Wikipedia’s Smear Piece on WCH Represents a Badge of Honour
The World Council for Health's message of health sovereignty is clearly a threat to the establishment.

World Council for Health
Written by World Council for Health Correspondent Alice Ashwell, PhD.


They say that you pick up the most flack when you’re right over the target.

Since the Covid phenomenon began, the degree of flack has become a navigational aid in the pursuit of Truth. Wikipedia’s hit piece on the World Council for Health (WCH) is evidence that their message of health sovereignty has become a threat to the establishment.

Brainwashing goes global

Ever more brazenly over the past four years, members of the ‘Great Reset Establishment’ have been involved in a process of what Psychoanalyst Dr Bruce Scott calls ‘menticide’, or brainwashing on a global scale. Through the unethical use of applied psychology, governments, corporations, and organisations around the world have been manipulating the masses into compliance with their globalist agenda.

Whether the issue has been Covid-19, the war in Ukraine, economic meltdown, or climate hysteria, the outcome has been an environment of heightened fear and uncertainty. People seeking direction have been subjected to unprecedented levels of propaganda and censorship, which have added to the confusion by creating a ‘through-the-looking-glass’ world in which it feels like truths have become lies, and vice versa.

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Wikipedia - no longer reliable

One of the ‘trusted’ sources we have become accustomed to turning to when seeking information on a host of topics is Wikipedia, The Free Encyclopedia. This online encyclopedia was established in 2001 with the aim of being a free, open, and neutral source of information that anyone could access and edit. The idea was that all sides of controversial issues would be welcomed and readers would be left to make up their own minds. But, as Wikipedia co-founder-turned-critic Larry Sanger complained in an interview with Glenn Greenwald in July 2023, “It didn’t work out that way.”

Over time, the platform has moved away from its non-negotiable editorial policy that content should strive to reflect a ‘neutral point of view’ (NPOV). As Kristin Heflin described in her PhD thesis in 2010, this means that:

… all Wikipedia content must represent―fairly, proportionately, and as far as possible without bias, all significant views that have been published by reliable sources. By insisting articles represent [―] all significant views without bias, the policy of striving for NPOV shares similarities with objectivity … (p. 89)

In 2015, Heather Ford observed in her D. Phil. Thesis that Wikipedia was by that time offering “a skewed representation of the world that favours some groups at the expense of others” (p. 3). She continued:

Instead of everyone having the same power to represent their views on Wikipedia, those who understand how to perform and speak according to Wikipedia's complex technical, symbolic and policy vocabulary tend to prevail over those who possess disciplinary knowledge about the subject being represented.

This means that Wikipedia is able to decide which facts are stabilised or destabilised on its platform, according to the ideological positions of its editors. While Wikipedia originally provided the opportunity for people to publish without the need for gatekeepers or mediators, this is no longer the case. Especially since the Covid-19 event boosted the fortunes of the Censorship Industrial Complex, Wikipedians have become foot soldiers in the battle to scrub from the Internet information they consider to be mis-, dis-, or mal-information.

Larry Sanger, in the interview mentioned above, described how he has watched Wikipedia’s neutrality evaporate over the years, shifting around 2005 to establishment views on topics like global warming and certain drugs, and starting to show bias against holistic medicine in the early 2010s. Its reliable sources of information are now left-of-centre media corporations such as CNN, MSNBC, and the New York Times, while in their policies 80% of news sources on the right are deemed unreliable. Independent news outlets and self-published subject experts are also not able to edit a Wikipedia page. Before it is deemed acceptable, information needs to be filtered through a mainstream news source, which in turn is constrained by fact-checking services.

Misrepresenting Covid dissidents

The World Council for Health (WCH) is one of many organisations and individuals who have been defamed by Wikipedia since the advent of Covid-19. As discussed at the WCH’s 83rd General Assembly meeting in April 2023, this has been part of a much broader strategy to silence dissent with regard to the so-called pandemic and its protocols.

WCH was established to challenge the official Covid response and its Wikipedia article was created in September 2022. The current Wikipedia entry is fairly close to the original version, although it has been edited a number of times. However, a number of Wikipedia pages created prior to Covid-19 have been completely amended since 2020, resulting in a ‘hero-to-zero’ fall from grace for people such as the author Dr Vernon Coleman (compare his October 2019 entry with the current article), and the early developer of the mRNA vaccine technology, Dr Robert Malone, whose role in this invention has been deleted from the page on mRNA vaccines.



https://worldcouncilforhealth.org/multimedia/fact-checkers-independent-media/
Who’s fact-checking the fact-checkers? A trio of independent media creators—Derrick Broze, Jason Bassler & Joe Martino—reveal their eye-opening shared experience in dealing with fact-checkers and censorship dating back years before Covid-19 emerged.


Scarcely worth commenting on … but we shall!

Let’s take a look at the WCH Wikipedia article (accessed 18 December 2023) to see just how deeply flawed and factually incorrect it is.

Firstly, the content – comprising just eight paragraphs – is entirely inadequate. Other than stating that the organisation “appears to have been formed in September 2021” [emphasis mine], and that it was “founded by Jennifer A. Hibberd and Tess Lawrie”, nothing substantive is mentioned about what WCH is or what it does, despite its goals, values, and initiatives being clearly represented on its website and social media channels.

Secondly, most of the article attempts to smear WCH by association. The bulk of the content refers to people or organisations who are part of the broader health freedom network but neither WCH staff nor council members, including Robert F Kennedy Jr of Children’s Health Defense and esteemed cardiologist Dr Aseem Malhotra. Wikipedia maligns these experts for their efforts to cancel the rollout of the experimental Covid-19 gene therapies which, contrary to the protestations of the fact-checkers, have caused millions of deaths worldwide. Ironically, Wikipedia accuses Dr Malhotra of “cherry-picking” sources to substantiate his concerns about the jab, yet they themselves cherry-pick tangential content and questionable opinions from, with only two exceptions, rather dubious sources.

So, thirdly, let’s have a look at the references Wikipedia uses to back up its potentially libelous statements.

The reference to Kerr et. al (March 2022) is simply a brief Erratum, noting that some of the authors of the paper quoted were using ivermectin to treat patients, which one would expect as they were reporting on its efficacy.

The flawed Cochrane Review by Popp et. al (2022) that criticised a systematic review by Bryant et. al (2021) on the use of ivermectin to prevent and treat Covid-19 was thoroughly debunked in a letter sent to them by Fordham and colleagues in September 2021, but this has not been acknowledged on Wikipedia. The Bryant et al review remains in the top 10 most read out of 23 million tracked scientific papers.

Three references are to fact-checking sites: AAP FactCheck (Australia), AFP Fact Check (France), and Health Feedback (USA), which employ teams of people to prevent the dissemination of information that is not in line with the menticidal narratives of the Great Reset Establishment.

Four of the nine sources come from two Vice magazine journalists, Anna Merlan and Tim Hume. Their articles are replete with worn-out terms such as right-wing, conspiracy theorist, Covid-denier, anti-vaxxer, and mis-/disinformation-peddler. They also predictably take issue with ivermectin, common law, and even the notion of sovereign citizens! The tone of the articles ranges from wryly dismissive to scathingly scornful, with words such as discredited, nonsense, completely false, misleading, and fringe peppering the text. They also delight in reporting cases of doctors and scientists who have been barred from their professions for refusing to deny their professional oaths and personal principles. Underlying the supercilious slurs, however, runs a definite current of concern that these ‘discredited conspiracy theorists’ who are promoting health, freedom, and human rights may actually be gaining traction.

Larry Sanger reflects on how far Wikipedia has departed from its original commitment to neutrality by pointing out the features of biased reporting, all of which apply to the Wikipedia article on WCH:

negative information is so predominant that readers can infer that the authors harbor great hatred, resentment, or strong disapproval of the subject (especially when the target has a popular following among many ordinary people);

dismissive epithets and judgments are used in Wikipedia’s own voice; or

what a person is legitimately famous for is omitted, dismissed, or misrepresented

While WCH might wish to create a more accurate Wikipedia entry, this is not possible. According to the view source button, only registered users are allowed to edit this article. In other words, WCH has no right of reply.


Wikipedia, like a child having a tantrum, refuses point-blank to engage with those people and ideas it just WILL NOT acknowledge.
Is there a future for Wikipedia?

Why anyone would bother to search Wikipedia for information about WCH, which has a perfectly informative website and Substack, is anyone’s guess. But the more Wikipedia produces atrocious articles like the one on WCH, the faster they will lose credibility among those who simply want information and do not have an ideological axe to grind.

In fact, it is worth subjecting this article to a well-known credibility test developed by California State University, and appropriately named the CRAAP test!

Its five components (plus comments on the WCH article) include:

Currency: Is the source up-to-date? – No, for one thing, it does not mention WCH’s second conference in 2023. Although editing of the Wikipedia article continues, no up-to-date information has been added.

Relevance: Is the source relevant to your research? – Not if one wants to know anything about WCH. But it has been very relevant to an investigation into the decline and fall of Wikipedia.

Authority: Where is the source published? Who is the author? Are they considered reputable and trustworthy in their field? – Absolutely not. Wikipedia’s policy on Reliable Sources specifically discounts independent experts in favour of large news corporations, which are committed to promoting Establishment narratives.

Accuracy: Is the source supported by evidence? Are the claims cited correctly? – Not at all. Please visit the WCH website to confirm this.

Purpose: What was the motive behind publishing this source? – The only purpose appears to be to discredit WCH.

At least in the case of the WCH article, Wikipedia’s credibility is clearly questionable. More broadly, Wikipedia co-founder, Larry Sanger, believes that the platform can no longer be trusted. Observing that it has become a useful propaganda mouthpiece for the Establishment, he mused: “If only one version of the facts is allowed, then that gives a huge incentive to wealthy and powerful people to seize control of things like Wikipedia in order to shore up their power.”

Indeed, in recent years, Google has invested substantially in the Wikipedia Foundation, paying them to provide the “most accurate and up-to-date information” for its search engine. Google is now elevating Wikipedia articles in Internet searches, using their content to populate their ‘knowledge panels’, and inserting their articles under videos on YouTube (its subsidiary) in an effort “to fight misinformation and conspiracy theories.” In this way, the actual spreaders of misinformation flood the Internet with their post-truth propaganda, causing those who value Truth, Beauty, and Goodness to look elsewhere for information.

What is particularly interesting, though, is that the Wikipedia edifice may be crumbling from within. Thanks to the transparency of the Wikimedia system, one is able to peer behind the curtain into the online discussions of the various editors working on a particular article. And here we discover dissention in the ranks. Recent discussions between Wikipedia editors working on the WCH article reveal anything but agreement regarding this flimsy hit-piece. For example, one editor asks why the article on WCH focuses on Dr Lawrie. The person then asks why Dr Lawrie’s qualifications, directorship, publication record, and over 4,000 citations are not mentioned (actually Dr Lawrie has over 5,000 citations and is ranked among the top 5% of Researchgate scientists), but only her prior role as an obstetrician. It is encouraging to read the following comment:

Science is research and debate, not dogma; even in the case Lawrie could be wrong on some things, that doesnt's [sic.] make her a conspiracy theorist, but a good researcher. Suppression of scientific debate is not scientific method.

Later, and for good reason, concerns are expressed about the use of Vice magazine as a ‘reliable source’ (RS).


Anna Merlan, author of three of the Vice articles.
Conclusion

WCH’s Wikipedia experience is the tip of a very large iceberg of censorship and suppression (Shi-Raz et al. 2023) that, especially over the past four years, has been threatening to sink those opposing Establishment narratives. Media and tech companies, including Wikipedia, Google, and the fact-checkers mentioned in this article, have played a central role in stifling debate and attempting to constrain narratives and minds. But, as Larry Sanger puts it, “people have natural BS detectors” and are not satisfied with condescending journalists or one flavour of opinion.

Instead, as described by Shi-Raz et al., many people who are concerned about public health and committed to freedom of speech have not been deterred by the efforts of the Establishment. Instead, they have been motivated to create a world in parallel to the mainstream, using alternative channels of communication, establishing multi-disciplinary support networks, and developing alternative medical and health information systems such as, of course, the World Council for Health.

And, recognising the decline of Wikipedia, Larry Sanger is in the process of creating what he calls the ‘Encyclosphere’, a massive network of online encyclopaedias covering a plethora of specialist and generalist areas of knowledge, that is set to literally put Wikipedia in its place as an equal among many others.

So, while Wikipedia spends an inordinate amount of time, energy, and money on a business that not only lacks substance but is also mean-spirited and divisive, initiatives like WCH and the Encyclosphere shine like candles in the dark, illuminating a better way.

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PromptPro

Introduction


Question
Are you tired of language models generating repetitive and uninspired responses?

Just like a musician needs a variety of instruments to create a diverse range of melodies, language models require diverse prompts to generate unique and creative responses.
Meet Devin, a Generative Prompt Engineer (GPE) who revolutionizes language models by crafting prompts that encourage diverse and dynamic responses.

"Thanks to Devin's prompt engineering, our language model's responses are more creative and engaging than ever before." - Anissa Thomas

In this blog post, we'll explore how Generative Prompt Engineering can revolutionize language models and how skilled engineers like Devin can make it happen.
Ready to take your language model usage to the next level? Keep reading to learn more about the power of Generative Prompt Engineering (GPE).
Generative Prompt Engineering is a technique used to generate high-quality text using natural language processing (NLP) models.

Question
How can we generate more diverse and interesting responses from language models?

GPE can help by designing prompts that encourage language models to generate more diverse and creative responses. For example, GPE might experiment with using more open-ended prompts, providing more context or background information, or asking more thought-provoking questions.

The Impact of AI on the Future of Work

As artificial intelligence continues to advance, its impact on the labor market is becoming increasingly important to consider.

Diverse and creative responses in language models are critical because they enable the model to produce a range of unique and interesting outputs that are not limited to a single response. Language models that are capable of generating diverse and creative responses have a greater chance of producing outputs that are relevant and engaging to the user, thereby improving the user experience. In this section, we will discuss the importance of diverse and creative responses in language models.
Avoiding Repetitive Response
One of the primary benefits of diverse and creative responses in language models is the ability to avoid repetitive responses. Language models that produce the same or similar responses repeatedly can quickly become boring and uninteresting to the user. This can lead to a lack of engagement and a decrease in user satisfaction. By generating diverse and creative responses, language models can keep the user engaged and interested in the conversation.
Providing a Range of Options
Another benefit of diverse and creative responses in language models is the ability to provide a range of options to the user. This can be especially useful in situations where the user is looking for information or assistance. For example, a language model that is capable of providing multiple solutions to a problem can help the user find the solution that works best for them. By providing a range of options, language models can also help to build trust with the user by demonstrating that they are capable of providing useful and relevant information.
Personalization
Diverse and creative responses in language models can also help to personalize the conversation with the user. By generating responses that are tailored to the user's interests and preferences, language models can create a more engaging and enjoyable conversation. This can also lead to increased user satisfaction and loyalty.
Enhancing Creativity
Finally, diverse and creative responses in language models can help to enhance creativity. Language models that are capable of generating unique and interesting responses can inspire the user to think more creatively and explore new ideas. This can be especially useful in situations where the user is looking for inspiration or new perspectives.
Overall, diverse and creative responses in language models are critical because they can help to avoid repetitive responses, provide a range of options, personalize the conversation, and enhance creativity. By generating unique and interesting responses, language models can keep the user engaged and interested in the conversation, leading to increased user satisfaction and loyalty. As language models continue to evolve, the ability to generate diverse and creative responses will become even more important.

Why You Should Learn About Generative Prompt Engineering
Discover how Generative Prompt Engineering can help you create innovative content, save time and costs, personalize your communication with customers, and advance your career.
Generative Prompt Engineering is an emerging field that combines natural language processing, machine learning, and creativity to generate new and original content based on prompts or cues. The field has been gaining popularity in recent years due to its potential to automate content creation and enable personalized communication with customers. In this blog, we will discuss in detail why you should learn about Generative Prompt Engineering.
Innovative Content Creation
Generative Prompt Engineering is an innovative approach to content creation that can help you create unique and engaging content. Unlike traditional content creation methods, which often involve a lot of manual effort, Generative Prompt Engineering can produce a large amount of content in a short amount of time. The content generated through Generative Prompt Engineering can be used for a variety of purposes, including marketing, advertising, and content creation.
Time and Cost Efficiency
Generative Prompt Engineering can save you time and money by automating content creation tasks that would otherwise be done manually. This can be especially useful if you work in an industry where content creation is a frequent and time-consuming task. With Generative Prompt Engineering, you can produce content faster and at a lower cost, freeing up time and resources to focus on other aspects of your business.
Personalization
Generative Prompt Engineering can help you create personalized content tailored to your audience's interests and preferences. Personalization is becoming increasingly important in marketing and advertising as customers expect a more personalized experience. With Generative Prompt Engineering, you can create content that is relevant and engaging to your audience, which can lead to increased engagement and customer loyalty.
Career Opportunities
Generative Prompt Engineering is an emerging field with a growing demand for skilled professionals. Learning about Generative Prompt Engineering can help you stay ahead of the curve and open up new career opportunities. As more businesses start to adopt Generative Prompt Engineering, there will be a growing need for experts who can develop and implement these technologies.
Advancements in Artificial Intelligence
Generative Prompt Engineering is a prime example of the advancements being made in artificial intelligence and machine learning. Learning about Generative Prompt Engineering can help you understand the potential of these technologies and stay up-to-date with the latest developments. As the field continues to evolve, there will be more opportunities to apply these technologies to new areas and industries.
Learning about Generative Prompt Engineering can provide you with a range of benefits, from innovative content creation and time and cost efficiency to personalization, career opportunities, and a better understanding of artificial intelligence and machine learning. If you are interested in pursuing a career in the tech industry or looking to enhance your skills, learning about Generative Prompt Engineering is a great place to start.

Why Generative Prompt Engineering is an Essential Skill for Content Creators

In a world where content is king, Generative Prompt Engineering can help you create unique, personalized, and engaging content quickly and efficiently.

Generative Prompt Engineering is an innovative approach to content creation that combines natural language processing, machine learning, and creativity to generate new and original content based on prompts or cues. This field is becoming increasingly important as it has the potential to automate content creation and enable personalized communication with customers. Here are some reasons why content creators should learn about Generative Prompt Engineering:
Creating Unique and Engaging Content
Generative Prompt Engineering can help you create unique and engaging content that stands out from the competition. With traditional content creation methods, it can be challenging to come up with new and exciting ideas. Generative Prompt Engineering can produce a large amount of content in a short amount of time, allowing you to explore new ideas and produce content that is original and engaging. For example, if you're a social media marketer, you can use Generative Prompt Engineering to create unique and eye-catching social media posts that will capture your audience's attention.
Time and Cost Efficiency in Content Creation
Generative Prompt Engineering can save you time and money by automating content creation tasks that would otherwise be done manually. With Generative Prompt Engineering, you can produce content faster and at a lower cost, freeing up time and resources to focus on other aspects of your business. For example, if you're a blogger, you can use Generative Prompt Engineering to generate article topics and outlines, allowing you to spend more time researching and writing the actual content.
Personalization for Better Customer Engagement
Generative Prompt Engineering can help you create personalized content tailored to your audience's interests and preferences. Personalization is becoming increasingly important in marketing and advertising as customers expect a more personalized experience. With Generative Prompt Engineering, you can create content that is relevant and engaging to your audience, which can lead to increased engagement and customer loyalty. For example, if you're an email marketer, you can use Generative Prompt Engineering to generate personalized email subject lines and body text based on the recipient's preferences and behavior.
Career Opportunities in the Emerging Field of Generative Prompt Engineering
Generative Prompt Engineering is an emerging field with a growing demand for skilled professionals. Learning about Generative Prompt Engineering can help you stay ahead of the curve and make you a valuable asset to any company looking to improve their content creation process. There are a variety of career opportunities in this field, including positions in content creation, marketing, advertising, and technology. For example, companies like OpenAI and GPT-3 are actively seeking talented individuals with skills in Generative Prompt Engineering.
In full, Generative Prompt Engineering is an essential skill for content creators in today's digital age. It can help you create unique, personalized, and engaging content quickly and efficiently while also providing career opportunities in an emerging field. Whether you're a blogger, social media marketer, or email marketer, learning about Generative Prompt Engineering can help you take your content creation game to the next level.
Generative Prompt Engineering is an emerging field that combines natural language processing, machine learning, and creativity to generate new and original content based on prompts or cues. While the field is relatively new, it has its roots in a long history of research and development in natural language processing and machine learning.

A Moment in Time: Historical Context and Development of Generative Prompt Engineering
The development of natural language processing can be traced back to the 1950s, when researchers first began experimenting with computer algorithms that could understand and process human language. However, progress in this area was slow, and it wasn't until the 1990s that natural language processing began to gain wider attention and recognition.
During the 1990s, the focus of natural language processing research shifted towards statistical approaches and machine learning. This led to the development of algorithms that could analyze large datasets of text and identify patterns and relationships between words and phrases. These algorithms were used to build more sophisticated language models, which could be used to generate new text based on existing data.
In the early 2000s, this approach was further refined with the development of neural language models. These models used artificial neural networks to simulate the way the human brain processes language, and they were able to produce more natural-sounding text than earlier language models. This led to the development of applications like chatbots, virtual assistants, and automated customer service systems.
However, the text generated by these models was often generic and lacked creativity, leading researchers to explore new ways to generate more engaging and original content. This led to the emergence of Generative Prompt Engineering as a field of study and research.
Today, Generative Prompt Engineering is an area of active research and development, with new techniques and approaches being developed and tested all the time. One of the most important recent developments has been the use of generative adversarial networks (GANs) to generate text. GANs are a type of machine learning algorithm that can generate new text based on a set of prompts, and they are becoming increasingly popular in the field of natural language processing.
Overall, the historical context and development of Generative Prompt Engineering can be traced back to a long history of research and development in natural language processing and machine learning. The emergence of this field represents a new frontier in creative content generation, and it holds the potential to revolutionize the way we communicate and interact with technology.

How GPE Can Help in Creating Diverse and Creative Responses
Designing Prompts for Diverse and Creative Responses in GPE
The key to generating diverse and creative responses in language models lies in the design of prompts. In this segment, we will discuss how Generative Prompt Engineers (GPE) can design prompts to encourage language models to produce unique and engaging content.
Understanding the Importance of Prompts
The first step in designing effective prompts is understanding their importance in generating diverse and creative responses in language models. A prompt serves as a cue or stimulus for the language model to generate content. The quality and specificity of the prompt can greatly influence the type of response the model generates. A well-designed prompt can lead to a range of diverse and creative responses, while a poorly designed prompt may limit the model's output.
Using Open-Ended Prompts
Open-ended prompts are a great way to encourage language models to produce diverse and creative responses. These prompts give the model the freedom to generate content without constraints. For example, consider the prompt "Describe your ideal vacation." This prompt allows the language model to generate a variety of responses, from tropical beach getaways to adventurous hiking trips.
Incorporating Novelty and Surprise
Incorporating novelty and surprise into prompts can also lead to more diverse and creative responses. This can be achieved by using prompts that are unexpected or unusual. For example, consider the prompt "Write a story about a giraffe who can fly." This prompt introduces an unexpected element that can lead to unique and engaging responses.
Focusing on Specific Details
Focusing on specific details in prompts can also encourage language models to generate more diverse and creative responses. Specific details can provide context and constraints for the language model, while still allowing for flexibility and creativity. For example, consider the prompt "Describe a day in the life of a firefighter." This prompt provides specific details about the subject matter, while still allowing for a range of responses.
Incorporating User Feedback
Incorporating user feedback can also be a valuable tool in designing effective prompts. User feedback can help GPEs understand what types of prompts lead to the most diverse and creative responses. For example, a GPE can analyze user responses to a set of prompts and use that information to refine and improve their prompt design in the future.
In full, effective prompt design is crucial for generating diverse and creative responses in language models. By using open-ended prompts, incorporating novelty and surprise, focusing on specific details, and incorporating user feedback, GPEs can design prompts that encourage language models to produce unique and engaging content.

Techniques for designing effective prompts in Generative Prompt Engineering
By using open-ended prompts, contextual prompts, and thought-provoking questions, Generative Prompt Engineers can encourage language models to generate diverse and creative responses that can be used for a variety of purposes, including marketing, content creation, and personal communication.
In order to generate diverse and creative responses, Generative Prompt Engineers employ a variety of techniques to design prompts that encourage language models to produce unique and engaging content. Here are some examples of techniques that are commonly used.
Open-Ended Prompts
One technique that Generative Prompt Engineers use is to create open-ended prompts. These prompts encourage language models to generate responses that are not limited by a specific set of parameters. By giving the model more freedom to explore different possibilities, the resulting content can be more diverse and creative. For example, an open-ended prompt might ask the model to generate a story that begins with the phrase "Once upon a time."
Contextual Prompts
Another technique that can be effective is to provide more context in the prompt. This can help guide the language model towards a specific topic or idea while still allowing for creativity. For instance, a prompt asking the model to generate a recipe for a vegan chili would provide more context than simply asking for a recipe, which could lead to a wider range of responses.
Thought-Provoking Questions
Generative Prompt Engineers can also design prompts that provoke thought and inspire the language model to generate more unique and interesting responses. These types of prompts can be especially effective in generating content that is engaging and thought-provoking for the audience. For example, a prompt asking the model to generate a conversation between two characters who have just met on a deserted island could lead to a range of creative responses that explore themes such as survival, isolation, and human connection.
Key Skills for a Generative Prompt Engineer
The ideal candidate for this role will have a strong technical background, excellent problem-solving skills, and the ability to work both independently and as part of a team. Additionally, excellent communication, organization, and time management skills are crucial in order to ensure projects are completed on time and on budget.
Technical Background
A Generative Prompt Engineer must have a strong technical background in natural language processing, machine learning, and programming languages such as Python. Understanding the fundamentals of these fields is essential for designing effective prompts and developing high-quality models. Familiarity with software development tools and platforms is also important for creating and testing models.
Problem-Solving Skills
Problem-solving skills are critical for a Generative Prompt Engineer, as they must be able to identify and address issues that arise during the model development process. They must also be able to analyze data and adjust models to improve their performance. Strong problem-solving skills allow a Generative Prompt Engineer to create models that are accurate, efficient, and effective.
Communication
Effective communication is crucial for a Generative Prompt Engineer, as they often work as part of a team that includes developers, designers, and other stakeholders. Clear communication helps to ensure that everyone is on the same page and working towards the same goals. Additionally, communicating technical concepts to non-technical stakeholders is essential for gaining buy-in and support for projects.
Organization
A Generative Prompt Engineer must be highly organized, as they are often working on multiple projects simultaneously. They must be able to prioritize tasks and manage their time effectively to meet deadlines and ensure that projects are completed on time and within budget. Strong organizational skills allow a Generative Prompt Engineer to be efficient and effective in their work.
Time Management
Time management is essential for a Generative Prompt Engineer, as they must balance multiple competing priorities and deadlines. Effective time management allows them to ensure that they are meeting deadlines, managing their workload, and delivering high-quality work. It also helps them to stay on top of emerging trends and technologies, which is critical in this rapidly evolving field.
Overall, A Generative Prompt Engineer requires a diverse skill set that includes technical knowledge, problem-solving skills, communication, organization, and time management skills. These skills are essential for developing and implementing effective models that generate high-quality, diverse and creative responses.
The Importance of Language Skills in Generative Prompt Engineering
Parsing, Syntax, and Grammar Skills

Tip
Language skills, including parsing, syntax, and grammar, are essential for creating effective prompts in Generative Prompt Engineering, enabling the generation of diverse and creative responses."

Generative Prompt Engineering (GPE) is an interdisciplinary field that combines natural language processing, machine learning, and creativity to generate new and original content based on prompts or cues. As we discussed earlier, GPE is an emerging field with a growing demand for skilled professionals. While technical background, problem-solving skills, communication, organization, and time management skills are important in this field, language skills are also key to success.
In this section, we will discuss the importance of parsing, syntax, and grammar skills in GPE. These language skills are essential for creating effective prompts that can generate diverse and creative responses.
Parsing Skills
Parsing refers to the process of analyzing a sentence to understand its grammatical structure. In GPE, understanding the grammatical structure of a prompt can help the engineer create prompts that are grammatically correct and easy for the language model to understand. For example, consider the prompt "The cat sat on the mat." By parsing this sentence, a GPE can identify the subject ("the cat"), the verb ("sat"), and the object ("the mat"). This understanding can then be used to create similar prompts that are grammatically correct and easy for the language model to understand.
Syntax Skills
Syntax refers to the arrangement of words and phrases to create well-formed sentences. In GPE, understanding syntax is important for creating prompts that are clear and easy to understand. For example, consider the prompt "Write a story about a man with a dog who goes on an adventure." By using proper syntax, a GPE can create a clear and concise prompt that is easy for the language model to understand and generate a creative response.
Grammar Skills
Grammar refers to the rules that govern the use of language. In GPE, understanding grammar is important for creating prompts that are grammatically correct and use proper word choice. For example, consider the prompt "Write a poem about nature." By using proper grammar, a GPE can create a prompt that is clear and easy for the language model to understand, while also encouraging the generation of a creative and engaging response.

Language skills play a critical role in Generative Prompt Engineering as they enable GPEs to create effective prompts that can generate diverse and creative responses. Parsing, syntax, and grammar skills are particularly important for GPEs as they enable them to create prompts that are grammatically correct, clear, and easy for the language model to understand.
These language skills also allow GPEs to identify and address any issues that may arise during the model development process. For example, if a language model generates responses that are not grammatically correct or do not make sense, a GPE can use their parsing, syntax, and grammar skills to identify the issue and adjust the model accordingly.
Furthermore, language skills are essential for creating prompts that are engaging and thought-provoking. By using proper grammar and syntax, GPEs can create prompts that are clear and easy to understand, while also encouraging the generation of creative and engaging responses. For example, a prompt like "Write a story about a man with a dog who goes on an adventure" is more engaging and thought-provoking than a prompt like "Write a story about a man who goes on an adventure."
Lastly, language skills are crucial for GPEs to create effective prompts and ensure the successful completion of projects on time and within budget. By having strong parsing, syntax, and grammar skills, GPEs can create prompts that are grammatically correct, clear, and engaging, which in turn results in the generation of diverse and creative responses.
By combining technical knowledge, problem-solving skills, communication, organization, and time management skills, GPEs can effectively develop and implement models that generate high-quality, diverse and creative responses, while ensuring project completion on time and on budget. Additionally, language skills such as parsing, syntax, and grammar skills are crucial for creating effective prompts that can generate diverse and creative responses, which is a key component of GPE.


Example
Let's say a GPE is working on a project to develop a chatbot that can provide customer service for an e-commerce platform. The GPE would need to have a strong technical background in natural language processing, machine learning, and programming languages such as Python to design effective prompts and develop high-quality models that can accurately understand customer queries and provide helpful responses.

As the GPE works on the project, they may encounter issues such as poor model performance, data quality issues, or unexpected user behavior. Strong problem-solving skills are crucial in such situations as they allow the GPE to quickly identify and address the issues, keeping the project on track and minimizing delays.
Effective communication is also critical for the success of the project. The GPE would need to communicate clearly and effectively with other team members, stakeholders, and clients to ensure everyone is on the same page and working towards the same goals. This would reduce the likelihood of misunderstandings or miscommunication that can lead to project delays or cost overruns. Additionally, clear communication of technical concepts to non-technical stakeholders is essential for gaining their buy-in and support for the project, which can help to secure adequate resources and funding.
As the GPE works on multiple projects simultaneously, effective organization skills would enable them to prioritize tasks and manage their time effectively to meet deadlines and ensure that projects are completed on time and within budget. Good time management skills would help them balance competing priorities and deadlines, allowing them to stay on top of emerging trends and technologies that are critical in this rapidly evolving field.
In full, the combination of technical knowledge, problem-solving skills, communication, organization, and time management skills is crucial for a GPE to effectively develop and implement models that generate high-quality, diverse and creative responses, while ensuring project completion on time and on budget. Language skills such as parsing, syntax, and grammar skills are also important for creating effective prompts that can generate diverse and creative responses, which is a key component of GPE.

The Role of a Generative Prompt Engineer
I'm a skilled Generative Prompt Engineer with a technical background and exceptional problem-solving abilities. My organization, communication, and time management skills set me apart, allowing me to thrive both independently and as part of a team.
What makes me particularly effective is my ability to parse the English language using my knowledge and understanding of syntax and grammar. These tools enable me to craft prompts rapidly and with efficiency, getting swiftly to the heart of the project requirements.
My experience with technical planning and communicating complex requirements make me particularly adept at outlining project scope, goals, and requirements for clients and team members. I'm tenacious when it comes to developing and testing new software and systems, using customer feedback and data to drive iterative improvements.
Collaboration is key for me, and I'm able to communicate effectively and work well with multiple stakeholders, guiding them through the process and keeping them updated as the project evolves. Lastly, staying at the forefront of tech and AI advancements is of utmost importance to me to ensure that I always offer the best solutions to clients.
As a Generative Prompt Engineer, I am skilled in quickly and effectively creating prompts with precision and accuracy. My extensive knowledge of English parsing, syntax, and grammar is instrumental in crafting prompts that are efficient and effective. By understanding the intricacies of language, I am able to ensure that my prompts are grammatically sound and convey the intended meaning.
Additionally, my attention to detail and analytical skills allow me to identify patterns and generate unique and diverse prompts. I am also proficient in using natural language processing tools and techniques to aid in prompt creation. Overall, my skills and expertise make me a valuable asset in the development of intelligent and dynamic prompt systems.
Ultimately, my skills and experience as a Generative Prompt Engineer make me a valuable asset to any team looking to implement intelligent and dynamic prompt systems. With my technical expertise, problem-solving abilities, and communication skills, I can help clients and team members meet their project goals efficiently and effectively. If you are seeking a Generative Prompt Engineer with a passion for language and a dedication to staying at the forefront of technology, look no further than me.

The Importance of English Parsing, Syntax, and Grammar in Crafting Effective Prompts

English parsing, syntax, and grammar are instrumental in crafting effective prompts that resonate with a target audience. With the help of NLP technology, writers can use these tools to generate marketing copy that achieves desired results.

Natural Language Processing (NLP) is a powerful tool that can be used to analyze and generate human language. As an avid user of NLP technology, I have utilized its intelligent algorithms to assist me in writing two books. NLP technology has helped me streamline my writing process, improve my prose, and develop a unique voice. Now, I plan to leverage its capabilities once again to create a marketing campaign that will wow my audience.
Effective prompts are essential for any marketing campaign. They need to be carefully crafted to resonate with the target audience and achieve the desired results. English parsing, syntax, and grammar are critical components of creating effective prompts. Parsing is the process of breaking down a sentence into its component parts to understand its meaning. Syntax refers to the rules for constructing phrases and sentences in a language, while grammar is the set of rules for using language correctly.
By utilizing NLP technology, writers can use these tools to analyze and understand the language used by their target audience. This allows them to craft compelling marketing copy that resonates with their audience and achieves the desired results. NLP technology can even help generate language that is unique, creative, and effective.
In my personal experience, NLP technology has been instrumental in improving my writing process, allowing me to create unique and compelling content that resonates with my readers. It has also helped me in crafting marketing copy that achieves my desired results. By leveraging the power of NLP technology and these essential language tools, writers can create effective prompts that generate high-quality, diverse, and creative responses.

The Role of Analytical Skills and Attention to Detail in Writing Books and Crafting Marketing Campaigns
Analytical skills and attention to detail are crucial in crafting effective writing, whether it be in the form of a book or a marketing campaign. These skills allow the writer to identify patterns, discern important information, and generate unique and diverse prompts that resonate with the intended audience.
In writing the two books, the use of analytical skills and attention to detail helped in developing the plot, identifying plot holes, and creating well-rounded characters. Analyzing character motivations, for example, helped to ensure that each character's actions and decisions were consistent and believable throughout the book. Attention to detail also aided in creating vivid descriptions of the setting, immersing the reader in the story and bringing the fictional world to life.
Similarly, in crafting the marketing campaign, analytical skills and attention to detail played a crucial role in developing a message that resonates with the target audience. Analyzing market trends, consumer behavior, and demographics helped to ensure that the campaign message was tailored to the specific needs and interests of the target audience. Attention to detail was also important in creating effective prompts that engaged the audience and generated interest in the product or service being marketed.
In both cases, the use of analytical skills and attention to detail helped to create writing that was engaging, informative, and effective in achieving its intended purpose.
Conclusion
Generative Prompt Engineers (GPEs) are instrumental in revolutionizing language models by creating diverse and creative responses. With their technical knowledge of natural language processing, machine learning, and programming languages such as Python, GPEs can design effective prompts and develop high-quality models that can accurately understand customer queries and provide helpful responses.
GPEs also need strong problem-solving skills to quickly identify and address issues such as poor model performance, data quality issues, or unexpected user behavior, keeping the project on track and minimizing delays. Effective communication is also critical for the success of the project, as GPEs need to communicate clearly and effectively with other team members, stakeholders, and clients to ensure everyone is on the same page and working towards the same goals.
In addition to technical knowledge and communication skills, GPEs also need strong analytical skills and attention to detail to identify patterns and generate unique and diverse prompts. This is essential for creating effective prompts that can generate compelling marketing copy, resonate with the target audience, and achieve desired results.
Overall, the combination of technical knowledge, problem-solving skills, communication, organization, time management skills, and analytical skills is crucial for a GPE to effectively develop and implement models that generate high-quality, diverse, and creative responses, while ensuring project completion on time and on budget.
Generative Prompt Engineering (GPE) has numerous implications and applications in various fields. Here are some of them:

Language Generation: GPE can revolutionize language generation by creating more diverse and creative responses to prompts. It can be applied in chatbots, virtual assistants, customer service, and other natural language processing (NLP) applications.
Creative Writing: GPE can help writers develop their unique writing voice, streamline their writing process, and generate new ideas. It can be used to create different types of content, including novels, screenplays, and marketing copy.
Marketing: GPE can be applied in marketing to craft compelling and persuasive messages that resonate with the target audience. It can help create unique and diverse copy that grabs the audience's attention and drives conversions.
Education: GPE can be used in education to generate questions and responses for quizzes, exams, and homework assignments. It can help create personalized learning experiences for students and provide them with immediate feedback.
Data Analysis: GPE can be applied in data analysis to generate natural language summaries of data and insights. It can help automate data reporting and make it easier for non-technical stakeholders to understand complex data.
Content Creation: GPE can be applied in content creation to generate content for websites, blogs, and social media. It can help generate diverse and creative content that engages the audience and drives traffic.
Personalization: GPE can help create personalized experiences for users by generating tailored responses based on their preferences and past interactions.

One thing's for sure, Generative Prompt Engineering has significant implications and applications in language generation, creative writing, marketing, education, data analysis, content creation, and personalization. Its potential applications are vast, and it has the potential to transform many industries and fields.
I hope this discussion on Generative Prompt Engineering has inspired you to think about the power of natural language processing and the potential for creating diverse and creative responses. As you reflect on this topic, I challenge you to consider how you can apply this knowledge to your own lifescape.
Perhaps you can take some time to refresh your language and analytical skills, exploring new vocabulary and grammatical structures to improve your own communication. Or maybe you can explore the potential for using natural language processing to improve your own business, writing, or creative projects.
Whatever path you choose, I encourage you to take action and apply your learning to make a positive impact in your life and in the world around you. Let's harness the power of technology and language to create something truly remarkable.
If you're feeling inspired by what you just read, don't just sit there, take action! Leave your comments, give me an upvote, and hit that follow button to stay tuned in for more content that'll uplift your soul. And if you're new to #hive and #ecency, don't worry, sign up is free and easy. Just click the link in the description and you'll be ready to go.
But wait, there's more! If you want to help me out and support my somewhat ok posts, you can make a donation to help me with free giveaways, contests, and airdrops. You can upvote, comment, follow/subscribe, and share on different social media platforms like [HIVE, PublishOx, Medium, Reddit,](<HIVE, PublishOx, Medium, Reddit, or other social media platforms.>) and more. The quickest methods of donation are Cash.App and PayPal, and your contributions and gifts are greatly appreciated.
And hey, I'm not just here to inspire you, I'm here to learn too. I'm looking for advice to help me create new communities on Hive and other platforms, and I need your help. So if you've got some great ideas, or just want to help me pay it forward, hit me up with a tip or two and let's keep making the world a better place.

Disclaimer
Please note that the above-provided information is for general educational purposes only and is not intended to be a substitute for professional advice. It is always best to check with a licensed professional before making any decisions regarding your professional life.

Great audio interview describing what Woke is and very informative if you had no clue as to what the movement was real about like myself. About a half hour listen and great information.
https://historyreclaimed.co.uk/podcast/how-woke-won/

Informative

I scrutinized this and it is very informative. https://www.youtube.com/watch?v=uCKkeP8kBUk #christianity #mystery #cine #sps #somee #awesme #meme #pob

Why you should always wash your hands: this is a petri dish of a hand showing what microbes are in there.
#science #informative #technology

#SoMeeUserTips~The Importance of Keeping your Content Fresh, Interesting, Original and Informative. At the very least, Original and Interesting

The two main differences between FaceBook and #BlockchainSocials are that the majority of your friends and family aren't here and you earn through your content. In the rare case that all of your friends and family are here, this might not pertain to you, but if you want to earn more, you must gear your content towards those who don't know you personally. For this reason, selfies and close-ups of your latest dinner or drink probably won't interest most of your followers.

To get more upvotes you must figure out what your followers are interested in or find a way to make what you post more interesting for others. This not only means keeping your content fresh, but also making sure it has enough detail, so that others can learn something from it. If you consistently post close-up selfies or a picture of the beer you're drinking, your followers will get bored fast. On top of that, low effort descriptions aren't very helpful or interesting to the masses either.

Right now SoMee is pretty small, so competition is quite light. You may be getting enough upvotes to earn a decent amount now, but as the platform grows those upvotes will move to those putting more effort into their content. A picture of your lunch with a description simply saying 'Lunch' is going to get old fast and will probably result in your followers either unfollowing you or ignoring your content more and more. I'm upvoting posts I wouldn't normally want to compensate and that will change when more content creators sign up.

The key is to bring others somewhere new and give them information they may not already know. It's fine if you are in the photograph, but you shouldn't be the main focus. The scenery in the background is what most of your followers are interested in, your culture, the product you're using or even the food you're eating. The key is to give them some useful information about those things.

Instead of just showing us your 'Lunch', let us know if you made it or bought it from a restaurant. If so, what's it called? What special ingredients are used in it? Give us enough, so we can at least research it further on our own. We can't do that if you just tell us it's 'Lunch'.

Author~ notconvinced

I hope you find this information useful. If so, follow Awesme Tutorials by hitting that 'Like' button and visit https://awesme.blog for more in-depth tutorials, tips and useful information. There's plenty to learn about SoMee and increase your SME potential earnings. You are just one click away.

#originalcontent #Awesme #AwesmeTutorials #UserTips #SoMeeFeatures #SoMeeGrowth #howto #features #voting #maximizingearnings #advice #help #faq #unofficialfaq

#SoMeeUserTips~The Importance of Interaction

If you want to #succeed on any #SocialMediaPlatform, you need to give to get. If you want to be seen, you must look for and see others. If you want interaction, you must interact. If you want upvotes, you need to give upvotes. You'll usually receive a few regardless, but they will be temporary, and the post won't earn to its potential.

Just like in real-life, when you are new, if you want to meet people you need to greet people. It's rare, especially in large communities that a new person adding themselves into the mix is seen or acknowledged. There's already a routine in place, cliques, niches and #VotingCircles who are happy with their group and don't need a change to be fulfilled.

If you want in, you need to sell yourself. On #SoMee the way to do that is to post, Add Friend/follow, upvote and comment. So first, you must post. Your posts need to be original, of decent quality and should be informative. People like to see places they've never been to and learn something new. The key is that whatever you post should offer some sort of relevant information. If you aren't offering any real information, then many will just scroll past.

That's minor though compared to upvoting others and commenting on other's posts. This is because through these two types of interactions your username and a direct link to you is delivered right into their notifications. The same goes for follows and Friends requests, but they are not viewed the same.

The key is to make these interactions meaningful, so you stand out. Don't just Friend or follow to go through the motions. You should at least visit their profile and upvote a post first. This implies you have enjoyed their content and are not just wanting a shallow follow back. The #Follow4Follow method will increase your follower numbers but is unlikely to return upvotes.

When you upvote something, the best thing you can do is add a quality thoughtful comment that is on topic. Again, this shows you've actually read and enjoyed the content. It also solicits a return comment, which helps to solidify you in their memory. And... ALWAYS reply to any comment left on your content or relevant reply to your comments. If a user doesn't reply, then they aren't deserving of you.

You should never comment with something vague or shallow and never just spam the same or similar comment on everyone's posts down the feed. This will probably earn you a block. Being real is the most important thing you can do.

Since our voting power is limited, everyone must serve out their votes carefully. So, as a new user, unless you follow this advice, you're unlikely to get substantial votes simply by posting content. Not only do you need to make yourself seen, but you need to support others with your upvotes as well. If you aren't giving love, you probably won't receive any in return.

It's very important to interact with intent and sincerity. Do so often and you'll be welcomed into the community. Once you are welcomed in, you'll become a success in no time.

You need to prove yourself and work your way in. This is relevant for #NewUsers and longtime users equally. If you've been here a while and aren't receiving the interaction you think you deserve, you need to review what you are doing and change it up.

I hope you find this information helpful. If so, make sure to LIKE this page and visit https://awesme.blog for more in-depth tutorials, tips and more!

Author~ notconvinced

#SoMee #tips #advice #originalcontent #someeoriginals #someeofficial #AweSoMee #AweSoMeeFacts #interaction #facts #faq #GiveToReceive #Awesme #AwesmeFacts #BeAuthentic #SucceedOnSoMee

Some useful trading acronyms

TA: Technical Analysis
FA: Fundamental Analysis
ATH: All-Time High
ALT: All-Time Low
HOD: High Of Day
LOD: Low Of Day
HH: High High
HL: High Low
LL: Low Low
LH: Low High
HTF: High Time Frame
LTF: Low Time Frame
Be: Bearish
Bu: Bullish
TP: Take Profit
SL: Stop Loss

If you find this quite informative an upvote will be appreciated.
Posted using SoMee