The Evolution of ChatGPT: From GPT-3.5 to GPT-4 and Beyond

Introduction

ChatGPT 4 shows us what AI can do, scoring in the 90th percentile on the BAR exam. This is a big deal as it means that GPT-3.5’s performance pales in comparison. The latest language model, with training costs north of $100 million, proves how fast AI technology keeps evolving.

Looking at both versions reveals some eye-opening differences. ChatGPT comes from a GPT-3.5 model that completed training at the start of 2022. GPT-4, however, takes things to another level – it’s 10 times more advanced. The new version processes up to 25,000 words in one prompt, which makes it excellent at handling lengthy content. Test scores tell an impressive story too – GPT-4 grabbed 1410 on the SAT (94th percentile), reached 163 on the LSAT (88th percentile), and beat the USMLE passing score by more than 20 points.

These models face some common challenges. ChatGPT’s answers might sound right, but they can be wrong sometimes. This happens because finding absolute truth sources during training isn’t easy. OpenAI’s steadfast dedication to building better and safer AI systems shines through in the jump from GPT-3.5 to GPT-4. Users should consider ChatGPT 4’s cost when picking the right version for their needs.

From GPT-3.5 to GPT-4: Key Differences in Architecture and Performance

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The jump from GPT-3.5 to GPT-4 shows how far AI language models have come. GPT-4 packs nearly 1 trillion parameters, dwarfing its predecessor’s 175 billion. This huge upgrade lets it reason better and understand complex inputs with more depth.

Token Limit Expansion: 4K vs 32K Context Windows

GPT-4 brings major improvements in how much text it can process at once. GPT-3.5 could only handle 4,096 tokens (about 3,000 words). GPT-4 takes this up to 32,000 tokens—roughly 25,000 words. Users now have eight times more processing power.

OpenAI pushed the boundaries even further with GPT-4 Turbo, which handles 128,000 tokens. This bigger capacity means you can:

• Process entire books or long documents in one go
• Keep conversations flowing naturally
• Look through the complex code
• Create a detailed analysis of big datasets

ChatGPT Plus users started with 8,192 tokens in the standard GPT-4 interface. Later, they got access to the same token limit as API users. This boost helps the model remember more during long chats.

GPT-3.5 vs GPT-4 on Standardized Tests (SAT, LSAT, BAR)

Test scores show what GPT-4 can do. The numbers speak for themselves:

GPT-4 scored 298 out of 400 on the Bar exam, landing in the 90th percentile. GPT-3.5 only reached the 10th percentile. New York’s passing score is 266, right around the 50th percentile.

On the SAT, GPT-4 hit 1410 out of 1600. It scored 710 in Reading & Writing (93rd percentile) and 700 in Math (89th percentile). GPT-3.5 lagged with 1260 overall and struggled with math.

GPT-4 aced nine AP exams with perfect scores of 5, including Biology, Statistics, and US History. GPT-3.5 only managed this in two subjects—Art History and Psychology.

Multilingual Support in GPT-4: 26+ Languages

GPT-4 speaks 26+ languages right out of the gate. This makes AI help available to billions more people worldwide.

The model handles different languages more efficiently, too. GPT-4o, the optimized version, needs fewer tokens:

• Gujarati needs 4.4x fewer tokens
• Telugu uses 3.5x fewer
• Tamil requires 3.3x fewer
• Hindi takes 2.9x fewer
• Arabic needs 2.0x fewer

European languages also got better, though not as much (1.1-1.2x more efficient). Users can now work with longer content in these languages without hitting token limits.

The leap from GPT-3.5 to GPT-4 isn’t just an upgrade—it’s a breakthrough in AI. It thinks deeper, remembers longer, and helps people worldwide.

Multimodal Capabilities and System Message Control in GPT-4

GPT-4 brought more than just better architecture. Its state-of-the-art multimodal capabilities changed how people interact with AI. The expansion beyond text-only processing is a vital step to make AI systems more versatile and available.

Image Input and Visual Reasoning in GPT-4V

GPT-4V (Vision) stands out as OpenAI’s first multimodal model that reasons about images and text together. The model processes visual inputs from users and responds based on what it “sees.”

GPT-4V shows impressive visual reasoning skills, including:

• Analysis of documents with text, photographs, diagrams, and screenshots
• Visual question answering about image content
• Understanding of complex visual relationships and spatial reasoning
• Description and interpretation of visual content

But this technology has its limits. OpenAI admits that GPT-4V sometimes makes simple errors with “misleading matter-of-fact confidence”. Tests with organizations like Be My Eyes, which helps visually impaired users, have helped reduce these hallucinations and errors.

The rise continues with models like GPT-4o (“o” for “omni”), which takes visual reasoning further. It can “think with images” during its reasoning process. The model zooms, crops, flips, or enhances images to extract meaning from imperfect photos. It processes visual information much like humans do—it focuses on important details instead of analyzing every pixel equally.

System Message Prompting for Role and Format Control

GPT-4’s system message feature gives users unprecedented control over model behavior. These messages act as special instructions at the start of conversations.

System messages let users:

• Shape the model’s personality and tone
• Choose what topics to address or avoid
• Set response formatting rules
• Put responsible AI safeguards in place

Microsoft’s documentation explains that system messages “are handled specially by the model, and intended to have more influence on the model’s responses than User Message text”. These messages range from one-line instructions to detailed guidelines with rules and context.

This feature helps developers and organizations customize user experiences within safe boundaries. System messages work well but aren’t perfect guardrails—OpenAI notes they can be “the easiest way to ‘jailbreak’ the current model”.

Voice Interaction via Whisper Integration

GPT-4 rounds out its multimodal capabilities by adding audio through OpenAI’s Whisper speech recognition technology. Users can now interact through voice-to-text functionality.

The mobile app showcased this feature first, but web users have asked for it too. Voice recognition makes interaction more natural by letting people speak instead of type.

GPT-4o takes audio capabilities to new heights. It performs better than OpenAI’s dedicated Whisper-v3 model in both speech recognition and translation. Users now have a true multimodal experience. They can communicate through text, images, or voice—whatever feels most natural.

These multimodal capabilities mark a radical alteration in human-AI interaction. The accessible interface meets various communication priorities and needs.

Real-World Applications and Integrations of GPT-4

Companies of all sizes now utilize GPT-4’s technical capabilities through strategic collaborations that prove its practical value. These ground applications show how advanced AI models add value beyond standard measurements.

Duolingo Max: Language Learning with GPT-4

Duolingo introduced Max, a premium subscription that uses GPT-4 technology to improve language learning. The service comes with two new features: “Explain My Answer” gives tailored feedback on user responses, while “Roleplay” lets learners practice conversations with AI characters in realistic settings. Max costs $30 monthly or $168 annually, and users can access it in 188 countries on iOS and Android devices. The service supports English speakers who want to learn Spanish, French, German, Italian, and Portuguese. This shows how GPT-4 solves educational challenges by scaling human-like tutoring.

Khanmigo by Khan Academy: AI Tutoring

Khan Academy’s Khanmigo shows GPT-4’s potential in education through Socratic tutoring. The AI tutor asks thought-provoking questions to promote deeper understanding instead of giving direct answers. Students can get help with math, writing, AP exam prep, and programming. Personal subscriptions cost $4 monthly or $44 annually, and schools can buy district-wide plans. Teachers save time because the platform handles tasks like lesson planning and exit tickets, which lets them spend more time with students.

Microsoft Copilot and GitHub Copilot X

GitHub Copilot changes how developers work by offering AI-powered coding help. Developers report 75% higher job satisfaction and 55% better productivity with this tool. Users can access the service in Visual Studio Code, Visual Studio, and JetBrains IDEs. GitHub Copilot X adds more features like chat and voice interfaces, plus GPT-4-powered pull request support. This progress shows how GPT-4 improves professional technical workflows.

Be My Eyes: Visual Assistance for the Visually Impaired

Be My Eyes makes use of GPT-4’s visual capabilities to help about 253 million people worldwide who are blind or have low vision. The app’s Virtual Volunteer analyzes images and describes surroundings in detail. A user can take a photo of their refrigerator’s contents, and the AI identifies items and suggests recipes. This application shows how GPT-4’s multimodal features solve accessibility challenges by providing immediate help without human volunteers.

The Leap to GPT-4 Turbo and GPT-4o: Speed, Cost, and Real-Time AI

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OpenAI’s drive to optimize performance has led to big improvements with GPT-4 Turbo and GPT-4o. These updates bring faster responses, bigger context windows, and better pricing options.

GPT-4 Turbo: 128K Context Window and Lower Cost

GPT-4 Turbo arrived in late 2023 with major improvements. The model can now process over 300 pages of text in one prompt thanks to its 128K token context window. Developers can now handle complete codebases, long documents, and extended conversations without losing context. The price dropped by a lot, too – GPT-4 Turbo costs 3x less for input tokens at $0.01 per 1,000 tokens and 2x less for output tokens at $0.03 per 1,000 tokens. These changes made advanced AI available to many developers and applications. The Chat Completions API now supports image inputs, and processing a 1080×1080 pixel image costs about $0.01.

GPT-4o: Unified Model for Text, Image, and Audio

OpenAI revealed GPT-4o (“o” for omni) in May 2024. This first truly unified multimodal model can process text, audio, image, and video inputs together and generate text, audio, and image outputs. The model responds to audio inputs quickly, as fast as 232 milliseconds, with an average of 320 milliseconds, matching human conversation speed. GPT-4o performs as well as GPT-4 Turbo on English text and code, but does better with non-English languages. The new model runs 2x faster, costs half as much, and handles 5x more requests than GPT-4 Turbo.

ChatGPT 4 Price vs ChatGPT 4 Cost in API and Plans

Users can choose from several pricing options across subscription tiers and API access. ChatGPT Plus subscribers pay $20 monthly and get expanded GPT-4o access with 5x higher message limits than free users. API users pay $5 per million input tokens and $20 per million output tokens for GPT-4o. Free users now have some access to GPT-4o features that were once limited to paying customers. Each subscription tier has different context window sizes: Free (8K), Plus (32K), Pro (128K), Team (32K), and Enterprise (128K). Team subscriptions cost $25-30 per user monthly, while Pro users pay $200 monthly for unlimited access to all reasoning models and GPT-4o.

Looking Ahead: What to Expect from ChatGPT 5 and Beyond

“The development of full artificial intelligence could spell the end of the human race.” — Stephen Hawking, Theoretical Physicist, former Director of Research at the Center for Theoretical Cosmology, University of CambridgeOpenAI’s development path suggests GPT-5 will emerge as a unified intelligence system that goes well beyond GPT-4’s capabilities. Sam Altman has revealed that this next version will use their “o3” reasoning engine to boost contextual memory and logical processing.

Speculated Features of ChatGPT 5

OpenAI plans to transform its approach with GPT-5 by combining its separate GPT and o-series models into a single unified system. The system will direct tasks to appropriate underlying models based on complexity. It will use chain-of-thought reasoning and take time to process complex problems when needed. Standard intelligence settings will be available to free users without limits. Plus and Pro subscribers will get access to higher intelligence tiers with more computational power.

Key predicted capabilities include:

• Better processing of text, images, audio, and potentially video
• Built-in search and deep research functions
• Larger context windows for better memory retention
• Advanced reasoning for complex problem-solving

Safety and Alignment Challenges in Future Models

AI systems’ growing power makes alignment with human values crucial. OpenAI evaluates current risks and predicts future challenges. Their Preparedness Framework helps balance capability development with risk management.

The core alignment challenge lies in making AI systems beneficial as they become more advanced. This includes coding human values into AI systems—values that often change with context and culture.

OpenAI’s Roadmap for Multimodal AI

OpenAI aims to create simple user experiences through unified intelligence. They will release GPT-4.5 (codenamed “Orion”) as their final non-chain-of-thought model before GPT-5. Their ultimate goal focuses on creating systems that combine all tools and capabilities naturally.

The company believes developing artificial general intelligence requires shared efforts from industry, academia, government, and the public. OpenAI continues to develop its framework to handle increasing risks as AI capabilities advance toward and beyond human-level intelligence.

Conclusion

The rise from GPT-3.5 to GPT-4 and its later versions marks a fundamental change in AI capabilities. We have seen more than just small improvements – AI systems now process information and interact with humans in completely new ways. ChatGPT started with basic text-only interactions and modest test scores. Now it has grown into a sophisticated multimodal intelligence system that understands images, processes audio, and keeps track of conversations spanning thousands of words.

GPT-4’s expanded context window stands out as a game-changing feature. The jump from 4K tokens to 128K tokens in GPT-4 Turbo has boosted its practical use in all disciplines. Visual and audio capabilities make these systems available to users of all backgrounds, including those with disabilities. Real examples like Duolingo’s language learning and GitHub Copilot’s coding assistance show how these advances help millions of users worldwide.

OpenAI keeps developing more powerful models like the predicted GPT-5, but challenges persist. Questions about safety, arrangement, and ethical use grow more crucial. The next chapter in AI development will likely focus on balancing advanced capabilities with responsible implementation.

The future points to unified intelligence systems that combine reasoning engines with multimodal capabilities. These systems will think deeper, remember better, and interact more naturally with users. While we can’t predict their exact path, innovation continues at full speed. The experience from GPT-3.5 to GPT-4 and beyond shows not just technical progress but also how AI becomes part of our everyday lives.

FAQs

Q1. What are the key differences between ChatGPT 3.5 and ChatGPT 4? ChatGPT 4 represents a significant leap in capabilities. It has a much larger context window (up to 32,000 tokens compared to 4,096 in 3.5), improved accuracy and reduced hallucinations, and superior performance on standardized tests. ChatGPT 4 also introduces multimodal capabilities, allowing it to process both text and images.

Q2. How has the context window expanded in GPT-4 iterations? The context window has dramatically increased from 4,096 tokens in GPT-3.5 to 32,000 tokens in standard GPT-4. This was further expanded to 128,000 tokens in GPT-4 Turbo, allowing it to process the equivalent of over 300 pages of text in a single prompt.

Q3. What new multimodal capabilities does GPT-4 offer? GPT-4 introduced visual processing capabilities with GPT-4V, allowing it to analyze and reason about images alongside text. The latest iteration, GPT-4o, can process and generate content across text, audio, image, and even video modalities, creating a truly unified multimodal AI system.

Q4. How has GPT-4 been integrated into real-world applications? GPT-4 has been integrated into various applications across different sectors. Examples include Duolingo Max for enhanced language learning, Khanmigo by Khan Academy for AI tutoring, GitHub Copilot X for coding assistance, and Be My Eyes for visual assistance to visually impaired individuals.

Q5. What improvements can we expect in future iterations like GPT-5? Future iterations are expected to feature enhanced multimodal processing, built-in search and deep research functionalities, expanded context windows, and more sophisticated reasoning for complex problem-solving. There’s also a focus on unifying different AI capabilities into a single system, potentially allowing for automatic task routing based on complexity.