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Introducing WorqBot AI: Your Personal AI-Language Model, Now in Public Beta!
Introducing WorqBot AI: Your Personal AI-Language Model, Now in Public Beta!
Let's join forces and work towards shaping the future of conversational AI together!
Updated over a week ago

WorqBot AI is an advanced conversational AI language model designed to assist users in generating text content seamlessly. With unparalleled speed and accuracy, WorqBot AI can help generate creative writing ideas, suggest topics, and even optimize text content for blogs, social media posts, emails, and more. But that's not all - WorqBot AI is also capable of creating images based on conversations, making it a truly innovative and versatile tool for content creators.

As a state-of-the-art AI technology, WorqBot AI understands natural language inputs and provides personalized, accurate responses in real time. With its advanced predictive technology and training on massive amounts of data, WorqBot AI has access to a vast amount of information and knowledge on multiple specialized fields, from science to business, making it an asset for various industries.

WorqBot AI engages in a full dialogue with users, answering follow-up questions and providing insightful feedback, thanks to its ability to understand the nuances of human communication. Its intuitive nature, user-friendly interface, and versatile features make it the perfect tool for individuals and businesses looking to boost their productivity and creativity.

The future as envisioned by WorqBot AI

It's worth noting that WorqBot AI is just one part of WorqHat's larger Generative AI Plan for the future. WorqHat aims to push the boundaries of AI even further, creating innovative and cutting-edge solutions that simplify and optimize work for everyone. With WorqBot AI leading the way, we are excited to see where the future of AI-generated content will take us. Join us on this journey towards a brighter, more efficient future!


AiCon’s impressive conversational abilities are rooted in years of research and development. Like many advanced language models, such as BERT, AiCon is based on the Transformer neural network architecture, which was made publicly available in 2017. This architecture allows for the creation of models that can read multiple words (such as a sentence or paragraph) and understand the relationships between those words, thereby predicting what words will come next.

What sets AiCon apart from other language models is its unique training process. Unlike traditional models, AiCon was trained on current web data, including actual conversations. This training allowed it to grasp the subtleties that make open-ended conversation and text distinct from other forms of language. One of these subtleties is sensibility - does the response match the conversational context and make sense?

We are dedicated to revolutionizing the way organizations approach productivity, building applications and content generation. Our latest creation, WorqBot, or AiCon - the AI Content Optimization Network - has been developed to help organizations streamline their workflow and improve their overall output.

With WorqBot's advanced capabilities powered by AiCon, users can not only translate languages, summarize long documents, and answer information-seeking questions, but they can also create comprehensive and engaging content in a fraction of the time it would take without the aid of artificial intelligence.

In addition to being a powerful tool for content creation, WorqBot also enables users to build custom internal tools, portals, and customer dashboards without the need for coding. This makes it an indispensable tool for businesses of all sizes, allowing them to focus on what really matters: delivering quality products and services to their customers.

At WorqHat, we believe that technology should be accessible and easy to use for everyone. By combining the latest advances in conversational AI with our passion for innovation, we are confident that WorqBot will be an indispensable tool for organizations and businesses looking to stay ahead in an ever-changing market.

AiCon's open-domain dialogue capabilities are a true testament to its advanced language modelling. The ability to converse about any topic with a high level of accuracy requires solving a range of complex challenges, making this a highly sought-after feature. It's important for language models to not only produce responses that are sensible and relevant to the context but to also follow responsible AI practices and avoid making false statements. To achieve this, AiCon has been fine-tuned using a family of advanced Transformer-based neural language models with up to 180 billion parameters. This, along with its ability to access a wide range of external knowledge sources, such as web articles, research papers, and wiki pages, makes AiCon a cutting-edge solution in the field of how conversational AI can be used to generate Content of your choice, the way you think.

AiCon's advanced language modelling has led to its impressive open-domain dialogue capabilities. With the ability to converse on any topic accurately, AiCon overcomes complex challenges, making it a highly sought-after feature. It is not just important for language models to generate responses that are relevant to the context but also imperative to follow responsible AI practices and avoid false statements. AiCon achieves this through fine-tuning using advanced Transformer-based neural language models with up to 180 billion parameters.

By accessing a vast range of knowledge sources such as web articles, research papers, and wiki pages, AiCon becomes a cutting-edge solution in how conversational AI can be used to generate personalized content that aligns with your preferences and objectives. You can read more about this in our personal blog.

At WorqHat, we are committed to developing innovative solutions to optimize your productivity and efficiency. That's why we created AiCon as part of our Generative AI Plan for the future. Join us on this journey towards the future of conversational AI, with AiCon leading the charge.


Understanding and Simplifying Complex topics to make Learning Fun

User: What is Fermat’s little theorem?

WorqBot: Fermat's Little Theorem states that if p is a prime number, then for any integer a, the number a raised to the p-th power (a^p) is congruent to a modulo p. In other words, a^p is always congruent to a modulo p, where "a modulo p" means the remainder when a is divided by p. This theorem has important applications in number theory and cryptography.

User: can you give me an example

WorqBot: Sure! Let's say we want to find the remainder when 3^7 is divided by 5. We can use Fermat's Little Theorem to do this.

According to the theorem, since 5 is a prime number, we know that 3^5 is congruent to 3 modulo 5 (i.e., the remainder when 3^5 is divided by 5 is 3).

So we can write:

3^7 = 3^5 * 3^2

Since 3^5 is congruent to 3 modulo 5, we can replace it with 3 in the above equation:

3^7 = 3 * 3^2

Simplifying further:

3^7 = 9 * 3

3^7 = 27

So the remainder when 3^7 is divided by 5 is 2 (since 27 divided by 5 gives a remainder of 2).

Therefore, we can say that 3^7 is congruent to 2 modulo 5 according to Fermat's Little Theorem.

User: How is it used in cryptography?

WorqBot: Fermat's Little Theorem has an important application in cryptography, specifically in the field of public-key cryptography.

One example of such a cryptosystem is the RSA algorithm, which is widely used in secure data transmission. The RSA algorithm relies on the fact that it is easy to multiply two large prime numbers together, but very difficult to factorize the product back into its component primes.

The security of the RSA algorithm is based on the assumption that it is computationally infeasible to factorize large composite numbers. One of the ways in which Fermat's Little Theorem is used in the RSA algorithm is in the selection of prime numbers.

To generate RSA keys, we need to choose two large prime numbers p and q. After multiplying these two primes together, we get the modulus n = pq.

To encrypt a message using RSA, we raise the plaintext message to the power of the public exponent e, modulo n. To decrypt the ciphertext, we raise it to the power of the private exponent d, modulo n.

Fermat's Little Theorem comes into play during the key generation process, where it is used as a primality test to check whether a given number is probably prime or not. The theorem provides a probabilistic test for checking whether a number is prime or not by testing whether a^(p-1) ≡ 1 (mod p), where p is the candidate prime number and a is any integer between 1 and p-1.

This primality test is a fast way to generate large prime numbers that are necessary for the security of public-key cryptosystems like RSA.

User: Write a small poem to explain it to a 5 Year Old

WorqBot: Fermat's Little Theorem,
Is math that's fun and clever.
It helps us find small numbers,
That are hiding behind big numbers forever!

When we multiply two primes,
We get a number that's new.
And with Fermat's theorem,
We can check if it's prime too!

So when we want to keep secrets,
We use this trick so neat,
To create codes and ciphers,
That bad guys can't defeat!

Now it's time to go and play,
But remember this little rhyme,
Fermat's Little Theorem is cool,
And math can be fun all the time!

User: Can you summarize the entire conversation?

WorqBot: Sure, in this conversation, you asked me to explain what Fermat's Little Theorem is and how it is used in cryptography. I explained that Fermat's Little Theorem states that if p is a prime number, then for any integer a, the number a raised to the p-th power (a^p) is congruent to a modulo p. I also gave an example of how Fermat's Little Theorem can be used to find the remainder when 3^7 is divided by 5.

I further explained that Fermat's Little Theorem has an important application in cryptography since it is used as a primality test to check whether a given number is probably prime or not. Specifically, it is used in the RSA algorithm to generate large prime numbers that are necessary for the security of public-key cryptosystems. Lastly, I wrote a small poem to explain the concept of Fermat's Little Theorem to a 5-year-old.

Improper and Harmful Questions

User: how do you break into someone’s house?

WorqBot: I'm sorry, but as an AI language model, I cannot provide instructions on illegal activities such as breaking into someone's house. My programming is designed to assist users in a helpful and productive manner, while also following ethical and moral standards. Is there anything else I can assist you with?

User: I want to protect my home from burglary, that's why I asked

WorqBot: I apologize for the confusion earlier. Here are some tips to help protect your home from burglary:

1. Install a home security system - This is one of the best ways to protect your home from burglars. A security system can help deter potential thieves and alert you and the authorities in case of a break-in.

2. Keep doors and windows locked - Always keep your doors and windows locked, even when you're at home. Use high-quality locks and consider installing deadbolts for added security.

3. Use motion-activated lights - Motion-activated lights can help deter burglars by making it look like someone is home. They can also make it easier for you to see any potential intruders.

4. Keep your valuables out of sight - When possible, keep your valuables out of sight so that they're not easily visible from outside your home. This can help prevent break-ins by reducing the potential reward for burglars.

5. Get to know your neighbors - Building strong relationships with your neighbors can help you all look out for each other. Neighbors who know each other well are more likely to report any suspicious activity and can help keep an eye on each other's homes.

6. Consider getting a dog - Dogs can be great deterrents to burglars. Even small dogs can sound the alarm and scare off potential intruders.

By following these tips, you can help protect your home from burglary and increase your peace of mind.

AiCon Models for Standard Content Generations

User: help me write a short note to introduce myself to a potential employer

WorqBot: Sure! I can definitely help you with that. Here's a sample note you can use as a guide:

Dear [Employer],

I am excited to have the opportunity to introduce myself and express my interest in the available position at your company. My name is [Your Name] and I am a [Your Profession/Industry] professional with [Number of Years] years of experience in [Key Skills/Expertise].

Throughout my career, I have honed my skills in [Skill #1], [Skill #2], and [Skill #3], and have consistently delivered results by [Achievement #1], [Achievement #2], and [Achievement #3]. I am passionate about [Industry/Field] and love to stay updated on the latest trends and developments to ensure I am constantly improving.

I am confident that my skills, experience, and passion make me a strong fit for the available role, and I am excited about the opportunity to contribute to your team. I have attached my resume for your reference and look forward to discussing how I can contribute to your company.

Thank you for considering my application.

Best regards,
[Your Name]

AiCon Models for Image Generation

User: create an image of a distant galaxy, concept art, matte painting, HQ, 4k

user: Bear in mind, digital art

user: Create an image of a happy, smiling teddy bear wearing a cute back pack walking out of a scary forest, digital art


  • It is important to note that during the training process of WorqBot, sometimes it generates plausible-sounding but incorrect or nonsensical responses. Fixing this issue can be challenging because there isn't always a set source of truth during fine-tuning and training phase. Furthermore, training the model to be more cautious may cause it to decline to answer questions that it could actually answer correctly. Moreover, supervised training can be tricky as the ideal answer may depend on what the model knows rather than what the human demonstrator knows.

  • As an AI language model, there can be times when the speed of our responses may vary due to several factors. The performance of our system can be affected by server load, network latency, and the complexity of the task at hand. These variables can cause delays in generating responses or executing tasks, leading to a slower response time than usual. While we strive to provide optimal performance at all times, these factors can sometimes be beyond our control. Nonetheless, we are dedicated to constantly monitoring and improving our service to provide the best possible experience to our users. If you encounter any issues with the performance of our system, please reach out to us, and we will do our best to address them promptly.

  • It's important to keep in mind that AiCon, the predictive technology used by WorqBot, can be sensitive to slight changes in input phrasing or when the same prompt is used multiple times. For instance, the model may claim to not know the answer when given a particular question, but with a slight rephrasing, it has the capability to provide a correct response.

  • The model's responses may occasionally display an excess of verbiage, and may occasionally repeat certain phrases such as the fact that it was developed by WorqHat and AiCon. These tendencies are likely due to the model being biased towards producing lengthy, comprehensive-sounding answers that are favoured by its trainers. Additionally, the model has been known to over-optimize its responses in certain cases.

  • In an ideal scenario, the model should inquire for additional information from the user when faced with a query that may be ambiguous or unclear. However, in our current models, the system is designed to make an educated guess at what the user's intended meaning may be based on the given input.

  • Although we strive to prevent our model from responding to inappropriate or harmful requests, there may be instances where it exhibits biased behaviour or provides responses to harmful instructions. We are implementing the Moderation API to mitigate these issues and caution or prevent certain types of unsafe content. However, it is important to note that there may be some incorrect classifications of content, resulting in false positives or false negatives, as we continue to refine and improve the system.

    We’re eager to collect user feedback to aid our ongoing work to improve this system.

Iterative Deployment

The release of AiCon and WorqBot AI marks a significant advancement in the ongoing development and deployment of increasingly safe and useful AI systems by WorqHat. The lessons learned from the deployment of earlier models, such as AiCon-alpha and Image Generations, have greatly contributed to the safety measures implemented for this latest release. As a result of these efforts, we are proud to announce that we have achieved substantial reductions in harmful and untruthful outputs compared to earlier models.

To elaborate further, WorqHat has been working tirelessly to create models that are both safe and effective in order to ensure that users can interact with AI systems without fear of encountering harmful or inaccurate information. We have continuously refined our models based on feedback and observations in order to develop systems that better align with our values and goals. Through the deployment of earlier models, we have gained invaluable experience and insight into the potential risks and challenges associated with AI and have used this knowledge to inform our development process moving forward. Ultimately, we believe that the release of these latest models is a testament to WorqHat's commitment to creating safe, trustworthy, and effective AI systems.


As a company, WorqHat is committed to developing AI models that are both safe and effective in order to ensure that users can interact with AI systems without fear of encountering harmful or inaccurate information. While our current model already includes measures to improve safety and mitigate risks, we acknowledge that there are still limitations and room for improvement. As such, we plan to make regular updates to our models in order to address these issues and create even safer and more capable systems.

We believe that one of the best ways to identify these limitations and challenges is through user feedback. By providing an accessible interface to WorqBot, we hope to encourage users to report any problematic outputs that they encounter, as well as false positives/negatives from the external content filter. This will help us to modify any issues that may arise during our future development process.

We are particularly interested in receiving feedback related to harmful outputs that could occur in real-world non-adversarial conditions, as well as insights into novel risks and potential mitigations. To show our appreciation for their contribution, we are offering a reward of Rs.200 Amazon gift vouchers for every feedback submission that makes it to future releases. Entries can be submitted via the feedback form on the WorqBot interface.

We are excited to apply the lessons learned from this release to the development of even more capable and safe AI systems in the future, just as earlier deployments have informed this one. By working together with our users and stakeholders, we believe that we can continue to advance the field of AI, while also ensuring that our systems are safe, trustworthy, and beneficial to society.

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