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8 Killing Features of GPT models in Web Applications

4 min read

Summary

The Generative Pre-trained Transformers (GPT) rocked the world of human-like text writing, turning neural networks into a vivid creative power. This article analyzes how GPT models in web applications enhanced their functionality and how they will develop in the future.

Goals of using ChatGPT models in web applications:

GPT is essentially a language model built on a transformer architecture. A GTP model was designed to help us generate human-like text and better understand language patterns, semantics, and grammar. 

Now, applications increasingly employ the opportunities provided by GPT models. And there is a simple explanation for this fact. Obtaining reliable information directly from the LLM based on identifiable sources is challenging. The information the user receives requires careful verification and control. The distortions of ChatGPT make developers seek a solution in processing information from specific sources or a group of sources instead of using the capabilities of ChatGPT in general. 

Integrating Large Language Models (LLM), such as ChatGPT, is advantageous for app owners for many reasons: 

  • Obtaining the most valuable information for the consumer, including texts in foreign languages. Think of ChatGPT as an alternative to search engines. 
  • Comparison of data from different sources.
  • For further analysis, retrieve data in the text and other forms (contracts, protocols, etc.).
  • Transformations of texts, including 1) abstracting and summarizing, 2) modifying data in formal documents, 3) creating educational materials, etc.
  • Meta-analysis of sources.
  • Use in other tasks related to working with the knowledge base 
  • Roleplay. The chat works on potential questions and hypothetical scenarios for designated groups of users.  
  • New capabilities of GPT-4: Better memory capacity (being able to process up to 25,000 words of text), image processing, larger context

GPT models in web applications

The integration of GPT models into web services has natural limitations.

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 GPT models in web applications offer limited capacities for processing input text. A ChatGPT prompt is limited to 4097 tokens covering both query and response. On average, it includes about 3000 words in English and can be even smaller in other languages. According to the ChatGPT, the GPT-4 version can work with 32,000 data tokens, but this is not a solution. 

Many online services claim to be GPT-4 based or provide you with access to GPT-4. However, integrating the ChatGTP service is meticulous work; most such services will be false. GPT-4 API access is limited, while development costs are relatively high. So, at the moment, only well-established apps can afford to develop valuable services based on the capabilities of ChatGPT models in web applications. We suggest you bear this fact in mind when you’re doing your search for ChatGPT resources. 

 

Best ChatGPT-powered applications

The use of GPT models in web applications:

Duolingo 

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A renowned EdTech learning platform offers courses in more than 40 languages. Early in 2023, Duolingo released a new tier subscription enhanced by ChatGPT and an AI tutor. A paid subscription program became available the same day the GPT-4 version was launched. The company says the “Explain My Answer” and “Roleplay” features were developed closely with OpenAI and took months of testing. 

“Explain My Answer” verifies if the answer given by the user at the lesson was correct. The app “explains” why their answer was right or wrong, enhancing this reply with examples. This feature helps language learners avoid making repetitive mistakes in the future. 

With the “Roleplay” feature, users talk to characters in the app and improve their conversational skills using different scenarios — from ordering coffee in a cafe to discussing vacations. The capabilities of GPT-4 ensure the conversation is responsive and interactive simultaneously. The text prompts consider the user’s language skill level.

So far, these features are limited to particular languages, and the company plans to expand the range of languages supported by the in-app AI tutor. Duolingo experts improve the AI knowledge base and enhance generative explanations’ relatability, ensuring all answers are provided in the same tone and factually correct. 

Khan Academy

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Khan Academy, a non-profit educational center, launched the Khanmigo AI tool in March 2023. A self-learning tool, Khanmigo supports students and teachers by generating relevant prompts and providing real-time feedback. Testing a new version of OpenAI’s language model began in 2022.

An AI tutor offers personalized learning experiences, highlighting students’ errors, engaging them in exercises, and asking them questions. Students need to elaborate on their thought processes, as prompted by the AI tutor. The educational flow is close to the human approach, guiding a student with the help of hints instead of referring them to ready solutions. The reasoning and thought process become accents of such an approach. 

ChatGPT Plus

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A paid subscription plan from the AI company provides users with guaranteed (without the popup message  “ChatGPT at Capacity”) and stable access to the service even at peak times for $20 a month. It means priority access to the latest features, for example, GTP-4, the ability to read (but not produce) images, and a faster response time. The paid subscription model is expected to gradually bring new services and release some features to paid users before including them in the free plan.  

Bing Chat

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A fresh iteration of Bing released by Microsoft features an AI chatbot as its distinct innovation. This chatbot is fueled by the same technology that powers ChatGPT models in web applications. As Microsoft states, the upgraded Bing incorporated a conversational function driven by an advanced iteration of OpenAI’s extensive language model, surpassing the capabilities of ChatGPT.

Subsequently, it appeared that Bing’s AI chat functionality was based on OpenAI’s GPT-4, the pinnacle of OpenAI’s advancements. With this enhanced Bing version, users can engage the AI chatbot to seek answers and receive comprehensive responses akin to human-like interactions, complete with footnotes and citations that connect to primary sources and current data.

Beyond assisting with inquiries, the chatbot also caters to creative needs, such as composing poems, essays, or songs. Moreover, it utilizes Bing’s Image Creator tool to generate visuals based on textual input, all within the same integrated platform.


Be My Eyes

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Since 2012, the “Be My Eyes” app has been assisting the expansive community of over 250 million individuals who are visually impaired or blind. This Danish app is the point of connection between volunteers and people with visual challenges, navigating product identification and orientation in airports.

Harnessing the cutting-edge capabilities of GPT-4 through its research preview phase, Be My Eyes has embarked on creating a GPT-4 powered Virtual Volunteer™ integrated within their app. This innovative feature can emulate a human volunteer’s contextual understanding and empathy.

In early 2023,  the company initiated a beta-testing of this GPT-supported assistant. The outcomes have been remarkably positive, leading to the imminent availability of this feature for users within a matter of weeks.

Unlike other machine learning models, GPT-4  has outstanding conversational prowess and heightened analytical capabilities. It is a transformative technological advancement and a significant advantage of using GPT models in web applications.

Stripe

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Earlier this year, Stripe embarked on an unconventional initiative, engaging its employees in a unique endeavor: temporarily setting aside their regular tasks to think about the platform’s new features, using OpenAI’s latest language learning model, GPT-4. The team identified the areas where artificial intelligence, particularly GPT-4, could be utilized to comprehend unstructured text and images, generate human-like responses, and enhance existing features and workflows.

Stripe provides small and large businesses with payment tools across the digital landscape. With developers being the primary users of Stripe’s software, strengthening their development proficiency is the focus. Previously employing GPT-3 to augment their team’s effectiveness in tasks like serving issue tickets and handling user inquiries, Stripe has now advanced to the GPT-4 phase.

The Stripe team implemented 15 GPT-4 prototype models to enhance personalized support, improve responses to support-related queries, and fortify fraud detection measures.

Morgan Stanley

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A financial service corporation of global standing has a vast database of knowledge and market research analysis. Morgan Stanley’s employees must dig into numerous internal sites to sift through extensive content and develop a solution. 

Morgan Stanley has turned to OpenAI’s GPT-4 capabilities to address this challenge. This journey started when the GPT-3 model was in place, and the approach has now evolved to incorporate the capabilities of GPT-4.

The focal point of this endeavor is the development of an internal chatbot powered by GPT-4. This advanced chatbot performs comprehensive searches across the knowledge base, allowing employees to resolve their requests most efficiently.

Morgan Stanley is currently considering employing AI capabilities to streamline client communication.

 

Conclusion

 

We hope that our review of the GPT-4 resources in top applications could shed some light on the opportunities of this language model. Please enter your email address in the headline above and subscribe to our blog to learn about the latest IT developments!

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