Artificial Intelligence (AI) is a field that has left many onlookers amazed by its ability to contextualize data sets using advanced techniques like machine learning and neural network connections. AI has generated a massive amount of data but had limited uses for it besides tracking customer analytics.
Investors are Driving the Evolution of Artificial Intelligence
After a stagnant period in R&D, AI is slowly gaining traction with an increased focus on perceptive reasoning. It has increased in scope to cover a myriad of business applications from integration to systematic templates. AI uses a built-in motion camera with image sensors to capture information for software systems to process.
In fact, over 9000 patents were issued to IBM inventors to support AI engineering in 2018 alone. Likewise, Tesla founder, Elon Musk donated $10 million to fund ongoing research into algorithm-based machine learning at OpenAI. As tech giants continue to spend billions on developing robotic technology, major breakthroughs are expected to happen soon.
Data scientists predict that the AI-powered workforce will accelerate job displacement in banking, retail, and manufacturing. Repetitive, scripted tasks will be performed by adaptive machines in the near future, leaving uneducated, low-income workers most at risk of losing their jobs.
This is true for jobs that measure quantifiable goals (i.e. sorting objects, cleaning floors, harvesting food, and transferring calls).–Data-trained models can perform these functions while powered by IoT connectivity. Businesses have been using AI to solve specific problems affecting their bottom line.
AI plays an important role in the following fields:
Testing Autonomous Vehicles and Self-driving Cars
AI is playing a bigger part in public transportation as traffic congestion becomes unbearable for those who work a 9 to 5 in major cities. Self-driving cars are hitting the roads, capable of mapping out their surroundings before navigating around obstacles.
A prototype of a self-driving car must follow the rules in the driver’s manual: To prevent accidents, it has a biometric system that detects the relative motion of people or other cars. Google has been testing the earliest autonomous vehicle model known as Waymo. Waymo cars are equipped with light detection sensors to determine the speed and trajectory of other vehicles.
Driving can be complicated, especially if bad weather conditions arise or drivers have to decide who has the right of way. It’s hard to encode road conditions into a software system so a car recognizes where other vehicles and pedestrians are located. Right now, self-driving cars are trained on simulation data, derived from driving thousands of miles on many types of roads.
Assembly and Production with Machine Learning
On Amazon’s manufacturing sites, over 100,000 robots can be seen stocking shelves and packaging items from their huge warehouse inventory. Executive managers plan to cut down on a portion of their workforce which means laying off employees who do most of the heavy lifting. Since technical skills are more valuable than ever, retraining seems to be the best option for making structural unemployment less devastating.
AI can automate manufacturing equipment to make warehouse management more efficient. Many cutting tools are integrated with machine vision to mark where to slice materials like fabrics or metal surfaces so they all have the same dimensions. Then, finished products are transported via conveyor belts to robotic arms that inspect them for quality purposes before they are shipped out to customers.
Machine learning is demonstrated in AI CAD printing for assembling parts.–A CAD program prints 3-D machine parts modeled after user-generated designs using a combination of rigid and elastic materials. Engineers will need accurate digital twins to test robotic arms and other equipment on the production line. This allows warehouses to keep replenishing their inventories so that supply meets the demand from online shoppers.
Medical Imaging, Diagnosis, and Patient Checkups
AI is improving healthcare on a wider scale from drug discovery to patient outcomes. AI allows medical practitioners to discover more insights into patient outcomes, diagnostics, precise treatments, and mental health evaluations. Using image analytics, radiologists can narrow down abnormalities in body scans before clinical data is reviewed.
Psychiatrists have access to electronic health records for extracting patient data that would indicate a higher risk of anxiety or depression. Doctors are also given the resources to develop proactive interventions that stay ahead of chronic diseases. Clinical decision-making tools can predict early signs of complex conditions like epilepsy.
Some smart devices can track a wearer’s heartbeat with built-in sensors to measure a person’s fitness relative to the average BMI. In addition, there are health records for highlighting patterns of infection in patients before the onset of disease symptoms to identify strains of bacteria resistant to antibiotics. AI has also made progress in immunotherapy for battling cancer by measuring the efficacy of various treatments.
Virtual Tutors Assist Students with Different Learning Styles
AI is transforming STEM education in the classroom. Many institutions have been employing AI to personalize learning based on students’ interests and familiarity with concepts. Instructors are no longer using traditional textbooks to teach their core curriculum. Instead, a voice assistant lectures supplemental course materials to students or answers their questions as needed.
Interactive platforms enable professors to give feedback on graded assessments with cutting-edge digital learning software. Since K-12 classrooms have limited budgets, they can benefit from having an AI assistant to distribute supplemental materials to children in case they struggle with language or arithmetic benchmarks.
AI solutions like the Presentation Translator features translations of multilanguage courses in real-time to provide ESL students with instructions in their native language. It also lets students take remote lessons from home whenever they are unable to participate in person. AI could be leveraged for grading exams or taking care of administrative duties to give teachers a much-needed break.
The Not-So-Distant Future of AI as We Know it
AI is comprised of general adversarial networks implemented into algorithms. Currently, AI testing is focused on reinforcement learning to distinguish between rewards and punishments.–One method involves teaching a robot how to solve simple puzzle games in a limited number of moves. The robot will have to plan its next course of action framed around the game’s objective.
Powered by big data, AI’s contributions to society are nearly endless. It could play a significant part in environmental sustainability such as civil engineering and road construction in cities. AI is a medium for businesses to profile individuals by their data and find patterns in their spending behavior. So far, AI has found its place in diagnosing diseases, building scalable algorithms, generating spoken language, and processing visuals to recognize people’s faces.
Even though AI systems could one day draw connections between ideas we would never think of, it is unlikely to reach the intelligence of humans anytime soon. Inventive developers are rising up to the challenge of copying a human brain’s cognitive abilities to replicate our thought processes. They have already figured out how to provide machines with working procedural and semantic memory so it can acquire knowledge at a faster pace.
