3 key differences between AI and robotics


Robots could replace around 800 million jobs worldwide in the future, making about 30% of all occupations irrelevant. As well, only 7% of companies are not currently using AI, but are considering it. Statistics like these blur people’s heads and make them think that robots and AI are one and the same, which they never were. Instead, businesses and governments are using robotics-based applications which can be described as a convergence of AI and robots. Contrary to what is shown in most dystopian sci-fi movies or books, not all robots are intelligent. Artificially intelligent robots, a combined application of AI and standard automation robots, are just one of many types of robots. These robots use AI algorithms and models to perform more than just a series of repetitive movements and increase their autonomy, but more on that later. AI robots are highly sought-after resources today with several applications, either by them selves Where in combination with other technologies.

There are several differentiating factors between AI and robotics, but the three enlisted here let people understand them clearly.

1) AI and robotics: conceptual differences

The basic definition of AI is to allow machines to make complex decisions autonomously. AI-based hardware and software tools can solve complex real-world problems by analyzing large amounts of data and finding patterns in them that humans cannot see. Machine learning and reinforcement learning refine the analytical capabilities of these applications over time. Therefore, AI-based applications possess unlimited capacity to improve in the tasks they perform.

For example, consider an app like TikTok. Like most social media apps, TikTok also uses a “social graph” to provide recommendations to users based on the pages they follow and the videos they like. TikTok’s machine learning algorithms go one step further than other social media apps by also using an “interest graph”– using video watch time numbers to provide suggestions to users. These suggestions will include creators and videos with similarities to those viewed by users for the longest duration. For example, if a user continues to watch a cat video for, say, more than 20 seconds, TikTok’s algorithms will direct more videos about cats, other feline creatures, and other animals to their personalized video feed to eventually get them addicted to the app. As TikTok videos are usually less than a minute long, they can collect huge amounts of data and accomplish maximum personalization faster than other social media apps.

This is how AI works – using various types of data as a benchmark to improve its performance over a period of time. As stated earlier, the larger the dataset, the better an AI-powered tool will perform in terms of operating speed and accuracy.

Simply put, robotics can be defined as a branch of technology that deals with the design, development, and construction of robots. These machines are programmable and interact with other devices or humans through actuators and data collection sensors. Robots can be used to perform autonomous or semi-autonomous tasks. Some robots, such as telerobots, are entirely non-autonomous because their operation must be controlled by human operators. As you can see, rule-based bots don’t “think” and make decisions.

Robots and AI allow companies to move towards a common goal: AI-powered automation.

2) AI and robotics: differences in degree of automation

People in the highest positions in organizations need to be aware of the type of technology they need for their business operations. Those who are not tech savvy may be unable to tell the difference between automation and robotics.

Simple automation involves the use of software, devices, sensors, or other technologies in combination to perform tasks that would normally be performed by an individual or group of workers. The complexity of the combination of devices depends on the type of operation to be automated. Automation can be of two types: software automation and industrial automation.

Software automation involves devices programmed to perform repetitive tasks using math and logic.

Software automation can include automation of the graphical user interface used to test computer programs. This type of software automation is used to record the actions of a user when interacting with a GUI and is useful for making changes to an application’s underlying software.

In addition, software automation also includes business process automation (BPA), the use of standard automation tools to improve the quality of customer service or minimize costs. BPA integrates software applications, personnel, and hardware tools to streamline business operations. Robotic Process Automation (RPA) involves software robots, or bots, to write computer programs like human programmers. RPA works on the basis of programmed scripts. Intelligent Process Automation (IPA) involves the use of AI to make software applications more intuitive and “humanized”. In IPA, bots use past data as a reference to perform actions more intelligently than software automation devices that use a rule or script-based work mechanism.

Industrial automation involves the use of robots to control and manage heavy industrial operations, such as product packaging, warehouse management, and manufacturing.

While robotics also meddles with automation, it also combines with other fields – mechanical engineering, computer science as well as, in many cases, AI. AI-driven robots can perform the functions and tasks expected of them autonomously with machine learning algorithms. AI robots can best be explained as intelligent automation applications in which robotics provides the body while AI provides the brain. Industrial automation, AI and robotics also involve other technologies such as computer vision and NLP. As a result, AI robots can perform several tasks without human intervention, such as spotting an object on a warehouse floor and placing it where it should be.

Although standard automation bots are already used for several types of business tasks, bots that work autonomously with AI algorithms will optimize the future of organizational operations.

3) AI and robotics: differences in adaptability

AI is taking robotics into new territories, such as the concept of self-aware robots. Normally, robots are just machines made of metal, sensors, cables and several electronic components. Thus, they lack the “sixth sense” that humans have when someone approaches them. The combination of AI and robotics, machine learning and sensory technology enables the creation of situationally aware robots that can “sense” the presence of humans around them. These robots possess the sense of smell, spatial proximity and responsiveness to stimuli. AI is also useful in making robots almost as skilled as humans. AI also enables robotics developers to create concepts such as Sophia, one of the world’s most renowned social robots. Along with autonomous thinking, decision-making, and mobility, Sophia also possesses abilities to determine people’s emotions and engage with individuals in interactive, human-like conversations.

Robots exist to take over tasks that a human shouldn’t have to do. Generally, robots work under strict guidelines to automate tasks and allow humans to focus on tasks that require intelligence. In other words, standard automation robots do not need to “learn”, make decisions or analyze data during their design, development, manufacture or while they perform tasks. for which they were designed. As a result, the use cases for robots are limited to such tasks as cleaning, transporting packages from one place to another, mowing the lawn, and the like.

AI, on the other hand, is all about humanizing technology as much as possible. AI models are an integral part of CRMs, personal assistants and ERP systems. These tasks are very complex and require precise data evaluation and decision-making skills. Additionally, decisions must be made considering a wide range of factors and thousands of terabytes of data. For example, an AI-powered purchasing management system will assess factors such as past material purchase records, vendor operating hours, the time it takes for materials to arrive from each vendor-route combination, and other factors. The models used in such a system “learn” and continually improve over time. Thus, their decision-making and data analysis improve just as humans improve with experience. The combination of AI and robotics capitalizes on the automation aspect of robots and the learning and cognitive aspects of AI models.

AI and robotics are a great combination for businesses, smart cities and other fields. AI allows robotic automation to continue to improve and perform difficult business operations without the slightest error.


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