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The EASIEST Way To Create A Custom Trained AI ChatBot (2023 Full Tutorial)



The EASIEST Way To Create A Custom Trained AI ChatBot (2023 Full Tutorial)


ENTIRE TRANSCRIPT NO TIME  

hey guys today I want to show you the easiest way to build and train your own custom AI chatbot let's do it all right so today we're going to be using a tool called custom GPT dot AI I'll have this link down in the description below for you to go sign up all right so step number one is we're going to hit create our first project all right it's going to bring us to this page right here now this entire custom trained AI chat bot is going to be built on the back of something called a site map now a site map is just what it sounds like it's a map of your website that basically gives Google or other Bots or things like that kind of a map of how your website is structured together so we need to give custom GPT a map of our website so it knows where to find all the data that it's going to train on so for this example I'm not going to use my website but I have found just a local financial planner I pulled up his website and it looks pretty solid alright so what we're looking for here and this is very important we need to give our bot content to train on if our website or the website we are putting the bot on does not have a lot of content the bot won't know anything it'll be a dumb bot so we gotta feed it intelligence we gotta feed it content and information so that it can train itself up and become smart and basically usable all right so in this case this website looks pretty good there's a lot of different content on here I think we have a few blog posts which definitely helped so yeah we have a Blog here which will be awesome to feed into our bot all right so you want to get something with some decent content on it and then to get the site map all we want to do is we want to basically grab our domain all right and then forward slash sitemap dot XML and hit enter and most of the time you'll be brought to something that looks like this where we can then grab our site map URL we'll copy it just like that and then paste it back in customgpt.ai so that is how you find your site map remember you want to find a Content Rich site or make sure that your site has a bunch of content that the bot can train on all right I'll give this project a name my fake bot and I'll hit create project and so then we are brought to kind of the project dashboard and I'll show you what's kind of going on here right now by using the sitemap customgpt.ai is essentially finding items to feed into our bot so here's all the items it found okay so it found 369 items and then slowly but surely it will index all of those items and all of the words in those items across that website and feed it into our bot to make it smart and turn it into a bot that can give our visitors information so all we have to do now is wait and let our items get indexed as our bot trains itself up all right so you can see here as I refresh we can see that our 369 items are getting indexed every few seconds we can see the words that we are feeding into our bot all right basically giving it data to eat giving it data that it can then gurgle and spit back out to our visitors all right and answer their questions for us so that we don't have to so we'll just let this run until all of our items are indexed okay so our bot is done training let's hop in now and test it out make sure that it kind of digested all the information that we just fed into it so we'll hit ask me anything now remember this website we're on is like a financial advisor website so Wealth Management so I'm gonna ask it something like hey I just graduated college with a bunch of student debt should I pay this down fast and see what it says all right so the bot's thinking and we'll see what it gives me yes it's recommended to develop a plan to pay off your student loans over a certain amount of time it's beneficial to start with your high interest rate loans first and work your way down the list perfect so we now have a custom trained bot based on the information on our website so this bot can now answer questions for visitors in real time instead of having them wait for one of the members of my team to get back to them you know like if it's the weekend they won't hear from me until Monday so this is awesome all right so let's do another example what kind of clients do you guys serve all right we'll see what it pops out we serve clients who are looking for financial services particularly in the areas of Investments retirement and wealth management sweet so we're getting custom answers based on the data on our website this is perfect now the next step is I'm going to come to settings here and show you guys that we can kind of update different things about our chatbot so we can upload a new photo for a new Avatar or whatever the company logo is we can upload that here we can change our background image to make it more on brand I can change our prompt so I can say you know what's up something like that when we hit save changes so you have a bunch of different settings here within customgpt.ai that you can use to customize this bot but it's all pretty simple all pretty basic once you get in you'll you'll figure out what to do okay so the last thing we want to do is we want to embed this on our websites all right so we're gonna come to the sharing tab I'm going to come down to live chat I'm going to hit enable live chat I'm going to just copy this script here and then come to my website all right I'm using webflow but you can do this on any different website builder you're using I'm just going to paste this script in right here I'm going to hit save changes I'm going to publish the website and then we should see our live custom trained chat bot on our website working for all of our visitors so I will launch my page and then as you can see boom right here we have our little chat bot that I can pull up I can ask it little questions here hey how should I manage my money there are several ways to manage your money effectively first consider saving money as a non-negotiable habit blah blah blah blah blah this thing's working perfectly so it's that easy to get a custom trained AI chat bot live on your website what did that take us five minutes that's it guys so if you guys like this video go down and smash that like button for me I'd really really appreciate it if you want to see more videos like this in the future consider subscribing if you have any questions get down in the comments and let me know I'll get back to you as soon as I can I hope you guys enjoyed this video and got a lot of value out of it and I'll be back with another valuable video next week thanks for being here peace

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8 Custom Chatbot Builders Powered by ChatGPT for Your Website


8 Custom Chatbot Builders Powered by ChatGPT for Your Website

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Chatbots are modern programs that can help a business take its customer experience to a new level. 

Chat support is a demanding choice among modern customers, and automation of customer support using AI has skyrocketed the ticketing system to a great extent. 

You might have at least once interacted with a chatbot, especially when talking to a customer agent through a chat system.

Many organizations, especially e-commerce platforms, are using Chatbots in their websites or applications to automate their customer support. 

When OpenAI introduced ChatGPT, it opened up the path for endless possibilities, including the ability to create chatbots powered by ChatGPT.

Businesses can use a custom chatbot with ChatGPT to train the models based on customer requirements and provide better service.

So, if you are thinking about implementing a chatbot in your application or site, read on.

In this article, I’ll talk about chatbots, how useful they are, and some of the best ChatGPT-powered custom chatbot builders to create useful chatbots. 

What Is a Chatbot?

Chatbot is basically a computer program that is built to simulate and process human conversation through text or voice interaction. The program leverages natural language processing (NLP) and artificial intelligence (AI) to understand customers’ queries and automate responses. 

Chatbots have been designed in such a way using algorithms and AI models that it interacts with customers like humans do. From messaging apps and websites to virtual assistance systems, Chatbots are being utilized in both business-to-consumer (B2C) and business-to-business (B2B) environments. 

The use of this program is increasing with time since it provides an efficient way for businesses to automate customer interaction in a friendly way. There are Chatbots that primarily respond in one line, and they usually provide answers to frequently asked questions, offering a simple customer interaction. 

AI-enabled Chatbots are trained with language intent, spot patterns, human behavior, and recorder interaction to provide the most appropriate response without involving humans. 

With instant access to consumer information, customer service function, sales, and marketing, chatbots are increasing their efficiency gradually.  

Chatbots vs. ChatGPT-Powered Chatbots

When you compare ChatGPT-powered chatbots with other chatbots, you are likely to find many noticeable differences while using them.

Although both are conversational AI systems, some aspects make them different from one another:

Response

ChatGPT-powered chatbots are sophisticated and trained to offer responses depending on the context and tone of your conversation. Unlike other chatbots, it is not limited to specific responses and provides answers to all your queries.

On the other hand, other chatbots are more purpose-oriented because they are pre-programmed with a particular set of responses. Therefore, they can only respond to specific questions related to the website or app where it is integrated. The response set is also quite limited but accurate when you ask the right question. 

Use Cases

ChatGPT is more suited for personalized applications, and you can use it to get answers to even personal queries. You just have to log in to your ChatGPT account and use it depending on your requirements.

In contrast, since chatbots are designed for specific responses, you can’t use them to obtain answers to personal queries. They can only be used for pre-defined queries. 

Implementation

ChatGPT is quite challenging to implement. If you aren’t well-versed in machine learning, you won’t be able to implement it. It also needs you to be proficient in advanced programming for its implementation. 

Implementing other chatbots in your website or e-commerce app is quicker and easier than ChatGPT-powered chatbots. These are based on simple rule-based decision trees and don’t require complex programming. 

How to Create a Custom Chatbot Without Using External Applications 

If you are new to creating a custom chatbot, it might seem like a daunting task. But if you follow the below-mentioned steps correctly, the process will get easier. 

Step-1: Figure Out the Purpose 

Your first task is to figure out the purpose of your chatbot so it can function accordingly. You must also define the features that your Chatbot will have before you proceed to the next step. 

Step-2: Where to Implement

After defining the purpose and features, you will need to decide where to implement your custom chatbot. If your customer interacts mainly on your site through a live chat widget, then you must implement it on the website. 

However, if most of the customer interaction happens in your app through Whatsapp, Instagram, Telegram, or another messaging platform, then you need to implement it there.

Step-3: Choose a Chatbot Provider 

Once you are aware of the type of chatbot you want, it is time to select the chatbot provider. Chatbot platforms serve as the easiest option to create a chatbot as they are fast and convenient. 

However, if you are good with coding, then you use a chatbot framework such as Google’s Dialogflow to create your own custom chatbot.

Step-4: Designing 

After selecting the provider, It is time for you to design the chatbot conversation in a chatbot editor. To start the process, log in to the chatbot builder first and then start designing the conversation. 

Some modern editors let you sequence the conversation flow through the simple dragging and dropping mechanism. You will need to be proficient in conversation design because it will determine your customer experience. For software developers, designing the conversation might be tedious, but with precision; you will be able to implement it quickly.

Step-5: Testing 

After the designing part is over, it is time to test your chatbot and find out whether it is working according to your requirement. Depending upon how you have created the chatbot, you can choose a test process.

Step-6: Training 

If you want your custom chatbot to offer a better response and customer experience, you must train it. You will need to utilize an NLP engine along with an NLP trigger to train the chatbot and let the systems find the most common issues and queries. 

However, if you want to keep the chatbot simple and allow it to work according to the pre-defined flow, then you can skip the training part.

Step-7: Feedback Collection 

After you have created the custom chatbot and integrated it into your website or chat platform, the last thing you can and must do is collect customer feedback. Your customers are the best people who can analyze the effectiveness of your chatbot. 

So, just ask your customers to provide their honest feedback based on their usage and experience. Once you gather the details, you can improve your chatbot to make it more useful for your customers.

You can even build custom chatbots powered by ChatGPT through various websites and platforms without any coding.

Here are some of the best platforms to create custom ChatGPT-powered chatbots on your own. 

Botsonic

Botsonic AI chat builder is a go-to choice for many business owners to create custom chatbots. The AI chat builder is straightforward to use, and it doesn’t require you to write any code or have deep technical skills. 

Thanks to its strong GPT-4 backing, Botsonic enables you to train the chatbot you create on your own data to enable an impressive customer experience. Moreover, the platform can analyze the chats to enhance customer support and increase engagement with them like a human. 

You can train your chatbot to collaborate with human-customer support whenever needed and also redirect the customer to specific products or services to enhance the experience. It is an award-winning chat builder that is trusted by top tech giants throughout the world.

Chatbase

Chatbase is a popular custom chatbot builder that harnesses the power of ChatGPT. It has garnered a lot of attention in recent times. The platform makes it a breezy task for you to build and integrate a chatbot on your site and train it on your business data. 

Building a custom chatbot using this AI chat builder is a no-brainer task; you just need to add a link to your website or upload all the required data files for scraping it. Importantly, you can easily make changes to your chatbot, like answering patterns and providing names and personality traits, to enable it to provide a personalized customer experience. 

The geolocation of your website won’t matter because Chatbase supports around 95 languages, so you can provide customer support in popular global languages. Chatbase is designed to cater to businesses of all sizes, and that is why they have come up with different pricing tiers, starting from $19/month. 

CustomGPT.ai

If you are planning to provide unbeatable customer service using a custom chatbot and quickly resolve customers’ issues, try CustomGPT.ai. It makes building a custom chatbot easier by uploading documents or integrating it on your website with CustomGPT.ai’s congregation.

Once your chatbot is ready, you can easily deploy it via the embedded widget or API. Since the chatbot you get is powered by ChatGPT, your bot will be armed with many modern AI capabilities to improve customer interaction to a great extent. 

They offer four pricing plans that you can choose based on your needs – Basic, Standard, Premium, and Enterprise – starting from  $49/month. 

ActiveChat

If you want to build a chatbot that can utilize your business knowledge base and provide unparalleled customer support and knowledge management, try ActiveChat. This AI chat builder harnesses the capabilities of ChatGPT to ensure that your chatbot provides accurate answers to all the queries of your customers. 

With this tool, you can introduce a natural language AI assistant to your website, which will automate most of the tasks and also simplifies many labor-intensive tasks. Unlike other bots that people train on generative models, this AI builder utilizes your data and provides high-quality text generation while reducing errors. 

Another interesting thing about ActiveChat is that you can fine-tune the Large Language Models (LLM) with just a single click, and the total process is entirely free. This AI builder is not free, and you will have to choose between Team, Company, and Enterprise plans. The basic plan starts from $149/month. 

AISTA

Use AISTA chat builder to scrape your business data and create a highly efficient chatbot backed by ChatGPT that will improve your customer interaction by 67% (as claimed by the company). 

With AISTA’s AI builder, you can effortlessly create a customized chatbot that integrates with your CMS and generates leads along with Q&A support.

The chatbots built using AISTA are efficient, with the capability to provide better, personalized interactions and reduce customer support costs by almost 30%. 

One huge benefit that you will experience is the complete control you will have over your chatbot, which ranges from managing training data and modifying configuration to caching requests. 

Since it is built on Magic Cloud, it is capable of analyzing all the questions that your chatbot receives and how to effectively answer them. It also provides replicated storage, security, and CDN. 

The brand understands that not every business has the same need, and this is why it offers three separate plans, which are Basic, Professional, and Enterprise.

Data Monsters

Do you want to automate the customer service on your website but can’t decide which chat builder to select for creating a custom chatbot? 

Data Monsters is a good option.  

This is a well-known brand that can help you customize and implement a ChatGPT-based Chatbot in your website or system. Data Monster uses its experience in the field of artificial intelligence and data analysis to design a chatbot that will help you provide a better customer experience. 

Besides helping you in creating a wonderful chatbot, Data Monsters can also help you integrate it with existing systems, optimizing cycles and ROI estimation. Top organizations like Nvidia, Siemens, Cisco, Nestle, and P&G have trusted this AI builder, so you can also lay your trust in it.

Nova

Nova is a revolutionary AI chatbot builder that can help you create a ChatGPT-powered chatbot to scale your customer service and enhance customer engagement. 

Since it harnesses the capabilities of ChatGPT and GTP 3.5, the chatbot you create using this chatbot builder can generate human-like responses to customer queries accurately while reducing human intervention. 

Your chatbot can easily be integrated with your systems so that it can use all the relevant data to create accurate responses during customer interaction. It is a highly customizable AI chatbot builder that you can use according to your unique requirements.

The chatbot you create with Nova can be integrated not only on websites but also into mobile applications and smartwatches.

PowerBrainAI

Try PowerBrainAI chatbot builder if you want to build an AI assistant for your application. Whether you want to create a custom chatbot for iOS or Android platform, this AI builder is compatible with both platforms. 

From automating repetitive tasks, solving customer issues, and suggesting products to order management and escalating requests, the AI chatbot you will create can help you with a lot of tasks. 

This AI chatbot based on ChatGPT will help you design your bot in such a way that it not only answers according to the customer’s intent but also provides accurate information. The app is entirely free to use, which is a huge boon, especially for small businesses that want to implement the power of AI in their ecosystem.

Conclusion

Creating a custom chatbot powered by ChatGPT for your website may seem like a daunting task, especially if you are unaware of coding and NLP. But don’t worry; modern AI chat builders have made developing ChatGPT-backed chatbots a child’s play. It will help you easily automate the chat service on your website with a few clicks. 

So, choose the best ChatGPT-powered custom chatbot builder based on your use case and budget. All of them utilize advanced technology and the power of data science to train chatbots on your business data and provide accurate, relevant responses like human agents. 

You may also explore the best chatbot development frameworks to build powerful bots.


https://geekflare.com/custom-chatbot-builders-powered-by-chatgpt/

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A Guide for AI-Enhancing YOUR Existing Business Application


A guide to improving your existing business application of artificial intelligence

מדריך לשיפור היישום העסקי הקיים שלך בינה מלאכותית

What is Artificial Intelligence and how does it work? What are the 3 types of AI?

What is Artificial Intelligence and how does it work? What are the 3 types of AI? The 3 types of AI are: General AI: AI that can perform all of the intellectual tasks a human can. Currently, no form of AI can think abstractly or develop creative ideas in the same ways as humans.  Narrow AI: Narrow AI commonly includes visual recognition and natural language processing (NLP) technologies. It is a powerful tool for completing routine jobs based on common knowledge, such as playing music on demand via a voice-enabled device.  Broad AI: Broad AI typically relies on exclusive data sets associated with the business in question. It is generally considered the most useful AI category for a business. Business leaders will integrate a broad AI solution with a specific business process where enterprise-specific knowledge is required.  How can artificial intelligence be used in business? AI is providing new ways for humans to engage with machines, transitioning personnel from pure digital experiences to human-like natural interactions. This is called cognitive engagement.  AI is augmenting and improving how humans absorb and process information, often in real-time. This is called cognitive insights and knowledge management. Beyond process automation, AI is facilitating knowledge-intensive business decisions, mimicking complex human intelligence. This is called cognitive automation.  What are the different artificial intelligence technologies in business? Machine learning, deep learning, robotics, computer vision, cognitive computing, artificial general intelligence, natural language processing, and knowledge reasoning are some of the most common business applications of AI.  What is the difference between artificial intelligence and machine learning and deep learning? Artificial intelligence (AI) applies advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take actions.  Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.  Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled.  What are the current and future capabilities of artificial intelligence? Current capabilities of AI include examples such as personal assistants (Siri, Alexa, Google Home), smart cars (Tesla), behavioral adaptation to improve the emotional intelligence of customer support representatives, using machine learning and predictive algorithms to improve the customer’s experience, transactional AI like that of Amazon, personalized content recommendations (Netflix), voice control, and learning thermostats.  Future capabilities of AI might probably include fully autonomous cars, precision farming, future air traffic controllers, future classrooms with ambient informatics, urban systems, smart cities and so on.  To know more about the scope of artificial intelligence in your business, please connect with our expert.

מהי בינה מלאכותית וכיצד היא פועלת? מהם 3 סוגי הבינה המלאכותית?

מהי בינה מלאכותית וכיצד היא פועלת? מהם 3 סוגי הבינה המלאכותית? שלושת סוגי הבינה המלאכותית הם: בינה מלאכותית כללית: בינה מלאכותית שיכולה לבצע את כל המשימות האינטלקטואליות שאדם יכול. נכון לעכשיו, שום צורה של AI לא יכולה לחשוב בצורה מופשטת או לפתח רעיונות יצירתיים באותן דרכים כמו בני אדם. בינה מלאכותית צרה: בינה מלאכותית צרה כוללת בדרך כלל טכנולוגיות זיהוי חזותי ועיבוד שפה טבעית (NLP). זהו כלי רב עוצמה להשלמת עבודות שגרתיות המבוססות על ידע נפוץ, כגון השמעת מוזיקה לפי דרישה באמצעות מכשיר התומך בקול. בינה מלאכותית רחבה: בינה מלאכותית רחבה מסתמכת בדרך כלל על מערכי נתונים בלעדיים הקשורים לעסק המדובר. זה נחשב בדרך כלל לקטגוריית הבינה המלאכותית השימושית ביותר עבור עסק. מנהיגים עסקיים ישלבו פתרון AI רחב עם תהליך עסקי ספציפי שבו נדרש ידע ספציפי לארגון. כיצד ניתן להשתמש בבינה מלאכותית בעסק? AI מספקת דרכים חדשות לבני אדם לעסוק במכונות, ומעבירה את הצוות מחוויות דיגיטליות טהורות לאינטראקציות טבעיות דמויות אדם. זה נקרא מעורבות קוגניטיבית. בינה מלאכותית מגדילה ומשפרת את האופן שבו בני אדם קולטים ומעבדים מידע, לעתים קרובות בזמן אמת. זה נקרא תובנות קוגניטיביות וניהול ידע. מעבר לאוטומציה של תהליכים, AI מאפשר החלטות עסקיות עתירות ידע, תוך חיקוי אינטליגנציה אנושית מורכבת. זה נקרא אוטומציה קוגניטיבית. מהן טכנולוגיות הבינה המלאכותית השונות בעסק? למידת מכונה, למידה עמוקה, רובוטיקה, ראייה ממוחשבת, מחשוב קוגניטיבי, בינה כללית מלאכותית, עיבוד שפה טבעית וחשיבת ידע הם חלק מהיישומים העסקיים הנפוצים ביותר של AI. מה ההבדל בין בינה מלאכותית ולמידת מכונה ולמידה עמוקה? בינה מלאכותית (AI) מיישמת ניתוח מתקדמות וטכניקות מבוססות לוגיקה, כולל למידת מכונה, כדי לפרש אירועים, לתמוך ולהפוך החלטות לאוטומטיות ולנקוט פעולות. למידת מכונה היא יישום של בינה מלאכותית (AI) המספק למערכות את היכולת ללמוד ולהשתפר מניסיון באופן אוטומטי מבלי להיות מתוכנתים במפורש. למידה עמוקה היא תת-קבוצה של למידת מכונה בבינה מלאכותית (AI) שיש לה רשתות המסוגלות ללמוד ללא פיקוח מנתונים שאינם מובנים או ללא תווית. מהן היכולות הנוכחיות והעתידיות של בינה מלאכותית? היכולות הנוכחיות של AI כוללות דוגמאות כמו עוזרים אישיים (Siri, Alexa, Google Home), מכוניות חכמות (Tesla), התאמה התנהגותית לשיפור האינטליגנציה הרגשית של נציגי תמיכת לקוחות, שימוש בלמידת מכונה ואלגוריתמים חזויים כדי לשפר את חווית הלקוח, עסקאות בינה מלאכותית כמו זו של אמזון, המלצות תוכן מותאמות אישית (Netflix), שליטה קולית ותרמוסטטים ללמידה. יכולות עתידיות של AI עשויות לכלול כנראה מכוניות אוטונומיות מלאות, חקלאות מדויקת, בקרי תעבורה אוויריים עתידיים, כיתות עתידיות עם אינפורמטיקה סביבתית, מערכות עירוניות, ערים חכמות וכן הלאה. כדי לדעת יותר על היקף הבינה המלאכותית בעסק שלך, אנא צור קשר עם המומחה שלנו.

Glossary of Terms


Application Programming Interface(API):

An API, or application programming interface, is a set of rules and protocols that allows different software programs to communicate and exchange information with each other. It acts as a kind of intermediary, enabling different programs to interact and work together, even if they are not built using the same programming languages or technologies. API's provide a way for different software programs to talk to each other and share data, helping to create a more interconnected and seamless user experience.

Artificial Intelligence(AI):

the intelligence displayed by machines in performing tasks that typically require human intelligence, such as learning, problem-solving, decision-making, and language understanding. AI is achieved by developing algorithms and systems that can process, analyze, and understand large amounts of data and make decisions based on that data.

Compute Unified Device Architecture(CUDA):

CUDA is a way that computers can work on really hard and big problems by breaking them down into smaller pieces and solving them all at the same time. It helps the computer work faster and better by using special parts inside it called GPUs. It's like when you have lots of friends help you do a puzzle - it goes much faster than if you try to do it all by yourself.

The term "CUDA" is a trademark of NVIDIA Corporation, which developed and popularized the technology.

Data Processing:

The process of preparing raw data for use in a machine learning model, including tasks such as cleaning, transforming, and normalizing the data.

Deep Learning(DL):

A subfield of machine learning that uses deep neural networks with many layers to learn complex patterns from data.

Feature Engineering:

The process of selecting and creating new features from the raw data that can be used to improve the performance of a machine learning model.

Freemium:

You might see the term "Freemium" used often on this site. It simply means that the specific tool that you're looking at has both free and paid options. Typically there is very minimal, but unlimited, usage of the tool at a free tier with more access and features introduced in paid tiers.

Generative Art:

Generative art is a form of art that is created using a computer program or algorithm to generate visual or audio output. It often involves the use of randomness or mathematical rules to create unique, unpredictable, and sometimes chaotic results.

Generative Pre-trained Transformer(GPT):

GPT stands for Generative Pretrained Transformer. It is a type of large language model developed by OpenAI.

GitHub:

GitHub is a platform for hosting and collaborating on software projects


Google Colab:

Google Colab is an online platform that allows users to share and run Python scripts in the cloud

Graphics Processing Unit(GPU):

A GPU, or graphics processing unit, is a special type of computer chip that is designed to handle the complex calculations needed to display images and video on a computer or other device. It's like the brain of your computer's graphics system, and it's really good at doing lots of math really fast. GPUs are used in many different types of devices, including computers, phones, and gaming consoles. They are especially useful for tasks that require a lot of processing power, like playing video games, rendering 3D graphics, or running machine learning algorithms.

Large Language Model(LLM):

A type of machine learning model that is trained on a very large amount of text data and is able to generate natural-sounding text.

Machine Learning(ML):

A method of teaching computers to learn from data, without being explicitly programmed.

Natural Language Processing(NLP):

A subfield of AI that focuses on teaching machines to understand, process, and generate human language

Neural Networks:

A type of machine learning algorithm modeled on the structure and function of the brain.

Neural Radiance Fields(NeRF):

Neural Radiance Fields are a type of deep learning model that can be used for a variety of tasks, including image generation, object detection, and segmentation. NeRFs are inspired by the idea of using a neural network to model the radiance of an image, which is a measure of the amount of light that is emitted or reflected by an object.

OpenAI:

OpenAI is a research institute focused on developing and promoting artificial intelligence technologies that are safe, transparent, and beneficial to society

Overfitting:

A common problem in machine learning, in which the model performs well on the training data but poorly on new, unseen data. It occurs when the model is too complex and has learned too many details from the training data, so it doesn't generalize well.

Prompt:

A prompt is a piece of text that is used to prime a large language model and guide its generation

Python:

Python is a popular, high-level programming language known for its simplicity, readability, and flexibility (many AI tools use it)

Reinforcement Learning:

A type of machine learning in which the model learns by trial and error, receiving rewards or punishments for its actions and adjusting its behavior accordingly.

Spatial Computing:

Spatial computing is the use of technology to add digital information and experiences to the physical world. This can include things like augmented reality, where digital information is added to what you see in the real world, or virtual reality, where you can fully immerse yourself in a digital environment. It has many different uses, such as in education, entertainment, and design, and can change how we interact with the world and with each other.

Stable Diffusion:

Stable Diffusion generates complex artistic images based on text prompts. It’s an open source image synthesis AI model available to everyone. Stable Diffusion can be installed locally using code found on GitHub or there are several online user interfaces that also leverage Stable Diffusion models.

Supervised Learning:

A type of machine learning in which the training data is labeled and the model is trained to make predictions based on the relationships between the input data and the corresponding labels.

Unsupervised Learning:

A type of machine learning in which the training data is not labeled, and the model is trained to find patterns and relationships in the data on its own.

Webhook:

A webhook is a way for one computer program to send a message or data to another program over the internet in real-time. It works by sending the message or data to a specific URL, which belongs to the other program. Webhooks are often used to automate processes and make it easier for different programs to communicate and work together. They are a useful tool for developers who want to build custom applications or create integrations between different software systems.


מילון מונחים


ממשק תכנות יישומים (API): API, או ממשק תכנות יישומים, הוא קבוצה של כללים ופרוטוקולים המאפשרים לתוכנות שונות לתקשר ולהחליף מידע ביניהן. הוא פועל כמעין מתווך, המאפשר לתוכניות שונות לקיים אינטראקציה ולעבוד יחד, גם אם הן אינן בנויות באמצעות אותן שפות תכנות או טכנולוגיות. ממשקי API מספקים דרך לתוכנות שונות לדבר ביניהן ולשתף נתונים, ועוזרות ליצור חווית משתמש מקושרת יותר וחלקה יותר. בינה מלאכותית (AI): האינטליגנציה שמוצגת על ידי מכונות בביצוע משימות הדורשות בדרך כלל אינטליגנציה אנושית, כגון למידה, פתרון בעיות, קבלת החלטות והבנת שפה. AI מושגת על ידי פיתוח אלגוריתמים ומערכות שיכולים לעבד, לנתח ולהבין כמויות גדולות של נתונים ולקבל החלטות על סמך הנתונים הללו. Compute Unified Device Architecture (CUDA): CUDA היא דרך שבה מחשבים יכולים לעבוד על בעיות קשות וגדולות באמת על ידי פירוקן לחתיכות קטנות יותר ופתרון כולן בו זמנית. זה עוזר למחשב לעבוד מהר יותר וטוב יותר על ידי שימוש בחלקים מיוחדים בתוכו הנקראים GPUs. זה כמו כשיש לך הרבה חברים שעוזרים לך לעשות פאזל - זה הולך הרבה יותר מהר מאשר אם אתה מנסה לעשות את זה לבד. המונח "CUDA" הוא סימן מסחרי של NVIDIA Corporation, אשר פיתחה והפכה את הטכנולוגיה לפופולרית. עיבוד נתונים: תהליך הכנת נתונים גולמיים לשימוש במודל למידת מכונה, כולל משימות כמו ניקוי, שינוי ונימול של הנתונים. למידה עמוקה (DL): תת-תחום של למידת מכונה המשתמש ברשתות עצביות עמוקות עם רבדים רבים כדי ללמוד דפוסים מורכבים מנתונים. הנדסת תכונות: תהליך הבחירה והיצירה של תכונות חדשות מהנתונים הגולמיים שניתן להשתמש בהם כדי לשפר את הביצועים של מודל למידת מכונה. Freemium: ייתכן שתראה את המונח "Freemium" בשימוש לעתים קרובות באתר זה. זה פשוט אומר שלכלי הספציפי שאתה מסתכל עליו יש אפשרויות חינמיות וגם בתשלום. בדרך כלל יש שימוש מינימלי מאוד, אך בלתי מוגבל, בכלי בשכבה חינמית עם יותר גישה ותכונות שהוצגו בשכבות בתשלום. אמנות גנרטיבית: אמנות גנרטיבית היא צורה של אמנות שנוצרת באמצעות תוכנת מחשב או אלגוריתם ליצירת פלט חזותי או אודיו. לרוב זה כרוך בשימוש באקראיות או בכללים מתמטיים כדי ליצור תוצאות ייחודיות, בלתי צפויות ולעיתים כאוטיות. Generative Pre-trained Transformer(GPT): GPT ראשי תיבות של Generative Pre-trained Transformer. זהו סוג של מודל שפה גדול שפותח על ידי OpenAI. GitHub: GitHub היא פלטפורמה לאירוח ושיתוף פעולה בפרויקטי תוכנה

Google Colab: Google Colab היא פלטפורמה מקוונת המאפשרת למשתמשים לשתף ולהריץ סקריפטים של Python בענן Graphics Processing Unit(GPU): GPU, או יחידת עיבוד גרפית, הוא סוג מיוחד של שבב מחשב שנועד להתמודד עם המורכבות חישובים הדרושים להצגת תמונות ווידאו במחשב או במכשיר אחר. זה כמו המוח של המערכת הגרפית של המחשב שלך, והוא ממש טוב לעשות הרבה מתמטיקה ממש מהר. GPUs משמשים סוגים רבים ושונים של מכשירים, כולל מחשבים, טלפונים וקונסולות משחקים. הם שימושיים במיוחד למשימות הדורשות כוח עיבוד רב, כמו משחקי וידאו, עיבוד גרפיקה תלת-ממדית או הפעלת אלגוריתמים של למידת מכונה. מודל שפה גדול (LLM): סוג של מודל למידת מכונה שאומן על כמות גדולה מאוד של נתוני טקסט ומסוגל ליצור טקסט בעל צליל טבעי. Machine Learning (ML): שיטה ללמד מחשבים ללמוד מנתונים, מבלי להיות מתוכנתים במפורש. עיבוד שפה טבעית (NLP): תת-תחום של AI המתמקד בהוראת מכונות להבין, לעבד וליצור שפה אנושית רשתות עצביות: סוג של אלגוריתם למידת מכונה המבוססת על המבנה והתפקוד של המוח. שדות קרינה עצביים (NeRF): שדות קרינה עצביים הם סוג של מודל למידה עמוקה שיכול לשמש למגוון משימות, כולל יצירת תמונה, זיהוי אובייקטים ופילוח. NeRFs שואבים השראה מהרעיון של שימוש ברשת עצבית למודל של זוהר תמונה, שהוא מדד לכמות האור שנפלט או מוחזר על ידי אובייקט. OpenAI: OpenAI הוא מכון מחקר המתמקד בפיתוח וקידום טכנולוגיות בינה מלאכותית שהן בטוחות, שקופות ומועילות לחברה. Overfitting: בעיה נפוצה בלמידת מכונה, שבה המודל מתפקד היטב בנתוני האימון אך גרועים בחדשים, בלתי נראים. נתונים. זה מתרחש כאשר המודל מורכב מדי ולמד יותר מדי פרטים מנתוני האימון, כך שהוא לא מכליל היטב. הנחיה: הנחיה היא פיסת טקסט המשמשת לתכנון מודל שפה גדול ולהנחות את הדור שלו Python: Python היא שפת תכנות פופולרית ברמה גבוהה הידועה בפשטות, בקריאות ובגמישות שלה (כלי AI רבים משתמשים בה) למידת חיזוק: סוג של למידת מכונה שבה המודל לומד על ידי ניסוי וטעייה, מקבל תגמולים או עונשים על מעשיו ומתאים את התנהגותו בהתאם. מחשוב מרחבי: מחשוב מרחבי הוא השימוש בטכנולוגיה כדי להוסיף מידע וחוויות דיגיטליות לעולם הפיזי. זה יכול לכלול דברים כמו מציאות רבודה, שבה מידע דיגיטלי מתווסף למה שאתה רואה בעולם האמיתי, או מציאות מדומה, שבה אתה יכול לשקוע במלואו בסביבה דיגיטלית. יש לו שימושים רבים ושונים, כמו בחינוך, בידור ועיצוב, והוא יכול לשנות את האופן שבו אנו מתקשרים עם העולם ואחד עם השני. דיפוזיה יציבה: דיפוזיה יציבה מייצרת תמונות אמנותיות מורכבות המבוססות על הנחיות טקסט. זהו מודל AI של סינתזת תמונות בקוד פתוח הזמין לכולם. ניתן להתקין את ה-Stable Diffusion באופן מקומי באמצעות קוד שנמצא ב-GitHub או שישנם מספר ממשקי משתמש מקוונים הממנפים גם מודלים של Stable Diffusion. למידה מפוקחת: סוג של למידת מכונה שבה נתוני האימון מסומנים והמודל מאומן לבצע תחזיות על סמך היחסים בין נתוני הקלט והתוויות המתאימות. למידה ללא פיקוח: סוג של למידת מכונה שבה נתוני האימון אינם מסומנים, והמודל מאומן למצוא דפוסים ויחסים בנתונים בעצמו. Webhook: Webhook הוא דרך של תוכנת מחשב אחת לשלוח הודעה או נתונים לתוכנית אחרת דרך האינטרנט בזמן אמת. זה עובד על ידי שליחת ההודעה או הנתונים לכתובת URL ספציפית, השייכת לתוכנית האחרת. Webhooks משמשים לעתים קרובות כדי להפוך תהליכים לאוטומטיים ולהקל על תוכניות שונות לתקשר ולעבוד יחד. הם כלי שימושי למפתחים שרוצים לבנות יישומים מותאמים אישית או ליצור אינטגרציות בין מערכות תוכנה שונות.

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