Artificial intelligence (AI) was built around the entire concept of imitating human intelligence in machines. Today, we are surrounded by numerous AI models and products that are capable of replicating intelligence (although not as intelligent as humans). Moreover, 2023 has been a great year for AI trends and has seen the inception of numerous large language models. Tools like ChatGPT, Bing Chat, and Meta’s LLama 2 are being used by several businesses and individuals as their companions. But, how will the field of AI look in the future and what can we expect? Well, we are here with our predictions for the future of AI development that you must surely check out!

Top Predictions For The Future Of AI Development That You Must Keep In Mind

With so many trends in the AI industry, we must make predictions related to the future of AI development to help businesses get the headstart they need. So, what are you waiting for? Check out the following section to learn about the future of AI development in 2024 and beyond!

Automated Machine Learning

Machine Learning is undoubtedly the largest and most important subset of AI and has contributed to the development of applications with self-learning and decision-making skills. These applications (also known as models) are trained on large amounts of data which can be quite time-consuming. This is where automated machine learning can be beneficial and can transform the way these models are developed. 

Also known as AutoML, this process focuses on helping researchers, data scientists, developers, and analysts create models that are easily scalable and efficient. According to a report published by Yahoo Finance, the AutoML market is expected to grow at a CAGR of 49.2% and reach USD 15,499 million by 2030. This clearly shows that there are multiple benefits of the technology and a lot of companies will jump at the opportunity.

Generative AI

If you are a techie or read technology news, we are sure that you have heard about Generative AI. If not, you have surely heard about ChatGPT, which is a beautiful example of a generative AI model. As the name ChatGPT suggests, it is based on the GPT model, i.e. Generative Pre-Trained models which is an NLP (Natural Language Processing) technology and is open-source.

Other than ChatGPT, some other technologies and platforms utilizing the GPT model include Copysmith, Kafka, Zyro, and Jasper. ChatGPT has also launched its GPT-4 model which is available via a paid subscription, whereas the free version of ChatGPT uses the GPT-3.5 version. ChatGPT gained so much popularity that several tech giants have started investing in Generative AI and building their language processing models.

Natural Language Processing

As the hype around Generative AI is on the rise, the attention on Natural Language Processing (or NLP) is also increasing. When NLP was relatively new, it gave rise to multiple technologies like document automation, chatbots, and conversational AI. However, NLP is becoming a mainstream technology and is being used by multiple companies and platforms. Companies using NLP to launch better products and generate more revenue include Google Search, Netflix, Alexa, LinkedIn, Slack, and Grammarly.

Some benefits of NLP that have contributed to its popularity include:-

• Ability to better understand the human language and communicate
• Enabling the extraction of text from multiple data sources (structured, unstructured, and semi-structured)
• Better understanding of the user sentiment
• Easy implementation via chatbots
• Quick summarization of large amounts of data
• Seamless compatibility with voice assistants
• Extraction of specific entities with Named Entity Recognition (NER) is possible

Ethical AI

With NLP models accessing large amounts of data available, it raises security concerns about the storage and processing of personal data. This also led to Italy banning ChatGPT saying that the platform is processing the personal data of its citizens. Although the ban was removed soon, it forces us to determine whether AI models should follow an ethical code or not. This has also led to the formation of a new AI field known as ethical AI, which is set to gain a lot of popularity in the coming years.

The ethics of AI refer to a new field of ethics that revolves specifically around technology and platforms that are artificially intelligent. And, truth be told, it is needed especially because these platforms can exceed their limits. This field is also on the rise especially because the mass population is skeptical about the capabilities of AI.

AI As A Service

AI as a Service (AIaaS) refers to the process where businesses and individuals can outsource AI technologies. Traditionally, to create an AI model, companies had to set up an in-house team or outsource their team from the top AI development companies. Now, as more and more companies are offering their AI technologies and capabilities as services to allow other businesses to check the capabilities of the platform and experience the future, AIaaS is on the rise.

Some benefits of AIaaS that have contributed to its rising popularity include:-

• Ease of deployment
• Can be implemented with low-code or no-code
• Saves on costs
• Higher transparency
• Better scalability of models

AI Trend Predictions For Years After 2024

Our team has also made some predictions for the future of AI development and its popular trends that are set to boom after 2024. Although these will gain popularity in 2024, they have the potential to stay on the top even during the upcoming years.

Artificial General Intelligence

Artificial General Intelligence (or AGI) refers to the capability of machines to solve new problems that are unrecognized. This means that machines will have to utilize cognitive and problem-solving skills that are similar to humans. Although today’s platforms and models successfully incorporate intelligence, there is still a lot of way to go.

Quantum Computing

Another notable and advanced concept is quantum computing which refers to the type of computation that is based on quantum mechanics. Computers and platforms with quantum computing capabilities are used to solve problems that general-purpose computers cannot. Tech giants like IBM use Quantum computers to solve complex problems related to the exploration of electric vehicles, space, energy challenges, and more. Although Quantum Computing is a powerful technology, it still has several limitations that need to be addressed and solved.

Brain-Computer Interfaces

A brain-computer interface refers to a device or a platform that allows communication between humans and computers. Although this technology is relatively new and in its early developmental stages, it has the capability to revolutionize the way we communicate with technology.

Final Words

As we approach 2024, it is important for us to reevaluate our positions and better contribute to the future of AI development. After all, the tech industry is quite dynamic and it is wise to get ahead of your competitors rather than getting left behind.