AI and ML are like siblings. These two technologies go hand in hand in every domain. AI and ML complement each other when it comes to functionality and innovation. The last two years have seen significant advances in these fields and continue to do so every day.
Here is a blog to keep you updated on the latest developments and Top 10 Emerging AI and ML Trends 2022.
- Explore the latest Artificial Intelligence trends in the industry.
- Learn about the latest machine learning trends in 2022.
Top 10 Emerging AI and ML Trends 2022
1. Hyper Automation
Hyper automation is a business-oriented AI trend used by IT organizations to automate processes. Hyperautomation uses machine learning and artificial intelligence models like OCR (Optical Character Reading) and reading emails using NLP.
Optical Character Recognition converts readable pdf files into machine-readable files for data processing and entry. Machine-readable files are written in machine language.
2. Conversational Artificial Intelligence
Conversational AI combines natural language processing and chatbots or voice assistants to understand human speech and carry out voice tasks.
Examples of conversational AI are in Amazon’s voice assistant Alexa which understands human language using NLP and carries out tasks accordingly.
Must Read: Top 7 Emerging Technology Trends In 2022
3. Latest AI Trends in Medicine
Artificial Intelligence can help medical imaging identify early signs of diseases and spot cancer cells in potential patients. AI can also retrieve previous health records of patients who’ve had similar conditions.
The most common issue in the medical field is human error. AI can help reduce these errors significantly.
4. Latest AI Trends in Education
Personalization is a huge part of AI, where the algorithm is trained to provide the user with personalized content. For example, Netflix has a feature called ‘play something’ where it plays similar media content based on the past movies or tv shows viewed by the user.
In the education sector, various students study and understand concepts differently.
Some of them might be able to grasp concepts quickly and efficiently, while some may take time to do so.
Personalization is applied in learning applications to learn and understand how a student performs from assessments and provide study material accordingly.
5. Tiny ML
Tiny ML is a fast-growing trend in Machine Learning today. It is utilized in hardware components such as microcontrollers deployed in electric cars, refrigerators, etc. Tiny ML involves embedding artificial intelligence in these devices.
Microcontrollers are attached to machine parts to monitor and notify the authorities when malfunctions occur. Farmers use TensorFlow Lite’s application to monitor the crops’ health and take pictures if the crops require immediate attention.
6. Quantum ML
Quantum ML is an area of research in quantum computing and machine learning that focuses on converting machine learning algorithms into qubits instead of bits.
Quantum computers are the most powerful computers in the world that are being developed to solve the world’s most complex problems. Multinational corporations can use quantum computers to process large datasets and provide in-depth analysis.
Quantum ML algorithms combined with quantum mechanics run these giant computers.
7. AI Conceptual Design
Artificial intelligence is now used to create visual designs by combining language and images from simple text descriptions.
Conceptual AI design is used in finance and retail to deal with repetitive tasks. OpenAI has recently developed two models, DALL E and CLIP (Contrastive Language Image Pre-training), to create these designs.
This trend is expected to disrupt sectors like fashion, architecture and other creative domains in the coming years.
8. AI in Cybersecurity
Cybersecurity attacks are omnipresent. As new companies develop and sprout worldwide, cyber-attacks will always rise. The time has now come to upgrade cyber security in every possible way.
It would not be immediately possible to eradicate these attacks, but it is possible to prevent most of them by applying artificial intelligence and machine learning methods.
Cyber attack trends keep changing over time, and it is hard to keep up with them constantly.
Machines identify attack patterns and notify the authorities as potential threats are detected.
Using AI, it is possible to train the model to discover new hacking trends as they come.
9. Edge AI
Edge AI combines Edge computing and Artificial intelligence into the same system. Here AI helps in data processing in intelligent devices. Edge AI devices are smart speakers, smart cars, robots etc.
Edge AI devices are known for real-time data processing. They can send data during emergencies in a smart car when certain parts are not responsive or have failed to comply.
10. AI and ML in the Metaverse
A common term used by technologists today is the Metaverse. The Metaverse is a virtual space where people can work, play and socialize. One can enter the Metaverse using an AR or VR headset.
AI and ML can be incredibly significant in the Metaverse to better user experience. AI beings are built in the Metaverse to assist the users with various activities like shopping, playing games and even teaching young children.
As a tech enthusiast, I can assure you that the future looks bright in technology.
Both AI and ML, when used for the proper purpose and intentions, can hugely benefit users like us worldwide.
The beauty of Artificial intelligence and Machine learning is that they can be applied in literally any domain to solve problems or optimize mundane processes.
I hope this blog was helpful and you learned something new today!
Frequently Asked Questions (FAQs)
1. What is TensorFlow, and what is it used for?
TensorFlow is an open-source software library for AI and machine learning mainly used to train neural networks.
2. How are AI and ML connected?
Artificial intelligence houses various other technologies like ML, NLP, deep learning etc. AI is embedded in machine learning methods.
3. Which programming language is used to code AI?
Python is mainly used to create AI and ML applications.