Stay informed on the latest AI advancements and their impact across industries with our structured updates.
On this page, we cover specific industries and recent developments in a timeline format.
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⏰ AI Timeline
- ChatGPT was released to general public on November 30, 2022 as a prototype (may not be available in all countries).
- December 2020: OpenAI released GPT-3 fine-tuned version named GPT-3 in other languages.
- October 2020: OpenAI released GPT-3 fine-tuned version named DALL·E, which can generate images from text descriptions.
- June 2020: OpenAI released GPT-3 (Generative Pre-training Transformer 3), which has 175 billion parameters, making it the largest language model to date.
- October 2019: OpenAI released GPT-2 fine-tuned version named DialoGPT (Dialog Pre-training Transformer), which was fine-tuned for the task of conversational understanding.
- December 2018: OpenAI released GPT-2 (Generative Pre-training Transformer 2), an upgraded version of GPT-1 with more parameters and better performance.
- June 2018: OpenAI released GPT-1 (Generative Pre-training Transformer 1), a language model that uses deep learning to generate human-like text.
- Emergence of third-party products:
- 2021: Jasper, a conversational AI platform that uses GPT-3 for language understanding, was released.
- 2020: multiple other third-party products such as Hugging Face's transformers library, that allows developers to fine-tune GPT-3 for various NLP tasks, Copy.ai, Replika.ai, OpenAI's own GPT-3 Playground, GPT-3 based website builders like Landbot.io, GPT-3 based chatbot platforms like octane.ai, and more emerged to use GPT-3 in their products
⌨️ AI Content
💥 Ongoing Effects
- Widespread use of AI content → The use of AI-generated content has become a common sight on the Internet. More and more individuals, businesses and organizations are turning to AI to create and optimize their online content, from writing articles, blog posts, to generating product descriptions, chatbot responses, and more. The ease of access to powerful AI models like GPT-3, and the increasing availability of third-party tools and platforms, have made it easier for content creators to generate high-quality, unique, and engaging content at scale.
- New content delivery formats and decline of conventional search engines → Chat GPT and other AI applications taking away users from conventional content mediums. GPT-3 has made it easier for developers to create advanced conversational AI applications, such as chatbots and virtual assistants, with human-like language understanding and generation capabilities. Increasing number of users turn to AI instead of more traditional information channels such as conventional search engines and this directly affects traffic levels. This tranformation is already taking place here.
- Advanced translation → GPT-3 has also been used in natural language processing tasks like language translation. With the help of GPT-3, developers are creating machine translation tools that are more accurate and natural-sounding.
- AI creativity → GPT-3 is being used in creative tasks, like writing poetry and fiction, creating art, composing music, and more.
- Dimishing demand for static learning content hosted on websites → Increasing number of people are using AI as an on-demand tutor for learning and research.
🧐 Future Predictions
- Certain types of content will lose its importance. People might not want to read articles that are just about spitting out facts. For example, an article about "What is project management" might not be worth reading because people can just ask a chat bot for the answer instead.
- Search engines will evolve into AI chat-based systems. The traditional search bar will be replaced by an AI chat bar, allowing users to interact with the search engine in a more natural and conversational way. This will enable users to easily find the information they need by asking questions or providing additional context about their search queries and without visiting the websites.
- Existing AI virtual assistants will become more advanced and efficient, with the ability to understand user intent, anticipate needs and provide personalized responses in real-time. They will communicate more naturally, leading to improved user experience and unprecedented efficiency.
👨💻 AI Code
💥 Ongoing Effects
AI is currently being employed in code creation:
- Code Completion → AI is being utilized to complete partially written code, by suggesting and writing the next line of code based on the context of the code written so far.
- Code Generation → AI is being employed to generate entire code snippets or functions based on a set of requirements or inputs. For example, it generates code to implement a specific algorithm or data structure, or to connect to a specific API.
- Bug fixing → AI is being utilized to identify and fix bugs in code by analyzing the code and suggesting changes to fix the issue.
- Explaining Code → AI is being employed to generate explanations of how a specific code snippet works, its function, and potential use cases.
- Documenting Code → AI is being utilized to generate documentation for code, including comments, explanations, and usage examples.
- Code suggestions → AI is being employed to generate suggestions for improving or optimizing code by analyzing the code and suggesting changes that could improve its performance, security, or maintainability.
- Code Translation → AI is being utilized to translate
🧐 Future Predictions
- Increased automation → AI-assisted coding is likely to become more prevalent in the future, leading to increased automation of repetitive tasks such as code generation, bug fixing, and documentation. This could lead to more efficient and cost-effective software development.
- Improved code quality → AI-assisted coding has the potential to improve code quality by identifying and fixing bugs, suggesting improvements, and providing more accurate and detailed documentation. This could lead to more reliable and secure software.
- More complex tasks → AI-assisted coding could enable the automation of more complex tasks, such as writing entire programs or even developing entire software systems. This could lead to the development of more advanced and powerful software.
- Increased adoption → As AI-assisted coding becomes more prevalent and its benefits become more widely recognized, it is likely that more businesses and organizations will adopt it in their software development processes.
- New opportunities for AI-coding → AI-coding will open new opportunities for businesses, such as creating new products, services, and business models that were not possible before.