The whole idea behind the inception of AI as a technology was to create something that can learn like a human and then later on perform tasks like a human. This thought was initially conceptualized by Alan Turing, who is often considered the founding father of AI or artificial technologies.
Right now, we are surrounded by AI-based applications and products. For instance, our favorite OTT platforms, such as Netflix, Hotstar, Hulu, etc, all use AI to provide relevant content to their users. Adding to it, multiple e-commerce platforms, including Amazon (the largest e-commerce platform), uses AI technology too. The use of AI technology today is multifaceted; from IoT (Internet of Things) to electricity grids, the application of AI is at par.
To further define AI development,” The development of any product or service that has integrated AI technology comes under the umbrella of AI development”.
Note: The definition provided above is not an official definition. It is simply used for ease of understanding.
AI Development Technologies Trending in 2024
2024 is the year of AI, with multiple technologies surfacing to make its name and become a part of the mainstream market. Multiple apps for startups, commercial products, services, etc., are using AI technology as a base. To reveal important ones, we have mentioned the AI technologies popular in 2024.
Therefore, here we go…
1. Automated Machine Learning
Machine Learning is by large considered the subset of Artificial Intelligence. It is important for the AI development of applications that have self-learning and decision-making capabilities. It is because the self-learning part comes from it.
In order to create an initial ML model, the ML models in focus are trained using different types of data. This process of training data is very time-consuming and can sometimes take months and even years that too with powerful processors.
Enters Automated Machine Learning aka AutoML. With AutoML, the researchers behind it aim to automate the iterative process of machine learning model development. This technology intends to help data scientists, developers, analysts, etc to create models at a much higher scale with better efficiency and scalability.
Right now, there are plenty of AutoML tools that can be used for creating machine-learning models with this capability. Some common examples of these tools would be Pytorch, Tensor Flow, H2O, Keras, etc. A report by Yahoo Finance already states the market of AutoML to reach $15,499 million by 2030 with a CAGR of 49.2%. This clearly shows that there are multiple takers of the technology and it will sooner or later replace the conventional way of developing ML models.
2. Generative AI
It is impossible to ignore “Generative AI”. Chances are, if you haven’t heard what generative AI is then you must have definitely heard about ChatGPT. If both of these cases are untrue then either you are a caveman or someone who doesn’t know how to use a computer.
ChatGPT has been one of the fastest-growing online applications with over 100 million users post its launch. However, generative AI is limited to ChatGPT. Well, the answer is no. ChatGPT is based on GPT (Generative Pre-trained models)model i.e. an NLP technology that is open source. Right now, there are plenty of tools that are using GPT technology such as Jasper, Copysmith, Kafka, Zyro, etc. In fact, everyone’s favorite ChatGPT has recently been upgraded with a GPT-4 model. The only issue is that it can be accessed via a paid subscription. However, the free version of ChatGPT still uses the GPT-3.5 version.
3. Natural Language Processing (NLP)
With Generative AI taking space in everyone’s life, the amount of attention that is being given to NLP technology has definitely increased. Initially, there were multiple technologies such as document automation, Chatbots, conversational AI, etc that were using NLP. However, now the technology is becoming a lot more mainstream.
If you don’t know what NLP is then it is simply another subset of AI technology that helps the machine to understand the human language.
Below Are Several Advantages of Nlp:
- Capability to understand the context of the human language
- Capability to extract text from both structured and unstructured sources
- It can understand the sentiment of the user
- It can be easily implemented with Chatbots
- Summarization of data
- Works seamlessly with voice assistants
- It can extract specific entities using NER (Named Entity Recognition)
Here Are Some Common Names that Use NLP for A Better Product. These Are:
- Google Search
- Alexa SIRI
- Netflix
- Grammarly
- Slack
4. Ethical AI
In a recent event, Italy put a temporary ban on ChatGPT stating that it was processing personal data of Italian citizens which was against GDPR policies. The ban was removed, however, that begs a real question “Should AI technologies follow an ethical code?”
To frame that into a structure, ethical AI came into being. Now what is ethical AI?:
The ethics of artificial intelligence is the branch of the ethics of technology specific to artificially intelligent systems.” It is because these technologies have the capability to often trespass their limit. The idea also became prominent in the tech circle because the general population was skeptical about AI technologies.
Here are some ethical AI guidelines:
- We won’t allow totalitarian states to use our AI to advance their regimes or control their citizens.
- We won’t allow our AI to be used to deceive people or assign values to them through social scoring and other AI-powered systems.
- We will work in the energy industry to improve the efficient production and delivery of energy of all kinds, including renewables.
5. AI-as-a-Service (AIaaS)
AIaaS is the technology that lets you outsource the technology of AI. Generally in order to create an AI model, companies either have to set up an in-house team or hire one of the top artificial intelligence companies. With , companies offer their AI as a third party to let the client company experiment with the AI models and check their effectiveness.
There are several benefits of using AI-as-a-Service such as:
- Easy to deploy
- Low-code or no-code implementation
- It saves a lot of costs
- Higher transparency
- Better scalability
Must Read: Artificial Intelligence App Ideas
AI Development Technologies Beyond 2024
There are some of the AI development technologies are most likely to blow up after 2024. It’s not that these technologies are not in conversation, however, they reek of much higher potential in the forth-coming years when the existing technology is mature enough to embrace them.
1. Artificial General Intelligence
If you are unaware of what AGI is then AGI is basically the capability of a machine to solve unrecognized problems just like humans would do. It involves machines that have human-like cognitive skills such as learning, reasoning, solving problems, and communicating in a natural way.
This technology is still a pipe dream and hasn’t been conceived yet. However, while developing the latest GPT-4 model, it is said that an incomplete model exhibited hallucination. It is alarming because hallucination is a very human trait and it is interesting to see a similar thing happening in the case of a machine.
2. Quantum Computing
Quantum computing is the type of computing that harness its power from the laws of quantum mechanics. These types of computers are used for solving problems when a general-purpose computer fails.
Giant companies like IBM use Quantum Computers to solve complex problems such as the exploration of electric vehicles, complex energy challenges, cosmic mysteries, etc. However, despite being a powerful technology, Quantum Computing still struggles to solve any mysteries.
It is because right now these computers are limited by errors, applications, size, and many other constraints. The future holds the key to liberating the existing system from its adversities, therefore, it is going to be a lot more prominent in the future.
3. Brain-Computer Interfaces
A brain-computer interface is a device that allows people to interact with a computer using brain activity. This technology is in its early stages of software development. However, it does have the capacity to revolutionize the way we interact with technology.
The idea came into being in 2021 when researchers from the University of California, Berkeley, developed a robotic arm for people with paralysis. In 2023, the University of Pennsylvania has created a BCI that allows blind people to see with their thoughts. These are simply some of the few examples. Yet, there are many chances to see this technology in full fruition in a couple of years.
How Emizentech Can Help?
As we approach 2024, AI development is set to redefine various sectors, from healthcare to finance. Trends suggest a greater focus on ethical AI, automation, and human-AI collaboration. At Emizentech, a leading AI development company, we are committed to staying ahead of these trends. Our expert team can help you integrate cutting-edge AI solutions into your business model, ensuring you remain competitive and agile in this fast-evolving landscape. Trust Emizentech to be your guide in navigating the future of AI, delivering tailored solutions that anticipate industry shifts.
Wrapping Up!
Staying in touch with the AI counterpart is essential. It is because AI is the future of technology. The majority of technologies that we use are using AI in some form or way. These technologies that we mentioned are simply the tip of the iceberg. In reality, there are numerous inventions that take benefits from AI technology. To stand tall and embrace the changing market and features associated with products, companies need AI as the backbone of their product. With AI, they would be able to provide a complete custom experience and serve & retain customers with ease.
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