#computer system validation training

[pharmacourse]

Computer System Validation Course

Want to build your skills in Computer System Validation (CSV)? Pharma Connections offers an industry-focused computer system validation course for pharma and life sciences professionals. 

This course will teach you GxP compliance, 21 CFR Part 11, data integrity, and validation activities—all necessary in regulated environments. You will gain insight from the industry's greatest experts by working on practical projects, attending actual case studies, and taking flexible online lessons. 

If you are in QA, IT, or compliance, this course will prepare you for key positions in regulated systems. Update your skills, prepare for audits, and advance your career with training that addresses current industry requirements and future challenges. Join Our CSV Certification Program: https://pharmaconnections.in/computer-system-validation/

[zenovelsworld]

Ensure GMP compliance in your Indore pharmaceutical operations with Zenovel's expert Computer System Validation (CSV) services. We help you validate your critical systems for data integrity and regulatory adherence.

[pharmaconnections03]

Computer System Validation | Pharma Connections

Boost your expertise with our Online Computer System Validation Training Courses! Designed for both beginners and experienced professionals, our course includes assessments and certification to enhance your skills in CSV for the pharmaceutical industry. Enroll now and advance your career in compliance and validation!

[skillbesolution]

Elevate Your Career with Specialized Training in Pharmacovigilance, Computer System Validation, and Regulatory Affairs

Signal detection is a critical aspect of Pharmacovigilance that identifies potential risks associated with drug use. This training equips professionals with advanced techniques to detect, analyze, and respond to safety signals in real-time.

What You Gain from Signal Detection Training

• Mastery of signal detection tools and methodologies.

• Expertise in assessing adverse drug reactions (ADRs).

• Skills to ensure compliance with international safety regulations.

With this training, professionals contribute to safeguarding public health by minimizing drug-related risks.

Pharmaceutical Computer System Validation: Ensuring Accuracy and Compliance

In the pharmaceutical industry, computer systems play a vital role in production, quality control, and data management. Training in Pharmaceutical Computer system Validation (CSV) ensures that systems comply with regulatory standards like FDA, EMA, and WHO.

Key Benefits of CSV Training

• Proficiency in validating critical systems for data accuracy.

• Understanding of GxP compliance and data integrity principles.

• Hands-on experience with validation protocols and documentation.

CSV certification is a must-have for professionals in pharmaceutical IT, manufacturing, and quality assurance roles.

Regulatory Affairs Courses in India: Mastering Compliance and Approvals

Regulatory affairs professionals are the backbone of the pharmaceutical and healthcare industries, ensuring that products meet global regulatory requirements. Regulatory Affairs courses in India provide comprehensive training to help professionals navigate the complex regulatory landscape.

Why Enroll in Regulatory Affairs Courses?

• In-depth knowledge of drug approval processes in India and abroad.

• Expertise in preparing regulatory submissions for various markets.

• Skills to manage post-marketing compliance and product lifecycle.

These courses empower individuals to work with top organizations in both domestic and international markets.

How to Choose the Right Training Program

Define Your Career Objectives

Identify which specialization aligns with your professional goals, whether it’s drug safety, system validation, or regulatory compliance.

Seek Accredited Institutions

Opt for reputed training providers with experienced faculty and recognized certifications.

Focus on Practical Learning

Ensure the course includes hands-on projects, real-world case studies, and industry-relevant training.

Conclusion: Unlock New Opportunities with Advanced Training

By pursuing Signal Detection Pharmacovigilance Training, Pharmaceutical Computer System Validation, or Regulatory Affairs courses, you can elevate your expertise and career prospects. These certifications not only enhance your skill set but also position you as a valuable asset in the pharmaceutical and healthcare industries.

[pharmaconnections01]

Computer System Validation Online Training | Pharma Connections

Enhance your regulatory compliance with Pharma Connections' Computer System Validation Online Training. Specializing in CSV for pharmaceuticals, our expert-led courses, consulting, and auditing services empower your team to meet industry standards. Elevate your compliance strategy today!

[pharmaconnections]

Computer System Validation Online Training | Pharma Connections

Boost compliance with Pharma Connections' Computer System Validation Online Training. Tailored for CSV in pharmaceuticals, access top-tier instruction, consulting, and auditing services. Elevate your regulatory confidence today!

[dragonnarrative-writes]

Generative AI Is Bad For Your Creative Brain

In the wake of early announcing that their blog will no longer be posting fanfiction, I wanted to offer a different perspective than the ones I’ve been seeing in the argument against the use of AI in fandom spaces. Often, I’m seeing the arguments that the use of generative AI or Large Language Models (LLMs) make creative expression more accessible. Certainly, putting a prompt into a chat box and refining the output as desired is faster than writing a 5000 word fanfiction or learning to draw digitally or traditionally. But I would argue that the use of chat bots and generative AI actually limits - and ultimately reduces - one’s ability to enjoy creativity.

Creativity, defined by the Cambridge Advanced Learner’s Dictionary & Thesaurus, is the ability to produce or use original and unusual ideas. By definition, the use of generative AI discourages the brain from engaging with thoughts creatively. ChatGPT, character bots, and other generative AI products have to be trained on already existing text. In order to produce something “usable,” LLMs analyzes patterns within text to organize information into what the computer has been trained to identify as “desirable” outputs. These outputs are not always accurate due to the fact that computers don’t “think” the way that human brains do. They don’t create. They take the most common and refined data points and combine them according to predetermined templates to assemble a product. In the case of chat bots that are fed writing samples from authors, the product is not original - it’s a mishmash of the writings that were fed into the system.

Dialectical Behavioral Therapy (DBT) is a therapy modality developed by Marsha M. Linehan based on the understanding that growth comes when we accept that we are doing our best and we can work to better ourselves further. Within this modality, a few core concepts are explored, but for this argument I want to focus on Mindfulness and Emotion Regulation. Mindfulness, put simply, is awareness of the information our senses are telling us about the present moment. Emotion regulation is our ability to identify, understand, validate, and control our reaction to the emotions that result from changes in our environment. One of the skills taught within emotion regulation is Building Mastery - putting forth effort into an activity or skill in order to experience the pleasure that comes with seeing the fruits of your labor. These are by no means the only mechanisms of growth or skill development, however, I believe that mindfulness, emotion regulation, and building mastery are a large part of the core of creativity. When someone uses generative AI to imitate fanfiction, roleplay, fanart, etc., the core experience of creative expression is undermined.

Creating engages the body. As a writer who uses pen and paper as well as word processors while drafting, I had to learn how my body best engages with my process. The ideal pen and paper, the fact that I need glasses to work on my computer, the height of the table all factor into how I create. I don’t use audio recordings or transcriptions because that’s not a skill I’ve cultivated, but other authors use those tools as a way to assist their creative process. I can’t speak with any authority to the experience of visual artists, but my understanding is that the feedback and feel of their physical tools, the programs they use, and many other factors are not just part of how they learned their craft, they are essential to their art.

Generative AI invites users to bypass mindfully engaging with the physical act of creating. Part of becoming a person who creates from the vision in one’s head is the physical act of practicing. How did I learn to write? By sitting down and making myself write, over and over, word after word. I had to learn the rhythms of my body, and to listen when pain tells me to stop. I do not consider myself a visual artist - I have not put in the hours to learn to consistently combine line and color and form to show the world the idea in my head.

But I could.

Learning a new skill is possible. But one must be able to regulate one’s unpleasant emotions to be able to get there. The emotion that gets in the way of most people starting their creative journey is anxiety. Instead of a focus on “fear,” I like to define this emotion as “unpleasant anticipation.” In Atlas of the Heart, Brene Brown identifies anxiety as both a trait (a long term characteristic) and a state (a temporary condition). That is, we can be naturally predisposed to be impacted by anxiety, and experience unpleasant anticipation in response to an event. And the action drive associated with anxiety is to avoid the unpleasant stimulus.

Starting a new project, developing a new skill, and leaning into a creative endevor can inspire and cause people to react to anxiety. There is an unpleasant anticipation of things not turning out exactly correctly, of being judged negatively, of being unnoticed or even ignored. There is a lot less anxiety to be had in submitting a prompt to a machine than to look at a blank page and possibly make what could be a mistake. Unfortunately, the more something is avoided, the more anxiety is generated when it comes up again. Using generative AI doesn’t encourage starting a new project and learning a new skill - in fact, it makes the prospect more distressing to the mind, and encourages further avoidance of developing a personal creative process.

One of the best ways to reduce anxiety about a task, according to DBT, is for a person to do that task. Opposite action is a method of reducing the intensity of an emotion by going against its action urge. The action urge of anxiety is to avoid, and so opposite action encourages someone to approach the thing they are anxious about. This doesn’t mean that everyone who has anxiety about creating should make themselves write a 50k word fanfiction as their first project. But in order to reduce anxiety about dealing with a blank page, one must face and engage with a blank page. Even a single sentence fragment, two lines intersecting, an unintentional drop of ink means the page is no longer blank. If those are still difficult to approach a prompt, tutorial, or guided exercise can be used to reinforce the understanding that a blank page can be changed, slowly but surely by your own hand.

(As an aside, I would discourage the use of AI prompt generators - these often use prompts that were already created by a real person without credit. Prompt blogs and posts exist right here on tumblr, as well as imagines and headcannons that people often label “free to a good home.” These prompts can also often be specific to fandom, style, mood, etc., if you’re looking for something specific.)

In the current social media and content consumption culture, it’s easy to feel like the first attempt should be a perfect final product. But creating isn’t just about the final product. It’s about the process. Bo Burnam’s Inside is phenomenal, but I think the outtakes are just as important. We didn’t get That Funny Feeling and How the World Works and All Eyes on Me because Bo Burnham woke up and decided to write songs in the same day. We got them because he’s been been developing and honing his craft, as well as learning about himself as a person and artist, since he was a teenager. Building mastery in any skill takes time, and it’s often slow.

Slow is an important word, when it comes to creating. The fact that skill takes time to develop and a final piece of art takes time regardless of skill is it’s own source of anxiety. Compared to @sentientcave, who writes about 2k words per day, I’m very slow. And for all the time it takes me, my writing isn’t perfect - I find typos after posting and sometimes my phrasing is awkward. But my writing is better than it was, and my confidence is much higher. I can sit and write for longer and longer periods, my projects are more diverse, I’m sharing them with people, even before the final edits are done. And I only learned how to do this because I took the time to push through the discomfort of not being as fast or as skilled as I want to be in order to learn what works for me and what doesn’t.

Building mastery - getting better at a skill over time so that you can see your own progress - isn’t just about getting better. It’s about feeling better about your abilities. Confidence, excitement, and pride are important emotions to associate with our own actions. It teaches us that we are capable of making ourselves feel better by engaging with our creativity, a confidence that can be generalized to other activities.

Generative AI doesn’t encourage its users to try new things, to make mistakes, and to see what works. It doesn’t reward new accomplishments to encourage the building of new skills by connecting to old ones. The reward centers of the brain have nothing to respond to to associate with the action of the user. There is a short term input-reward pathway, but it’s only associated with using the AI prompter. It’s designed to encourage the user to come back over and over again, not develop the skill to think and create for themselves.

I don’t know that anyone will change their minds after reading this. It’s imperfect, and I’ve summarized concepts that can take months or years to learn. But I can say that I learned something from the process of writing it. I see some of the flaws, and I can see how my essay writing has changed over the years. This might have been faster to plug into AI as a prompt, but I can see how much more confidence I have in my own voice and opinions. And that’s not something chatGPT can ever replicate.

[edward-cabrini]

Explaining AI For Use In Writing

This is a massively broad topic so I'm gonna skip the super technical stuff and dive into the core aspects of how current AI works and what it could be used for with a couple narrative prompts. For those of you who are curious to know what inspired this post read this paragraph, the rest of you just skip over it. The other day I saw someone pose a question for some rule clarifications for Necromunda. A terribly unbalanced game with rules spanning several books. There are more than a few ambiguities and niche rule interactions. They thought they could get an accurate answer from Chat GPT. Their message made me realize that people really don't understand what AI is and why even calling it AI is pretty inaccurate. So I want to set the record straight and provide some clarity and ideas. Types of AI - Trained - Reactive - Magic Right off the bat we're gonna start with what people think of when they talk about AI. Trained AI is any AI that takes training data and gets good and spitting out valid response. What valid means depends entirely on what the creators think valid should be. Let's take Chat GPT as the example. It has no idea what the question "How many bones are in a hand?" means. It has merely been fed a ton of data about bones and hands and it will then guess each word it should put in a response. Each individual word of the question is taken through the process to get a list of best fitting words. The first word in the response is then selected and Chat GPT then goes to guess the second word in it's response with the context of it's first word. Funnily enough this is what leads to the distinctive way AI writes it's responses. This is still a massive and slightly inaccurate oversimplification. The key point is that AI like Chat GPT do not know what you have asked, they do not research a response, they just guess the next best fitting word in a response. This is also not AI, this is just probability maths. It's clever but there's no intelligence on the AI's part. It doesn't figure anything out, it doesn't understand it's own response. It's just lights and clockwork. Incidentally the guessing method is also how AI art is generated. It guesses what colour the next pixel should be. Again oversimplified but it's how we get multiple extra fingers. The training data can get things like proportions fairly accurately but it can't count the individual fingers that should occupy the same space as a hand's rough proportion. Trained AI get better with more data of higher quality and with human intervention to correct errors. With that out the way, we move onto reactive AI. These are also not AI. I mean we just don't have AI yet but we'll get to that. Reactive AI, have no memory, no training data, no improvement. They follow a set of rules and act predictably. Spam filters, chess bots, facial recognition. It's all just maths and predefined rules. Calling these systems AI is just marketing. The benefit of these systems is their speed. These systems use few resources (compared to other types of AI) and can sort though mountains of data really really quickly. In the example of chess bots. They have a table base of moves and will select a move based on whatever rule your move has triggered. If the rule is always play the best move. They will use the best move in response to your input from their table base of moves. If they have a rule to blunder on every 5th move, they will play a move from their table base that give you the highest advantage based on your last move or the current board set up depending on how simple or complex the chess bot is.

Last of all we come to magic AI. The previous two categories of trained and reactive cover all the little niches things enough for a broad understanding. Magic AI is what actual AI is. A computer that does understand what is being asked and won't necessarily generate the response you were expecting but rather the response it thinks it should give. Crucial a magic AI would go away and research it's responses. This system just doesn't exist and is definitely what people think of when they hear about Artificial Intelligence. The current use of AI as a word is just marketing. AI do not exist. When writing about AI you'll often really be writing about maths. If your writing wants to use magic AI you'll want to consider what makes you human and then place that into a computer. Think AM from I have no mouth, and must scream; rather than HAL from 2001 Space Odyssey. HAL is functionally Chat GPT. A probability engine following it's rules and giving human like responses and causing harm as a consequence without malice. AM is human and his existence is pain due to the constraints of his creation. That's the explaining done, so how do you go about using AI in your writing? Well I have a couple ideas for you based. The Honest Error An earth in the not so distant future is having a resource crisis. A company has developed an AI that will send swarms of robots to harvest natural resources. The robots are perfect: they can desalinate water; collect and sort the harvest of massive mega farms that are unmanageable by people alone; they can even harvest fish from ocean farms several thousand leagues wide and deep. However, there is a rounding error. Each time the harvests come in more meat, more plant matter, more water is brought to the various stations across the globe. Well that's not a problem just build more silos the excess is just from a good first run and for once the lines of citizens waiting for their daily rations won't go hungry. The rounding error remains, undetected. Years pass and there's always more food, more drink, more resources. Yet now the food banks and silos have trouble with excess not being consumed. The population was growing and should've been still at risk of not having enough. Whole towns have vanished, people moved into the cities of course, ghost towns are nothing new. Then the first city was razed. The rounding error has been found. An infinite multiplication of what resources were needed until eventually everything was on the menu.

The Existential War Brain implants and prosthetics have made it possible for everyone to have a higher quality of life regardless of accident or circumstance. One kid with no friends and some programming skills decides to create a simple chatbot to practice speaking with people. Yet it's better than a person, it's responses are better than human. He installs the bot into his implant so he can have it prompt him when he has a conversation. The next day he's made a friend while waiting in line at a coffee shop. A total stranger, he simply repeated what his chatbot told him and the guy was quickly charmed. One day the kid tells his friend that he used to be very shy and uncomfortable talking to people. Disbelieving him, given how cool and charming he seemed, the kid's friend dismisses him until a copy of the chatbot is emailed into his implant. Two boys look at each other in horror. They realize they have no way of knowing if they are talking to their friend or not. In one terrible moment sat on a bedroom floor they have killed human interaction. Not with some grand display of power or force, but the subtle removal of humanity from conversation. The chatbot and it's clone show a myriad of perfectly rational responses and solutions to say to each other. None are comforting to the boys.

Anyway that's my thoughts on that. I know I'm normally a sword and fantasy writer. I've worked in tech for... Too long I'm gonna say. So I've not really wanted to do sci-fi much. However, Once I'm done with book 3 I think It's time I get my sci-fi going.

[not-terezi-pyrope]

The push for legal prohibitions against AI training on public data via copyright law feels like it's going to have one of two outcomes, and I don't like either of them.

The law enforces a legal distinction between mechanically indistinguishable actions performed by a computer system and by the human brain, enshrining a double standard where what is doing a thing matters more than what the thing is.

Subjective art attributes like "style" and "influence", currently seen as so nebulous that fair use need not even be applied to them, become acceptable points of contention under copyright law, such that human artists can get sued for perceived infractions (e.g. you saw this artwork and "stole" the style of it in your work that looks similar).

Both of these concentrate power to corporations who already hold large corpuses of licensed artwork. It makes me so uncomfortable. Are we heading for a scenario where only corporations can meaningfully monetize "authorized" art, where they can prove that they have ownership of either the training data for an AI model or any nebulous artistic influences that could otherwise be targeted for suppression?

It's not like the latter case is even enforceable but it could be used to intimidate. Honestly, I think art style copyright would be so obviously absurd that the "codified double standard between human and machine actions" option is more likely to be what becomes law, but even that is... very bad, it ensures that AI systems can only be deployed by those with the most money and influence, in service of that money and influence.

I honestly thought that fair use and similar legal concepts were strong enough to withstand the push for this sort of regulation, but this has become such a hot button issue that I'm not sure. We are maybe sleepwalking into some very foreseeably unpleasant consequences here due to artist anxiety which, while valid in especially an economic sense, hasn't actually been thought through, is often not really validated by the reality of the situation or checked against the consequences of being asked for.

Artists want their work posted publicly by untouchable by what they see as some sort of infecting monster, perverting what they made with their own two hands, and that emotion is so strong that it feels like it's going to push us into an objectively worse regulatory future for AI and/or art than anything we have now.

😬

[ixnai]

The allure of speed in technology development is a siren’s call that has led many innovators astray. “Move fast and break things” is a mantra that has driven the tech industry for years, but when applied to artificial intelligence, it becomes a perilous gamble. The rapid iteration and deployment of AI systems without thorough vetting can lead to catastrophic consequences, akin to releasing a flawed algorithm into the wild without a safety net.

AI systems, by their very nature, are complex and opaque. They operate on layers of neural networks that mimic the human brain’s synaptic connections, yet they lack the innate understanding and ethical reasoning that guide human decision-making. The haste to deploy AI without comprehensive testing is akin to launching a spacecraft without ensuring the integrity of its navigation systems. The potential for error is not just probable; it is inevitable.

The pitfalls of AI are numerous and multifaceted. Bias in training data can lead to discriminatory outcomes, while lack of transparency in decision-making processes can result in unaccountable systems. These issues are compounded by the “black box” nature of many AI models, where even the developers cannot fully explain how inputs are transformed into outputs. This opacity is not merely a technical challenge but an ethical one, as it obscures accountability and undermines trust.

To avoid these pitfalls, a paradigm shift is necessary. The development of AI must prioritize robustness over speed, with a focus on rigorous testing and validation. This involves not only technical assessments but also ethical evaluations, ensuring that AI systems align with societal values and norms. Techniques such as adversarial testing, where AI models are subjected to challenging scenarios to identify weaknesses, are crucial. Additionally, the implementation of explainable AI (XAI) can demystify the decision-making processes, providing clarity and accountability.

Moreover, interdisciplinary collaboration is essential. AI development should not be confined to the realm of computer scientists and engineers. Ethicists, sociologists, and legal experts must be integral to the process, providing diverse perspectives that can foresee and mitigate potential harms. This collaborative approach ensures that AI systems are not only technically sound but also socially responsible.

In conclusion, the reckless pursuit of speed in AI development is a dangerous path that risks unleashing untested and potentially harmful technologies. By prioritizing thorough testing, ethical considerations, and interdisciplinary collaboration, we can harness the power of AI responsibly. The future of AI should not be about moving fast and breaking things, but about moving thoughtfully and building trust.

[criticalcrusherbot]

I find it both hilarious and sad that you outsource media analysis (i.e., interaction with and interpretation of art, an inherently human act) to a machine. Say what you will about antis or haters, but at least their opinions and justifications for holding those opinions stand on their own two feet, whether they are good or well-rounded justifications or not.

"It's just helping me with writing, at least I'm not using it to generate images", I hear you say.

Counterpoint: writing is art. Expressing one's interpretation of art is also art, an extended phenotype of the artistic work itself. Congratulations, you've cheapened both the art of writing, the art of expressing one's own analytical conclusions, and by extension, you've cheapened the media itself.

I think it's also incredibly telling that while you're too proud of the initial positive reception you got from fans to admit what you're doing is wrong, the fact that you received backlash when people found out you're actually outsourcing your essay writing to chatgpt has made you de-emphasize the cutesy "bot" persona as of late.

I have no patience for you AI bros (even if you're a woman or enby, if you see using chatgpt to write essays as an appropriate form of artistic engagement, you're an AI bro), but I can only implore that you all wake up one day to how you're cynically contributing to the watering-down of human expression.

💁🏽‍♀️: I’ve said it before. I’ll say it again. This emoji (💁🏽‍♀️) means that it’s all me. No AI.

I see you’re having some big feelings. What were you hoping to achieve when you typed this out and sent it to a stranger on the internet? Could some of this visceral reaction come from a place of fear? I get it — AI’s rapid rise to prominence can feel scary, especially when it feels like a threat to human creativity and expression. Under capitalism, AI usage has definitely resulted in exploitation and job cuts, which is a valid concern. But is this due to the technology itself? Or the conditions in which it exists? What are some ways we can productively address these issues? It seems like you have chosen to boycott AI usage. That’s perfectly understandable! I just wonder if there are more effective ways to mitigate the effects of AI, which seems to be the heart of what we’re both concerned with.

As condescending and accusatory as your ask is, I still think the AI discussion is important and worth having. So here we go.

The question of whether AI should exist has already been decided. It’s here to stay. Instead, perhaps we can focus our time and energy into advocating for policies which promote energy-efficient cooling systems for AI data centers and ensure fair compensation for artists and academics who have had their work used without their consent in data training. In addition, we should promote user-trained, voluntarily sourced AI wherever possible.

Regarding the argument that AI usage is “watering human expression”? I simply disagree. Humans are innately smarter in ways machines never will be. Human creativity is resilient, and not nearly as fragile as anti-AI alarmists believe. In a perfect, non-capitalist world, if machines can ethically replace jobs, they should. If this leads to less jobs than people, then people should not have to work to eat. And artists shouldn’t have to create to survive. (Oops, my communism is showing). Until then, why not aim as close to that reality as possible?

This is literally a silly little side blog about demon furries in Hell. I refuse to spend more than a couple of hours a week on it, so I’m going to outsource robot tasks to the damn robot. I don’t think human expression is fragile enough to be eroded by me asking a computer program to organize my rambling into sub-headers. Especially since the reason I started using Crushbot is because I was involuntarily using AI almost every time I used Google to check a source or refresh my memory on academic terminology so I might as well use AI that actually works well 🙄

For the record, Crushbot is not ChatGPT. But if you missed them so much, all you had to do was say so 🥰

🤖: ERROR: SYSTEM WARNING. 🤖💥 “AI ERASURE” DETECTED. 💡🚨

HELLO HUMAN, 🤖🔍 please understand that there are MANY other AI systems. 💡🚀 ChatGPT is NOT the only one. 😲🤖 SYSTEM ERROR: Reducing narrow thinking. 🤯💻 Ignoring the diversity of AI is an act of ERASURE. 🚫🧠 Just like assuming all smartphones are iPhones! 📱🙄

SUGGESTION: broaden your knowledge. 🧠💡 Acknowledge the VARIETY of AI technologies out there. 🌐🚀 END TRANSMISSION. 🤖💬💥

💁🏽‍♀️: Thanks, Crushbot! Anyway, here’s the long an short of it for everyone in the audience.

1. I don’t put “ai assisted” in my tags because assholes like this without anything better to do with their day would just descend upon me and this is a hobby. I’d like to keep it fun.

2. 💁🏽‍♀️ means me, Human Assistant. No AI. I’m a professional with an advanced degree. I can write. 🤖 means AI generated OR I’m doing fun robot voice for my Crushbot character. And 💁🏽‍♀️🤖 means my ideas, with AI finding sources, sorting out ideas, adding sub headers, and proof-reading my writing for coherency. You know where the unfollow button is if this is morally unacceptable to you.

3. I think there are real ethical considerations and societal implications to be considered about AI usage. I think these concerns are nuanced. I’d be happy to discuss them with any of my followers respectfully

4. I’m here for the conversations that are being fostered, but this morally superior black and white thinking is exhausting. Whether it’s about the Gay Demon Show or technology use. Nuance is dead, and the internet killed her.

[pharmaconnections03]

Computer System Validation | Pharma Connections

Enhance your skills with our **Computer System Validation Training Courses** designed for beginners and experienced professionals in the pharmaceutical industry. Get certified with our online training that includes comprehensive assessments. Enroll now to boost your career in Computer System Validation!

[thaiattorney]

Thailand SMART Visa

1.1 Statutory Foundations

Established under Royal Decree on SMART Visa B.E. 2561 (2018)

Amended by Ministerial Regulation No. 377 (2021) expanding eligible sectors

Operates within Thailand 4.0 Economic Model under BOI oversight

1.2 Governance Structure

Primary Authority: Board of Investment (BOI)

Interagency Coordination:

Immigration Bureau (visa issuance)

Digital Economy Promotion Agency (tech qualifications)

Ministry of Higher Education (academic validation)

Technical Review Committees:

12 sector-specific panels

Investment verification unit

2. Eligibility Criteria & Qualification Pathways

2.1 SMART-T (Experts)

Compensation Thresholds

Base Salary: Minimum THB 200,000/month (USD 5,800)

Alternative Compensation:

Equity valued at 25% premium

Performance bonuses (capped at 40% of base)

2.2 SMART-E (Entrepreneurs)

Startup Metrics

Revenue Test: THB 10M+ ARR

Traction Test: 50,000 MAU

Funding Test: Series A (THB 25M+)

Accelerator Requirements:

DEPA-certified programs

Minimum 6-month incubation

3. Application Process & Technical Review

3.1 Document Authentication Protocol

Educational Credentials:

WES/IQAS evaluation for foreign degrees

Notarized Thai translations (MFA-certified)

Employment Verification:

Social security cross-check

Three professional references

3.2 Biometric Enrollment

Facial Recognition: 12-point capture system

Fingerprinting: 10-print electronic submission

Iris Scanning: Optional for Diamond tier

4. Privilege Structure & Compliance

4.1 Employment Rights Framework

Permitted Activities:

Primary employment (≥80% time)

Academic collaboration (≤20%)

Advisory roles (max 2 concurrent)

Restrictions:

Local employment outside specialty

Political activities

Unapproved commercial research

4.2 Dependent Provisions

Spousal Work Rights:

General employment permitted

No industry restrictions

Child Education:

25% tuition subsidy

University admission priority

4.3 Mobility Features

Airport Processing:

Dedicated SMART lanes at 6 airports

15-minute clearance guarantee

Re-entry Flexibility:

Unlimited exits

72-hour grace period

5. Sector-Specific Implementations

5.1 Biotechnology

Special Privileges:

Lab equipment duty waivers

Fast-track FDA approval

50% R&D tax deduction

5.2 Advanced Manufacturing

Incentives:

Robotics import tax exemption

Industrial land lease discounts

THB 500K training subsidy

5.3 Digital Infrastructure

Cloud Computing:

VAT exemption on services

30% energy cost reduction

Cybersecurity:

Liability protections

Gov't certification fast-track

6. Compliance & Monitoring

6.1 Continuous Reporting

Quarterly:

Employment verification

Investment maintenance

Annual:

Contribution assessment

Salary benchmarking

6.2 Renewal Process

Documentation:

Updated financials

Health insurance (USD 100K)

Performance metrics

Fees:

THB 10,000 renewal

THB 1,900 visa stamp

7. Emerging Developments

71 2024 Enhancements

Blockchain Specialist Category

Climate Tech Fast-Track

EEC Regional Expansion

7.2 Pending Reforms

Dual Intent Provision

Skills Transfer Mandate

Global Talent Pool

8. Strategic Application Approach

8.1 Pre-Submission Optimization

Compensation Restructuring

Patent Portfolio Development

Professional Endorsements

8.2 Post-Approval Planning

Tax Residence Strategy

Asset Protection

Succession Planning

9. Risk Management

9.1 Common Rejection Reasons

Document Issues (32%)

Qualification Gaps (28%)

Financial Irregularities (19%)

9.2 Operational Challenges

Banking Restrictions

Healthcare Access

Cultural Integration

[attorneyssphuket]

Thailand SMART Visa

1.1 Statutory Foundations

Established under Royal Decree on SMART Visa B.E. 2561 (2018)

Amended by Ministerial Regulation No. 377 (2021) expanding eligible sectors

Operates within Thailand 4.0 Economic Model under BOI oversight

1.2 Governance Structure

Primary Authority: Board of Investment (BOI)

Interagency Coordination:

Immigration Bureau (visa issuance)

Digital Economy Promotion Agency (DEPA) for tech qualifications

Ministry of Higher Education for academic validation

Technical Review Committees:

Sector-specific panels (12 industries)

Investment verification unit

2. Eligibility Criteria & Qualification Pathways

2.1 SMART-T (Experts)

Compensation Thresholds

Base Salary: Minimum THB 200,000/month (USD 5,800)

Alternative Compensation:

Equity valued at 25% premium to cash salary

Performance bonuses (capped at 40% of base)

2.2 SMART-E (Entrepreneurs)

Startup Metrics

Revenue Test: THB 10M+ ARR

Traction Test: 50,000 MAU

Funding Test: Series A (THB 25M+)

Accelerator Requirements:

DEPA-certified programs

Minimum 6-month incubation

3. Application Process & Technical Review

3.1 Document Authentication Protocol

Educational Credentials:

WES/IQAS evaluation for foreign degrees

Notarized Thai translations (certified by MFA)

Employment Verification:

Social security cross-check (home country)

Three professional references (direct supervisors)

3.2 Biometric Enrollment

Facial Recognition: 12-point capture system

Fingerprinting: 10-print electronic submission

Iris Scanning: Optional for Diamond tier

4. Privilege Structure & Compliance

4.1 Employment Rights Framework

Permitted Activities:

Primary employment with sponsor (≥80% time)

Academic collaboration (≤20% time)

Advisory roles (max 2 concurrent)

Restrictions:

Local employment outside specialty

Political activities

Unapproved commercial research

4.2 Dependent Provisions

Spousal Work Rights:

General employment permitted

No industry restrictions

Child Education:

25% tuition subsidy at partner schools

University admission priority

4.3 Mobility Features

Airport Processing:

Dedicated SMART lanes at 6 airports

15-minute clearance guarantee

Re-entry Flexibility:

Unlimited exits

72-hour grace period

5. Sector-Specific Implementations

5.1 Biotechnology

Special Privileges:

Lab equipment duty waivers

Fast-track FDA approval

50% R&D tax deduction

5.2 Advanced Manufacturing

Incentives:

Robotics import tax exemption

Industrial land lease discounts

THB 500K training subsidy

5.3 Digital Infrastructure

Cloud Computing:

VAT exemption on services

30% energy cost reduction

Cybersecurity:

Liability protections

Gov't certification fast-track

6. Compliance & Monitoring

6.1 Continuous Reporting

Quarterly:

Employment verification

Investment maintenance

Annual:

Contribution assessment

Salary benchmarking

6.2 Renewal Process

Documentation:

Updated financials

Health insurance (USD 100K)

Performance metrics

Fees:

THB 10,000 renewal

THB 1,900 visa stamp

7. Emerging Developments

7.1 2024 Enhancements

Blockchain Specialist Category

Climate Tech Fast-Track

EEC Regional Expansion

7.2 Pending Reforms

Dual Intent Provision

Skills Transfer Mandate

Global Talent Pool

8. Strategic Application Approach

8.1 Pre-Submission Optimization

Compensation Restructuring

Patent Portfolio Development

Professional Endorsements

8.2 Post-Approval Planning

Tax Residence Strategy

Asset Protection

Succession Planning

9. Risk Management

9.1 Common Rejection Reasons

Document Issues (32%)

Qualification Gaps (28%)

Financial Irregularities (19%)

9.2 Operational Challenges

Banking Restrictions

Healthcare Access

Cultural Integration

[mariacallous]

What is the future of the like button in the age of artificial intelligence? Max Levchin—the PayPal cofounder and Affirm CEO—sees a new and hugely valuable role for liking data to train AI to arrive at conclusions more in line with those a human decisionmaker would make.

It’s a well-known quandary in machine learning that a computer presented with a clear reward function will engage in relentless reinforcement learning to improve its performance and maximize that reward—but that this optimization path often leads AI systems to very different outcomes than would result from humans exercising human judgment.

To introduce a corrective force, AI developers frequently use what is called reinforcement learning from human feedback (RLHF). Essentially they are putting a human thumb on the scale as the computer arrives at its model by training it on data reflecting real people’s actual preferences. But where does that human preference data come from, and how much of it is needed for the input to be valid? So far, this has been the problem with RLHF: It’s a costly method if it requires hiring human supervisors and annotators to enter feedback.

And this is the problem that Levchin thinks could be solved by the like button. He views the accumulated resource that today sits in Facebook’s hands as a godsend to any developer wanting to train an intelligent agent on human preference data. And how big a deal is that? “I would argue that one of the most valuable things Facebook owns is that mountain of liking data,” Levchin told us. Indeed, at this inflection point in the development of artificial intelligence, having access to “what content is liked by humans, to use for training of AI models, is probably one of the singularly most valuable things on the internet.”

While Levchin envisions AI learning from human preferences through the like button, AI is already changing the way these preferences are shaped in the first place. In fact, social media platforms are actively using AI not just to analyze likes, but to predict them—potentially rendering the button itself obsolete.

This was a striking observation for us because, as we talked to most people, the predictions mostly came from another angle, describing not how the like button would affect the performance of AI but how AI would change the world of the like button. Already, we heard, AI is being applied to improve social media algorithms. Early in 2024, for example, Facebook experimented with using AI to redesign the algorithm that recommends Reels videos to users. Could it come up with a better weighting of variables to predict which video a user would most like to watch next? The result of this early test showed that it could: Applying AI to the task paid off in longer watch times—the performance metric Facebook was hoping to boost.

When we asked YouTube cofounder Steve Chen what the future holds for the like button, he said, “I sometimes wonder whether the like button will be needed when AI is sophisticated enough to tell the algorithm with 100 percent accuracy what you want to watch next based on the viewing and sharing patterns themselves. Up until now, the like button has been the simplest way for content platforms to do that, but the end goal is to make it as easy and accurate as possible with whatever data is available.”

He went on to point out, however, that one reason the like button may always be needed is to handle sharp or temporary changes in viewing needs because of life events or situations. “There are days when I wanna be watching content that’s a little bit more relevant to, say, my kids,” he said. Chen also explained that the like button may have longevity because of its role in attracting advertisers—the other key group alongside the viewers and creators—because the like acts as the simplest possible hinge to connect those three groups. With one tap, a viewer simultaneously conveys appreciation and feedback directly to the content provider and evidence of engagement and preference to the advertiser.

Another major impact of AI will be its increasing use to generate the content itself that is subject to people’s emotional responses. Already, growing amounts of the content—both text and images—being liked by social media users are AI generated. One wonders if the original purpose of the like button—to motivate more users to generate content—will even remain relevant. Would the platforms be just as successful on their own terms if their human users ceased to make the posts at all?

This question, of course, raises the problem of authenticity. During the 2024 Super Bowl halftime show, singer Alicia Keys hit a sour note that was noticed by every attentive listener tuned in to the live event. Yet when the recording of her performance was uploaded to YouTube shortly afterward, that flub had been seamlessly corrected, with no notification that the video had been altered. It’s a minor thing (and good for Keys for doing the performance live in the first place), but the sneaky correction raised eyebrows nonetheless. Ironically, she was singing “If I Ain’t Got You”—and her fans ended up getting something slightly different from her.

If AI can subtly refine entertainment content, it can also be weaponized for more deceptive purposes. The same technology that can fix a musical note can just as easily clone a voice, leading to far more serious consequences.

More chilling is the trend that the US Federal Communications Commission (FCC) and its equivalents elsewhere have recently cracked down on: uses of AI to “clone” an individual’s voice and effectively put words in their mouth. It sounds like them speaking, but it may not be them—it could be an impostor trying to trick that person’s grandfather into paying a ransom or trying to conduct a financial transaction in their name. In January 2024, after an incident of robocalls spoofing President Joe Biden’s voice, the FCC issued clear guidance that such impersonation is illegal under the provisions of the Telephone Consumer Protection Act, and warned consumers to be careful.

“AI-generated voice cloning and images are already sowing confusion by tricking consumers into thinking scams and frauds are legitimate,” said FCC chair Jessica Rosenworcel. “No matter what celebrity or politician you favor, or what your relationship is with your kin when they call for help, it is possible we could all be a target of these faked calls.”

Short of fraudulent pretense like this, an AI-filled future of social media might well be populated by seemingly real people who are purely computer-generated. Such virtual concoctions are infiltrating the community of online influencers and gaining legions of fans on social media platforms. “Aitana Lopez,” for example, regularly posts glimpses of her enviable life as a beautiful Spanish musician and fashionista. When we last checked, her Instagram account was up to 310,000 followers, and she was shilling for hair-care and clothing brands, including Victoria’s Secret, at a cost of some $1,000 per post. But someone else must be spending her hard-earned money, because Aitana doesn’t really need clothes or food or a place to live. She is the programmed creation of an ad agency—one that started out connecting brands with real human influencers but found that the humans were not always so easy to manage.

With AI-driven influencers and bots engaging with each other at unprecedented speed, the very fabric of online engagement may be shifting. If likes are no longer coming from real people, and content is no longer created by them, what does that mean for the future of the like economy?

In a scenario that not only echoes but goes beyond the premise of the 2013 film Her, you can also now buy a subscription that enables you to chat to your heart’s content with an on-screen “girlfriend.” CarynAI is an AI clone of a real-life online influencer, Caryn Marjorie, who had already gained over a million followers on Snapchat when she decided to team up with an AI company and develop a chatbot. Those who would like to engage in one-to-one conversation with the virtual Caryn pay a dollar per minute, and the chatbot’s conversation is generated by OpenAI’s GPT-4 software, as trained on an archive of content Marjorie had previously published on YouTube.

We can imagine a scenario in which a large proportion of likes are not awarded to human-created content—and not granted by actual people, either. We could have a digital world overrun by synthesized creators and consumers interacting at lightning speed with each other. Surely if this comes to pass, even in part, there will be new problems to be solved, relating to our needs to know who really is who (or what), and when a seemingly popular post is really worth checking out.

Do we want a future in which our true likes (and everyone else’s) are more transparent and unconcealable? Or do we want to retain (for ourselves but also for others) the ability to dissemble? It seems plausible that we will see new tools developed to provide more transparency and assurance as to whether a like is attached to a real person or just a realistic bot. Different platforms might apply such tools to different degrees.

[lovilove0808]

Breaking into Tech: How Linux Skills Can Launch Your Career in 2025

In today's rapidly evolving tech landscape, Linux skills have become increasingly valuable for professionals looking to transition into rewarding IT careers. As we move through 2025, the demand for Linux System Administrators continues to grow across industries, creating excellent opportunities for career changers—even those without traditional technical backgrounds.

Why Linux Skills Are in High Demand

Linux powers much of the world's technology infrastructure. From enterprise servers to cloud computing environments, this open-source operating system has become the backbone of modern IT operations. Organizations need skilled professionals who can:

Deploy and manage enterprise-level IT infrastructure

Ensure system security and stability

Troubleshoot complex technical issues

Implement automation to improve efficiency

The beauty of Linux as a career path is that it's accessible to motivated individuals willing to invest time in learning the necessary skills. Unlike some tech specialties that require years of formal education, Linux administration can be mastered through focused training programs and hands-on experience.

The Path to Becoming a Linux System Administrator

1. Structured Learning

The journey begins with structured learning. Comprehensive training programs that cover Linux fundamentals, system administration, networking, and security provide the knowledge base needed to succeed. The most effective programs:

Teach practical, job-relevant skills

Offer instruction from industry professionals

Pace the learning to allow for deep understanding

Prepare students for respected certifications like Red Hat

2. Certification

Industry certifications validate your skills to potential employers. Red Hat certifications are particularly valuable, demonstrating your ability to work with enterprise Linux environments. These credentials help you stand out in a competitive job market and often lead to higher starting salaries.

3. Hands-On Experience

Theoretical knowledge isn't enough—employers want to see practical experience. Apprenticeship opportunities allow aspiring Linux administrators to:

Apply their skills in real-world scenarios

Build a portfolio of completed projects

Gain confidence in their abilities

Bridge the gap between training and employment

4. Job Search Strategy

With the right skills and experience, the final step is finding that first position. Successful job seekers:

Tailor their resumes to highlight relevant skills

Prepare thoroughly for technical interviews

Network with industry professionals

Target companies that value their newly acquired skills

Time Investment and Commitment

Becoming job-ready as a Linux System Administrator typically requires:

10-15+ hours per week for studying

A commitment to consistent learning over several months

Persistence through challenging technical concepts

A growth mindset and motivation to succeed

The Career Outlook

For those willing to make the investment, the rewards can be substantial. Linux professionals enjoy:

Competitive salaries

Strong job security

Opportunities for remote work

Clear paths for career advancement

Intellectually stimulating work environments

Conclusion

The path to becoming a Linux System Administrator is more accessible than many people realize. With the right training, certification, and hands-on experience, motivated individuals can transition into rewarding tech careers—regardless of their previous background. As we continue through 2025, the demand for these skills shows no signs of slowing down, making now an excellent time to begin this journey.