#artificial intelligence and machine learning

[thenightfolknetwork]

I have a problem. Somebody asked me if I was pro-AI, and I said yes, of course, every sensible person is. "A person's a person, whether they were coded or conceived or came to life through other means," I didn't say, because I felt it was obvious. Now I've found out that people use "AI" to refer to non-sentient computer models, so that means I gave off the COMPLETE wrong impression, and it's mortifying. How do I deal with this, and how do I prevent it from happening again?

I completely understand your frustration, reader. The use of the term “AI” to refer to generative algorithms has had several unfortunate side effects, not least among them being the confusion this terminology causes for genuinely sentient programmes and otherwise coded consciousnesses.

I would first like to note that there is no way to completely prevent such miscommunication from happening. There is a hard limit to how much we can control other people's perceptions of us, after all, and language has always had a rather slippery relationship with meaning. All you can do is try your best, and to speak up when you think things have gone awry.

In this specific situation, the simplest way to avoid this confusion is to speak precisely and ask others to do the same. If a person asks whether you are pro-AI, ask them to clarify whether they're referring to sentient coded consciousnesses, or to a glorified spell checker.

If you have the energy, and if you think it would be productive, you might also push back a little on the terminology they're using. Encourage them to specify either “coded consciousnesses” when speaking about actual people, or “generative AI” when speaking about the automated plagiarism machines.

Otherwise, the best thing you can do here is to lead by example. Be clear and precise in your own language, continue to advocate for the rights and dignities of coded consciousnesses where appropriate, and be prepared to correct any misunderstandings as they arise. That's really all any of us can do.

[For more creaturely advice, check out Monstrous Agonies on your podcast platform of choice, or visit monstrousproductions.org for more info]

[lets-talk-gundam]

The MSA-0011 S Gundam

The early success of Project Zeta led to many new and innovative mobile suit designs. The introduction of new materials, new mechanisms, new weapons technologies, and new design talent at Anaheim opened the door for the company to dominate the MS development sector into the mid 90s UC.

During this period, a number of machines based on Project Zeta would see deployment by factions all across Earth-sphere. many of these post-Zeta machines would come to be known as "Anaheim Gundams", and would be regarded as some of the most influential designs in the history of mobile suits.

Developed for the Earth Federation forces sometime in the late 80s UC, the MSA-0011 S Gundam, also called the Superior Gundam and Iota Gundam internally at Anaheim, is a bit less well-known than its other Project Zeta siblings.

The machine featured a modular design, made up of three high-performance aerospace craft which combined via a core block system to form the full mobile suit. These units were the FXA-08BG Core Fighter, the G-Bomber, and the G-Attacker.

Despite similarities to the MSZ-010 ZZ Gundam, the design teams for the two machines largely worked independently of one another.

The S Gundam featured some unique equipment for the time, including the Beam Smart Gun, a powerful rifle that connected directly to the machine's power plant. It was also one of the earliest adopters of INCOMs and the quasi-psycommu system. Quasi-psycommu technology allows non-Newtype pilots to make use of formerly Newtype-exclusive weapon systems.

The S Gundam also saw several upgrade plans. These plans included the MSA-0011 [BST] S Gundam Booster Unit Type, the MSA-0011 [Bst] S Gundam Booster Unit Plan 303E "Deep Striker" , and the MSA-0011 [Ext] Ex-S Gundam.

The MSA-0011 [BST] S Gundam Unit Type and the MSA-0011 [Ext] Ex-S Gundam are both upgrades applied to the original unit, but the "Deep Striker" equipment was never built. The "Deep Striker" does appear as a playable unit in the SD Gundam G Generation series of games.

The S Gundam would also be developed into the Nero, a mass-production variant taking cues from it and the Lambda Gundam. It was used as the mainstay MS of the Federation's Task Force Alpha.

While all of this is rather impressive, the most notable part of the machine was undeniably its greatest strength. The S Gundam was equipped with the Advanced Logistic and Inconsequence Cognizing Equipment system. "ALICE" - as she was better known - was an advanced artificial intelligence designed to replace a human pilot.

WARNING!

The following section contains MAJOR SPOILERS for Gundam Sentinel! If you are interested in reading it, I highly recommend you do so!

ALICE was developed by Anaheim scientists Dr. Carol and Dr. Roots to automate certain functions of mobile suits. While this was possible previously, commands had to be programmed into the MS via a command console. The final objective of the project was to fully automate a Gundam-type mobile suit using ALICE.

She was programmed to grow and learn by observing and analyzing the actions of pilots, and was treated like a daughter by Dr. Roots. This caused tensions with Dr. Carol and other factions at Anaheim. A suspected act of sabotage resulted in an explosion that nearly destroyed ALICE, but Dr. Roots gave her life protecting her. The project was shelved for a time.

ALICE was picked back up later, being installed in the S Gundam and paired with Ryou Roots under the Federation's Task Force Alpha. She, along with the S Gundam, saw action during the Pezun rebellion perpetrated by the New Desides faction. This faction of Titans remnants and loyalists sought to break away from the Federation to further their own interests.

During combat, Ryou's lack of skill resulted in multiple near-death experiences. ALICE was responsible for saving his life on multiple occasions.

Learning from Ryou and other Task Force Alpha pilots, ALICE eventually developed an awareness of the world. She would deduce that friends were the most important thing to a person, after initially failing to comprehend Ryou's grief at the death of his fellow pilots.

Following this logic, she would eventually sacrifice herself to save the lives of her comrades. Her final words were thanks to Ryou for the memories and lessons she learned from him.

She would be destroyed during atmospheric entry.

The above machines were all designed by Hajime Katoki for the 1987 photo-novel Gundam Sentinel. Gundam Sentinel was written by Masaya Takahashi and published in Model Graphix magazine.

[securemycareer]

Top Skill development courses for Students to get Good Placement

Please like and follow this page to keep us motivated towards bringing useful content for you.

Now a days, Educated Unemployment is a big concern for a country like India. Considering the largest number of youth population in world, India has huge potential to be a developed nation in the next few years. But, it can be only possible if youth contribute in economy by learning skills which are in global demand. However, course structure in colleges are outdated and do not make students job…

[krazytechnews]

How Generative AI Is Helping Industries to Increase Productivity in 2024

Have you ever wondered how some industries seem to be flying forward & getting closer to a bright future while others are still struggling? Well, Generative AI is the magic bullet behind this rapid progress. This superb technology is a subset of Artificial Intelligence (AI) that is transforming the way businesses operate, making them more efficient & productive. It utilizes the power of…

[pidgetechnologies]

The Impact of Artificial Intelligence and Machine Learning on Last Mile Logistics

The timely and effective delivery of goods has become essential for the success of businesses across a range of industries in today's fast-paced and fiercely competitive business climate. The last mile of the logistics process is critical to customer satisfaction and overall business performance, regardless of the industry—enterprise restaurant chains, diagnostic lab chains, e-commerce companies, direct-to-consumer (D2C) companies, retail, or grocery delivery services.

[mobileappdevelopmentsolution]

How to Create an SEO Strategy To Survive the Impact of AI

Artificial intelligence and machine learning have caused major shifts in how search engines operate. As AI capabilities rapidly improve, search engines like Google are relying more on advanced algorithms and neural networks and less on traditional SEO tactics.

While this creates new challenges for white-label SEO, with the right strategy focused on high-quality content and user experience, there are still many effective ways to optimize pages for search in an AI world.

The Impact of AI on SEO

In recent years, artificial intelligence has had a transformative effect on the field of search engine optimization. A decade ago, SEO services largely depended on straightforward tactics like keyword targeting, backlink building, and metadata optimization. However, modern search engines like Google now use extremely sophisticated AI and machine learning systems to analyze pages and determine relevance.

These AI capabilities allow search engines to parse pages based on semantic meaning instead of just specific keywords. They can better understand the context and intent behind searches to match queries to optimal content. And they are getting increasingly effective at determining the expertise and authority of pages through analysis of content and links. ‍

This shift towards AI has diminished the power of traditional keyword-focused SEO techniques. Tactics used by top SEO agencies, like overloading pages with target keywords or cramming keywords into metadata, now provide a little boost in search rankings. Meanwhile, tactics aimed at manipulating search algorithms, like using keyword-rich links or content, can actually hurt rankings.

While disconcerting at first, this shift powered by AI presents new opportunities as well. Pages that might have been buried previously due to a lack of backlinks or keyword volume can now rapidly gain traction if they offer high-quality content tailored to intent and reader value. AI has leveled the playing field in many respects.

The key to white-label SEO success is targeting the human audience while leveraging AI's capabilities. Optimizing for long-form readability, expertise building, semantic relevance, and overall user experience can position pages to thrive in modern search.

 Focusing on Creating High-Quality Content

Creating high-quality content is one foundational element for any SEO agency that wants to remain successful & essential in an AI-driven world. When looking to gain search visibility and traffic today, the most important consideration is producing content that delivers exceptional value for readers and site visitors.

Search engines powered by deep learning algorithms have become highly adept at analyzing content to determine the overall quality and usefulness. Google's RankBrain algorithm specifically parses pages syntactically and semantically to evaluate authority, depth, and insight. Creating content solely to target keywords or rank for specific searches provides little benefit.

Instead, sites should focus on publishing in-depth, thoroughly researched content on topics that engage the target audience. Well-written guides, long-form explainers, and data-driven analyses perform exceptionally well in AI-powered searches thanks to the wealth of information they contain. Conversely, thin pages with little substance routinely get buried or filtered out of prominent results.

Here are some key elements of high-quality content designed to survive the impact of AI:

Comprehensive Research and Insight

Content should provide ample information and insight into the topic at hand. This requires thorough research from diverse sources to create a complete picture. Any claims or facts presented must be backed up by citations and data to reinforce authority on the subject. Articles should deliver insights and analysis beyond what readers can easily find on their own. This shows search engines the depth of knowledge and effort put into creating the content.

Original Perspectives and Reporting

Rehashing the same information and perspectives found on thousands of other sites adds little value for readers. To stand out, content should present original analysis and viewpoints on the topic. First-hand research, interviews with experts, and thoughtful commentary demonstrate the unique assets your site offers. This original reporting has become increasingly important for any top SEO company’s success.

Clear, Concise Writing and Structure

Even when covering complex topics, content must be broken down into clear, easy-to-digest writing. This involves using plain language suited for a general audience, avoiding jargon and obscure phrasing. Content should have a logical narrative structure with transitions between ideas. Sections and lists help break down information into scannable sections. Clear writing has always benefitted readers, but now it also helps search engine AI better extract information.

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Media Elements and Interactivity

Charts, data visualizations, images, video, and other interactive embeds help engage readers while also breaking up blocks of text. These elements also provide additional signals search engines can use to understand page topics and content better. Surfacing media elements in search snippets can entice users to click as well.

Value and Utility for The Reader

Most importantly, all the content should be crafted to address the needs and interests of readers directly. Answering and anticipating key user questions demonstrates the usefulness and value of the content. Meeting reader needs earns trust, elevating page authority in AI assessments.

By focusing efforts on publishing high-caliber content across these elements, sites can significantly improve search visibility through AI-based algorithms. Favoring substantive value for readers over keyword quotas or link metrics sets sites up for sustainable SEO services success in the AI era and beyond.

Optimizing for Semantic Search and User Intent

Another key shift in white-label SEO powered by AI is optimizing content for semantic search and user intent rather than just specific keywords. Modern search engines analyze the overall meaning and context of pages in addition to targeting keywords.

For instance, Apollo Digital's strategic optimization for semantic search and user intent led to a single blog post generating $25,000 in revenue. By addressing the pain points of SaaS founders in a 14,000+ words post, enriched with visual elements and a Smart Content Filter plugin, the content attracted over 11,000 page views and 20+ leads in the first month. The use of relevant semantic keywords and a targeted promotion strategy across 12 channels, including ads on platforms like Quora and Facebook, contributed to the post's virality and overall success.

To fully capitalize on this, sites must take a holistic semantic optimization approach to satisfy user search goals.

Conduct In-Depth Keyword Research

The first step is researching keywords not just for volume and difficulty, but also the intent and meaning behind queries. Reviewing search trends and related questions provides insight into the reasoning and goals of users searching for a given term or topic. Understanding the full context around keywords is crucial for optimizing semantic relevance.

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For example, the intent behind a query for [best practices for SEO] may focus on introductory education for newcomers to the field. Whereas [advanced SEO techniques] convey very different user goals. Optimizing pages for each of these related keyword themes requires catering to very different semantic intentions.

Craft Content to Match Search Intent

With insight into query intentions, sites can create content expressly designed to satisfy specific user needs. Each piece can be crafted to align with semantic search goals: tutorials for newcomer education, comparisons for purchase decisions, and troubleshooting for solving problems.

Optimizing individual pages for clearly defined semantic intent makes them exponentially more findable in search for queries signaling those needs. And pages strongly aligned with intent routinely outperform only those loosely related to vague keywords.

Use Natural Language and Readability

Keyword usage should flow naturally within written and visual content while maintaining strong readability. Forcing awkward keyword cramming creates a poor user experience while diluting semantic signals. Discussion of key topics using synonyms and related terminology reinforces relevance.

Likewise, a clear page structure with descriptive headers and metadata ensures both visitors and search bots can easily extract semantic meaning. This natural language optimization balances search engine targeting with human readability.

By holistically aligning content with core semantic intent for key searches, any SEO optimization company can greatly strengthen discoverability and rankings. Users find pages better suited for their query goals, while search AI identifies stronger signals revealing what content is about and who it serves.

Comparison of Core On-Page Optimization Factors

Building Expertise, Authoritativeness and Trust

As search engines rely more on AI, they are getting extremely efficient at analyzing signals to determine the expertise and authority of pages and sites. Known as E-A-T (Expertise, Authoritativeness, Trustworthiness), these core elements of high-quality sites are becoming essential for success.

Establish Clear Site Expertise

Having pages and writers dedicated to specific topics allows sites to build recognized expertise in those areas. This establishes clear authority for searches within those themes. An automotive site with dedicated new car reviewers and mechanics has inherent advantages for "review of new Honda Civic" searches versus general sites.

Curate High-Quality External References

Sites should demonstrate knowledge of influential references, research, and quotes within their niche. Citing recognized industry experts and authoritative external sources shows a command of the broader topic ecosystem. This helps establish overall authoritativeness through connections to trusted domains.

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Transparent Company Details and Contact

Providing clear company information like addresses, contact forms, and bios of key contributors helps build user trust through transparency. Quick response times and proactive communication also demonstrate respect for audiences. Sites from undefined entities struggle to develop relations and authority.

As search algorithms analyze these expertise and authority signals, sites can optimize content to reinforce their capabilities and trustworthiness. This earns the page merit in AI assessments to rank for relevant searches. Users also inherently place more trust in sites demonstrating deep understanding versus generic pages. Organic optimization for expertise pays dividends across the board.

Optimizing Site Architecture and On-Page Factors

While high-value content is essential for SEO services in an AI world, optimizing site architecture and on-page factors makes it easier for search bots to access, crawl, index, and categorize pages appropriately. A content-first approach must still be complemented by key technical optimizations.

Page Speed and Performance

Slow-loading pages negatively impact user experience, hurting organic search rankings. Performance is analyzed by AI algorithms as one of many relevant signals. Optimizing pages for faster load times through image compression, efficient code, caching, and more benefits SEO services.

For instance, Etsy improved site speed by implementing progressive image loading, caching, and code optimizations. These enhancements helped improve organic clicks by 16% year-over-year.

Mobile Optimization

With Google's mobile-first indexing, sites need responsive pages tailored for smartphones and tablets. This improves accessibility along with crawlability for Google bot and other search robots. Clear navigation and minimal blocking elements also aid crawling.

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URL Structure

URL paths should reflect the semantic page structure using relevant keywords and phrases. For example, www.site.com/buyers-guide-seo-tools  clearly conveys page content.

Dynamic URLs or overly complex parameters can inhibit proper indexing.

Headings and Metadata

Proper page titles, descriptions, and H1 tags help search bots segment and categorize pages for improved relevance. These tags should focus on defining page purpose and establishing a hierarchy of critical topics covered.

Media Integration

Images, videos, and other rich media not only engage visitors but also provide additional signals for search engine comprehension. The alt text describes non-text elements while tags attach metadata.

Together, these architectural elements and on-page optimizations reinforce page content for search bots while providing a better experience for human visitors. AI-powered engines use these signals judiciously in assessing overall quality and relevance.

Conclusion

The rise of artificial intelligence presents both enormous opportunities as well as significant challenges for any top SEO company looking to optimize organic search performance. As search becomes increasingly driven by machine learning, many familiar search engine optimization tactics are becoming obsolete.

However, while AI disrupts some traditional SEO services & strategies, it also opens new pathways to success by focusing on expertise, authority and delivering true value to audiences. Any top SEO agency that adapts to leverage AI’s capabilities can actually excel in modern search environments.

Still, sustaining search visibility in the long term will require embracing constant change. With search algorithms rapidly evolving, no single white-label SEO approach will remain optimal forever. Maintaining agility, continuously tracking performance, and optimizing based on the latest learning will be imperative.

For brands struggling to realign SEO services in an AI world, seeking guidance from proven search experts can shortcut the path to sustainable success. At Consagous Technologies, a top SEO agency, our premium digital services are designed to help future-proof brands for lasting organic search excellence amidst an AI revolution.

As pioneers in digital marketing, we combine decades of optimization experience with cutting-edge technical capabilities. Our holistic approach delivers across all facets of modern search success:

- Strategic content creation optimized for ranking potentials of AI

- Comprehensive site and architecture enhancements

- Industry-leading expertise in enterprise SEO integration

- Ongoing performance tracking, testing, and improvement

We help clients achieve and sustain top visibility in organic search through any shifts in algorithms. Our tailored white-label SEO strategies empower brands to maximize relevance, authority, and discoverability in an AI-driven search landscape.

To learn more about future-proofing your SEO, Contact us and see how Consagous can help your brand thrive on the cutting edge of artificial intelligence and machine learning.

Claim your edge and take the next step towards search dominance!

[dbajaj48]

Unveiling the Future: AI and ML Revolutionize Product Development

In the fast-paced world of technology, two game-changers have emerged: Artificial Intelligence (AI) and Machine Learning (ML). Once confined to the realms of science fiction, they now reign supreme in the landscape of product development. But what does this mean for the future of innovation?

Enter AI and ML, the dynamic duo reshaping how products are conceived, designed, and perfected. Gone are the days of guesswork; these technologies harness the power of data-driven insights, predictive analytics, and intelligent automation to create products that are not just efficient but also intuitive and user-centric.

At the heart of AI lies the simulation of human intelligence in machines. Think of it as teaching a computer to think and learn like us. ML, on the other hand, is the brainchild of AI, focusing on algorithms that enable machines to understand and improve from experience. Together, they form the backbone of modern product development.

The journey of AI and ML in this realm began humbly, with simple automated tasks, but has since evolved into a symphony of sophisticated systems capable of complex analysis and decision-making. Thanks to advancements in computing power, data accessibility, and algorithmic innovations, AI and ML now stand at the forefront of technological advancements in product development.

Today, businesses across industries are embracing AI and ML to gain a competitive edge. Predictive analytics tools powered by AI can navigate intricate datasets, creating detailed user profiles and recommendations in mere moments – tasks that would take human analysts significantly longer. This level of unstructured data analysis is critical in understanding user needs and preferences, guiding product design in unprecedented ways.

But it doesn't stop there. AI and ML are also masters of predictive modeling, capable of foreseeing market trends and user behaviors with uncanny accuracy. By recognizing patterns in data, these technologies enable proactive product development strategies, ensuring that products stay ahead of the curve.

So, what does this mean for the future of product design? It means a seismic shift towards personalized, user-centric experiences. AI and ML excel at crafting designs tailored to individual preferences, analyzing user interactions to deliver seamless, intuitive interfaces. Imagine a world where your favorite products anticipate your needs, adapting and evolving in real-time – that's the power of AI and ML.

Real-world applications abound. From e-commerce platforms offering personalized shopping recommendations to tech companies using AI for predictive maintenance in hardware products, the possibilities are endless. AI and ML are not just buzzwords; they're driving tangible, measurable results.

But, as with any revolution, challenges abound. Data security, transparency, and ethical considerations loom large. Ensuring responsible use of AI and ML is paramount, safeguarding against biases and privacy infringements.

Yet, the future is bright. With AI and ML leading the charge, product development is poised for unprecedented innovation. As these technologies continue to evolve, the possibilities are limitless. It's a brave new world – one where products are not just tools but experiences, crafted with precision and care.

In conclusion, AI and ML are not just shaping the future of product development; they're redefining it. With their transformative power, we stand on the cusp of a new era – one where innovation knows no bounds. So, let's embrace the journey together, as we unveil the endless possibilities of AI and ML in product development.

And as you embark on this journey of innovation, consider leveraging the expertise of product development solutions providers. With their deep understanding of AI and ML, they can help you navigate the complexities of modern product design and development, ensuring that your products are not just cutting-edge but also market-ready. Let's explore the future of product development together, with AI and ML leading the way.

[cromacampusinstitute]

Machine learning and artificial intelligence (AI) are closely intertwined, with machine learning being a subset of AI. AI involves creating systems that can perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, and making decisions.

[reallytoosublime]

AI, or Artificial Intelligence, refers to the capability of machines or computer systems to mimic and simulate human intelligence processes. These processes include learning from experiences, reasoning to solve problems, understanding natural language, recognizing patterns, and making decisions. AI enables computers to perform tasks that typically require human intelligence, such as understanding speech, recognizing images, playing games, and even driving cars.

AI Ethics: Navigating the Dark Side of Artificial Intelligence

[youtubemarketing1234]

AI, or Artificial Intelligence, refers to the capability of machines or computer systems to mimic and simulate human intelligence processes. These processes include learning from experiences, reasoning to solve problems, understanding natural language, recognizing patterns, and making decisions. AI enables computers to perform tasks that typically require human intelligence, such as understanding speech, recognizing images, playing games, and even driving cars.

AI techniques can vary widely, and they include machine learning, neural networks, natural language processing, computer vision, and more. Machine learning, in particular, is a subset of AI that involves training algorithms to learn patterns from data and improve their performance over time.

AI ethics is a critical and evolving field that addresses the ethical challenges and concerns arising from the development and deployment of artificial intelligence (AI) technologies. As AI systems become increasingly integrated into various aspects of our lives, from healthcare to finance, entertainment to transportation, it's essential to navigate the potential "dark side" of AI to ensure its responsible and beneficial use.

Navigating the dark side of AI ethics requires a multidisciplinary approach involving technology experts, ethicists, policymakers, and society as a whole. By addressing these concerns proactively, we can maximize the benefits of AI while minimizing its potential negative impacts.

Addressing the dark side of AI requires a combination of robust regulations, responsible development practices, transparency, and ongoing research to mitigate potential risks and ensure that AI technologies are aligned with human values and interests. It's important for governments, industries, researchers, and the general public to work together to navigate these challenges and maximize the positive impacts of AI while minimizing its potential negative consequences.

AI Ethics: Navigating the Dark Side of Artificial Intelligence

[krazytechnews]

Transforming Railways with AI: Opportunities & Challenges

The integration of AI in railways promises to enhance efficiency, safety, and innovation. #artificialintelligence #ai

Artificial Intelligence (AI) is revolutionizing industries across the globe, and the railway sector is no exception. The integration of AI in railways promises to enhance efficiency, safety, and innovation, while also posing new challenges. Transforming Railways with AI includes autonomous trains, skill enhancement, optimized scheduling, enhanced safety, etc. Would you think AI will eventually…

[mobiloitteuk]

UK’s Pioneering Role in AI Regulation: A Pro-Innovation Blueprint for AI Technology

The realm of artificial intelligence (AI) is rapidly evolving, and with it comes the imperative for robust regulation. The United Kingdom, a hub for AI solutions and AI-powered mobile apps, has emerged as a trailblazer in this domain. This article delves into the UK’s recent White Paper on AI regulation, its implications for the global AI technology community, and how it aims to enhance customer experiences.

[krceseo]

Highlights of the Mechanical Engineering Department at KRCE

The Mechanical Engineering Department at K.Ramakrishnan College of Engineering (KRCE) stands as a beacon of excellence in engineering education and research. In fact, accredited by NBA and recognized as a Research Centre by Anna University, the department offers a nurturing environment for students to engage in the intricacies of mechanical engineering. Moreover, with state-of-the-art facilities, a seasoned faculty, and a dedication to innovation, the department at KRCE prepares students to thrive in the evolving landscape of modern engineering.

[f-identity]

[Image description: A series of posts from Jason Lefkowitz @jalefkowit@octodon.social dated Dec 08, 2022, 04:33, reading:

It's good that our finest minds have focused on automating writing and making art, two things human beings do simply because it brings them joy. Meanwhile tens of thousands of people risk their lives every day breaking down ships, a task that nobody is in a particular hurry to automate because those lives are considered cheap https://www.dw.com/en/shipbreaking-recycling-a-ship-is-always-dangerous/a-18155491 (Headline: 'Recycling a ship is always dangerous.' on Deutsche Welle) A world where computers write and make art while human beings break their backs cleaning up toxic messes is the exact opposite of the world I thought I was signing up for when I got into programming

/end image description]