24th of May 2024, “Sembang AIoT” open up a topic on generative AI on exploring Generative AI application in the industries. The primary focus of the whole live session is about the generative AI and the application of Generative AI in the industries. the session is hosted by Mr. CC Lee at technology trainer and speaker, along with Mr. Tan Kien Leong, the AIoT trainer and solution architect of AIoTmission.
In the live session, an old piece of literature on microcomputer system design was referenced to discuss the role of math coprocessors like the Intel 8087 in handling complex calculations, such as multiplication and floating-point operations. Today, a similar reliance is seen in AI, which heavily depends on sophisticated computing, especially for handling floating-point operations. Most GPUs now come equipped with dedicated processors for this purpose. This underscores the importance of specialized processors in performing mathematical calculations, which are crucial for running many AI applications.
A reference design book that was used in one of the microprocessor system design laboratory.
Math co processor 8087 build in design with 80186 in handling the computing in the old design
What is Generative AI
Generative AI is a type of artificial intelligence that can create new content. In simple terms, it’s like a smart machine that can write text, draw pictures, make music, or even design products on its own, just by learning from examples. It’s similar to how humans create new things by using their imagination and what they’ve learned before. For example, it can write a story based on a few sentences you give it, or it can draw a picture if you describe what you want. That is how powerful the Generative can be, So what could be the applications in the industries?
A generative AI is of deep learning AI model that is able to suggest and predict the possible output from the huge learned dataset. It is a subset of the Deep Learning. Take for example of a standard Machine Learning (ML) system, with the inputs, it is able to provide the two sets of outputs. One being the descrete ouput like number, Class and probability and the other one being natural language (Text), image and Audio. where the later is a Gen AI version of ML ( machine learning).Generally, there are several industries that allow the Generative AI to assist in improving, optimize and forecast the outcome of the current processes.
Here are some examples of generative AI currently being used across different industries:
1. Healthcare
Drug Discovery: Generative AI models, such as those developed by Insilico Medicine, are used to generate potential new drug compounds. These models can predict molecular structures that may have desired therapeutic effects.
Medical Imaging: AI systems like those from Zebra Medical Vision use generative algorithms to enhance and generate detailed medical images, aiding in more accurate diagnostics.
2. Finance
Algorithmic Trading: Generative AI models create and test trading strategies by simulating different market conditions, helping traders make more informed decisions.
Fraud Detection: Companies like Darktrace use generative AI to identify unusual patterns in financial transactions, helping to detect and prevent fraud.
3. AI Manufacturing
Product Design: Generative design tools from companies like Autodesk allow engineers to input design goals into the software, which then generates multiple design alternatives optimized for performance and cost.
Predictive Maintenance: Generative AI predicts when machinery is likely to fail and generates maintenance schedules, reducing downtime and costs.
4. Creative Industries
Content Creation: Tools like OpenAI’s GPT-4 and DALL-E are used to generate written content, such as articles, stories, and advertisements, as well as visual content like images and graphics.
Music and Art: Platforms like Amper Music and DeepArt.io use generative AI to compose music and create visual art, providing new tools for artists and musicians.
5. Customer Service
Chatbots and Virtual Assistants: AI systems like IBM Watson Assistant and Google Dialogflow generate natural-sounding responses to customer queries, improving customer service and support.
Personalized Marketing: Generative AI models analyze customer data to generate personalized marketing content and product recommendations, enhancing customer engagement.
6. Entertainment
Game Development: Companies like Ubisoft use generative AI to create complex game environments and characters, speeding up the development process and enhancing player experiences.
Film and Animation: Generative AI tools are used to create realistic special effects and animations, as seen in movies and TV shows.
7. Education
Personalized Learning: Platforms like Squirrel AI use generative AI to develop personalized learning plans and generate educational content tailored to individual student needs.
Virtual Labs: Generative AI helps create virtual laboratory environments where students can conduct experiments and practice skills without the need for physical resources.
These examples illustrate the diverse applications of generative AI and its potential to revolutionize various sectors by enhancing efficiency, creativity, and innovation
Watch our live session on Youtube channel:-