ChatGPT+

ChatGPT+ is a Chrome extension developed by smartify.ai. According to the data from Chrome web store, current version of ChatGPT+ is 0.0.3.0, updated on 2023-03-20.
1,000+ users have installed this extension. 29 users have rated this extension with an average rating of .
developer website: myaiappstore.com

Useful and customizable prompts for ChatGPT

🏆 We are really proud to announce that ChatGPT+🧠 is officially THE FIRST AI TOOL to Run on GPT-3.5-TURBO powered by OpenAI.

🧠ChatGPT+🧠 is an ALL-IN-ONE tool that enables you to use GPT-3.5-turbo on any Web page of your browser💻 by using an API-key🔑

🙌 Supported by EVERY Web-Based apps!!!
• Google Chrome, Microsoft Edge, Microsoft Bing, Safari, 🔍
• Gmail, outlook, Apple Mail ✉️
• Notion, Remnote, Evernote, Obsidian and EVERY Apple app when accessed
through icloud.com 📝
• LinkedIn 🔗
• Github 🐙
• PDF's*, to use a PDF, you can either :
• 📂 Open finder and Right click on your file + Select "open with Google".
• ❏ Drag and drop it.
• And so on..., as long as you remain on your browser 🌐.

🙋‍♂️ Why ChatGPT+? :

➡️ 100% FREE (NO CREDIT CARD REQUIRED)💰.
➡️ An ALL-IN-ONE tool🔨 with a list off DEFAULT prompts that are ready to use. Also, we gave you access to the parameters so that you can CUSTOMIZE your own prompts to fit your specific needs.
➡️ Powerful features🤓. It's like using ChatGPT on Steroids 💉:
📧 Reply to emails in no time.
🚀 Summarize ANY Content in seconds.
🧑‍💻 Master Complex Excel Formulas and Codes.
➡️ User-friendly interface, with :
𝌼 A Minimalistic design to facilitate the navigation around the app.
⏱️ A Built-In HISTORY section to keep track of all your work and researches at
the same place ✅.
🖥️ The possibility to Download your History.
➡️ We're constantly adding new cool Features, making ChatGPT+🧠 the BEST free AI tool.

🙅‍♂️ As of march 5 2023, we're making some promises!!!
-After discovering ChatGPT+🧠, most of your remaining apps will end in the
trash can🗑️
-You will never waste your time switch between apps and pages again⌛️.

Visit our website for more information💻!!! https://myaiappstore.com/

🪜 Use ChatGPT+ in 3 simple steps:

1️⃣ Select any text in your web browser.
2️⃣ Right-click and go to ChatGPT+ 🧠 in the contextual menu.
3️⃣ Choose a request. A pop-up window will appear while ChatGPT-3 generates a response😎!!

🔑 How to generate your API key:

1) Pin 📌 the extension in the menu bar to make it more accessible.
2) Click on the ChatGPT+ logo 🧠 and then click on the link « where can I generate my API key? ». It will bring you to the OpenAI API key website page.
3) Copy your existing API key or Create a new one by clicking on “+ Create new secret key”and paste it into ChatGPT+🧠.
Here is a video tutorial on how to get it : https://www.youtube.com/watch?v=NmlcmQTxKSI&ab_channel=ChatGPT%2B

😧 Did you know that ChatGPT+🧠 still works during OpenAI crash time?

The reason for that is that ChatGPT+🧠 is using an API key to access ChatGPT. The API provider (OpenAI) has implemented strategies such as load balancing and caching to optimize performance and prevent overloading. Additionally, OpenAI may have allocated sufficient resources to handle a high volume of requests or traffic🚦.

🤔 Simple definitions to understand AI models:

➡️ Temperature: A setting that controls the creativity and randomness of the AI-
generated text. Lower temperatures result in more predictable responses,
while higher temperatures result in more random and creative responses.
➡️ AI Models: Text-davinci-003, Text-davinci-002, Text-curie-001, Text-babbage,
Text-ada-001, Code-davinci-002 are all different pre-trained AI models with
varying levels of sophistication, capable of generating text or code in
response to prompts. To learn more about the different models and their
particularities, I would recommend checking out the section on AI models in
the comprehensive guide located at the end of the description.
➡️ Token: A unit of text that the AI model uses to generate responses.
It allows the model to focus on individual units of meaning in the prompt.
➡️ Length: Refers to the number of words or characters in the AI-generated
response.
➡️ Prompts and Completions: Prompts are the initial input provided to the AI
model, while completions are the generated outputs in response to the
prompts.
➡️ API key: An API key is a unique code that allows you to access and use the
features of an API (Application Programming Interface). It acts as a digital
signature to authenticate your requests to the API server.

💫 The history behind ChatGPT creation:

Artificial intelligence is a branch of computer science that deals with creating intelligent machines that can perform tasks that typically require human , such as learning, reasoning, problem-solving, and decision-making. AI systems use algorithms and mathematical models to analyze and interpret data, identify patterns, and make predictions.

OpenAI is a research organization that aims to advance AI technology in a safe and beneficial way. One of their major achievements is the development of GPT (Generative Pre-trained Transformer) language models, which use deep learning algorithms to generate human-like text. OpenAI’s GPT-3 model is a massive neural network trained on vast amounts of text data, allowing it to learn the patterns and structures of language. ChatGPT, one of the GPT models, is an AI language model that can generate human-like text in response to given prompts. It is a powerful tool with many applications, from chatbots and customer service to content creation and language translation.

📈 The number of parameters and the size of the training data set is increasing significantly in each version of GPT:

* GPT-1 was trained on around 40 GB of text data and had 117 million parameters.
* GPT-2 was trained on a much larger dataset of around 45 terabytes of text data and had 1.5 billion parameters.
* GPT-3 is currently the largest GPT model, trained on a massive dataset of around 570 GB of text data and has 175 billion parameters.
* GPT-4 is expected to be released around the beginning of 2023. It has been trained on roughly the same size as the previous one. When asked about the viral rumour that purportedly stated that GPT-4 is being trained on over 100 trillion parameters, OpenAI CEO Sam Altman called it “complete bullshit.”

💾 Understanding the Role of GB and Parameters in AI Models:

GB (data size) and parameters are important factors in determining the performance and capabilities of an AI model. Both are measures of size and complexity but refer to different aspects of AI models.

* GB refers to the amount of data the model has been trained on. Generally, the more training data a model has, the better it can learn to recognize patterns 🐾and make predictions.
* Parameters, on the other hand, refer to the number of learnable elements in the model. These weights and biases are adjusted during the training process to optimize the model's performance. Generally, the more parameters a model has, the more complex it is and the more capable it is of learning complex patterns in the data.

🐶 One way to think about the difference between GB and parameters is to use the example of learning to recognize different breeds of dogs.

* If you are given a small set of pictures of dogs to learn from (small size of the training data/GB), you may only be able to recognize a few breeds accurately. However, a much larger set of pictures would increase your ability to recognize different breeds of dogs, because you have more examples to learn from.
* Parameters: Now, imagine that you want to teach a computer to recognize different breeds of dogs. In order to do this, you might want to create a model that takes in pictures of dogs and outputs the breed. The model will have a set of adjustable weights that are optimized during the training process to improve its accuracy. The number of these adjustable weights can be thought of as the parameters in the model. The more parameters the model has, the more complex it can be, and the better it may be able to learn the intricacies of each dog breed.

🙋 Why does GPT-3 by OpenAI experience performance issues or stop working when overloaded?

There are a few reasons for that. One of the main reasons is that it may not have enough computational resources or memory to handle a large number of requests or a high level of traffic. This can cause delays in response times or even system crashes💥.

Additionally, if there are software bugs or issues with the infrastructure 🧑‍💻supporting the system, this can also lead to performance problems. To prevent overloading or improve system performance, strategies such as load balancing, caching, and optimizing code can be implemented.

The performance of the extension could also depend on the current load on the system at the time ⏱️ of use. If there are fewer users or requests being made to the system, it is more likely that the extension will work smoothly and quickly. Conversely, if there is high traffic🚦 or many users making requests to the system, the response time may be slower🐢 or the system may experience delays or even crashes.

🌟 Each Model explained in detail:

1.GPT-3.5-turbo: Most capable GPT-3.5 model and optimized for chat at 1/10th the cost of text-davinci-003. Will be updated with our latest model iteration.
👍 Good at: Conversation and text generation
2. Text-davinci-003: This is the most advanced and powerful🔌 AI model from OpenAI. It can generate complex and creative responses to prompts, and is particularly good at generating text that sounds human-like. However, this model is also the most expensive and resource-intensive, and may take longer to generate responses than other models. Use this model when you need the highest-quality and most human-like text responses, and are willing to pay a premium for them.
👍 Good at: Complex intent, cause and effect, summarization for audience
3. Text-davinci-002: This is a slightly less advanced version of Text-davinci-003, but still produces high-quality and human-like text responses. It is less expensive💰 and less resource-intensive than Text-davinci-003, but may still take longer to generate responses than other models. Use this model when you need high-quality and human-like text responses, but want to save on costs.
👍 Good at: Complex intent, cause and effect, summarization for audience
4. Text-curie-001: This AI model is capable of generating long-form text and can also complete programming tasks. It is more affordable than Text-davinci-002 and Text-davinci-003, and is faster at generating responses. However, the text responses generated by this model may not be as human-like as those generated by other models. Use this model when you need longer-form text responses or need to complete programming tasks.
👍 Good at: Language translation, complex classification, text sentiment,
summarization
5. Text-babbage: This model is the least expensive and least resource-intensive of all the OpenAI models. It is best suited for generating short-form text, and can be used to complete simple tasks such as writing headlines✏️ or summaries. However, the responses generated by this model may not be as creative or sophisticated as those generated by other models. Use this model when you need to generate short-form text and want to keep costs and resources to a minimum.
👍 Good at: Moderate classification, semantic search classification
6. Text-ada-001: This is a newer model from OpenAI, designed specifically for language translation tasks. It is particularly good at translating between languages and can generate high-quality translations. However, it may not be as effective at generating other types of text responses as other models. Use this model when you need to translate text between languages.
👍 Good at: Parsing text, simple classification, address correction, keywords
7. Code-davinci-002: This model is specifically designed for generating code, and is particularly good at completing coding tasks such as auto-completing code or debugging code䷢. It is more expensive and resource-intensive than other models, but can save developers a lot of time and effort. However, the generated code may not be as efficient or optimized as code written by human developers. Use this model when you need to complete coding tasks quickly and efficiently.

👻 WHISPER, A Multilingual Speech Recognition and Translation Model:

Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification. The Whisper v2-large model is currently available through our API with the whisper-1 model name.

Currently, there is no difference between the open source version of Whisper and the version available through our API. However, through our API, we offer an optimized inference process which makes running Whisper through our API much faster than doing it through other means. For more technical details on Whisper, you can read the paper.

🖥️ ChatGPT API:

➡️ Model: The ChatGPT model family we are releasing today, gpt-3.5-turbo, is the same model used in the ChatGPT product. It is priced at $0.002 per 1k tokens, which is 10x cheaper than our existing GPT-3.5 models. It’s also our best model for many non-chat use cases—we’ve seen early testers migrate from text-davinci-003 to gpt-3.5-turbo with only a small amount of adjustment needed to their prompts.

➡️cAPI: Traditionally, GPT models consume unstructured text, which is represented to the model as a sequence of “tokens.” ChatGPT models instead consume a sequence of messages together with metadata. (For the curious: under the hood, the input is still rendered to the model as a sequence of “tokens” for the model to consume; the raw format used by the model is a new format called Chat Markup Language (“ChatML”).)

🔑 What is an API Key?

An API-key is a unique code that is used to authenticate access to a web-based application or service. Think of it as a special password that identifies you or your application to the service.

Your API-key is included in the proper request headers of the source code in ChatGPT+🧠. This will ensure that ChatGPT+ can access the GPT-3 OpenAI's API and make requests using your newly generated key.

When you use an application that makes requests to a web-based service or application, such as Google Maps or OpenAI's ChatGPT, an API key is often required to ensure that you have proper access to the service. This key is usually a long string of characters that you can copy and paste into your application or code to verify that you are authorized to use the service.

The API key serves as a way to control access to the service, and it also helps the service provider monitor usage and identify any abuse or unauthorized access attempts. It's important to keep your API key private and not share it with others or expose it publicly, as this could need out of don't don't downtown damn damn damn allow unauthorized access to the service and potentially cause issues or security risks.