AI has made waves across industries – from optimizing processes to boosting efficiency, accuracy, and customer service. This technology has innovated these industries and widened the possibilities of what each of them can offer. While applications of AI for each of them may differ, they are all driven by the common goal to create change for the better.
We discussed how the Iron Ox created a database of robotics and horticultural knowledge that could help facilitate the design of indoor farms. Automating agriculture means that harvested products will improve in quality and flavor. Robots make labor more cost-effective as they become responsible for repetitive and mundane tasks. This smart technology also addresses the unique needs of every plant. Since cloud software is utilized, monitoring the conditions of the farm ensures the overall health of the plants. Companies will be able to produce more to meet the needs of the growing population, through less wasteful and more sustainable means.
With diagnoses becoming more and more complex, AI in healthcare could assist in preventive medicine and the discovery of new drugs. Certain technologies help professionals collect and store data, and thus narrow down certain treatments for patients with chronic or terminal illnesses. Doctors and researchers can also analyze big data to spot genetic abnormalities and assess treatments from there. Since many healthcare costs are attributed to administrative tasks, AI can automate these to save resources and valuable time that healthcare providers use to improve patient care.
Printed circuit boards (PCBs) are arguably the building blocks of modern society. Given the multitude of component manufacturers and the extensive selection of circuit board parts now out on the market, keeping track of each component and putting them all together into one PCB can be an extremely taxing job, but robotics and AI address this. Automated optical inspection (AOI) speeds up the inspection process of manufacturing processes while also ensuring the products’ quality. Since PCBs have gotten smaller and more intricate, this spots defects that may not be visible to the human eye. Robots equipped with machine learning learn from previous errors, improve production from here, and thus, increase the yield of a product.
When businesses adopt AI in their retail stores, they can garner more information about their customers’ preferences and behavior to predict what exactly they want and need – even before they are aware. Feeding machine learning tools with sales data will allow it to uncover patterns in customers’ spending habits and suggest how to layout products to get them to buy more. Processes behind the scenes such as inventory can also leverage AI technology as it will keep track of stock and predict future revenue. It’s reported that experiential buying will also become more popular as immersive product catalog visualization will let customers try products before purchasing them.
In the education sector, AI encompasses all levels and skillsets. Accommodating different learning styles, aptitudes, and speeds are some of the biggest hindrances educators face. AI in education means that systems personalize learning for every student’s specific needs. Machine learning uses hyper-personalization to tailor learning materials for each student depending on their abilities and preferences. Some AI systems even have interactive interfaces that can generate feedback from students, address specific questions, and go over topics students are having trouble with.
While a good number of people are still reluctant to fully embrace AI, there is no denying the fact that it’s given us solutions that were once perceived as impossible.