propensity to generate incorrect and nonsensical information
- They mimic the biases in their training data that leads to unfair or discriminatory output
- Sensitivity to Input:
- Minor changes in input can drastically alter output that makes it difficult to control response
- Lack of Common Sense and Real-World Knowledge:
- They lack true common sense and worldly experience, the most they can access and process is the information based on their training data
- They fundamentally lack the understanding of everyday situations and interactions
- Ethical Concerns:
- They can be used to generate misleading and even harmful content
- They can be misused that have ethical implications
- Limited Creativity and Originality:
- They lack basic sense of creativity that is outside the fold of the patterns in training data to generate truly original concepts and ideas
- Emotions and Consciousness:
- They lack feelings, self-awareness and have no way of experiencing emotions
- Reliance on Data:
- They are only as good as the data they have been trained on and are a reflection of it
- Physical Actions:
- They are software programs in the digital realm and cannot interact with physical world
Labels:
big data
,
computer vision
,
data science
,
deep learning
,
machine learning
,
natural language processing
Why ex-Googlers make the worst hires?
- Lots of arrogance but very little to justify it in performance
- Mostly come with sexist, racist, and misogynistic attitude
- Lots of biases for minority hires so your diversity initiatives will suffer
- Lots of biases for pay, work, and benefits
- They significantly effect the team culture through negative attitudes
- Questionable skills and experience
- They will question everything with unconstructive ways of working and the solutions they come up with are usually bookish, unproductive, inefficient, and uncreative
- They lack pragmatism and common sense
- They want to interview people in convoluted ways which have no context nor relevancy to the role just like how they did at Google
- They want to make your organization function like Google like a mirror to their past
- They drive a toxic culture, whatever was bad at Google they bring to every other organization or team
- They like to harass other employees
- They look at others in a team as lesser individuals and make the collective team feel miserable
- Why did they leave Google to come to work at your organization if Google was so great?
- They demand higher compensation packages just for working at Google, while their pay at Google was at best mediocre
- If they are part of the team that has to screen candidate applications they seem to be stuck on where the candidate got their degree and their racial backgrounds then end up interviewing them with racist stereotypes and biases
- They lack job relevant experience and skills because they didn't exactly do much at Google
- They don't want to be interviewed the same way as other candidates, treated like special candidates for some reason (maybe special candidates with disabilities?!)
- You have to flex your entire organizational handbook to meet their ridiculous expectations
- They lack basic work ethics, integrity, and fundamental sense of professionalism in the workplace
- Pretty much every ex-Googler talks and acts like they are still in school or university with emotional immaturity
- They act like spoiled and pampered brats in the workplace
- They lack basic skills of being able to think outside the box
- They tend to be unwilling to learn new things or new ways of doing things
- They tend to frustrate easily on tasks and require a lot of micromanagement
- They tend to be resistant and unwilling to listen to constructive feedback, at times repeat the same mistakes without learning from them by overcompensating with a false sense of overconfidence and lack of experience
- They tend to waste people's time by pontificating and procrastinating
- Habitually putting people down to artificially inflate their egos and prop themselves up
- They tend to be the biggest cynics of other employees in workplace especially if they are not ex-Googlers
- Sometimes they can act as saboteurs or moles out of pure jealousy and resentment
Labels:
big data
,
data science
,
deep learning
,
human resources
,
jobsearch
,
machine learning
,
natural language processing
2 January 2025
Qwen
Labels:
big data
,
computer vision
,
data science
,
deep learning
,
machine learning
,
natural language processing
Cybertruck
Possibly, one the ugliest cars on the market. It is now also the deadliest after exploding outside of Trump Tower. The design especially is impractical, lacks usability, comfort, and a safe driving experience. This car falls short on a number of areas.
- Unconventional Design: angular stainless steel exterior that is easy on dings and dents
- Limited Visibility: narrow windows are problematic on visibility and safety
- Ride Quality: stiff suspension, mostly for off-road use, with uncomfortable driving experience on roads
- Interior Aesthetics: ugly interior to compliment the ugly exterior
- Unproven Technology: questionable, hit and miss technology
Worst Companies to Work For
- ServiceNow
- Salesforce
- NextEra
- S&P Global
- McDonald's
- Starbucks
- Burger King
- Whole Foods
- Walmart
- Union Pacific
- Signet
- Caffe Nero
- JD Sports
- WH Smith
- Betfred
- Zara
- Taco Bell
- Comfort Call
- Eden Futures
- Tim Hortons
- Max Spielmann
- Bodycare
- Poundstretcher
- Choice Care
- Victoria's Secret
- Valorum Care
- McColls
- Hertz
- Family Dollar Stores
- Steak n Shake
- Speedway
- The Children's Place
- Regal Cinemas
- The Fresh Market
- Rent-A-Car
- Forever 21
- Belk
- Alorica
- CompuCom
- Frontier Communications
- Dillard's
- CVS Health
- Kraft Heinz
- Dish Network
- Sears
- Kroger
- Tyson Foods
- Kmart
- TJMaxx
- Genesis Healthcare
- US Security Associates
- LA Fitness
- Charter Communications
- Amazon
- Tata
- Wipro
- Infosys
- HCL
- Tech Mahindra
- NTT
- Dell
- Cargill
- Reliance Industries
- Comcast
- Wells Fargo
- Bank of America
- Subway
- Shein
- Dollar General
- ExxonMobil
- Balenciaga
- BP
- Spirit Airlines
- Meta
- Fox Corporation
- Trump Organization
- Pfizer
- Coca Cola
- Tesco
- Microsoft
- Disney
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