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awayellis · 1 month ago

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✨ My Must-Have Base Game Friendly Mods! ✨

Hey Simmers! 💚

In some of my previous posts, I mentioned that I don’t own any paid expansions (except for the free ones from EA + Epic Games). So today, I wanted to share my favorite base game-friendly mods that make my gameplay so much better!

🌿 1) Wonderful Whims by Turbodriver This mod adds depth to attraction, preferences, and relationships—without the ahem explicit content from Wicked Whims (which was a bit too much for me 😅). Perfect if you want a more realistic romance system!

⚙️ 2) MC Command Center by Deaderpool An absolute must-have! This mod lets you control almost everything in your game—story progression, pregnancies, cheats, and more. The game just doesn’t feel complete without it.

💼 3) Career Mods by KiaraSims4Mods If you want more career options in the base game, Kiara has a ton of well-balanced and immersive careers to try out!

Astronomer Career

Banker Career

Computer Hardware Engineer Career

Computer Network Architect Career

Computer Research Scientist Career

Computer System Manager Career

Computer Systems Analyst Career

Database Administrator Career

Financial Analyst (No Promotion) Career

Gym Associate Career

Chess Player Career

Information Security Analyst Career

Insurance Sales Agent Career

IT Project Manager Career

Loan Officer Career

Management Analyst Career

Market Research Analyst Career

Publisher Career

Remote Office Assistant Career

Rocket Scientist Career

Simologist Career

Software Developer Career

Web Developer Career

Woodworker Career

💬 4) Interaction Mods by KiaraSims4Mods Adds new social interactions like “Discuss Future Together”, “Do You Like What You See?”, and “Discuss Having a Baby”—small things that make conversations feel way more natural.

Admire Woohoo Techniques Interaction

Discuss Future Together Interaction

Discuss Having a Baby Interaction

Discuss Relationship Status Interaction

Discuss Wedding Date Interaction

Do you like what you see? Interaction

Hate WooHoo Interaction

Chat about Baby Names Interaction

The Baby is Not Yours Interaction

💔 5) Miscarriage Mod by LittleMsSam A more realistic take on pregnancy, adding the possibility of miscarriage with emotional consequences for Sims. A heavy addition, but it makes storytelling more impactful.

🍼 6) Ultrasound Mod by LittleMsSam Lets your Sims go for an ultrasound and get a cute little scan to hang on their wall! One of my favorite small details.

🌍 7) Social Activities by LittleMsSam Adds tons of rabbit hole events—your Sims can send their kids to daycare, visit friends, or even attend concerts! It makes the world feel much more alive.

💘 8) SimDa Dating App by LittleMsSam Think of it as Tinder for Sims! Your Sims can go on blind dates, specific dates, or even find a hook-up.

🎓 9) Online Learning System by LittleMsSam Allows Sims to learn skills online—great for more realistic gameplay!

🤰 10) Pregnancy Overhaul by LittleMsSam Adds more depth to pregnancy. A small but immersive addition!

💤 11) Dreams & Nightmares by AlainBM_Mods Probably my favorite mod—it gives Sims actual dreams and nightmares that impact their mood. It’s such a unique touch to storytelling!

🌟 12) 100 Traits by Chingyu Adds SO many new personality traits, making Sims feel unique and realistic. No more identical Sims with the same base game traits!

💡 These mods have completely changed how I play, making the base game feel so much richer! What are some of your must-have mods? Let’s share recommendations! 💬✨

#simslegacy #simblr #sims4legacy #ts4 #thesims4 #the sims 4 mods #notsoberry #ts4 mods #sims 4 mods #the sims cc #the sims 4 community #sims4inspiration

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mathslear · 10 months ago

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Career Opportunities in Coding: How Coding Classes Benefit Future Career Prospects for Kids

Coding is the language of computers, and it is used to create everything from websites and apps to video games and robots. In today’s digital world, coding is a valuable skill that can open up a world of career opportunities for kids.

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Here are some of the benefits of joining Coding Classes at a young age:

Coding can help kids develop problem-solving skills. Coding teaches kids how to break down complex problems into smaller, more manageable steps. This is a valuable skill that can be applied to all aspects of life, from schoolwork to the real world.

Coding can help kids develop creativity. Coding is a creative process that allows kids to express their ideas and build things from scratch. This can help kids develop their imagination and problem-solving skills.

Coding can help kids develop a competitive edge in the job market. The demand for coders is growing rapidly, and kids who learn to code at a young age will have a significant advantage in the job market.

Exploring Career Opportunities through Coding Classes:

Web developer: Coding class graduates can become web developers, creating and maintaining websites and web applications using languages like HTML, CSS, and JavaScript. With a starting salary ranging from £30,000 to £45,000, the journey into web development promises both creativity and financial reward.

Software engineer: The skills acquired in coding classes prepare kids for a career as software engineers, designing, developing, and testing software applications using languages such as Java, Python, and C++. The starting salary for software engineers in the UK typically ranges from £35,000 to £55,000, reflecting the value of their expertise in the digital realm.

Mobile app developer: Coding class graduates can venture into mobile app development, creating and maintaining mobile apps for smartphones and tablets using languages like Java, Kotlin, and Swift. As they step into the role of a mobile app developer, they can anticipate a starting salary ranging from £30,000 to £50,000 – a testament to the demand for skilled app developers in the market.

Game developer: With coding skills from classes, kids can become game developers, creating and maintaining video games for consoles, computers, and mobile devices using languages like C++, C#, and Unity. The starting salary for game developers varies, but it often falls within the range of £35,000 to £60,000, reflecting the competitive and lucrative nature of the gaming industry.

Data scientist: Coding class graduates can pursue a career as data scientists, collecting, analysing, and interpreting large amounts of data to aid businesses in making informed decisions. They use languages like Python and R for data analysis and report creation. As data scientists, they can expect a starting salary ranging from £40,000 to £65,000, showcasing the high value placed on their expertise in the realm of data.

Conclusion

Investing in coding classes is a wise decision for kids of all ages. These classes not only help kids develop problem-solving skills, creativity, and a competitive edge but also open doors to a variety of exciting career opportunities. At BYITC, we offer a range of coding classes designed to be fun, engaging, and educational for kids of all ages.

If you’re keen on exploring the world of coding through BYITC’s classes, please visit our website or sign up for a free trial class. We are eager to assist your child on their journey to learning the language of the future!

Originally Published at:

https://www.byitc.org/career-opportunities-in-coding-how-coding-classes-benefit-future-career-prospects-for-kids/

#coding classes for kids #Coding Classes #Youtube

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thejobwala · 2 years ago

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Download Jobwala app for the easiest job search and hiring. Now get every type of job in one place with Jobwala. Be it 10th pass and below or postgraduate we have jobs for everyone. Now get a job that satisfies your career goals with maximum salary satisfaction. From part-time and Full time to working from home, everything is just a click. With a vast variety of jobs and so many best options available to choose from. Be it Central, Western, or Harbor line we are all over Mumbai to provide you with the best.

The only job portal that provides you with the nearest jobs with maximum salary satisfaction and career growth. Verified companies to apply with no fear of fraud and scam. We cover almost every blue collar job people struggle to get. Apply to your dream job and get a chance to work in your dream company in just a click.

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nmietbbsr · 24 days ago

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How to Become a Data Scientist as a CSE Student?

If you’re a CSE (Computer Science and Engineering) student, chances are you’ve already heard the term data science quite a few times. It’s one of the fastest-growing career fields in tech—and for good reason. Companies across the world rely on data to make decisions, and they need skilled people who can make sense of all that information.

So, how do you become a data scientist when you’re still a student? Let’s break it down step by step.

Understand What a Data Scientist Really Does

A data scientist is someone who collects, cleans, and analyzes large amounts of data to help businesses or organizations make smarter decisions. This can involve writing code, using math, working with databases, and communicating findings clearly.

It’s not just about writing programs—it’s also about thinking critically and solving real-world problems with the help of data.

Step 1: Get Your Basics Right

As a CSE student, you already have a head start. Your curriculum likely includes core subjects like programming, algorithms, databases, and computer networks. Pay close attention to:

Python or R (Python is more widely used in data science)

SQL for handling data in databases

Math and Statistics, especially probability, linear algebra, and basic statistics

Data Structures and Algorithms for handling data efficiently

These skills form the foundation of data science work.

Step 2: Learn Data Science Tools and Libraries

Once you’re comfortable with basic programming and math, it’s time to explore tools used by data scientists. You don’t need to master everything at once—start small.

NumPy and Pandas (for handling and analyzing data)

Matplotlib and Seaborn (for creating charts and graphs)

Scikit-learn (for machine learning models)

Jupyter Notebooks (for writing and sharing your code easily)

Plenty of free tutorials and YouTube videos can help you practice these.

Step 3: Take Online Courses and Certifications

While your college of engineering and technology in Bhubaneswar may offer some electives or workshops, adding extra courses can boost your learning. Platforms like Coursera, edX, Udemy, and Kaggle offer beginner-friendly courses in data science and machine learning.

Look for beginner tracks with practical projects. Try courses like:

"Introduction to Data Science in Python"

"Machine Learning" by Andrew Ng

"Python for Data Science and AI" by IBM

These certifications can also strengthen your resume later on.

Step 4: Work on Real Projects

Theory is important, but nothing beats hands-on experience. Try simple projects first:

Analyze sales or weather data

Build a movie recommendation system

Predict house prices using public datasets

Visualize COVID-19 data trends

You can find datasets on sites like Kaggle, UCI Machine Learning Repository, or Google Dataset Search. Try to write a short blog post or upload your project to GitHub so others can see your work.

Step 5: Join Internships and Communities

Real-world experience can help you build both skills and confidence. Look for internships related to data analysis, data science, or even software roles that deal with data.

Also, join online communities like:

Kaggle (for competitions and discussions)

Reddit’s r/datascience

LinkedIn groups focused on analytics

Discord or Telegram groups for peer learning

You’ll learn a lot from seeing what others are doing and sharing your progress too.

Step 6: Build a Portfolio

Before applying for full-time jobs, put together a portfolio. This can include:

2–3 well-documented projects

A GitHub profile with clean code

A short resume highlighting your tools and skills

A LinkedIn profile that reflects your interests in data science

If you're studying at a college of engineering and technology in Bhubaneswar, consider joining tech fests, project expos, or coding clubs that give you space to present your work.

Conclusions

Becoming a data scientist as a CSE student doesn’t require fancy degrees or expensive tools. What you do need is consistency, curiosity, and a clear plan. Start with your basics, explore tools, build small projects, and grow step by step.

The field of data science is full of opportunities—and your classroom is just the beginning.

#top 5 engineering colleges in bhubaneswar #top engineering colleges in odisha #bhubaneswar b tech colleges #college of engineering and technology bhubaneswar #best colleges in bhubaneswar #college of engineering bhubaneswar

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teamplusglobal · 1 month ago

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Hire Top Tech Talent Worldwide with TeamPlus Global: Your Trusted Partner

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ajay--sharma · 3 months ago

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Data Scientist vs. Data Engineer: Key Differences & Career Insights

Data is everywhere in today's world. Whatever apps we use or whatever websites we visit, everything is based on data. But have you ever thought about who does all this magic behind data? There are two very important roles: Data Scientists and Data Engineers. Though they deal with data, their jobs are completely different.

So, let's break it down in basic terms and go through the main key differences between a Data scientist vs Data engineer to help you decide which path might be right for you.

Difference Between Data Engineer And Data Scientist

In Data engineer vs Data scientist think of a Data Engineer as the person who designs the foundation and building of structures to allow data to flow well. Their job involves making sure data gets collected stored, and kept ready to analyze. A Data Scientist, however, works like a detective to use data to uncover patterns, trends, and insights that help businesses make smart choices.

Educational Requirements

In India, skill sets are more crucial than degree requirements for becoming a successful Data Scientist vs Data Engineer. You may observe many successful Data Scientists and Data Engineers from various educational backgrounds who are excelling in this industry, but if becoming a data scientist or data engineer is your ultimate aim, then studying data analytics courses in college can undoubtedly help you become the greatest.

Educational qualification to become a Data Scientist.

1. You will need a bachelor's degree in Computer Science, Mathematics, Statistics, or Engineering to start a career in data science. To get better opportunities you can also go for a master's and PHD degree.

2. If you have already completed your degree in another stream and then chose data analysis as your career short-duration data analyst course can help you with that.

3. Familiarity with data analysis, SQL, Excel, and software such as Tableau or Power BI are also important to be a good data scientist.

4. A good understanding of statistics and probability is important for analyzing data correctly.

Educational qualification to become a Data Engineer.

1. A bachelor's degree in Computer Science, Information Technology, or Engineering.

2. Strong programming skills in languages like Python, Java, or Scala. You also need to know databases and data processing frameworks.

3. Tools: Experience with cloud platforms (AWS, Google Cloud) and managing data pipelines (such as Apache Kafka or Hadoop) is important for designing efficient data systems.

4. The ability to solve problems and design systems that store and process large amounts of data efficiently.

Career Tips: Getting a Job as a Data Science VS Data Engineering

Here are some tips that can help you get jobs in data science vs data engineering.

Learn the Basics

Start by learning the basics of programming, databases, and math. These are the foundation for both data engineer vs data scientist. Once you understand these, you'll be able to learn more advanced topics easily.

Online Courses

There are many free online courses that teach skills like Python, SQL, and machine learning. Take advantage of these courses to learn at your own pace and build your knowledge step by step.

Hands-On Practice

Theory is important, but nothing beats practical experience. Work on small projects, such as analyzing datasets or building basic machine learning models. Use platforms like Kaggle to practice with real-world datasets.

Internships

Look for internships or part-time jobs related to data. Even a small role can help you gain experience and make your resume stronger in the data engineer vs data scientist vs data analyst field. You’ll also learn a lot by working in a real-world environment.

Stay Updated

The tech world moves quickly, so it’s important to keep learning new tools and techniques related to data engineer vs data analyst. Stay up-to-date to stay competitive in your field.

Networking

Connect with others in the field. Join online communities, attend meetups, or follow experts on social media. Networking can help you learn from others and lead to job opportunities in the data engineer vs data scientist field.

How to Enhance Your Job Application

To enhance your job application in data science vs data engineering, follow these simple tips.

Tailor Your Resume: Customize your resume to match the job you're applying for. Highlight your skills and experience that are most relevant to the role.

Write a Strong Cover Letter: Write a short, personalized cover letter and mention why you want the job and why you’re a great fit.

Showcase Your Achievements: Focus on your accomplishments, not just your responsibilities. Use numbers to show your impact if possible.

Keep it short and simple: Avoid big words or complicated sentences. Make everything easy to read and straightforward.

Proofread: Always look for errors. You may look careless to interviewers if one simple mistake occurs.

Be honest: Never exaggerate and write what you can not explain. Employers value honesty most of all.

Comparison Of Salary: Data Engineer VS Data Scientist

Both Data Engineers and Data Scientists have high-paying jobs, but data scientist vs data engineer salaries can vary a bit. In India, the average data science engineer salary is between ₹9,00,000 and ₹22,00,000, depending on their skills like machine learning and analytics, which are in high demand. If you're a senior Data Scientist, you could earn ₹25,00,000 or even more. Additionally, if you're considering a career as a data analyst, the data analyst job salary typically ranges between ₹4,00,000 and ₹8,00,000, depending on experience and expertise.

On the other hand, a Data Engineer's salary is usually between ₹7,00,000 and ₹15,00,000, depending on the type of work and experience. If you have knowledge of cloud computing and big data tools, your salary can be higher. Also, these are the estimates, it also depends on the company you are working with and the knowledge you have gained.

Career Growth and Pathways

The career growth you can expect as a Data engineer vs Data analyst or scientist.

Career Pathway for Data Engineers.

Starting Out: You might begin as a junior data engineer or a data analyst. This helps you understand how to handle data and learn the tools.

Mid-Level: After gaining some experience, you can become a senior data engineer. At this stage, you’ll take on bigger projects and maybe even manage teams.

Top-Level: With more experience, you could become a lead data engineer or even a chief data officer. These roles involve more decision-making and overseeing larger data systems for the company.

Career Pathway for Data Scientists.

Starting Out: Most people start as junior data scientists or data analysts. This is where you learn how to work with data and do basic analysis.

Mid-Level: As you gain experience, you can become a senior data scientist. You’ll work on bigger problems, analyze more complex data, and might even guide junior team members.

Top-Level: At this level, you can become a lead data scientist or a machine learning engineer. These positions involve using advanced techniques to solve difficult problems and sometimes creating new tools for analysis.

Conclusion

If you're looking to master Python, Analytics Shiksha is the perfect choice. Their Super30 Analytics course, part of their data analytics courses online, offers comprehensive training in data analysis and job preparation. Don’t miss out—secure your spot today, as only 30 seats are available!

The opportunities in both fields are immense, and with the right skills, you can make your mark in the data world.

Be sure to enroll and reserve your spot in our Super30 data analytics course to advance your skills. This program is built around problem-solving techniques and allows you to work with real data.

Frequently Asked Questions: Data Engineer vs. Data Scientist

Can Data Scientists Transition with Data Analytics Courses to Become Data Engineers?

Yes, by increasing knowledge of coding, databases, and system design through data analytics courses, a data scientist can easily become a data engineer.

Which is Better: Data Scientist Data Engineer vs Data Scientist?

It depends on what you enjoy doing to solve problems and make predictions or to build the infrastructure and tools to store and process data. If you love analyzing data and creating models, a data scientist role might be better. If you prefer working on technology and systems, a data engineer job could be the right fit for you.

What is The Difference Between Data Engineer and Data Scientist

A data engineer works on systems that collect, store, and process data. They make sure the data is clean and ready for analysis. A data scientist analyzes the data, creates models, and discovers insights to help businesses solve problems. In a nutshell, engineers prepare the data, while scientists analyze it. To excel in either role, enrolling in data analytics courses can help you build the necessary skills and expertise.

#data analytics courses #data analytics courses in Delhi #data analytics courses online #data analyst job salary #data science vs data engineering

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byitc · 8 months ago

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Career Opportunities in Coding: How Coding Classes Benefit Future Career Prospects for Kids

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Here are some of the benefits of joining Coding Classes at a young age:

Exploring Career Opportunities through Coding Classes:

Mobile app developer: Coding class graduates can venture into mobile app development, creating and maintaining mobile apps for smartphones and tablets using languages like Java, Kotlin, and Swift. As they step into the role of a mobile app developer, they can anticipate a starting salary ranging from £30,000 to £50,000 — a testament to the demand for skilled app developers in the market.

Conclusion

Originally Published at: https://www.byitc.org/career-opportunities-in-coding-how-coding-classes-benefit-future-career-prospects-for-kids/

#coding course #coding #coding for kids #Coding classes #Youtube

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aryacollegeofengineering · 1 year ago

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What is the most recent technology in the software industry?

Best Btech College in Jaipur, Rajasthan states that today's technology is advancing at a FAST RACE, allowing for speedier development and advancement and so accelerating the rate of change.

Some Trending Technology 2023.

1. Computing Power

As we all know data science experts have predicted that the computing infrastructure we will build and evolve for the better in the coming years. Also, we will be soon of 6G with more power in our hands and devices surrounding us, also (RPA) Robotic Process Automation is computing and automation software that can train. Top jobs:-

Data Scientist

AI Engineer

Robotics Researcher

AI Architect

Robotics Designer

2. Smarter Devices

It is not just simulating humans but going the extra mile to make our life hassle-free and simpler and these smarter devices are here to stay in 2023. Some jobs:-

IT Manager

Data Scientists

Product Testers

Product Managers

Automation Engineers

IT Researchers

3. Datafication

Datafication is simply transforming everything in our life into devices or software powered by data, From our smartphones to industrial machines. Some jobs:-

Big Data Engineers

Robotics Engineers

IT Architect

Business Intelligence Analyst

Data Scientists

4. Artificial Intelligence (AI) and Machine Learning

AI is part of our daily life for all normal work we need AI.

Machine Learning is the subset of AI, deployed in all kinds of industries, creating a huge demand for skilled professionals. Predictors said that

Some Jobs:-

AI Research Scientist

AI Engineer

Machine Learning Engineer

AI Architect

5. Extended Reality

This is between Virtual Reality, Augmented Reality to Mixed Reality. best jobs are here:-

Extended Reality Architect

Front Lead Engineer

Software Developer

AR/VR Support Engineers

Game Designers

Pro Gamers

Creative Directors

6. Digital Trust

Top Engineering Colleges in Jaipur Rajasthan have technology like these also with people being accommodated and tangled with devices and technologies, confidence and trust have been built towards digital technologies also people believe. Jobs:-

Cybersecurity Analyst

Penetration Tester

Security Engineer

Security Architect

Security Automation Engineer

Network Security Analyst

7. 3D Printing

It is impactful in the biomedical and industrial sectors. For companies in the data and healthcare sector that require a lot of 3D printing for their products, Some jobs are there:-

CX Program Manager

3D Printer Engineer

Emulation Prototyping Engineer

Robotics Trainer

AI Engineer

Operations Manager

Organ & Prosthetic Designer

8. Genomics

It helps you fight diseases and whatnot. Some jobs:-

Bioinformatics Analyst

Genome Research Analyst

Full Stack Developer

Software Engineer

Bioinformatician

Genetics Engineer

9. New Energy Solutions

Everything is energy like cars running on batteries and houses using solar or renewable energy.

Some Jobs:-

Energy Specialist (Solar, Thermal, Hydro-power, etc.)

Solar Plant Design Energy

Climate Strategy Specialist

Project Manager

Chemical Energy

Biotechnology Specialist

Renewable Energy Technologist

10. Robotic Process Automation (RPA)

It includes Processing Applications, Transactions, working on email, etc. Some Jobs:-

RPA Developer

RPA Analyst

RPA Architect

11. Edge Computing

With this new technology trend to watch, cloud computing has become mainstream, with major players AWS (Amazon Web Services), Microsoft Azure, and Google Cloud Platform dominating the market. You can grab amazing jobs like:

Cloud Reliability Engineer

Cloud Infrastructure Engineer

Cloud Architect and Security Architect

DevOps Cloud Engineer

12. Quantum Computing

Which is a form of computing that takes advantage of quantum phenomena like superposition and quantum entanglement as well as this amazing technology trend.

13. Virtual Reality and Augmented Reality

This (VR), (AR), and (ER). VR immerses the user in an environment while AR enhances their environment also it has been used for training, as with VirtualShip, a simulation software used to train Navy, Army, and Coast Guard ship, captains.

14. Blockchain

Blockchain can be described as data you can only add to, not take away from, or change, the term “chain” because you’re making a chain of data. Some jobs:-

Here are some variety of fields and industries:

Risk Analyst

Tech Architect

Crypto Community Manager

Front End Engineer

15. Internet of Things (IoT)

There are so many things that are now being built with WiFi connectivity, meaning they can be connected to the Internet.

16. 5G

The technology trend that follows the IoT is 5G. Where 3G and 4G technologies have enabled us to browse the internet, increased bandwidths for streaming on Spotify or YouTube and so much more.

17. CyberSecurity

It is a need nowadays, It is been used in every sector or industry, and it is in market demand. Some jobs:-

Ethical Hacker

Malware Analyst

Security Engineer

Chief Security Officer

Conclusion

Private Colleges of engineering in Jaipur Rajasthan teaches about these technologies also they are emerging and evolving all around us, these 9 technology trends offer promising career potential now and for the foreseeable future, and most of these trending technologies are welcoming skilled professionals, meaning the time is right for you to choose one.

Source: Click Here

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amritasaicollege · 2 years ago

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Navigating the Digital Age: Pursuing Computer Science and Engineering at Amrita Sai Institute of Science and Technology

In today's fast-paced world, technology reigns supreme, and the demand for skilled professionals in Computer Science and Engineering (CSE) continues to surge. Amrita Sai Institute of Science and Technology (ASIST) emerges as a leading light in preparing students for success in this exciting field.

Unveiling the ASIST Advantage:

At ASIST, the CSE program stands out for its commitment to excellence. Students delve into a dynamic curriculum that covers everything from coding and algorithms to software development and network engineering. The program is designed not just to impart knowledge but also to foster creativity and innovation.

Learning Beyond the Classroom:

What sets ASIST apart is its dedication to hands-on learning. Students are encouraged to participate in hackathons, coding competitions, and collaborative projects, allowing them to apply their knowledge in real-world scenarios. The faculty, composed of industry experts, is always at hand to guide and mentor students.

Innovation and Ethics:

ASIST places a strong emphasis on ethical tech practices. As technology continues to reshape our world, responsible and ethical use of it becomes paramount. Graduates from ASIST are not just technically proficient; they are also socially responsible tech leaders.

Career Pathways:

The career prospects for CSE graduates from ASIST are limitless. Whether you dream of being a software developer, data scientist, cybersecurity specialist, or tech entrepreneur, ASIST equips you with the skills and knowledge to excel. The program's forward-looking approach ensures you're prepared for the ever-evolving tech landscape.

Join the ASIST Community:

Choosing ASIST for your CSE journey means becoming part of a vibrant and innovative community. It's a place where technology meets ethics, and where your passion for computer science can truly thrive.

In a world increasingly driven by technology, ASIST ensures you're not just keeping pace but leading the way. So, if you're ready to embark on a journey of innovation, creativity, and ethical tech leadership, ASIST's CSE program is the perfect launchpad.

Feel free to reach out if you have any questions or need more information. Your future in CSE awaits!

#autonomous engineering college #best engineering college #engineering college #computer science and engineering

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nasa · 6 years ago

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Remember the Women Who Made #Apollo50th Possible

As the world celebrates the 50th anniversary of the historic Moon landing, we remember some of the women whose hard work and ingenuity made it possible. The women featured here represent just a small fraction of the enormous contributions made by women during the Apollo era.

Margaret Hamilton, Computer Programmer

Margaret Hamilton led the team that developed the building blocks of software engineering — a term that she coined herself. Her systems approach to the Apollo software development and insistence on rigorous testing was critical to the success of Apollo. In fact, the Apollo guidance software was so robust that no software bugs were found on any crewed Apollo missions, and it was adapted for use in Skylab, the Space Shuttle and the first digital fly-by-wire systems in aircraft.

In this photo, Hamilton stands next to a stack of Apollo Guidance Computer source code. As she noted, “There was no second chance. We all knew that.”

Katherine Johnson, Aerospace Technologist

As a very young girl, Katherine Johnson loved to count things. She counted everything, from the number of steps she took to get to the road to the number of forks and plates she washed when doing the dishes.

As an adult, Johnson became a “human computer” for the National Advisory Committee for Aeronautics, which in 1958, became NASA. Her calculations were crucial to syncing Apollo’s Lunar Lander with the Moon-orbiting Command and Service Module. “I went to work every day for 33 years happy. Never did I get up and say I don't want to go to work."

Judy Sullivan, Biomedical Engineer

This fabulous flip belongs to biomedical engineer Judy Sullivan, who monitored the vital signs of the Apollo 11 astronauts throughout their spaceflight training via small sensors attached to their bodies. On July 16, 1969, she was the only woman in the suit lab as the team helped Neil Armstrong suit up for launch.

Sullivan appeared on the game show “To Tell the Truth,” in which a celebrity panel had to guess which of the female contestants was a biomedical engineer. Her choice to wear a short, ruffled skirt stumped everyone and won her a $500 prize. In this photo, Sullivan monitors a console during a training exercise for the first lunar landing mission.

Billie Robertson, Mathematician

Billie Robertson, pictured here in 1972 running a real-time go-no-go simulation for the Apollo 17 mission, originally intended to become a math teacher. Instead, she worked with the Army Ballistic Missile Agency, which later became rolled into NASA. She created the manual for running computer models that were used to simulate launches for the Apollo, Skylab and Apollo Soyuz Test Project programs.

Robertson regularly visited local schools over the course of her career, empowering young women to pursue careers in STEM and aerospace.

Mary Jackson, Aeronautical Engineer

In 1958, Mary Jackson became NASA’s first African-American female engineer. Her engineering specialty was the extremely complex field of boundary layer effects on aerospace vehicles at supersonic speeds.

In the 1970s, Jackson helped the students at Hampton’s King Street Community center build their own wind tunnel and use it to conduct experiments. “We have to do something like this to get them interested in science," she said for the local newspaper. "Sometimes they are not aware of the number of black scientists, and don't even know of the career opportunities until it is too late."

Ethel Heinecke Bauer, Aerospace Engineer

After watching the launch of Sputnik in October 1957, Ethel Heinecke Bauer changed her major to mathematics. Over her 32 years at NASA, she worked at two different centers in mathematics, aerospace engineering, development and more.

Bauer planned the lunar trajectories for the Apollo program including the ‘free return’ trajectory which allowed for a safe return in the event of a systems failure — a trajectory used on Apollo 13, as well as the first three Apollo flights to the Moon. In the above photo, Bauer works on trajectories with the help of an orbital model.

Follow Women@NASA for more stories like this one, and make sure to follow us on Tumblr for your regular dose of space: http://nasa.tumblr.com.

#apollo 11 #apollo50th #women in STEM #history #nasa #space #women of NASA #Moon #Moon landing #lunar landing #STEM #mathematics #aerospace #apollo

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tim-mcnamara · 3 years ago

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1x Programming

It’s actually okay to be a 1x programmer. Or even a 0.7x programmer.

Programming is a tool, little more

It’s absolutely fine to treat programming like a tool, rather than something that has value in and of itself. If you’re worried about not being good enough, I assure that skill will come over time. If you’re making progress, extending yourself and somehow avoiding burnout - then you’re doing well.

What do I mean, “like a tool”? Well, programming is a tool in the sense that most programming is done to achieve something other than programming.

Spending three hours in front of a screen might enable you to start a business, to pursue some creative outlet or perhaps to fix some problem in the world. But, under this mindset, programming has no a value in itself.

If there was a better tool than programming to achieve your aims, you would be perfectly entitled to learn that instead. A formal way to describe this would be to say that programming’s value is purely instrumental, or its value is derived from the other things that you produce with it.

That’s not to say that you’re not entitled to refine your skills and improve your productivity. However, I want you to know that you’re not a lesser person because you’re not able to produce 10x of something that’s almost immeasurable, like software. It turns out that some programmers are at least 10x more productive than others, however no one is born as a better programmer.

Here are some principles that I think hold merit. I haven’t ranked them in any particular order. I hope that you feel like they’re slightly provocative. I don’t want this list to seem like it is in any sense canonical. I’m learning too. So feel free to pick and choose!

Principles of the 1x programmer

Software is a team sport

Even if you’re coding for yourself, you’re still coding for a team. Your future self will not have the same cognitive context that you do currently. Therefore, you should always code in a way that respects the people who are following you.

One of the best introductions to this type of socially minded programming is called Building Software Together (freely licensed under CC-BY-NC 4.0) by Greg Wilson and contributors.

Our aim is to teach you how to be a compassionate programmer: one who cares as much about the well-being of their colleagues and users as they do about their own. This focus is not entirely altruistic—everything you do to help others also helps your future self—but now that we all know how much harm software can do, we hope you’ll be interested in some practical idealism.

Learn through mimicry

Find the best software written in your programming language of choice. Usually, the language’s standard library is a good place to start. Look for patterns. Try to consider how you would implement things.

Small children learn by copying others. Why shouldn’t adults?

Being a computer scientist is less useful than you might think

Synthesis is essence of software engineering, whereas abstraction is the essence of computer science. Your job as a software developer will be to synthesise something new from composable pieces. What you create should be simple to understand and extend.

You are unlikely to implement sophisticated data structures and algorithms.

I don’t agree with everything that pg writes, but this struck out.

99.5% of programming consists of gluing together calls to library functions.

The time to fix things is now

Your team isn’t going to have fewer priorities next week or next month. There will not be an opportunity to do the wholesale rewrite that the code base deserves. The only way to improve a code base is incrementally.

I learned this through John Ousterhout’s book, A Philosophy of Software Design. The overall suggestion that I took away from the book is that if your team is struggling with a spaghetti code base, its members should be investing about 10-20% of their total development time cleaning it up.

You’re paid to build

If you think that you’re employed to write software, then you’ve not thought hard enough.

You’re employed to make money – or save money – for someone. And the way to do that is probably through programming.

The phrase is terrible, but it’s worth repeating anyway. Make sure that you “add value”.

This matters because sometimes – perhaps often – working on the boring thing that no one wants to work on is really the thing that you should be doing.

Simplicity really helps

We all want to write simple software, as hard as that is. Ideally, your code should be simple enough so that a junior programmer who doesn’t like you can understand it.

Ironically, simple code probably has a shorter lifespan than complex code. Complex and difficult code remains fixed because people are afraid to change it. Complex code is very hard to test. And without regression tests, we don’t know if we’ve broken behaviour. So it becomes brittle.

API beats algorithm

Syntax matters. One of the lessons from the success of Kenneth Reith’s requests package — which completely took over from the standard library’s own implementation of making web requests — is that the (public) API is more important than every millisecond that you save from implementing the perfect algorithm. Users care about convenience. Convenient code is easy to write, easy to read and easy to maintain. However, it’s also important to understand what comprises your “Porcelain API” and your “Plumbing API”.

Other people make mistakes

The majority of us are better drivers than average. I’m sure the same is true for programming. Brains are imperfect.

It’s impossible for you to assess your own skill level.

If you want adoption, software is just the start

If you care about adoption, there’s lots of work to do once the code has been written. That is, unless you’re Fabrice Bellard, I guess.

This, to me, is the ultimate reason why being a 1x programmer (even in a professional setting) can be sufficient. You might be able to contribute to other areas that someone who is focused purely on the code is not able (or, more commonly, unwilling) to do. 10x programmers care about the code. Everything else is secondary.

Users care about themselves. To them, they need to be the primary priority. This rift causes a problem when open source maintainers decide that their users are indeed secondary. But that might be the theme of a future post.

Please improve this list

What have you learned in the course of your learning journey? Please let me know. I have plenty to learn.

Thanks to Nimo Naamani for helping me fix some typos and grammar issues.

#programming #startups

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evitcani-writes · 4 years ago

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Is Reality a Simulation?

Okay, so I want to preface this post with: I am a computer scientist. I’m not a physicist. I want to talk about how and why the theory of reality being a simulation is ridiculous.

Main points you can read in the jump below (this will be long):

The people who argue reality is a simulation aren’t computer scientists (we have proof that reality isn’t a simulation... yes, really)

We are reaching a plateau in digital technological advancement

The technology needed to simulate the universe would require more matter than the universe holds

You are reading this post which is eliciting thoughts and feelings

Finally, I talk about the proof we have reality isn’t a simulation

Below the cut, I’ll go into detail.

The people who argue reality is a simulation aren’t computer scientists

I strongly believe that outsiders to a field can bring new insight. In this case, I think it comes from a lack of understanding of how computers “think” (your computer is “thinking” right now).

And yes, I’m choosing to focus on the philosophical explanation rather than the proofs reality isn’t a simulation because you won’t internalize the math required. But you will be able to see logical steps in reasoning with some light explanation. So, moving on...

When computer scientists and software engineers talk about computers “thinking”, we mean very specific things. Your computer has to prioritize tasks in a way that makes it feel seamless to you, the user. It’s making decisions. It’s thinking.

When other people talk about how computers “think”, they mean something more like how we think. Where decisions are a product of environment, past experience, personality and intention.

The problem we have with true AI is that we humans always give computers an intention and focus. When you are telling someone to do something they can’t refuse, it’s not free will when they do it.

We’ve reached a plateau in digital advancement

Have you noticed the trend of phones getting larger instead of smaller? This is because we’ve reached the limits of the law that says technology will get faster and smaller every year. That law is called Moore’s Law. What people fail to realize is Moore’s Law is not a straight line. It’s a logarithmic curve that eventually plateaus and ceases to get larger.

We fell below the pace predicted by Moore’s law in 2010. We slowed even further in 2015.

That makes sense though, right? I mean... At some point you get down to electrons and the things that make up electrons and then how are you supposed to get smaller? I mean, we are experimenting with using the density of electrons to designate 0 and 1 binary in computers.

This is what Gordon Moore (the “Moore” in “Moore’s Law”) said in 2005:

In terms of size [of transistors] you can see that we're approaching the size of atoms which is a fundamental barrier, but it'll be two or three generations before we get that far—but that's as far out as we've ever been able to see. We have another 10 to 20 years before we reach a fundamental limit. By then they'll be able to make bigger chips and have transistor budgets in the billions.

Just as he predicted, in 2015 transistors slowed to a crawl. The amount of technology we can pack into your phone is probably as good as it gets until we ditch computers altogether.

The technology needed to simulate the universe would require more matter than the universe holds

I’m not really gonna explain this one. I kind of did it above.

This section is just for the nerds. This will not make sense to people who aren’t nerds. You can skip it.

Perfect time to say that quantum computing will be a thing in the future probably. But even that would likely have to be simulated because the only way to get real quantum computer is to have the computers be kept at near 0 Kelvin which reaching 0 Kelvin is considered at this time to be impossible. So we can’t even perfectly do that until we do the impossible.

And if we’re simulating quantum bits by rapidly gating between 0 and 1, we still run into the issue of computers being fundamentally deterministic (i.e. unable to achieve True Random).

I’m not even sure we’ll be able to conceptualize quantum computers as “computers”. Their use would obliterate our entire digital infrastructure and a user’s understanding of how to interface with one. We might be able to do simulations with it, but we’ve found that quantum computers are actually pretty bad at doing things that our binary computers do pretty well. Like harnessing randomness from mother nature, we’d likely end up with a hybrid system where deterministic results are created by truly random quantum computers to be fed into a deterministic interface.

You are reading this post which is eliciting thoughts and feelings

Buried the lead on this one. This is what I really wanted to talk about. You are having thoughts about this post. Feelings.

Computers don’t do that. They won’t do that.

Fun fact about when you let AI talk to another AI: They completely transcend human understanding. Just like you come up with shorthand references like “yeet” that confuse boomers. AI will ultimately begin to develop language like that Dueling Carls video.

youtube

(Please god turn down your video before watching)

It’s almost hilarious how well this video demonstrates exactly what computers do. They start at the level of human understanding and then faster than you can blink, they ascend beyond what we could ever hope to conceptualize. The things about Facebook’s chatbots aren’t true of course, but they held a seed of truth.

AI will exist on another level.

This is because computers (like humans) are greedy. They use the fewest possible resources to reach the same goal. If you programmed a computer to simulate the universe, then it would try to take shortcuts where it could.

The fact that some people can think visually (seeing “pictures” in their mind) and others can’t really demonstrates that humans aren’t simulated. Or even further, did you know that humans really do have a 6th sense? It’s your ability to know where your body is when you can’t see it. Called propioception.

We know it exists because people can be born without it. When they close their eyes they physically can no longer use their limbs. It’s genetic.

Why would a computer account for these things? It’s made it harder to simulate a gene for propioception. Well, maybe the humans who programmed it, told it to account for that.

Then why are you having thoughts about this post? Why read it at all? It’s going to get what... 5 notes? Why account for you at all. It can have you do things without that “inner voice” that’s reading these words. It doesn’t have to give you intention behind your actions. So then humans made it give you intention.

Humans telling a computer to create humanity. And having to account for every single little thing. Telling it not to ignore the nuances of all human existence.

Why would we do that unless we wanted to simulate our entire human history?

How would we simulate all of our history if we didn’t know everything that everyone ever thought or felt?

If you are a simulation, then you are memory of someone who is real.

Finally, I talk about the proof we have reality isn’t a simulation

If you skipped to here, you’re going to be really disappointed. The math is complicated. You can read it here.

Here’s a summary of their findings.

In summary, we suggested that nontrivial gravitational/geometrical responses can be identified with obstructions to sign-free local QMC simulations. First, we pointed out that geometrical perturbations are unique in this context because they can always be added to a classical partition function without introducing complex phases or signs. Then, we established that having a global gravitational anomaly on an edge of a gapped system, as is the case for most fractional quantum Hall phases, implies a sign problem. The same argument extends to frustrated quantum magnets that support a chiral spin liquid phase, although here, some additional microscopic assumptions are currently required. Last, we pointed out that sign problems in critical 2D oriented loop models are also associated with a coupling of charge to curvature. Curiously, tensor network–based numerical approaches, for which the sign problem is irrelevant by construction, also struggle with simulating FQHE states (in the thermodynamic limit). This raises an intriguing connection between gravity and computational complexity via sign problems.

The point is that storing a single matrix of 20 spins of a quantum particle requires a terabyte of data. We’d run out of universe before we made even a small simulation.

#gif #gif warning #computer #technology #reality is a simulation

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system76 · 5 years ago

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Open Up: Open Source Hardware — A Chat with Carl

System76 is now a couple years into manufacturing open source hardware, with our efforts expanding in the form of an open source keyboard. In this week’s blog post, we sat down with System76 CEO Carl Richell to discuss the company’s journey into open source hardware and where its future may lead.

What is open source hardware?

Carl: From a broader lens, to produce “open source hardware” means that we have developed and shared the recipe to create a high-end commercial product that can be learned from, adapted, and used by anyone else. In the same way we’ve stood on the shoulders of the Linux and open source software giants who came before us, we now get to be pioneers in developing open source hardware for those who come next. If you want to learn more how a computer is designed or how something is made, our schematics are the instructions for how to do it. It describes every step of the process, from each piece of the machine and its dimensions, to the type of aluminum used and how to bend it.

It’s similar to open source software in that you can learn from the product, adapt it to your needs, and distribute it. The difference is that it requires outside equipment to produce your own version. Open hardware has become more accessible with 3-D printing, but as we found when we were making acrylic prototypes of Thelio, you reach a point where it’s time to work with metal, which presents its own challenges. You have to cut it, bend it, and paint it, all of which requires specific equipment.

We’ve also laid the ground work for the supply chain, in that anyone can use the same vendors for the fans or the same specs for how long the cables are. All those small yet extremely important pieces are open source.

How does open hardware fall into the System76 philosophy?

The phrase “intellectual property” gets thrown around a lot. It is my opinion, and the opinion that we express in this company, that intellectual property is a false idea. That nothing was just born out of nothing in your mind and just becomes your property. All these things you came up with, someone else was part of the building blocks for you to get there in the first place. And so you can’t own it. You can’t have it. It’s not yours. Like that hinge you’re making, well you’ve had some good ideas, you’ve tinkered with it for a while, you’ve figured out a cool hinge. But I guarantee you’ve looked at every other hinge out there and learned a lot from that research, just as we’ve done with everything we’ve ever built.

The world is full of smart, incredible people, and these ideas are mostly locked up in institutions and companies through the desire to maintain power and control over them. This is a broader idea we don’t believe in. Instead, we believe that ideas are free; that there is no such thing as “intellectual property”.

Why does System76 use copyrights for its hardware?

The reason we use copyright is because reputation matters. Our reputation is our name, it’s who we are, it’s how people perceive our value and the value that we put into something as individuals and as a company. You can’t just slap System76 on everything and say it’s a System76, because we have a reputation that we maintain through the product we deliver. But everything about that product is owned by the user just as much as it’s owned by us. Those beliefs and ideas that exist within open source software are no different than with open source hardware.

Speaking of open source, if there’s anything that should be open source, it’s a vaccine for COVID-19. There’s no lack of supply or resources to produce a vaccine, yet people are hiding secrets from each other to win a race for money. It’s absurd! We’re the ones paying for it. It should be a completely open source effort. I have quite a bit of confidence that the scientists and others working on a vaccine are in it because they really care about the science and getting results. That’s a striking example of where open source would make a lot of sense.

What would you say to someone who is interested in building machines, but is worried that making them open hardware would negatively impact their business?

There’s a risk if you build anything that is a commodity. When your product is a commodity, it doesn’t take a significant amount of effort to make it unique in the marketplace. It’ll just be copied by someone who can make it cheaper, with cheaper labor. With open hardware, what you want is for your product to be innovative and constantly progressing so that you’ll always be the best deliverer of that product. I think we’ll always be the best deliverer of the Thelio desktop product line—even if we’re not, I’m okay with it. The purpose of he GPL license is to lift all boats. If someone else comes along and does something innovative with our designs, the tide has risen.

We built Thelio Io, which is an open source hardware PCB (printed circuit board). It’s a commodity, but it’s one component of the entire system. You could take this to a manufacturer and have them make it, and then you have a 4-slot backplane that you can use in your design. That means you have the recipe for an open source backplane, controller, firmware, and software thermal system. Now Thelio Io is available on another company’s system because they can use our work? That’s fantastic! If they adopt the same philosophy, something they do in the future would be available for us to use as well.

What it really boils down to is, it doesn’t matter if your product is proprietary or open source; if people like it and it gets highly adopted, it will just be made by someone else. By making it open source, maybe their path is a little faster, but with reverse engineering and how quick product development is these days, it doesn’t seem to matter. You have to disarm at some point, you know? And somebody has to take the lead disarming. We have nukes and they have nukes, so nobody gets rid of their nukes, because that’s our leverage. We’re saying we don’t want this leverage anymore. We want to lead by example. We’re going to disarm and give away the instructions for how to make what we make.

Want to learn more about our open source efforts? Check out the software and firmware installments of our Open Up series.

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superlinguo · 6 years ago

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Linguistics Jobs: Interview with a Software Engineer

Like today’s interviewee, Brooke Lynne Weaver, I worked through my undergrad degree. While not everybody is lucky enough to be able to do both study and work, it can be a useful way to develop skills beyond those in the classroom. I now use my coffee making skills only for self-caffeination, but cafe life taught me a lot about task prioritising and staying upbeat under pressure. Brooke used her work experience to move into Software Engineering, and uses her linguistics in her approach to her work, and her everyday life. Brooke is also on Twitter (@Milayou).

What did you study at university?

My degree is in English Language (Linguistics with an emphasis on the English language) from Brigham Young University in Utah, U.S.A. Basically, when we covered morphology, syntax, phonetics, phonology, sociolinguistics etc. it mostly focused on those applications in English, with some examples and work from other world languages. I also took a couple computer science classes and worked as a web developer while in school.

What is your job?

I'm a software engineer. Right now my job title is Platform Engineer, and at my last job it was Platform Architecture Engineer. I write code based on the needs of my company, which generally involves understanding the task you need the computer to perform autonomously, and doing a bunch of Googling to remind yourself (or learn) how to tell it to do that. You run the code, look for certain things to happen, tweak the code, run it again, look for different results, tweak it again, run it again etc. The ask from the company is generally as specific as humans tend to be, which is not nearly as specific as machines tend to be; you have to be on the lookout for instructions that should be given that were never expressly asked for by the company in order for everything to run smoothly. Our stack is mostly written in Python 2.7 but we're moving to Go, and the project I just finished up has parts written in both. It's really satisfying when you've finally communicated your message properly to the machine and it behaves accordingly.

I work for Vivint.SmartHome right now, doing home automation. I help the Vivint centralized system interact with peoples' homes and phones all over North America. When someone pulls up their Vivint app on their phone, it requests data from our platform. When they want to make changes to their smart home system, it interacts with our platform. Recently I've been helping migrate our Nest integration from using the (now deprecated) Works With Nest API to the new Google Home/Assistant API (a transition Google recently made public).

How does your linguistics training help you in your job?

I like to tell myself I went into translation, just between human and machine languages rather than from one human language to another. The things I learned studying linguistics help me in less obvious ways.

Knowing how flexible semantics is and how language changes so much across time and space, I feel like I'm a much better communicator than I was when I first started college. I'm a lot more flexible in interpretations and I care a lot more about getting to the root of what a person is trying to communicate, rather than what words they chose and what those words mean to me specifically. Communication is a pretty important part of writing software, because you're almost always trying to realize the ideas of other people. Knowing how to be confident you're on the same page as the people requesting your work is critical.

Linguistics also gave me a much better understanding for how important context is. I leave comments everywhere it makes sense to in order to help future engineers understand why I did certain things, which puts them in a better position to understand what to change down the line. It's very common to come across some code written a few years back that seems to make no sense at all (or seems like a bad way to do something), and if someone left a comment explaining why they wrote it that way at that time, you can better decide whether to leave it or in what ways to change it. The comment might say "Here's the current state of affairs and we need to do this weird thing to avoid this problem" and now, several years later, that problem is irrelevant or the current state of affairs has drastically changed; you might not need to do that thing in such a weird way anymore. You can then feel more confident about making your change. Or, maybe the state of affairs has not changed or the problem still exists and still needs to be avoided; you now have really important context and that weird thing might actually look logical now, or you know how to change it while still avoiding the problem it was originally trying to avoid. As an example, earlier this year I implemented a library I wasn't very familiar with in a pretty short amount of time. I left a comment explaining that if someone else was more comfortable with the library, they should feel free to rewrite it in a more idiomatic way; I explained what parts of it I wrote somewhat poorly due to lack of time and familiarity (something like "I know you should be able to do it like A, but I couldn't figure out how to get A to work so I did B instead which isn't as good but gives an acceptable result. It's not deliberately done this way for any other reason, so if you know how to do A, please change it."). A lot of times we try to change legacy code as little as possible, for fear of unknown downstream affects, because we weren't there when it was written and don't know why it was done the way it was; I hope by leaving context comments I can help future engineers feel more comfortable keeping the codebase clean and efficient.

Do you have any advice you wish someone had given to you about linguistics/careers/university?

I have some advice I was given that I think is valuable. I had a really hard time choosing a major field of study because I was interested in almost everything. A counselor reminded me that you can still have any hobby you like, regardless of what you study at university. I was afraid that by choosing something I was cutting myself off from other things, but that's not actually true. I still love playing the piano even though I didn't go into music, and I still love math even though I didn't go into mathematics.

Also, my university offered a lot of student jobs. These were jobs that were only allowed to be worked by students, which meant the barrier to entry was fairly low. I don't know if other universities offer student on-campus jobs, but if they do, I very much recommend them. I worked student jobs the entire time I was at school, which meant I graduated with seven years of work experience. Yes, it took me seven years to get my bachelor degree, but that work experience meant I had no trouble getting jobs after (and even before) I graduated. That said, maintaining a job while going to school is an awful lot of work and it's not the right path for everyone; everyone's situation is different, this just worked out well for me.

Any other thoughts or comments?

Besides how linguistics training helps me at work, it's made me a FAR better human. I'm a reformed pedant. I was really condescending and had a bit of a superiority complex about language when I was young. I was all about correcting and fixing people and being exasperated when people wrote or said things "wrong." Studying linguistics has given me a LOT of empathy and understanding and freed me from most of my pet peeves. My perspective on language and communication is so different now. I feel free. It's a far pleasanter experience to put your energy toward really understanding and being understood by a person than on looking down on people and discrediting their thoughts because they don't know how some dude in the 19th century wanted a part of English to work that doesn't even make sense anyway. I think a lot of unnecessary conflict comes from different groups of people having different understandings of certain words, and fighting over the definition of the word rather than over the real human issue at the heart of the debate. It would be nice if we taught language a little differently in schools, so more people could be aware of how semantic drift occurs and how different people can use the same word to mean different things, and that language change is okay and actually beautiful.

Recently:

Interview with a Product Manager

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mostlysignssomeportents · 6 years ago

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#1yrago Oh for fuck's sake, not this fucking bullshit again (cryptography edition)

America, Canada, New Zealand, the UK and Australia are in a surveillance alliance called The Five Eyes, through which they share much of their illegally harvested surveillance data.

In a recently released Statement of Principles on Access to Evidence and Encryption, the Five Eyes powers have demanded, again, that strong cryptography be abolished and replaced with defective cryptography so that they can spy on bad guys.

They defend this by saying "Privacy is not absolute."

But of course, working crypto isn't just how we stay private from governments (though god knows all five of the Five Eyes have, in very recent times, proven themselves to be catastrophically unsuited to collect, analyze and act on all of our private and most intimate conversations). It's how we make sure that no one can break into the data from our voting machines, or push lethal fake firmware updates to our pacemakers, or steal all the money from all of the banks, or steal all of the kompromat on all 22,000,000 US military and government employees and contractors who've sought security clearance.

Also, this is bullshit.

Because it won't work.

Here's the text of my go-to post about why this is so fucking stupid. I just can't be bothered anymore. Jesus fucking christ. Seriously? Are we still fucking talking about this? Seriously? Come on, SERIOUSLY?

It’s impossible to overstate how bonkers the idea of sabotaging cryptography is to people who understand information security. If you want to secure your sensitive data either at rest – on your hard drive, in the cloud, on that phone you left on the train last week and never saw again – or on the wire, when you’re sending it to your doctor or your bank or to your work colleagues, you have to use good cryptography. Use deliberately compromised cryptography, that has a back door that only the “good guys” are supposed to have the keys to, and you have effectively no security. You might as well skywrite it as encrypt it with pre-broken, sabotaged encryption.

There are two reasons why this is so. First, there is the question of whether encryption can be made secure while still maintaining a “master key” for the authorities’ use. As lawyer/computer scientist Jonathan Mayer explained, adding the complexity of master keys to our technology will “introduce unquantifiable security risks”. It’s hard enough getting the security systems that protect our homes, finances, health and privacy to be airtight – making them airtight except when the authorities don’t want them to be is impossible.

What these leaders thinks they're saying is, "We will command all the software creators we can reach to introduce back-doors into their tools for us." There are enormous problems with this: there's no back door that only lets good guys go through it. If your Whatsapp or Google Hangouts has a deliberately introduced flaw in it, then foreign spies, criminals, crooked police (like those who fed sensitive information to the tabloids who were implicated in the hacking scandal -- and like the high-level police who secretly worked for organised crime for years), and criminals will eventually discover this vulnerability. They -- and not just the security services -- will be able to use it to intercept all of our communications. That includes things like the pictures of your kids in your bath that you send to your parents to the trade secrets you send to your co-workers.

But this is just for starters. These officials don't understand technology very well, so they doesn't actually know what they're asking for.

For this proposal to work, they will need to stop Britons, Canadians, Americans, Kiwis and Australians from installing software that comes from software creators who are out of their jurisdiction. The very best in secure communications are already free/open source projects, maintained by thousands of independent programmers around the world. They are widely available, and thanks to things like cryptographic signing, it is possible to download these packages from any server in the world (not just big ones like Github) and verify, with a very high degree of confidence, that the software you've downloaded hasn't been tampered with.

Australia is not alone here. The regime they proposes is already in place in countries like Syria, Russia, and Iran (for the record, none of these countries have had much luck with it). There are two means by which authoritarian governments have attempted to restrict the use of secure technology: by network filtering and by technology mandates.

Australian governments have already shown that they believes they can order the nation's ISPs to block access to certain websites (again, for the record, this hasn't worked very well). The next step is to order Chinese-style filtering using deep packet inspection, to try and distinguish traffic and block forbidden programs. This is a formidable technical challenge. Intrinsic to core Internet protocols like IPv4/6, TCP and UDP is the potential to "tunnel" one protocol inside another. This makes the project of figuring out whether a given packet is on the white-list or the black-list transcendentally hard, especially if you want to minimise the number of "good" sessions you accidentally blackhole.

More ambitious is a mandate over which code operating systems in the 5 Eyes nations are allowed to execute. This is very hard. We do have, in Apple's Ios platform and various games consoles, a regime where a single company uses countermeasures to ensure that only software it has blessed can run on the devices it sells to us. These companies could, indeed, be compelled (by an act of Parliament) to block secure software. Even there, you'd have to contend with the fact that other states are unlikely to follow suit, and that means that anyone who bought her Iphone in Paris or Mexico could come to the 5 Eyes countries with all their secure software intact and send messages "we cannot read."

But there is the problem of more open platforms, like GNU/Linux variants, BSD and other unixes, Mac OS X, and all the non-mobile versions of Windows. All of these operating systems are already designed to allow users to execute any code they want to run. The commercial operators -- Apple and Microsoft -- might conceivably be compelled by Parliament to change their operating systems to block secure software in the future, but that doesn't do anything to stop people from using all the PCs now in existence to run code that the PM wants to ban.

More difficult is the world of free/open operating systems like GNU/Linux and BSD. These operating systems are the gold standard for servers, and widely used on desktop computers (especially by the engineers and administrators who run the nation's IT). There is no legal or technical mechanism by which code that is designed to be modified by its users can co-exist with a rule that says that code must treat its users as adversaries and seek to prevent them from running prohibited code.

This, then, is what the Five Eyes are proposing:

* All 5 Eyes citizens' communications must be easy for criminals, voyeurs and foreign spies to intercept

* Any firms within reach of a 5 Eyes government must be banned from producing secure software

* All major code repositories, such as Github and Sourceforge, must be blocked in the 5 Eyes

* Search engines must not answer queries about web-pages that carry secure software

* Virtually all academic security work in the 5 Eyes must cease -- security research must only take place in proprietary research environments where there is no onus to publish one's findings, such as industry R&D and the security services

* All packets in and out of 5 Eyes countries, and within those countries, must be subject to Chinese-style deep-packet inspection and any packets that appear to originate from secure software must be dropped

* Existing walled gardens (like Ios and games consoles) must be ordered to ban their users from installing secure software

* Anyone visiting a 5 Eyes country from abroad must have their smartphones held at the border until they leave

* Proprietary operating system vendors (Microsoft and Apple) must be ordered to redesign their operating systems as walled gardens that only allow users to run software from an app store, which will not sell or give secure software to Britons

* Free/open source operating systems -- that power the energy, banking, ecommerce, and infrastructure sectors -- must be banned outright

The Five Eyes officials will say that they doesn't want to do any of this. They'll say that they can implement weaker versions of it -- say, only blocking some "notorious" sites that carry secure software. But anything less than the programme above will have no material effect on the ability of criminals to carry on perfectly secret conversations that "we cannot read". If any commodity PC or jailbroken phone can run any of the world's most popular communications applications, then "bad guys" will just use them. Jailbreaking an OS isn't hard. Downloading an app isn't hard. Stopping people from running code they want to run is -- and what's more, it puts the every 5 Eyes nation -- individuals and industry -- in terrible jeopardy.

That’s a technical argument, and it’s a good one, but you don’t have to be a cryptographer to understand the second problem with back doors: the security services are really bad at overseeing their own behaviour.

Once these same people have a back door that gives them access to everything that encryption protects, from the digital locks on your home or office to the information needed to clean out your bank account or read all your email, there will be lots more people who’ll want to subvert the vast cohort that is authorised to use the back door, and the incentives for betraying our trust will be much more lavish than anything a tabloid reporter could afford.

If you want a preview of what a back door looks like, just look at the US Transportation Security Administration’s “master keys” for the locks on our luggage. Since 2003, the TSA has required all locked baggage travelling within, or transiting through, the USA to be equipped with Travelsentry locks, which have been designed to allow anyone with a widely held master key to open them.

What happened after Travelsentry went into effect? Stuff started going missing from bags. Lots and lots of stuff. A CNN investigation into thefts from bags checked in US airports found thousands of incidents of theft committed by TSA workers and baggage handlers. And though “aggressive investigation work” has cut back on theft at some airports, insider thieves are still operating with impunity throughout the country, even managing to smuggle stolen goods off the airfield in airports where all employees are searched on their way in and out of their work areas.

The US system is rigged to create a halo of buck-passing unaccountability. When my family picked up our bags from our Easter holiday in the US, we discovered that the TSA had smashed the locks off my nearly new, unlocked, Travelsentry-approved bag, taping it shut after confirming it had nothing dangerous in it, and leaving it “completely destroyed” in the words of the official BA damage report. British Airways has sensibly declared the damage to be not their problem, as they had nothing to do with destroying the bag. The TSA directed me to a form that generated an illiterate reply from a government subcontractor, sent from a do-not-reply email address, advising that “TSA is not liable for any damage to locks or bags that are required to be opened by force for security purposes” (the same note had an appendix warning me that I should treat this communication as confidential). I’ve yet to have any other communications from the TSA.

Making it possible for the state to open your locks in secret means that anyone who works for the state, or anyone who can bribe or coerce anyone who works for the state, can have the run of your life. Cryptographic locks don’t just protect our mundane communications: cryptography is the reason why thieves can’t impersonate your fob to your car’s keyless ignition system; it’s the reason you can bank online; and it’s the basis for all trust and security in the 21st century.

In her Dimbleby lecture, Martha Lane Fox recalled Aaron Swartz’s words: “It’s not OK not to understand the internet anymore.” That goes double for cryptography: any politician caught spouting off about back doors is unfit for office anywhere but Hogwarts, which is also the only educational institution whose computer science department believes in “golden keys” that only let the right sort of people break your encryption.

https://boingboing.net/2018/09/04/illegal-math.html

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