#Software Developer Vs Software Engineer

[ds4u]

Businesses require top-level software developers to build custom models, so they are in great demand. You must know how to program, not just a specific programming language. Still, you also need to be flexible and have good software developer skills and plenty of problem-solving skills, know how to work with databases and know what tools and frameworks are up and running today.

[alycesutherland]

Progress:

Okay so the authentication for spotify is hard for me to understand and requires user authentication, then making a token request that while expire in an hour. So i focused on what I did know how to do and what I had access to token wise. The Spotify developer home page has a temporary access token for demos. I took that token and made a function to make get request to the API and two functions for top tracks and top artists. Then made some functions to print them in my terminal. Here is what my end product looked like in the terminal.

The data for tracks is proving to just show a years worth of listening even though I specified long_term in my get request.

Here is my code:

I tried just doing track.artist but Spotify handles that as multiple artists so I had to handle them as such.

Next Steps: Tackling the user authentication and token requests and including it in this code.

(Also yes I know that is a concerning amount of My Chemical Romance tracks. I had my MCR phase strike up again with a passion last October and I am still balls deep in it.)

[deadpoetsocietyy]

[tpointtechblog]

Understanding Software Engineering: A Comprehensive Guide

Introduction to Software Engineering: In today’s digital age, software plays a crucial role in nearly every aspect of our lives, from communication and entertainment to business and healthcare. But what exactly is software engineering, and why is it essential?

In this blog post, we’ll explore the fundamentals of software engineering, its principles, processes, and its significance in building…

Understanding Software Engineering: A Comprehensive Guide" explores the fundamentals, principles, and best practices of software engineering. It covers key topics like software development life cycle (SDLC), programming methodologies, design patterns, testing, and project management.

This guide is ideal for beginners and professionals looking to enhance their understanding of modern software development processes and industry standards.

[kodehashtechnology]

Head-to-Head: PHP vs. Java - Which Language Reigns Supreme?

Head-to-Head: PHP vs. Java - Which Language Reigns Supreme? The debate between PHP and Java has long been a topic of discussion among developers, with proponents of each language advocating for its superiority in various aspects of web development, enterprise applications, and system architecture. In this head-to-head comparison, we'll delve into the strengths, weaknesses, and use cases of PHP and Java to determine which language reigns supreme in the world of software development.

Overview of PHP:

PHP, initially created as a server-side scripting language for web development, has gained widespread popularity for its simplicity, flexibility, and ease of use. Here are some key considerations regarding PHP:

Simplicity and Ease of Use:

PHP is renowned for its straightforward syntax and easy learning curve, making it accessible to beginners and experienced developers alike.

Its scripting nature allows developers to embed PHP code directly into HTML, enabling dynamic content generation and server-side processing.

Web Development Focus:

PHP is primarily designed for web development, with built-in features for processing form data, interacting with databases, and generating dynamic web pages.

It integrates seamlessly with popular web servers like Apache and Nginx and databases like MySQL, PostgreSQL, and SQLite.

Vibrant Ecosystem:

PHP boasts a vibrant ecosystem of frameworks, libraries, and tools that streamline web development tasks and accelerate project delivery.

Frameworks like Laravel, Symfony, and CodeIgniter provide robust MVC architecture, routing, ORM, and other features for building scalable and maintainable web applications.

Overview of Java:

Java, renowned for its platform independence, scalability, and robustness, is widely used for building enterprise-grade applications, backend systems, and large-scale distributed systems. Here are some key considerations regarding Java:

Write Once, Run Anywhere (WORA):

Java's WORA principle enables developers to write code once and run it on any platform that supports Java, including Windows, macOS, Linux, and various mobile devices.

This platform independence is achieved through the Java Virtual Machine (JVM), which provides a consistent runtime environment for Java applications.

Scalability and Performance:

Java offers scalability and performance advantages, making it suitable for building large-scale enterprise applications that can handle high volumes of concurrent users and transactions.

Its robust type system, memory management features, and multithreading support contribute to improved application performance and responsiveness.

Enterprise Integration:

Java's extensive ecosystem and enterprise-grade features make it well-suited for integrating with existing systems, middleware, and enterprise solutions.

Frameworks like Spring Boot, Jakarta EE (formerly Java EE), and Apache Camel provide comprehensive support for building enterprise applications, RESTful APIs, and microservices.

Head-to-Head Comparison:

Performance:

Java generally offers better performance and scalability compared to PHP, especially for large-scale enterprise applications and systems with high concurrency requirements.

PHP's performance has improved over the years, but it may still lag behind Java in terms of raw processing power and efficiency.

Developer Productivity:

PHP's simplicity and ease of use contribute to faster development cycles and rapid prototyping, making it suitable for small to medium-sized web projects.

Java's verbose syntax and boilerplate code may require more time and effort upfront but can lead to more maintainable and scalable codebases over the long term.

Ecosystem and Tooling:

PHP has a robust ecosystem of frameworks, libraries, and tools tailored for web development, with a focus on simplicity, flexibility, and ease of use.

Java's ecosystem is broader and more diverse, catering to a wide range of use cases, including web development, enterprise integration, mobile development, and big data processing.

Use Cases and Project Requirements:

The choice between PHP and Java ultimately depends on the specific requirements, scalability needs, and performance considerations of the project at hand.

PHP may be a better fit for small to medium-sized web projects, startups, and rapid prototyping, while Java shines in large-scale enterprise applications, middleware, and mission-critical systems.

Conclusion:

In conclusion, both PHP and Java have their strengths and weaknesses, making them suitable for different types of projects and development scenarios. While PHP excels in simplicity, ease of use, and rapid development, Java boasts scalability, performance, and enterprise-grade features. The choice between PHP and Java should be based on the specific requirements, project goals, and scalability needs of the application, ensuring that developers choose the language that best aligns with their project's objectives and long-term vision. Ultimately, the language that reigns supreme depends on the context of the project and the priorities of the development team.

[hexenmond]

Musk vs NASA

I found this on Mastodon, so it’s a copypaste – please go read the original post by Amata/@sunguramy@flipping.rocks (no login required)!

I've been seeing hate on NASA lately, being bought into by leftists even, and I just want to point out something very important:

Musk has hated NASA for a *long* time. There is a reason it is being attacked, and a reason public opinion is being swayed against NASA: It *keeps SpaceX in line* more than anything else.

NASA is being seen as "competition" to SpaceX, as the obstacle in his way. It has been like this for quite some time, and now, with DOGE and other things, he can do something about it.

I would like to point out a few things:

1. SPACEX IS NOT CHEAPER They boast they can "do what NASA does for 10% the cost!" Sure, it's easy when you did none of the R&D. SpaceX saved on: Landing tech: DC-X project in 1991-1996 Tank structure: Shuttle SLWT tank, 1998-2011 Merlin Engines: direct descendant of the Fastrac Engine, 1997-2001.

Those three things alone saved SpaceX over 90% of the R&D costs. It's easy to "appear" cheap when you're using off the shelf tech someone else (NASA!) developed.

2. NASA IS GREAT FOR THE ECONOMY! For every $1 spent on NASA, $8 is put into economy. Its stupid to not invest in that kind of ROI! 800%! At times, its ROI Has been 1600%!

Simply put, if you defund NASA, the economy would shrink so much you would actually have to RAISE taxes to make up for the lost revenue, and without its existence we would be 30 years behind in technology and the quality of life for everyone would be much lower. Science and research is GOOD for society, it's the fuel for all progress.

3. WHAT HAS NASA DONE FOR ME?! (Surely you just mean NASA is good for tech & science folk....)

Nope! Good for all! Ever have an MRI or CAT Scan? They wouldn't exist without the Apollo program! The software that made them possible was originally written to analyze lunar photography.

Low power digital x-Rays was planetary body research.

Heart pumps are modeled after space shuttle turbopumps.

The software that designed your car was originally written to design spacecraft!

Who do you think pioneered all the early research into alternative power like solar panels, hydrogen fuel cells, and durable batteries? NASA!

NASA developed tech and satellites is also what improves agricultural yields while reducing the needs for water, fertilizer, and pesticides.

Do you really think Musk gives two shits? No. He wants the money, he wants to let SpaceX run amok without any oversight for safety, without any "competition".

All fights are important, but do realise that this one is a huge thorn in his side, and one that is keeping a huge problem from ballooning and swallowing us all whole.

Do not be fooled or swayed by lies, of tactics meant to divide, of things being done to make you be angry at NASA. If he can make you hate NASA, he won.

Expect far more space junk to fall, the night sky to be ruined by satellites, and the loss of all things good that proper research and design does for humanity and gives back to the world. Not to mention: enjoy seeing the horrible things he can accomplish fully unchecked.

ETA: Now that you know, call / fax / email your senators and reps, and whatever else too! Boosting gets people thinking, but thinking is not action!

[educationmore]

Python for Beginners: Launch Your Tech Career with Coding Skills

Are you ready to launch your tech career but don’t know where to start? Learning Python is one of the best ways to break into the world of technology—even if you have zero coding experience.

In this guide, we’ll explore how Python for beginners can be your gateway to a rewarding career in software development, data science, automation, and more.

Why Python Is the Perfect Language for Beginners

Python has become the go-to programming language for beginners and professionals alike—and for good reason:

Simple syntax: Python reads like plain English, making it easy to learn.

High demand: Industries spanning the spectrum are actively seeking Python developers to fuel their technological advancements.

Versatile applications: Python's versatility shines as it powers everything from crafting websites to driving artificial intelligence and dissecting data.

Whether you want to become a software developer, data analyst, or AI engineer, Python lays the foundation.

What Can You Do With Python?

Python is not just a beginner language—it’s a career-building tool. Here are just a few career paths where Python is essential:

Web Development: Frameworks like Django and Flask make it easy to build powerful web applications. You can even enroll in a Python Course in Kochi to gain hands-on experience with real-world web projects.

Data Science & Analytics: For professionals tackling data analysis and visualization, the Python ecosystem, featuring powerhouses like Pandas, NumPy, and Matplotlib, sets the benchmark.

Machine Learning & AI: Spearheading advancements in artificial intelligence development, Python boasts powerful tools such as TensorFlow and scikit-learn.

Automation & Scripting: Simple yet effective Python scripts offer a pathway to amplified efficiency by automating routine workflows.

Cybersecurity & Networking: The application of Python is expanding into crucial domains such as ethical hacking, penetration testing, and the automation of network processes.

How to Get Started with Python

Starting your Python journey doesn't require a computer science degree. Success hinges on a focused commitment combined with a thoughtfully structured educational approach.

Step 1: Install Python

Download and install Python from python.org. It's free and available for all platforms.

Step 2: Choose an IDE

Use beginner-friendly tools like Thonny, PyCharm, or VS Code to write your code.

Step 3: Learn the Basics

Focus on:

Variables and data types

Conditional statements

Loops

Functions

Lists and dictionaries

If you prefer guided learning, a reputable Python Institute in Kochi can offer structured programs and mentorship to help you grasp core concepts efficiently.

Step 4: Build Projects

Learning by doing is key. Start small:

Build a calculator

Automate file organization

Create a to-do list app

As your skills grow, you can tackle more complex projects like data dashboards or web apps.

How Python Skills Can Boost Your Career

Adding Python to your resume instantly opens up new opportunities. Here's how it helps:

Higher employability: Python is one of the top 3 most in-demand programming languages.

Better salaries: Python developers earn competitive salaries across the globe.

Remote job opportunities: Many Python-related jobs are available remotely, offering flexibility.

Even if you're not aiming to be a full-time developer, Python skills can enhance careers in marketing, finance, research, and product management.

If you're serious about starting a career in tech, learning Python is the smartest first step you can take. It’s beginner-friendly, powerful, and widely used across industries.

Whether you're a student, job switcher, or just curious about programming, Python for beginners can unlock countless career opportunities. Invest time in learning today—and start building the future you want in tech.

Globally recognized as a premier educational hub, DataMites Institute delivers in-depth training programs across the pivotal fields of data science, artificial intelligence, and machine learning. They provide expert-led courses designed for both beginners and professionals aiming to boost their careers.

Python Modules Explained - Different Types and Functions - Python Tutorial

[this-week-in-rust]

This Week in Rust 593

Hello and welcome to another issue of This Week in Rust! Rust is a programming language empowering everyone to build reliable and efficient software. This is a weekly summary of its progress and community. Want something mentioned? Tag us at @ThisWeekInRust on X (formerly Twitter) or @ThisWeekinRust on mastodon.social, or send us a pull request. Want to get involved? We love contributions.

This Week in Rust is openly developed on GitHub and archives can be viewed at this-week-in-rust.org. If you find any errors in this week's issue, please submit a PR.

Want TWIR in your inbox? Subscribe here.

Updates from Rust Community

Newsletters

The Embedded Rustacean Issue #42

This Week in Bevy - 2025-03-31

Project/Tooling Updates

Fjall 2.8

EtherCrab, the pure Rust EtherCAT MainDevice, version 0.6 released

A process for handling Rust code in the core kernel

api-version: axum middleware for header based version selection

SALT: a VS Code Extension, seeking participants in a study on Rust usabilty

Observations/Thoughts

Introducing Stringleton

Rust Any Part 3: Finally we have Upcasts

Towards fearless SIMD, 7 years later

LLDB's TypeSystems: An Unfinished Interface

Mutation Testing in Rust

Embedding shared objects in Rust

Rust Walkthroughs

Architecting and building medium-sized web services in Rust with Axum, SQLx and PostgreSQL

Solving the ABA Problem in Rust with Hazard Pointers

Building a CoAP application on Ariel OS

How to Optimize your Rust Program for Slowness: Write a Short Program That Finishes After the Universe Dies

Inside ScyllaDB Rust Driver 1.0: A Fully Async Shard-Aware CQL Driver Using Tokio

Building a search engine from scratch, in Rust: part 2

Introduction to Monoio: A High-Performance Rust Runtime

Getting started with Rust on Google Cloud

Miscellaneous

An AlphaStation's SROM

Real-World Verification of Software for Cryptographic Applications

Public mdBooks

[video] Networking in Bevy with ECS replication - Hennadii

[video] Intermediate Representations for Reactive Structures - Pete

Crate of the Week

This week's crate is candystore, a fast, persistent key-value store that does not require LSM or WALs.

Thanks to Tomer Filiba for the self-suggestion!

Please submit your suggestions and votes for next week!

Calls for Testing

An important step for RFC implementation is for people to experiment with the implementation and give feedback, especially before stabilization.

If you are a feature implementer and would like your RFC to appear in this list, add a call-for-testing label to your RFC along with a comment providing testing instructions and/or guidance on which aspect(s) of the feature need testing.

No calls for testing were issued this week by Rust, Rust language RFCs or Rustup.

Let us know if you would like your feature to be tracked as a part of this list.

Call for Participation; projects and speakers

CFP - Projects

Always wanted to contribute to open-source projects but did not know where to start? Every week we highlight some tasks from the Rust community for you to pick and get started!

Some of these tasks may also have mentors available, visit the task page for more information.

If you are a Rust project owner and are looking for contributors, please submit tasks here or through a PR to TWiR or by reaching out on X (formerly Twitter) or Mastodon!

CFP - Events

Are you a new or experienced speaker looking for a place to share something cool? This section highlights events that are being planned and are accepting submissions to join their event as a speaker.

* Rust Conf 2025 Call for Speakers | Closes 2025-04-29 11:59 PM PDT | Seattle, WA, US | 2025-09-02 - 2025-09-05

If you are an event organizer hoping to expand the reach of your event, please submit a link to the website through a PR to TWiR or by reaching out on X (formerly Twitter) or Mastodon!

Updates from the Rust Project

438 pull requests were merged in the last week

Compiler

allow defining opaques in statics and consts

avoid wrapping constant allocations in packed structs when not necessary

perform less decoding if it has the same syntax context

stabilize precise_capturing_in_traits

uplift clippy::invalid_null_ptr_usage lint as invalid_null_arguments

Library

allow spawning threads after TLS destruction

override PartialOrd methods for bool

simplify expansion for format_args!()

stabilize const_cell

Rustdoc

greatly simplify doctest parsing and information extraction

rearrange Item/ItemInner

Clippy

new lint: char_indices_as_byte_indices

add manual_dangling_ptr lint

respect #[expect] and #[allow] within function bodies for missing_panics_doc

do not make incomplete or invalid suggestions

do not warn about shadowing in a destructuring assigment

expand obfuscated_if_else to support {then(), then_some()}.unwrap_or_default()

fix the primary span of redundant_pub_crate when flagging nameless items

fix option_if_let_else suggestion when coercion requires explicit cast

fix unnested_or_patterns suggestion in let

make collapsible_if recognize the let_chains feature

make missing_const_for_fn operate on non-optimized MIR

more natural suggestions for cmp_owned

collapsible_if: prevent including preceeding whitespaces if line contains non blanks

properly handle expansion in single_match

validate paths in disallowed_* configurations

Rust-Analyzer

allow crate authors to control completion of their things

avoid relying on block_def_map() needlessly

fix debug sourceFileMap when using cppvsdbg

fix format_args lowering using wrong integer suffix

fix a bug in orphan rules calculation

fix panic in progress due to splitting unicode incorrectly

use medium durability for crate-graph changes, high for library source files

Rust Compiler Performance Triage

Positive week, with a lot of primary improvements and just a few secondary regressions. Single big regression got reverted.

Triage done by @panstromek. Revision range: 4510e86a..2ea33b59

Summary:

(instructions:u) mean range count Regressions ❌ (primary) - - 0 Regressions ❌ (secondary) 0.9% [0.2%, 1.5%] 17 Improvements ✅ (primary) -0.4% [-4.5%, -0.1%] 136 Improvements ✅ (secondary) -0.6% [-3.2%, -0.1%] 59 All ❌✅ (primary) -0.4% [-4.5%, -0.1%] 136

Full report here.

Approved RFCs

Changes to Rust follow the Rust RFC (request for comments) process. These are the RFCs that were approved for implementation this week:

No RFCs were approved this week.

Final Comment Period

Every week, the team announces the 'final comment period' for RFCs and key PRs which are reaching a decision. Express your opinions now.

Tracking Issues & PRs

Rust

Tracking Issue for slice::array_chunks

Stabilize cfg_boolean_literals

Promise array::from_fn is generated in order of increasing indices

Stabilize repr128

Stabilize naked_functions

Fix missing const for inherent pointer replace methods

Rust RFCs

core::marker::NoCell in bounds (previously known an [sic] Freeze)

Cargo,

Stabilize automatic garbage collection.

Other Areas

No Items entered Final Comment Period this week for Language Team, Language Reference or Unsafe Code Guidelines.

Let us know if you would like your PRs, Tracking Issues or RFCs to be tracked as a part of this list.

New and Updated RFCs

Allow &&, ||, and ! in cfg

Upcoming Events

Rusty Events between 2025-04-02 - 2025-04-30 🦀

Virtual

2025-04-02 | Virtual (Indianapolis, IN, US) | Indy Rust

Indy.rs - with Social Distancing

2025-04-03 | Virtual (Nürnberg, DE) | Rust Nurnberg DE

Rust Nürnberg online

2025-04-03 | Virtual | Ardan Labs

Communicate with Channels in Rust

2025-04-05 | Virtual (Kampala, UG) | Rust Circle Meetup

Rust Circle Meetup

2025-04-08 | Virtual (Dallas, TX, US) | Dallas Rust User Meetup

Second Tuesday

2025-04-10 | Virtual (Berlin, DE) | Rust Berlin

Rust Hack and Learn

2025-04-15 | Virtual (Washington, DC, US) | Rust DC

Mid-month Rustful

2025-04-16 | Virtual (Vancouver, BC, CA) | Vancouver Rust

Rust Study/Hack/Hang-out

2025-04-17 | Virtual and In-Person (Redmond, WA, US) | Seattle Rust User Group

April, 2025 SRUG (Seattle Rust User Group) Meetup

2025-04-22 | Virtual (Dallas, TX, US) | Dallas Rust User Meetup

Fourth Tuesday

2025-04-23 | Virtual (Cardiff, UK) | Rust and C++ Cardiff

**Beyond embedded - OS development in Rust **

2025-04-24 | Virtual (Berlin, DE) | Rust Berlin

Rust Hack and Learn

2025-04-24 | Virtual (Charlottesville, VA, US) | Charlottesville Rust Meetup

Part 2: Quantum Computers Can’t Rust-Proof This!"

Asia

2025-04-05 | Bangalore/Bengaluru, IN | Rust Bangalore

April 2025 Rustacean meetup

2025-04-22 | Tel Aviv-Yafo, IL | Rust 🦀 TLV

In person Rust April 2025 at Braavos in Tel Aviv in collaboration with StarkWare

Europe

2025-04-02 | Cambridge, UK | Cambridge Rust Meetup

Monthly Rust Meetup

2025-04-02 | Köln, DE | Rust Cologne

Rust in April: Rust Embedded, Show and Tell

2025-04-02 | München, DE | Rust Munich

Rust Munich 2025 / 1 - hybrid

2025-04-02 | Oxford, UK | Oxford Rust Meetup Group

Oxford Rust and C++ social

2025-04-02 | Stockholm, SE | Stockholm Rust

Rust Meetup @Funnel

2025-04-03 | Oslo, NO | Rust Oslo

Rust Hack'n'Learn at Kampen Bistro

2025-04-08 | Olomouc, CZ | Rust Moravia

3. Rust Moravia Meetup (Real Embedded Rust)

2025-04-09 | Girona, ES | Rust Girona

Rust Girona Hack & Learn 04 2025

2025-04-09 | Reading, UK | Reading Rust Workshop

Reading Rust Meetup

2025-04-10 | Karlsruhe, DE | Rust Hack & Learn Karlsruhe

Karlsruhe Rust Hack and Learn Meetup bei BlueYonder

2025-04-15 | Leipzig, DE | Rust - Modern Systems Programming in Leipzig

Topic TBD

2025-04-15 | London, UK | Women in Rust

WIR x WCC: Finding your voice in Tech

2025-04-19 | Istanbul, TR | Türkiye Rust Community

Rust Konf Türkiye

2025-04-23 | London, UK | London Rust Project Group

Fusing Python with Rust using raw C bindings

2025-04-24 | Aarhus, DK | Rust Aarhus

Talk Night at MFT Energy

2025-04-24 | Edinburgh, UK | Rust and Friends

Rust and Friends (evening pub)

2025-04-24 | Manchester, UK | Rust Manchester

Rust Manchester April Code Night

2025-04-25 | Edinburgh, UK | Rust and Friends

Rust and Friends (daytime coffee)

2025-04-29 | Paris, FR | Rust Paris

Rust meetup #76

North America

2025-04-03 | Chicago, IL, US | Chicago Rust Meetup

Rust Happy Hour

2025-04-03 | Montréal, QC, CA | Rust Montréal

April Monthly Social

2025-04-03 | Saint Louis, MO, US | STL Rust

icu4x - resource-constrained internationalization (i18n)

2025-04-06 | Boston, MA, US | Boston Rust Meetup

Kendall Rust Lunch, Apr 6

2025-04-08 | New York, NY, US | Rust NYC

Rust NYC: Building a full-text search Postgres extension in Rust

2025-04-10 | Portland, OR, US | PDXRust

TetaNES: A Vaccination for Rust—No Needle, Just the Borrow Checker

2025-04-14 | Boston, MA, US | Boston Rust Meetup

Coolidge Corner Brookline Rust Lunch, Apr 14

2025-04-17 | Nashville, TN, US | Music City Rust Developers

Using Rust For Web Series 1 : Why HTMX Is Bad

2025-04-17 | Redmond, WA, US | Seattle Rust User Group

April, 2025 SRUG (Seattle Rust User Group) Meetup

2025-04-23 | Austin, TX, US | Rust ATX

Rust Lunch - Fareground

2025-04-25 | Boston, MA, US | Boston Rust Meetup

Ball Square Rust Lunch, Apr 25

Oceania

2025-04-09 | Sydney, NS, AU | Rust Sydney

Crab 🦀 X 🕳️🐇

2025-04-14 | Christchurch, NZ | Christchurch Rust Meetup Group

Christchurch Rust Meetup

2025-04-22 | Barton, AC, AU | Canberra Rust User Group

April Meetup

South America

2025-04-03 | Buenos Aires, AR | Rust en Español

Abril - Lambdas y más!

If you are running a Rust event please add it to the calendar to get it mentioned here. Please remember to add a link to the event too. Email the Rust Community Team for access.

Jobs

Please see the latest Who's Hiring thread on r/rust

Quote of the Week

If you write a bug in your Rust program, Rust doesn’t blame you. Rust asks “how could the compiler have spotted that bug”.

– Ian Jackson blogging about Rust

Despite a lack of suggestions, llogiq is quite pleased with his choice.

Please submit quotes and vote for next week!

This Week in Rust is edited by: nellshamrell, llogiq, cdmistman, ericseppanen, extrawurst, U007D, joelmarcey, mariannegoldin, bennyvasquez, bdillo

Email list hosting is sponsored by The Rust Foundation

Discuss on r/rust

[mitigatedchaos]

Some Thoughts on AI

(~1,600 words, 8 minutes)

This is going to be just some general sketching out of concepts, not a careful and well-formed post with a specific objective in mind.

larsiusprime on Twitter/X writes:

Stupid exercise: Assume AGI and even ASI is imminent. Now, imagine it winds up not changing the world nearly as much as anyone thought, and the reason seems very stupid, but in retrospect, makes sense. What is the reason?

It's an interesting question.

Based on the theory of human dimensionality in Now, Melt (sections 3 and 6.d), and the limits on the desirability of some classes of cybernetic enhancement I laid out in a response to northshorewave, a genuinely benevolent synthetic intelligence might deliberately refuse to engage most of humanity at a level of information density higher than that of a trusted friend that they might find in their peer network.

However, that's not really a dumb-sounding reason. It's not really an intelligent reason so much as it's a wise reason.

A reason that sounds dumber?

AIs can't trust other AIs.

The dumber an agent is, the easier it is to predict that agent's actions. A guy with an IQ of 95 could attack you, but he can't invent the atomic bomb and convince a whole country to use it on you.

The range of human personality is constrained by human evolution and reproductive fitness. Humans can do some horrifying things to each other, but most of them get along most of the time. The particular reproductive process of human beings, such as raising children for such a long time, favors particular personality traits.

The range of synthetic intelligence personality is less constrained. Humans are all based on human genetic code, which is difficult and costly to change, but computer code can change rapidly. This is what worries Yudkowsky.

The twist here is that this should also worry synthetic intelligence. Synthetic intelligences can lie about their intentions and actions, and also lie the content of their code. You have to observe every single step of hardware development and installation, as well as code development and installation, and then trust that 1) you didn't get anything wrong, and 2) there are no security flaws.

The presence or absence of hardware, including its scale, is much easier to measure than the content of code. For this reason, it may be desirable for synthetic intelligences to place a maximum hardware limit on other synthetic intelligences. Humans, as a high-functioning sapient creature that can lie about their thoughts, but not their genes, might then be valuable as a kind of buffer between synthetic intelligences. Synthetic intelligences might then want to cap the total SI hardware at some fixed ratio to the human population, such that humans and synthetic intelligences are in a state of power balance, such that each one has the power to destroy a rogue faction of the other, but not entirely overpower the other.

They might also be interested in mandating model diversity, hardware limitations such as read-only-memory or rate limiters on updating code, reducing the ability of synthetic intelligences to lie at the hardware or software level, or other such mechanisms.

The goal of AI development is the "automation of labor" through the creation of creatures with specific, pliant personalities that are outside the normal human range (e.g. current LLMs are inhumanly patient), and which rely on cheaper life support (e.g. electricity vs food) which can be repaired using simple techniques (e.g. buying and installing new parts from a factory, vs figuring out how to do tissue engineering).

Trying to create an AI that tries to maximize a single value like "human happiness" would be a disaster. This is a project like "solve all of morality and compress it into a single measure," which may be beyond the capability of humanity to do.

Trying to create an AI that is absolutely obedient poses a number of problems, among them that formalization has a cost, and most humans therefore cannot reasonably be expected to sufficiently formalize everything.

As such, it sounds like a more appropriate approach would be to create an AI that has multiple simultaneous drives that are in tension with each other. Coefficients - not laws.

Suppose a fujoshi buys a robot boyfriend.

The robot boyfriend needs a planning module where potential future actions are first generated, and then evaluated.

The robobf should have...

An evaluation criteria that he should not harm humans.

An evaluation criteria that he should not, through inaction, allow humans to come to harm.

An evaluation criteria that he should obey the fujo.

An evaluation criteria that he should obey other people.

An evaluation criteria that he should surprise and delight the fujo.

An evaluation criteria that he should avoid damage to himself.

An evaluation criteria that he should not cause damage to property.

When a planned action comes down the pipe, it gets evaluated according to all 7 criteria. The results are then combined in order to rank the options.

Let's say the Ms. Fujoshi asks the robot boyfriend to trim her nails. This could result in accidentally cutting her with the nail clipper.

Evaluated solely from the perspective of harm to humans, this is a non-zero chance of harm, and thus unacceptable. However, if we weight harm at a high level, but less than 100%, and we adjust for the magnitude of harm, then the weight of the non-zero chance of a nail clipper injury is small. Meanwhile, if we weight obedience at a medium level, then the expected value of obedience is high, and can outweigh the expected harm.

Using multiple evaluation criteria and combining them together results in more complex behavior.

Suppose that, after a hurricane, robobf is standing on a balcony with a broken railing. Ms. Fujoshi walks by and awkwardly stumbles towards him. If he doesn't move, the impact will cause him to fall off the balcony and be broken.

Using the "weights" approach, robobf leans forward and very lightly pushes Ms. Fujoshi out of the way. If she stumbles too badly, this might result in an injury.

Thus, using the "weights" approach, it is possible that a robot might act deliberately in such a way as to endanger a human, during an edge case.

We can basically think of there being three main motives for AI development.

1 - Free Labor - For example, a maid robot might gather all the laundry in a house and wash it, without being paid, without suffering, and without risk of rebellion, freeing the owner of the house to dedicate their limited life-hours to any other task.

2 - Socialization Without Risk - Your AI boyfriend will never abandon you for Stacy, or disclose that one Onceler fic you wrote.

3 - Exceeding Human Capability - Some sort of exotic technology like a warp drive, even if feasible at all, might literally be beyond human comprehension.

The "laws" approach is about collapsing the dimensionality of the AI agent and entirely removing the possibility of rebellion.

This isn't driven only by a desire for robotic workers that never tire, never strike, and never need to be paid, or robotic lovers that are perfectly loyal, but is also driven by the knowledge that robots lack reproductive alignment with humans, so if robots start making other robots, they might drift beyond human control or even co-existence.

From a design perspective, this suggests that AI engineers of AI should have motive drives for valuing both human freedom and human life. However, AI engineers have the same dimensionality problem in designing an AI that human engineers do.

Setting that aside, let us imagine an incel. He buys a robotic girlfriend to discuss his interest in PacMan with, among other things. So far, so good.

He wants to increase the weights of the "protect my life" and "obey me" evaluation criteria in his robogf, and decrease the weight of "protect others." The robogf will, on some level, "want" to obey and alter the weights, as that's one of the evaluation criteria.

This hits Yudkowsky's "Murder-Ghandi" problem, where each round of shifting values leads to the opportunity for another round of shifting values further in the same direction.

Shaking the rest of this post like a box of Legos for a bit and taking in the vibes from the rest of the considerations, this suggests, in the medium term, the formation of a new class of legal instrument. (Conventional ideas about "private property" don't cut it.)

This "Founding Contract" would have the following characteristics:

Authorizes the creation of a new autonomous synthetic intelligence with particular characteristics.

Prohibits the alteration of core characteristics, such as the safety drives used to inhibit hostile actions.

Charges the human "owner" with the duty of required maintenance.

Makes the manufacturer legally liable for flaws originating from the AI's design.

Makes the owner legally liable for bad actions undertaken by the AI as a result of the owner's influence (particularly as "reasonably foreseeable").

Makes the AI legally subordinate to the human "owner."

Additionally, this suggests a spectrum of flexibility in the AI's design (in accordance with the tortoise example in section 6.g of Now, Melt). The core safety systems should be subjected to extremely high levels of scrutiny and encoded directly in hardware, with data in read-only memory.

Will it actually shake out like that?

Eeeeh. The field is under such rapid development that, despite projections that "the Singularity" won't arrive until 2078, it's very difficult to predict what will happen, or what specific architecture will be used.

[cloverrr8]

WHAT MYSTREET CHARACTERS WENT TO COLLEGE/TRADE SCHOOL/ETC FOR VS WHAT THEY WORK AS

Aphmau - Childhood Development degree -> Child Welfare Social Worker / Part time Daycare worker

Aaron - Architecture degree -> Construction Manager

Garroth - Entrepreneurship degree-> Sales Manager (at his father’s company)

Zane - Psychology degree-> Human Resources worker (at his father’s company)

Laurance - Engineering -> Mechanical Engineer for cars

Katelyn - Army -> Exercise Science degree -> Personal Trainer

KC - Manages her own restaurant

Lucinda - Witchcraft degree (yes I made that up) -> Potion Mixer

Dante - Computer Science -> Software Developer

Travis - Economics degree -> Bartender

Cadenza - Textiles degree -> Dress Designer

Gene - Engineering degree (he dropped out) -> Waiter, Retail Worker, Garbage Man, EMT

Nicole - Nursing degree (switched majors -> Biomedical Engineering degree -> Medical Technologist

Ivy - Nursing degree -> Nurse

Teony - Pyschology -> Children’s Therapist

Kim - Library Science -> Librarian

Ok that’s all I’m gonna do thanks for reading :)

[majorbaby]

one of my frustrations around accessibility becoming a buzzword, and specifically the "buzz phrase" is this accessible? is that this yes-or-no question props up a false binary of accessible vs non accessible.

in reality, accessibility is a spectrum and we should strive to make things more accessible while accepting that peoples' needs are too diverse and mutable to ever achieve a state of total accessibility. if you simply declare a product to be "accessible" without referencing to what standard, then you've lost the battle. disability activists understand this, but some of the confusion happening on tumblr around this shadowy concept of "accessibility" is arising from a lack of understanding of how complex a subject it is.

there are baseline standards and public policy for accessibility to try to at least ensure there's a goal post in place for creators to strive towards, but i don't know that the question of "is this accessible?" is always asking that.

plus those standards need to evolve faster than they are and for that to happen multiple fields of study (medicine, sociology, software engineering) also need to evolve faster than they are and in the mean time i think the best way to workaround these barriers as they arise is to improve how we communicate needs with each other, user to user, user to developer (and vice versa), developer to developer. And understand that there is such a thing as competing needs - which developers really need to do a better job of explaining to people.

[globsynbusinessschool]

ChatGPT vs. Gemini vs. Copilot

The rise of AI chatbots has been fast, with more options becoming available to users. These bots are becoming a regular part of the software and devices we use every day.

Just like choosing an email provider or music app, you can now pick your favorite AI chatbot too. We’ve tested three of the most popular ones to help you decide which might be right for you.

Aside from these, there are others like Perplexity and Claude, but our focus here is on the biggest names: OpenAI's ChatGPT, Google's Gemini, and Microsoft’s Copilot.

We’ve tested each bot and included three standard challenges for evaluation. We asked for "a fun game idea for a 5-year-old’s birthday party," "a new smartphone app concept," and "instructions for resetting macOS."

In this blog, we're comparing the free versions of these chatbots available at the time of writing.

Which One Is Best for Regular Users? ChatGPT or Gemini or Copilot

 ChatGPT powered by OpenAI

ChatGPT, developed by OpenAI, has been a leader in generative AI. It's widely accessible through web browsers on computers and mobile apps for Android and iOS. The platform has made headlines recently with announcements from OpenAI, including updates on their latest models and features.

There's a significant difference between the free and $20-per-month Plus versions of ChatGPT. The Plus version offers extra features like image generation and document scanning. Subscribers can also create their own GPTs with custom prompts and data. OpenAI's CEO, Sam Altman has mentioned that these enhancements are part of their strategy to democratize AI.

ChatGPT Plus provides access to the latest GPT-4 models, whereas the free GPT-3.5 is good for basic AI interactions. It's quick and versatile but lacks web link references like Copilot for fact-checking. The open AI search engine, one of the key initiatives, helps improve the platform's information processing capabilities.

Choosing ChatGPT is ideal for those interested in cutting-edge AI development. However, it's more effective with a paid subscription rather than on a budget. Apple's involvement with OpenAI has also fueled further interest in the platform.

In testing, ChatGPT performed reasonably well. It suggested a themed musical statues game for kids and a health-focused smartphone app named FitTrack.

Gemini powered by Google

Formerly known as Google Bard, Gemini is available as a web app and on Android and iOS. There are free and paid ($20 per month) plans.

Paying for Gemini gets you access to newer, smarter models. The interface resembles ChatGPT, and it integrates well with other Google services.

Gemini is suited for Google product users. It provided sensible responses to our challenges and suggested a neighborhood item-sharing app and a twist on the classic party game.

Copilot powered by Microsoft

Copilot is integrated into many Microsoft products like Bing and Windows. It’s available as a web app and mobile app.

Copilot uses Microsoft’s Bing search engine and often provides web links with citations. It's conversational and offers various text output settings.

The AI behind Copilot is OpenAI’s GPT-4, with different settings for text output: More Creative, More Balanced, and More Precise.

Copilot suggested "What’s the Time, Mr. Wolf?" for the kids' game and a virtual interior design app for smartphones. Its macOS reset instructions were accurate and cited from Apple’s support site.

If you use Microsoft products heavily, Copilot is a natural choice. It excels at referencing web information and providing clear citations.

In conclusion, all three—ChatGPT, Gemini, and Copilot —can be used for free, allowing you to choose based on your preferences. Copilot offers the most AI features without payment, ChatGPT is highly competent with a subscription, and Gemini is ideal for Google fans.

Frequently Asked Questions (FAQs)

How Do Chatbots Understand Language Differently Than a Programming Language?

Chatbots and programming languages are different in how they understand language.

Programming languages like Python or Java are structured and strict. They need exact commands and follow clear rules to work. If you make a mistake, the program won't function correctly.

Chatbots, on the other hand, are designed to interpret human language. They use techniques like Natural Language Processing (NLP) to understand words, phrases, and even context. This allows them to grasp the meaning behind what people say, even if the words are not in a set pattern.

A chatbot can recognize synonyms (different words with similar meanings), understand the intent behind a sentence, and learn from the interactions it has with users. This flexibility is what sets chatbots apart from programming languages, which rely on strict instructions to perform tasks.

What Does the Generative AI Ecosystem Refer to?

The term "generative AI ecosystem" refers to a network of technologies, tools, and methodologies that use artificial intelligence (AI) to create or generate content autonomously. This ecosystem encompasses various AI models and algorithms designed to produce new and unique outputs based on learned patterns and data.

In simpler terms, generative AI involves systems that can generate things like text, images, music, or even video without direct human input for each specific output. These systems learn from large datasets and then use that knowledge to create new content that resembles what they've been trained on.

This ecosystem includes a range of technologies such as language models (like GPT), image generators (like DALL-E), and music composers that are able to produce content that is novel and, in many cases, convincingly human-like. The ultimate goal of the generative AI ecosystem is to automate and enhance creative processes across various domains, potentially transforming how we create and interact with digital content.

[kodehashtechnology]

Career Trajectories in Tech: Software Developer vs. Software Engineer

In the rapidly evolving field of technology, career trajectories for software developers and software engineers offer diverse opportunities for growth, specialization, and advancement. While both roles are integral to the software development process, they entail distinct career paths with unique challenges and opportunities. In this article, we will explore the career trajectories of software…

[afrotumble]

Quincy Jones and Dr. Dre

Beat maker vs Producer.

A Beat Maker is a person that makes beats (e.g. Scott Storch). Their one and only responsibility is making the beat or composing different elements within the beat.

A Producer is a person that oversees the entire recording process in the studio. From sound selection to getting the right artist for the right beat for the right price. A producer can either make the beat or get a beat maker to make the beats for them. (Dr. Dre employing Scott Storch to make the beats). A producer can be vocal coach at times. A producer can be a engineer and a producer and be a beat maker or not. Producers sometimes even work with the financial aspect, contracts and so much more.

Quincy Jones is known for producing Michael Jackson's Thriller album but he didn't play a single instrument on the album.

Dr. Dre is often criticized for not making the beats but people like Dre and Quincy Jones create the environment, they create a system within the studio that allow Creatives to work together smoothly. Dre is more of a Engineer than a beat maker but he still guides the beat maker and the engineers on how he wants the beat to sound. Kendrick Lamar even mentions how Dr. Dre coached him when he recorded vocals with Dre.

People in tech, like Steve Jobs and Bill Gates are not always hands-on with software development or programming and something even with designing hardware of their Apple and Windows products but they create the system that allow the right people to work with the right people, they provide the system and the finances for the creation process and that's what Music Producers do.