Understanding the Differences Between AI, ML, and DL: Examples and Use Cases

Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are related but distinct concepts.

AI refers to the development of machines that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. For example, an AI-powered chatbot that can understand natural language and respond to customer inquiries in a human-like way.

AI example 

Siri - Siri is an AI-powered virtual assistant developed by Apple that can recognize natural language and respond to user requests. Users can ask Siri to perform tasks such as setting reminders, sending messages, making phone calls, and playing music.

Chatbots - AI-powered chatbots can be used to communicate with customers and provide them with support or assistance. For example, a bank may use a chatbot to help customers with their account inquiries or a retail store may use a chatbot to assist customers with their shopping.

Machine Learning (ML) is a subset of AI that involves the development of algorithms and statistical models that enable machines to learn from data without being explicitly programmed. ML algorithms can automatically identify patterns in data, make predictions or decisions based on that data, and improve their performance over time. For example, a spam filter that learns to distinguish between legitimate and spam emails based on patterns in the email content and user feedback.

ML example

Netflix recommendation system - Netflix uses ML algorithms to analyze user data such as watch history, preferences, and ratings, to recommend movies and TV shows to users. The algorithm learns from the user's interaction with the platform and continually improves its recommendations.
 

Fraud detection - ML algorithms can be used to detect fraudulent activities in banking transactions. The algorithm can learn from past fraud patterns and identify new patterns or anomalies in real-time transactions.

Deep Learning (DL) is a subset of ML that uses artificial neural networks, which are inspired by the structure and function of the human brain, to learn from large amounts of data. DL algorithms can automatically identify features and patterns in data, classify objects, recognize speech and images, and make predictions based on that data. For example, a self-driving car that uses DL algorithms to analyze sensor data and make decisions about how to navigate the road.

DL example: 

Image recognition - DL algorithms can be used to identify objects in images, such as people, animals, and vehicles. For example, Google Photos uses DL algorithms to automatically recognize and categorize photos based on their content. The algorithm can identify the objects in the photo and categorize them as people, animals, or objects.

Autonomous vehicles - DL algorithms can be used to analyze sensor data from cameras, LIDAR, and other sensors on autonomous vehicles. The algorithm can identify and classify objects such as cars, pedestrians, and traffic lights, and make decisions based on that information to navigate the vehicle.

So, AI is a broad concept that encompasses the development of machines that can perform tasks that typically require human intelligence. ML is a subset of AI that involves the development of algorithms and models that enable machines to learn from data. DL is a subset of ML that uses artificial neural networks to learn from large amounts of data and make complex decisions or predictions.

IS THERE ANY WATERMARKING TO IDENTIFY AI GENERATED TEXT?

With the rise of artificial intelligence (AI), there are growing concerns about the potential misuse of AI-generated text, such as the creation of fake news articles, fraudulent emails, or social media posts. To address these concerns, watermarking techniques can be used to identify the source of AI-generated text and detect any unauthorized modifications or tampering.Watermarking is a process of embedding a unique identifier into digital content that can be used to verify the authenticity and ownership of the content. For AI-generated text, watermarking can provide a means of identifying the source of the text and ensuring its integrity.

There are several watermarking techniques available for AI-generated text. Here are three examples:

• Linguistic patterns: This technique involves embedding a unique pattern of words or phrases into the text that is specific to the AI model or dataset used to generate the text. The pattern can be detected using natural language processing (NLP) techniques and used to verify the source of the text.
• Embedding metadata: This technique involves embedding metadata, such as the name of the AI model, the date and time of generation, and the source of the data used to train the model, into the text. This information can be used to verify the source of the text and identify the AI model used to generate it.
• Invisible watermarking: This technique involves embedding a unique identifier into the text that is invisible to the human eye but can be detected using digital analysis tools. The watermark can be used to verify the source of the text and detect any modifications or tampering.

Overall, watermarking techniques for AI-generated text can provide a means of identifying the source of the text and detecting any unauthorized modifications or tampering. These techniques can be useful in addressing concerns about the potential misuse of AI-generated text and ensuring the authenticity and integrity of digital content.

In addition to watermarking techniques, there are other approaches that can be used to address concerns about the potential misuse of AI-generated text. For example, NLP techniques can be used to detect fake news articles or fraudulent emails, and AI models can be trained to identify and flag potentially harmful content.

Why did IPFS made way for KUBO and discontinued earlier method via go-ipfs ?

KUBO is a new project by Protocol Labs, the same organization that created IPFS. While IPFS is a great tool for decentralized storage and content addressing, it still has some limitations when it comes to scalability, performance, and interoperability. In particular, IPFS relies on a single node to manage the content of a particular hash, which can be a bottleneck in a large-scale decentralized system.

KUBO, on the other hand, is designed to address these limitations by using a sharded architecture that distributes the storage and retrieval of data across multiple nodes in the network. This allows KUBO to scale more effectively and handle larger volumes of data with higher performance. Additionally, KUBO is designed to be more interoperable with other decentralized technologies, which makes it easier to integrate with other decentralized applications and networks.

As for why the earlier method via go-ipfs was discontinued, it's likely because Protocol Labs wanted to focus on developing KUBO as a replacement for IPFS. While go-ipfs is still an actively developed project and remains a popular implementation of IPFS, it may not have the scalability and performance capabilities that KUBO promises to deliver.

How to Avoid LLM Derived Text from Plagiarism using Text Watermarking?

Plagiarism is a growing concern for writers, researchers, and publishers. It not only harms the original authors but also undermines the credibility of academic and research institutions. One way to prevent plagiarism is by using text watermarking.

Text watermarking is a technique used to embed a unique identifier in the text of a document. This identifier can be used to identify the source of the document and to determine if the document has been tampered with or plagiarized. In this blog post, we'll explore how text watermarking can be used to avoid LLM derived text from plagiarism.

LLM (Latent Language Model) derived text is a technique used by some plagiarism detection tools to compare texts based on their linguistic features. However, this method can produce false positives and may result in innocent authors being accused of plagiarism. Text watermarking can be used to address this issue by providing a verifiable proof of ownership of the text.

Here are some steps that you can follow to avoid LLM derived text from plagiarism using text watermarking:

Step 1: Create a unique identifier for your text. This can be a sequence of characters or a digital signature that is generated using a hashing algorithm.

When we talk about creating a unique identifier for your text, we are essentially talking about generating a piece of information that is specific to the document or text you want to watermark. This identifier should be unique, unambiguous, and difficult to guess. The purpose of creating a unique identifier is to provide a way to verify the authenticity of the text and ensure that it has not been tampered with or plagiarized.

There are several ways to create a unique identifier for your text. One common method is to use a hashing algorithm to generate a digital signature for the document. A hash function takes input data, such as the text of a document, and produces a fixed-size output, which is the digital signature. The output generated by the hash function is unique to the input data, so any changes to the input data will result in a different output.

Another method to create a unique identifier for your text is to use a sequence of characters. You can create a unique sequence of characters by combining elements such as your name, the date of creation, or any other relevant information. For example, you can create a unique identifier by combining your initials with the date of creation in the following format: AB-2022-04-06.

It is important to ensure that the unique identifier you create is not easily guessable or replicated. Using a common sequence of characters or numbers could make it easier for someone to guess or create the same identifier, which defeats the purpose of having a unique identifier in the first place. Therefore, it is recommended that you use a combination of elements that are unique to your text or document.

Creating a unique identifier for your text is an important step in text watermarking. It provides a way to verify the authenticity of the text and protect it from plagiarism. You can create a unique identifier using a hashing algorithm or by combining relevant information to generate a unique sequence of characters. Whichever method you choose, it is important to ensure that the identifier you create is unique, unambiguous, and difficult to guess.


Step 2: Embed the identifier in the text using text watermarking software. There are several text watermarking tools available online that you can use for this purpose.

Once you have created a unique identifier for your text, the next step is to embed it in the text using text watermarking software. There are several text watermarking tools available online that you can use for this purpose. Here's a step-by-step guide to embedding the identifier in your text using text watermarking software:

1: Choose a text watermarking tool

There are many text watermarking tools available online, both free and paid. Some popular options include Digimarc, Visible Watermark, and uMark. Research and compare various tools to find the one that best suits your needs.

2: Install and open the text watermarking software

Once you have chosen a text watermarking tool, download and install it on your computer. Then, open the software.

3: Load the text you want to watermark

Next, load the text you want to watermark into the software. This can be done by selecting "Open" or "Import" from the file menu and selecting the text file.

4: Enter the unique identifier

Now, enter the unique identifier that you created earlier into the text watermarking software. The software should have an option to enter text, which is where you can input the identifier.

5: Choose the watermarking method

The text watermarking software will have different methods for embedding the identifier into the text. You can choose from options such as visible or invisible watermarks. Visible watermarks are typically added on top of the text, while invisible watermarks are embedded within the text itself.

6: Apply the watermark

After choosing the watermarking method, apply the watermark to the text. The software should have an option to apply the watermark, which will embed the identifier into the text.

7: Save the watermarked text

Finally, save the watermarked text as a new file. Be sure to keep the original text file and the watermarked text file in separate locations.

Step 3: Register the identifier with a trusted third-party service. This will provide a verifiable proof of ownership of the text.

Registering the identifier with a trusted third-party service is an important step in protecting your text and providing a verifiable proof of ownership. Here's a step-by-step guide on how to register the identifier with a trusted third-party service:

1: Choose a trusted third-party service

There are many third-party services available online that offer text registration and verification services. Some popular options include Copyright Office, Myows, and Safe Creative. Research and compare various services to find the one that best suits your needs.

2: Create an account

Once you have chosen a third-party service, create an account on their website. This will typically involve providing your name, email address, and other contact information.

3: Upload the watermarked text

After creating an account, you will be able to upload the watermarked text to the third-party service. This may involve filling out a form or simply uploading the file.

4: Enter the identifier

When registering the text with the third-party service, you will be prompted to enter the unique identifier that you created earlier. This will allow the service to verify your ownership of the text.

5: Pay the registration fee

Many third-party services charge a fee for text registration and verification. Make sure you understand the fee structure and pay the appropriate fee to complete the registration process.

6: Verify the registration

After registering the text, you will receive a verification of the registration from the third-party service. This will typically include a unique identifier for the registered text, as well as information on the registration date and time.

7: Keep a copy of the registration certificate

Make sure to keep a copy of the registration certificate in a secure location. This will serve as proof of ownership and can be used to defend your copyright in case of infringement.

Step 4: Monitor your text for plagiarism using a plagiarism detection tool. If your text is plagiarized, you can use the identifier to prove that you are the original author of the text.

Monitoring your text for plagiarism is an important step in protecting your intellectual property and ensuring that your work is not being used without your permission. Here's a step-by-step guide on how to monitor your text for plagiarism using a plagiarism detection tool:

1: Choose a plagiarism detection tool

There are many plagiarism detection tools available online, both free and paid. Some popular options include Turnitin, Grammarly, and Copyscape. Research and compare various tools to find the one that best suits your needs.

2: Sign up for an account

Once you have chosen a plagiarism detection tool, sign up for an account on their website. This will typically involve providing your name, email address, and other contact information.

3: Upload your text

After creating an account, you will be able to upload your text to the plagiarism detection tool. This may involve copying and pasting the text, or uploading a file.

4: Run the plagiarism check

Once the text is uploaded, run a plagiarism check using the tool's software. This may take several minutes or longer, depending on the length of the text and the complexity of the analysis.

5: Review the results

After the plagiarism check is complete, review the results provided by the tool. This will typically include a report on any instances of plagiarism found in the text, as well as information on the source of the plagiarism.

6: Take action

If plagiarism is detected in your text, take appropriate action to address the issue. This may involve contacting the person or organization responsible for the plagiarism, filing a DMCA takedown notice, or taking legal action.

7: Repeat the process regularly

To ensure ongoing protection of your text, repeat the process of monitoring for plagiarism regularly. This may involve setting up automated checks or manually checking your text periodically.


In addition to text watermarking, there are other ways to avoid plagiarism, such as citing sources properly, paraphrasing, and using plagiarism detection software. However, text watermarking is a powerful tool that can provide an additional layer of protection against plagiarism.

In conclusion, text watermarking is an effective way to avoid LLM derived text from plagiarism. By following the steps outlined in this blog post, you can ensure that your text is protected from plagiarism and that you have a verifiable proof of ownership. Remember, plagiarism is a serious offense that can have long-lasting consequences, so it's important to take all necessary precautions to prevent it.

How to Install IPFS via Kubo on Ubuntu ?

Are you interested in learning how to install IPFS (InterPlanetary File System) via Kubo on Ubuntu? Then you've come to the right place!

In this blog post, I'll be sharing a step-by-step video tutorial that will guide you through the process of installing IPFS on an Ubuntu platform using Kubo. But first, let's take a brief look at what IPFS is and why you might want to use it.

IPFS is a distributed file system that aims to replace HTTP as the primary protocol for transferring data on the internet. It allows users to store and share files with others without relying on a central server, making it more secure and efficient than traditional file-sharing methods.

Now, let's dive into the installation process. To follow along with the tutorial, you'll need to have access to an Ubuntu platform and have Kubo installed. If you don't have Kubo installed, you can find the instructions for installing it here.

Step 1: Open a terminal window on your Ubuntu platform.

Step 2: Clone the IPFS repository by running the following command:

git clone https://github.com/ipfs/ipfs.git

Step 3: Navigate to the IPFS directory by running the following command:

cd ipfs

Step 4: Install IPFS via Kubo by running the following command:


kubectl apply -f ./deployment/ipfs-kubo.yml

And that's it! IPFS should now be installed on your Ubuntu platform via Kubo.

If you'd like to see the installation process in action, check out the video tutorial below which shows IPFS installation vide another way 

In conclusion, IPFS is a powerful tool that can revolutionize the way we share and store files online. By following these simple steps, you can easily install IPFS via Kubo on your Ubuntu platform and start exploring all that this innovative technology has to offer.

We hope you found this tutorial helpful. If you have any questions or feedback, feel free to leave a comment below. Happy installing!