#AI technology data

[ahb-writes]

(from The Mitchells vs. the Machines, 2021)

[enneadau]

EMERGENCY AUTHOR UPDATE

I feel like this needs to be warned about. Everything on Ao3 that isn't set to private, HAS been data scraped and fed to 3 data sites that provide data for AI training, including writing and artwork.

Yes, this includes my entire Ennead series and everything else I've ever written and posted. As well as anything you all have written but not made private.

Ao3's legal team is fighting it and one site has made the data unavailable, but the other two aren't based in the USA so the fight is harder.

This is frustrating and upsetting news, especially for those of us who now need to pick between our Guest readers who have supported us for a long time and protecting the hard work that we've put our hearts and souls into and I just ask that we support each other and our choices during this time.

The link here has more details but from now on, until I can be sure there's a way to protect my work, which I've spent decades writing and planning, my stories will be posted for members of the site only.

[fo3lonewanderer]

This is fucking horrifying. Trump is literally trying to turn the US into an authoritarian black mirror-esque police state where there is no privacy, no rights, and AI can pick out anyone who might oppose the regime and track them down with our private information being funneled into it.

https://www.nytimes.com/2025/05/30/technology/trump-palantir-data-americans.html

[metalcrows]

So what I find really interesting is how I absolutely hate current AI, but how much I love fictional robots/artificial intelligence. Every time the issue, "Can robots feel?" Is brought up in any kind of fictional media, I always firmly believe that they can. Just because they are not human doesn't mean they can't create and experience things. So why don't I feel this way about Chat GPT? I mean, it's an AI. Let's use Data from Star Trek as an example. He's a robot that is deemed incapable of human emotions, yet he still seems to simulate such emotions. He paints quite a bit, and I love all his art. However, when Chat GPT "paints," I hate it. It's stolen art. But Data kind of does the same thing, using vast amounts of previous examples to create something new. Both are AI that supposedly can't feel, but simulate human emotions and traits. SO WHAT TRULY IS THE DIFFERENCE? Is it because Data is more humanoid? That he uses a brush instead of a screen? Mabye, but probably not. Other examples of fictional AIs without a body make things on screen, and I still love it. So I don't know. I don't know why I feel like this. All I know is that I don't like Chat GPT or what it stands for. However, there is a small part of me scared to hate modern AI. Because what if I'm wrong and it can feel in some sort of strang way. Mabye it can't think like us, but perhaps it CAN think. I doubt this is the case, but still. Im scared how apathetic I am towards these AIs. Because what if one day we get robots that can think, and I become one of the people dismissing them instead of accepting them. This is just something I think about a lot lol

[turns-out-its-adhd]

AI exists and there's nothing any of us can do to change that.

If you have concerns about how AI is being/will be used the solution is not to abstain - it's to get involved.

Learn about it, practice utilising AI tools, understand it. Ignorance will not protect you, and putting your fingers in your ears going 'lalalala AI doesn't exist I don't acknowledge it' won't stop it from affecting your life.

The more the general population fears and misunderstands this technology, the less equipped they will be to resist its influence.

[catherinadodson1976blog]

[sugarandice3]

Nothing makes me want to go on a full-blown punk rampage more than the explicit violation of privacy that has become the status quo nowadays. This added with the fact that the general population (myself included) is technologically illiterate just makes this problem worse. People struggle to strike back effectively because the knowledge that gives us the power to do so is hard to acquire.

Misinformation, hidden features, ai, convoluted terms of service; all of has just become the norm!!!! Mostly due to the modern addition to convenience. No. Thank you.

The only way to make a change is to put in the hard work of educating yourself. Learn how technology works. Be aware of everything you agree to. Ignore the lure of frivolous convenience. Take measures to protect your privacy. It may be a slow process. Maybe you just start by switching which browser you use. This is good, this is an excellent start!!! The important part is that you care and you genuinely want to make a difference. You don't have to become a tech genius overnight, you just need to know more than the people trying to control you want you to know.

There is so much to sort through and so much more to learn, but I personally am going to start working toward understanding the technological world so that I can have my privacy and independence.

[queen-mabs-revenge]

communist generative ai boosters on this website truly like

[farmerstrend]

What Makes a Great Agronomist? Unpacking the Traits of Agricultural Excellence

Agronomists are the unsung heroes shaping the future of farming. They’re the bridge between science and soil, the architects of abundance in a world hungry for both food and sustainability. Over the years, after sifting through hundreds of agronomist resumes and meeting countless professionals in this field, I’ve come to realize that greatness in agronomy isn’t just about a degree or a title.…

[ai-innova7ions]

Neturbiz Enterprises - AI Innov7ions

Our mission is to provide details about AI-powered platforms across different technologies, each of which offer unique set of features. The AI industry encompasses a broad range of technologies designed to simulate human intelligence. These include machine learning, natural language processing, robotics, computer vision, and more. Companies and research institutions are continuously advancing AI capabilities, from creating sophisticated algorithms to developing powerful hardware. The AI industry, characterized by the development and deployment of artificial intelligence technologies, has a profound impact on our daily lives, reshaping various aspects of how we live, work, and interact.

[noosphe-re]

We're all generative AIs — we're all vast data sets of every experience we've ever had. Generative AI can give you a bitmap and give you an image, but can't give you an emotion.

James Cameron, "Cameron says AI could one day direct films, but not out-act Schwarzenegger", Christopher Grimes, FT Weekend, 27/28 April 2024

[thoughtportal]

To be clear, AI can drive scientific breakthroughs. My concern is about their magnitude and frequency. Has AI really shown enough potential to justify such a massive shift in talent, training, time, and money away from existing research directions and towards a single paradigm?

Every field of science is experiencing AI differently, so we should be cautious about making generalizations. I’m convinced, however, that some of the lessons from my experience are broadly applicable across science:

AI adoption is exploding among scientists less because it benefits science and more because it benefits the scientists themselves.

Because AI researchers almost never publish negative results, AI-for-science is experiencing survivorship bias.

The positive results that get published tend to be overly optimistic about AI’s potential.

As a result, I’ve come to believe that AI has generally been less successful and revolutionary in science than it appears to be.

Ultimately, I don’t know whether AI will reverse the decades-long trend of declining scientific productivity and stagnating (or even decelerating) rates of scientific progress. I don’t think anyone does. But barring major (and in my opinion unlikely) breakthroughs in advanced AI, I expect AI to be much more a normal tool of incremental, uneven scientific progress than a revolutionary one.

[xaltius]

Unlocking the Power of Data: Essential Skills to Become a Data Scientist

In today's data-driven world, the demand for skilled data scientists is skyrocketing. These professionals are the key to transforming raw information into actionable insights, driving innovation and shaping business strategies. But what exactly does it take to become a data scientist? It's a multidisciplinary field, requiring a unique blend of technical prowess and analytical thinking. Let's break down the essential skills you'll need to embark on this exciting career path.

1. Strong Mathematical and Statistical Foundation:

At the heart of data science lies a deep understanding of mathematics and statistics. You'll need to grasp concepts like:

Linear Algebra and Calculus: Essential for understanding machine learning algorithms and optimizing models.

Probability and Statistics: Crucial for data analysis, hypothesis testing, and drawing meaningful conclusions from data.

2. Programming Proficiency (Python and/or R):

Data scientists are fluent in at least one, if not both, of the dominant programming languages in the field:

Python: Known for its readability and extensive libraries like Pandas, NumPy, Scikit-learn, and TensorFlow, making it ideal for data manipulation, analysis, and machine learning.

R: Specifically designed for statistical computing and graphics, R offers a rich ecosystem of packages for statistical modeling and visualization.

3. Data Wrangling and Preprocessing Skills:

Raw data is rarely clean and ready for analysis. A significant portion of a data scientist's time is spent on:

Data Cleaning: Handling missing values, outliers, and inconsistencies.

Data Transformation: Reshaping, merging, and aggregating data.

Feature Engineering: Creating new features from existing data to improve model performance.

4. Expertise in Databases and SQL:

Data often resides in databases. Proficiency in SQL (Structured Query Language) is essential for:

Extracting Data: Querying and retrieving data from various database systems.

Data Manipulation: Filtering, joining, and aggregating data within databases.

5. Machine Learning Mastery:

Machine learning is a core component of data science, enabling you to build models that learn from data and make predictions or classifications. Key areas include:

Supervised Learning: Regression, classification algorithms.

Unsupervised Learning: Clustering, dimensionality reduction.

Model Selection and Evaluation: Choosing the right algorithms and assessing their performance.

6. Data Visualization and Communication Skills:

Being able to effectively communicate your findings is just as important as the analysis itself. You'll need to:

Visualize Data: Create compelling charts and graphs to explore patterns and insights using libraries like Matplotlib, Seaborn (Python), or ggplot2 (R).

Tell Data Stories: Present your findings in a clear and concise manner that resonates with both technical and non-technical audiences.

7. Critical Thinking and Problem-Solving Abilities:

Data scientists are essentially problem solvers. You need to be able to:

Define Business Problems: Translate business challenges into data science questions.

Develop Analytical Frameworks: Structure your approach to solve complex problems.

Interpret Results: Draw meaningful conclusions and translate them into actionable recommendations.

8. Domain Knowledge (Optional but Highly Beneficial):

Having expertise in the specific industry or domain you're working in can give you a significant advantage. It helps you understand the context of the data and formulate more relevant questions.

9. Curiosity and a Growth Mindset:

The field of data science is constantly evolving. A genuine curiosity and a willingness to learn new technologies and techniques are crucial for long-term success.

10. Strong Communication and Collaboration Skills:

Data scientists often work in teams and need to collaborate effectively with engineers, business stakeholders, and other experts.

Kickstart Your Data Science Journey with Xaltius Academy's Data Science and AI Program:

Acquiring these skills can seem like a daunting task, but structured learning programs can provide a clear and effective path. Xaltius Academy's Data Science and AI Program is designed to equip you with the essential knowledge and practical experience to become a successful data scientist.

Key benefits of the program:

Comprehensive Curriculum: Covers all the core skills mentioned above, from foundational mathematics to advanced machine learning techniques.

Hands-on Projects: Provides practical experience working with real-world datasets and building a strong portfolio.

Expert Instructors: Learn from industry professionals with years of experience in data science and AI.

Career Support: Offers guidance and resources to help you launch your data science career.

Becoming a data scientist is a rewarding journey that blends technical expertise with analytical thinking. By focusing on developing these key skills and leveraging resources like Xaltius Academy's program, you can position yourself for a successful and impactful career in this in-demand field. The power of data is waiting to be unlocked – are you ready to take the challenge?

[rustedsnotter]

It is worrying that (new) technologies are being used in unethical ways to maximize profit.

[hallucineet9000]

Ancient Rome's Secret Data Center

When Caesar needs cloud storage 💾⚔️

Marble columns meet server farms in this temporal glitch