3 Literature review

Abstract

Artificial Intelligence [5] The creation of computer systems that are capable of doing tasks that frequently need human intelligence, such as learning, problem-solving, pattern recognition, and decision-making, is known as artificial intelligence. It involves developing models and algorithms that enable robots to perform tasks that often require human cognitive abilities, such as perception, language understanding, and reasoning. ChatGPT OpenAI's ChatGPT is a substantial language model that uses machine learning techniques to understand and produce language that is similar to that of humans. CHATGPT is an artificial intelligence-powered chatbot that can have a range of conversations with users, ranging from easy small talk to complex technical chats. One of CHATGPT's primary strengths is its ability to understand inputs in natural language, including slang, idioms, and colloquial phrases. As a result, it can be efficiently utilized to engage people in conversation about a range of topics, including customer service, education, and entertainment. Current Artificial Intelligence Trends: 1. Transformer-based designs, such as GPT-3, have become a significant trend in artificial intelligence. These models have state-of-the-art performance across a wide range of applications since they are pre-trained on enormous volumes of data and then fine-tuned for particular tasks. 2. Addressing bias, fairness, transparency, and ethical issues in AI systems is becoming more and more important as AI systems are integrated into society. Techniques to detect and reduce biases in AI models are being developed by academics and professionals. 3. Deep learning models are black boxes, which raises questions concerning their interpretability. In order for people to understand the thinking behind an AI model's decisions, XAI focuses on making AI models more transparent and intelligible. 4. This strategy trains machine learning models over dispersed servers or devices while maintaining localized data. It allows for collaborative model training without exposing raw data, which helps to solve privacy concerns. 5. Medical image analysis, medication research, patient care, and diagnostics all make use of AI more and more. The effectiveness and precision of healthcare procedures could be greatly increased. New Trends in Models Like GPT: 1. Researchers are striving to develop GPT-like models that are even bigger and more effective. These models have the capacity to discover more intricate patterns and produce results of higher caliber. 2. New models are combining several sorts of data into a single framework, such as text, graphics, and audio. This makes it possible to create AI systems that can comprehend and produce material in a variety of formats. 3. In the future, models may concentrate on producing interactive and dynamic replies to allow for more believable and interesting discussions between humans and AI systems. 4. AI models that are easily adapted to fit certain customers or niche industries are becoming more popular. This can result in interactions that are more relevant and customized. 5. Researchers are investigating methods that enable models to learn from a limited number of examples or change their approach to a problem without losing their prior understanding. This might increase the adaptability and flexibility of AI systems. 6. There is rising interest in creating more energy-efficient architectures while maintaining high performance because to the energy requirements of large AI models. LLM API commercialization [1]While OpenAI currently has the most well-known large language model, many businesses are likely to start providing APIs for these models in the future. With 540 billion parameters, Google already has the PaLM model, and it will likely soon offer an API for it. The Bloom model is freely obtainable at Hugging Face. A number of businesses are now growing or have already been established to provide this service, and this is true even as I write this essay. We should anticipate that huge language models will become a commodity offered by numerous organizations in the upcoming years. This technology will be included into a wide range of goods with a wide range of applications: 1. A medical record system, for instance, may automatically comprehend a patient's medical history and indicate any medications that can interact unfavorably with a condition the patient may have. This is an example of improved intelligence and reasoning in products.[2]