Deep Learning and AI

10 Artificial Intelligence Tasks You Didn’t Know AI Could Do

January 23, 2023 • 13 min read


Artificial intelligence tasks are as innumerable as humans can creatively conceive of ways to apply AI technology. With that in mind, there are artificial intelligence tasks the average person would probably never know that AI could even perform. In fact, there are amazing things AI can do that catch most people off-guard!

While much can be said about artificial intelligence, this list is more of an artificial intelligence 101 crash course. We could deep dive into specific ways AI has improved our lives in ways we may not realize, but let’s start by defining artificial intelligence.

What Is Artificial Intelligence (AI)? Artificial Intelligence 101

Artificial intelligence (AI) is the application of a computer or machine to perform tasks that would normally require human intelligence, such as learning, problem-solving, decision-making, and natural language processing. AI can be classified into two categories: narrow and general. Narrow AI is designed to perform a specific task, such as playing a game or driving a car, while general AI is designed to perform a wide range of tasks. Some of the goals of AI research include developing computers that are able to reason, learn, and adapt in a way that is similar to humans.

Data Scientists and Machine Learning specialists develop these AIs to be used to perform tasks that humans either don’t do, don’t want to do, or cannot do (efficiently).

While this last one might surprise some, that AI can, apparently, replace the need for humans to perform these tasks, it shouldn’t be so surprising. When trained correctly, artificial intelligence can perform tasks incredibly quickly and efficiently. 

Approach this article as an exploration into artificial intelligence 101 and see that there is a lot of opportunity for artificial intelligence tasks to surprise us and make us realize how much we depend on AI programs and models as well as inspire perhaps your own journey on developing a new AI.

Artificial Intelligence Tasks by Type

It's important to note that while AI can perform these tasks, humans may still be needed to set up the AI system, provide oversight and guidance, and make final decisions.

Do Not Want to Do

There are many tasks that AI can help humans with that humans may not want to do due to the nature of the task being repetitive, tedious, or otherwise undesirable. Some examples of tasks that AI can assist with include:

  • Data entry and data processing: transcribing data from one format to another or sorting and organizing large amounts of data.
  • Customer service: answering customer inquiries and resolving issues through chatbots and virtual assistants, or funneling inquiries to the correct department
  • Monitoring and surveillance: security camera surveillance and identifying potential threats. Can identify objects like stray cats as harmless or identify broken glass to alert officials
  • Manufacturing and assembly: AI can assist with tasks such as assembling products on a production line or inspecting products for defects with computer vision
  • Agriculture: AI can help identify pests or diseases in crops, optimize irrigation systems, and predict weather patterns.
  • Health care: AI can assist with tasks such as analyzing medical images, identifying patterns in patient data, and assisting with diagnosis and treatment plans.

Do Not Need to Do

There are many tasks that AI can help humans with that humans may not need to do due to the availability of AI technology. Some examples of tasks that AI can assist with include:

  • Data analysis: AI can help with tasks such as analyzing large datasets, identifying trends and patterns, and making predictions.
  • Natural language processing: AI can help with tasks such as language translation and understanding and generating human-like text.
  • Image and video analysis: AI can assist with tasks such as identifying objects and people in images and videos, as well as analyzing their behavior.
  • Prediction and optimization: AI can help with tasks such as predicting outcomes and optimizing processes.
  • Decision-making: AI can assist with tasks such as identifying the best course of action in a given situation and making recommendations.

Cannot Do (Efficiently)

There are some tasks that AI can perform that humans are simply not capable of doing or are unable to do efficiently. Some examples of tasks that AI can assist with that are beyond the capabilities of humans include:

  • Processing and analyzing large amounts of data at high speeds: AI can process and analyze vast amounts of data in a short period of time, making it possible to uncover patterns and trends that might be missed by humans.
  • Performing tasks with a high degree of precision: AI can perform tasks with a level of precision that is beyond the capabilities of humans. For example, an AI system might be able to identify differences in two genomic sequences with a much higher degree of accuracy and speed.
  • Operating in hazardous environments: AI can perform tasks in environments that are too dangerous for humans to work in, such as deep sea exploration or nuclear power plants.
  • Performing tasks that require a high level of endurance: AI systems can perform tasks that require a high level of endurance without getting tired, such as sorting packages in a warehouse or operating delivery vehicles within the factory.

How Does AI Work?

One final part of understanding as we conclude our artificial intelligence 101 crash course is to discuss how AI technology works. Basically, AI is simply coding programs that are trained using raw data points to perform certain tasks.

There is a lot more that goes into artificial intelligence than this simple definition, but this is a great place to start. There are two primary types of training for these artificial intelligence programs: machine learning and deep learning models.

Machine learning is a method of teaching computers to learn from structured data, without being explicitly programmed. It involves using algorithms to analyze and understand patterns in data and then using that understanding to make predictions or decisions. The data fed to machine learning algorithms need to be pristine, removing or capping outliers, omitting unneeded data, and monitoring biases. Machine learning algorithms and AI models are perfect for data science and analytics that assist users in parsing through millions of data points quickly and efficiently.

Deep learning is a subset of machine learning that uses neural networks, which are modeled after the human brain, to analyze and understand complex patterns in data. These networks are composed of layers of interconnected "neurons" that can learn to recognize patterns and make decisions based on input data. The data fed to a deep learning model can be unstructured but still require strong parameters and tuning to get correct. These AI models not only take in data and produce a result but generate an entirely new or unexpected result based on the plethora of data being processed. This is how we see computer programs that can perform artificial intelligence tasks like writing a blog post or a novel by “reading” 1,000 novels from different authors of the same genre.

Example: Recommender Systems

Recommender systems can be implemented using both deep learning and machine learning techniques.

Recommender systems using traditional machine learning algorithms like Collaborative Filtering (similar buyers/users), Matrix Factorization, and the Nearest Neighbors method (similar genre or aspects of a given product). These methods use the historical behavior of users and items to make predictions about what a user might like in the future using comparisons and averages. However, the cold start problem occurs when there is not enough data from new users to effectively suggest new products based on history.

On the other hand, the Deep Learning aspect of Recommender systems uses neural networks to learn the representations of users and items from their historical interactions. These representations are then used to predict the user's preferences for items. These methods are particularly useful for handling large and sparse data, and for problems where traditional methods struggle, like the cold-start problem.

Therefore, Recommender systems can be part of both deep learning and machine learning, depending on the specific techniques and architectures used to implement them.

10 Amazing Things AI Can Do You Didn’t Know About

Now that we have concluded a brief artificial intelligence 101, let’s talk about some of the most amazing artificial intelligence tasks that can be achieved. To keep learning more about AI, though, here is our list of the best courses to keep learning about artificial intelligence. These artificial intelligence tasks are in no particular order, but the majority of them likely affect a user’s daily life!

1. Read and Comprehend

There are AI programs that can not just read to a user, but the user can insert written text or a link to a blog post, and the AI program will read it. Then, once the article has been read, it can generate a summary or shorthand notes to glean the most important information from the text. Check out SummarizeBot to try it out!

2. Detect Gunshots and Alert Authorities

It is no surprise that one of the amazing things AI can do is listen and understand human speech, but AI programs can also be trained to hear and detect other sound patterns! ShotSpotter does this to keep neighborhoods safe and help authorities respond quickly to dangerous situations.

3. Generate Computer Code

We have come full circle to where we are now and training computers in code to learn to write code trained on vast amounts of code provided by online communities. While AI has a long way of approaching a full-scale project to tackle real-world problems, programmers can utilize AI to assist in writing small blocks for ideation and inspiration on how to tackle specific issues. ChatGPT, an AI chat model can help with writing basic code.

4. Play Highly Complex Games

We are not just talking about the CPU built into Chess or the Bots inside of MMOs. OpenAI developed AlphaGo which beat the best player Lee Sedol in the age-old board game Go. OpenAI also develops AIs able to play games like Dota2 and Starcraft at a competitive level beating world champions. MuZero is another AI developed to learn and play Chess, Shogi, and a plethora of Atari arcade games from scratch (with zero intervention).

5. Computer Vision

A special type of machine learning model called computer vision allows for AI technology to “see” by taking in visual information and processing and producing results based on that visual input. This can include various multi-step tasks such as agriculture monitoring, detecting cancerous cells, or operating machinery. Here is a list of 10 uses of computer vision to check out!

6. Create Original Art

As mentioned earlier, it is entirely possible for artificial intelligence to complete tasks such as creating blog posts and even novels. Taken a step further, some AI programs are even able to produce their own artwork. We are sure you’ve heard of OpenAI’s DALLE-2 in which text prompts generate compelling image representations.

7. Be a Stock Broker

AI systems can be trained to analyze financial data and make predictions about stock prices with decent confidence. It can identify to hold or sell when assets get risky. It’s fascinating to think that some brokers and individuals trust artificial intelligence with large sums of money!

8. Predict the Local Weather Accurately

Weather forecasting is almost entirely done by computer programs these days, but only in the broadest sense of the word. It still takes a lot of human interpretation to define what these results mean. However, by using AI computer vision, researchers have been able to predict sudden weather changes in local areas before they happen with far more accuracy. It has been so accurate to the point that the project to simulate Planet Earth can be feasible with advancements in weather forecasting and simulations to visualize and combat climate change.

9. Discover New Uses for Existing Pharmaceuticals

The company Recursion Pharmaceuticals has developed an AI program that can perform artificial intelligence tasks to assess all the possible uses of existing drugs and compare them with other existing drugs to determine overlap where one pharmaceutical drug can be equally or more effective than another. This allows doctors to have more ways to treat patients based on their specific needs and biological makeup. Artificial intelligence is playing a huge role in drug discovery. HPC is necessary for molecular dynamics, thus drug researchers are leveraging their HPC solutions to train and deploy AI models to evaluate potential drug targets.

10. Recommend Products with Scary Accuracy

Through a combination of multiple layers of AI technology, one of the most amazing things AI can do is suggest new products. Netflix’s recommender system was revolutionary in its ability to suggest extremely compelling shows to watch once one was finished. There are hundreds of shows to watch and thousands of movies to re-watch; having an automatic recommender makes the user experience easy and fluid. It even provides a percentage of confidence you will enjoy it. Now many companies deploy a highly complex recommender system to boost sales in online shopping, targeted ads, music streaming services, and more.

Fascinated by AI and Want to Know More?

Artificial intelligence is one of the most defining developments coming out of the 21st century because it is shaping the way humans do anything and everything. Hopefully, this artificial intelligence 101 crash course and a sample of 10 amazing things AI can do have piqued interest in the constantly changing world of AI. More new technologies are being accelerated by AI, and the market for new iterations and ideas in which AI can improve the daily lives of humanity is immense.

If you want to get started discovering how to build your own AI programs, then we would love to hear from you. SabrePC builds solutions for any stage of Deep Learning! From individuals and workstations to large teams and large-scale GPU servers,

Contact us if you have any questions or comments or would like to learn more about our Deep Learning Solutions. Otherwise, there are a plethora of articles on topics like this over on our blog!


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