Upstox Originals
The interesting evolution of AI tools
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8 min read | Updated on May 29, 2025, 13:47 IST
SUMMARY
What if someone told you that ChatGPT was never trained or originally coded to understand and respond in Hindi? But it has now not only learnt Hindi, but is actually even fluent in it. Just like Hindi conversations, image generation was also impossible in ChatGPT until 2024. But things have changed in 2025. In this article, we delve into how AI tools have evolved and which tools are most suited for various tasks.
AI versions have made tremendous progress in very limited time
Ever wondered how we went from childish chatbots that barely understood your questions to AI companions that can write poems, debug code, and even explain quantum physics?
In this article, we’ll trace the entire evolution, breaking down how each version got smarter, faster, and more useful for businesses, creators, students, and everyday users alike. Before that, what is GPT?
GPT stands for Generative Pre-trained Transformer, which learns to understand and generate human-like text. It is trained on huge amounts of data from books, websites, conversations, and more, and then fine-tuned to answer your questions, write content, and solve problems. Think of GPT models as increasingly advanced versions of a virtual assistant that learns not just to talk, but to reason, write, and even code.
GPT-1 (2018): The first step
OpenAI launched GPT-1 with 117 million parameters (think of parameters as the AI’s memory neurons).
| Key features | Limitations |
|---|---|
| Understand basic sentence structure | Often went off track, not able to give meaningful answers to the questions. |
| Generate short and somewhat coherent replies. | Struggled with complex logic or long conversations |
| Be fine-tuned for specific tasks like translation summarisation. |
GPT-2 (2019): The big leap
With 1.5 billion parameters, GPT-2 was 10x larger than GPT-1, and it showed.
| Key features | Limitations |
|---|---|
| Generated much more natural and coherent text | Concerns about abusive language, biased opinions persist. |
| Capable of writing news articles, poems, or summaries | A limited number of queries could be asked per user per day. |
| Could handle incomplete prompts better |
GPT-3 (2020): The game changer
With a jaw-dropping 175 billion parameters, GPT-3 was the model that took AI mainstream.
| Key features | Limitations |
|---|---|
| Could complete essays, write emails, code simple programs, and much more | Gave wrong but confident-sounding answers |
| Accessible via API, allowing developers to build apps around it | Lacked memory of previous chats (context was limited to the same session) |
| No real-time knowledge of current events |
GPT-4 (2023): Smarter, safer, and more accurate
GPT-4 focused less on getting bigger and more on getting better. While OpenAI hasn’t revealed its exact size, it introduced key improvements:
| Key features | Limitations |
|---|---|
| Fewer errors | No access to live data or current events |
| Better at understanding nuance, tone, and complex instructions | Sometimes verbose or overly cautious |
| More adaptable to industries—law, medicine, education, etc. | Gets slower when asked complex queries |
| Could understand image prompts |
GPT-4o (2024): Omnimodal, optimised,
The “o” in GPT-4o stands for omnimodal, meaning it can handle not just text, but voice, vision, and more in real-time.
| Key features | Limitations |
|---|---|
| Handled text, audio, and images as inputs in a single session only (Earlier, each kind of input required different versions to be used) | Even though it doesn’t have live internet access, its training data includes information up to October 2023. |
| Much faster (as fast as human responses) and cheaper to use than GPT-4 | Does not support video as input. |
| More concise, logical, and structured responses. Better at step-by-step reasoning | Lacks accuracy in document compilation and analysing larger documents. |
| APIs are 50% cheaper than the previous version | Responses include irrelevant information taken from previous conversations. |
| Ideal for coding, professional writing, and customer support |
o3 Mini, o4 Mini, o4 Mini-high, GPT 4.5 (2025): The most advanced versions
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If you simply ask what has changed:
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Allows real-time web search of information across the Internet
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Supports a wide range of tools within ChatGPT, including Python coding
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Emotional intelligence and improved understanding of user intent.
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Enhanced image analysis, file interpretation, and image generation.
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Makes 20% fewer major errors than OpenAI or on difficult, real-world tasks
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ChatGPT has now released a specialised version for each kind of task. This has increased the factual accuracy of various complex tasks.
Here is more about the existing versions of ChatGPT
| Model | Suitability |
|---|---|
| o3 | Ideal for complex, multi-faceted queries requiring advanced reasoning, especially in coding, math, science, and visual tasks. |
| o4-mini | Best for cost-efficient, high-throughput reasoning tasks, excelling in coding, math, and data science, with a focus on speed and volume. |
| GPT-4.5 | Perfect for tasks requiring deep understanding and creativity, including writing, programming, and problem-solving, with improved natural interaction and reduced hallucination. |
| o4-mini-high | Optimised for real-time, high-quality reasoning tasks with a balance of efficiency and performance, suitable for both general queries and technical tasks. |
| o1 and o1-mini | Focused on solving hard problems, ideal for research, strategy, and complex math or science tasks where problem-solving rigour is key. |
| GPT-4 | Best for general, sophisticated tasks that require advanced conversational capabilities, ideal for content creation, creative writing, and advanced technical problem-solving. |
Here is a quick summary of all the major AI tools
| AI tool | Best suited for | Unique features | Limitations |
|---|---|---|---|
| Google Gemini | -Content understanding & summarising videos, images, and audio. | - Seamless integration with Google Workspace tools (Gmail, Docs, Sheets) | - Lack of visual understanding - Cant upload files for processing |
| ChatGPT | - Task Management - Creative Writing - Coding Assistance | - Versatile content generation (emails, blog, and creative writing). | - May require explicit instructions for complex tasks. |
| Perplexity AI | - Real-Time Information Retrieval: For up-to-date information from various sources. | - A search-focused AI for sourcing and cross-checking information. | - May not provide deep analysis; surface-level insights. |
| Grok AI | - For coding problems and detailed explanations. - Assists in generating high-quality creative content. | - Known for humour and engaging conversational abilities. | - Potential issues with moderation and biases. |
| Llama AI (Meta) | -Textual processing and natural language understanding | - Understands natural language better, including an understanding of regional language - Leverages data from Meta’s ecosystem, especially social media, to give output. | -Lack of emotional Intelligence -Lacks factual accuracy of complex queries - Lacks web search to a wider internet |
Which tool is the best?
While each tool has unique capabilities as mentioned above, it is necessary to examine them on a uniform basis. We checked the probability of factual accuracy.
| Model | Factual Consistency Rate |
|---|---|
| Google Gemini-2.0-Flash-001 | 99.3% |
| OpenAI o3-mini-high | 99.2% |
| OpenAI GPT-4.5-Preview | 98.8% |
| OpenAI-o1-mini | 98.6% |
| OpenAI GPT-4o | 98.5% |
| Amazon Nova-Micro-V1 | 98.4% |
| OpenAI GPT-4o-mini | 98.3% |
| OpenAI GPT-4-Turbo | 98.3% |
| XAI Grok-2 | 98.1% |
| AI21 Jamba-1.6-Large | 97.7% |
| DeepSeek-V2.5 | 97.6% |
| Microsoft Orca-2-13b | 97.5% |
| Intel Neural-Chat-7B-v3-3 | 97.4% |
Source: GitHub
What’s coming bext?
OpenAI and other AI labs are already working on the next-gen models, and here’s what the future may hold:
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Personalised AI assistants - Models that learn your tone, style, and preferences like a tailored AI sidekick.
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Specialised GPT: We might see GPT for doctors, lawyers, marketers, and coders, each fine-tuned for niche use cases.
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Operator agent: Introduced as a research preview, the Operator agent allows ChatGPT to navigate websites, fill out forms, and complete transactions on behalf of users. This agent utilises a virtual browser to interact with web pages, mimicking human actions such as clicking and scrolling.
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Deep research agent: Designed for in-depth research tasks, this agent can analyse and synthesise information from multiple online sources to generate comprehensive reports. It's particularly useful for users requiring detailed insights on complex topics.
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Advanced voice mode: Enhancements in voice interaction capabilities aim to make conversations with ChatGPT more natural and fluid. The advanced voice mode reduces interruptions and improves real-time conversational flow, making interactions more human-like.
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Multimodal capabilities: Future versions are expected to support a broader range of inputs and outputs, including videos, text, images, and audio, facilitating more versatile interactions and applications
Final thoughts
The journey from GPT-1 to GPT-4 is like going from a typewriter to a personal assistant that can write, teach, code, and chat. Each version reflects how far AI has come—and how much more it can do.
As we move forward, expect AI to become more helpful, more personal, and more integrated into our daily lives. Whether you're a student, a CEO, a teacher, or just curious, understanding GPT means understanding the future of how we communicate and create.
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