AI Applications and Techniques
From Algorithms to Intelligence: The Advent of AI Technology
- Overview
Artificial Intelligence (AI) was coined in 1955 to introduce a new discipline of computer science. It is rapidly and radically changing the various areas of our daily lives as the market for AI technologies is demanding and flourishing.
The emergence of AI technology marks an important milestone in human history. From the earliest algorithms to the emergence of intelligent systems, AI has transformed industries, enabled breakthrough applications, and raised important social considerations.
As we navigate these exciting times, it is critical to embrace the potential of AI while addressing ethical, privacy, and workforce challenges. By promoting the responsible development and use of AI, we can unlock its full potential, revolutionize industries, and pave the way for a brighter future powered by artificial intelligence.
But the most sophisticated AIs are still far from solving problems that a human four-year-old can do with ease. Despite its impressive name, AI consists primarily of techniques for detecting statistical patterns in large data sets. Humans still have a lot to learn.
Please refer to the following for more information:
- Wikipedia: Applications of Artificial Intelligence
- Current AI Applications
Technology is changing the way humans and machines work together. People rely on machines to help them make smarter decisions, expand range and access, and improve safety and productivity. This new era of human-machine collaboration relies on trust and understanding — allowing each component of the team to do what it does best. The autonomous future is not without people. It's more of human nature.
AI has exploded over the past few years, especially since 2015. Much of this has to do with the widespread availability of GPUs that make parallel processing faster, cheaper, and more powerful. It also has to do with one or two hits of near-infinite storage going on at the same time and massive amounts of data per stripe (the whole big data movement) - images, text, transactions, mapping data, you name it.
AI has various applications in today's society. It has become critical in this day as it can effectively solve complex problems in multiple industries. AI is making our daily lives more comfortable and faster.
The following are several of the most notable examples:
- AI in healthcare
- AI in business
- AI in education
- AI in finance and banking
- AI in law
- AI in entertainment and media
- AI in journalism
- AI in software development and IT
- AI in security
- AI in manufacturing
- AI in transportation
- Generative AI and Large Language Models
Generative artificial intelligence (AI) describes algorithms (such as ChatGPT) that can be used to create new content, including audio, code, images, text, simulations, and video.
Recent new breakthroughs in this field have the potential to revolutionize the way we approach content creation. Generative AI systems fall under the broad category of machine learning.
Large language models (LLMs) represent a major advance in AI, promising to transform the field through learned knowledge. LLMs have grown in size by a factor of 10 per year over the past few years, and as these models have grown in complexity and size, so have their capabilities. However, LLM is difficult to develop and maintain, making LLM inaccessible to most businesses.
Generative AI based on Large Language Models (LLMs) and Transformer Neural Networks has definitely attracted a lot of attention. Unlike the hype cycles of new technologies like the Metaverse, encryption, and Web3, generative AI tools like Stable Diffusion and ChatGPT promise to have a massive, possibly revolutionary impact. These tools have disrupted multiple sectors -- including the film industry -- and have the potential to change the game for enterprise software.
Ready to take your creativity to the next level? Just look at generative AI! This ingenious form of machine learning enables computers to generate all kinds of exciting new content, from music and art to entire virtual worlds. And it’s not just for fun—generative AI has many practical uses, too, such as creating new product designs and optimizing business processes.
[More to come ...]