In the last week of February 2021, I attended the AWS Innovate Online Conference which was focused on the usage of Artificial Intelligence (AI) and Machine Learning (ML). I wanted to touch on some of the learnings I picked up from the online conference.
Let’s first discuss what AI and ML are:
Artificial Intelligence (AI):
AI can be described as a branch of computer science which deals with the intelligence demonstrated by machines based on the simulation of human intelligence. For example, a system or machine that is structured based on the characteristics and traits of a human mind. This could involve learning and problem-solving. Think about how many different industries and professions could be positively impacted by AI.
Machine Learning (ML):
ML is a part of AI that analyses data and uses the information to automates analytical model building. It stems from the theory that machines can learn from data, identify patterns and trends and use that information to reduce human interaction in decision making. The main thing behind machine learning is that it uses the data to enable systems to improve and update without human programming or supervision.
Session 1: Innovation is never normal!
This was the first session that I attended, it really caught my attention and opened my eyes to the varying industries making use of AI & ML. The role played by the two technologies can be vital in dealing with simple to complex operational problems. They discussed the usage in 4 different industries, the farming industry, conservation genomics, digital people and the trucking and freight industry. To keep things short and sweet, I will discuss the two that interested me the most: Conservation Genomics & Digital People.
Conservation Genomics is important as it is highly essential to species survival and attempts to preserve a species population size. Saving species diversity is not cheap and requires cheaper sequencing technologies but deals with a lot of data that needs large amounts of space on computers. The size of the data cannot be determined till it arrives and may not be in line with storage on the PCs. AWS’s scalable and flexible cloud technologies help to maximize conservation growth by being able to expand space in the cloud in real-time. Usually, on a PC the data could take up to 10 days to run, meanwhile, AWS cloud services make it possible in 6 hours.
A company called Soul Machine works in the realm of autonomous animation which speaks to the ability to create digital characters to interact within real-time. In essence, creating a digital brain carried by a digital human with who you can engage emotionally and build trust. The benefits of digital people are that they are infinitely scalable as millions of conversations can occur at one time. They are a valuable asset to any organization as they will never leave or need a break. You have the ability to build different types of people depending on the purpose down to demographics such as age, gender, ethnicity and language. ML and AI with AWS make this possible at a scale that has not been possible before.
I hope this gave you a high-level idea of what I learnt in this session and how AWS solutions can be implemented across various industries for various purposes and have a great impact.
Are you using AWS solutions for AI or ML? Do you think your business could make use of it?