Top AI Trends in 2024

Top AI Trends in 2024

We have seen the significant advancements of Generative AI in every field of life, in 2023. Millions of people started utilizing AI tools like ChatGPT, Bard, Copilot, and many more. We are expecting AI to become more accessible and more advancements in AI technologies in 2024. Although With these advancements, we are looking at some major AI trends of AI in 2024. In this article, we will highlight some major AI Trends that researchers are expecting to be Top AI trends in 2024.

The Rise of Small Language Models (SLMs):

Most of the AI models developed in 2023 are of Large language models (LLMs) like Copilot. These models have shown their remarkable power in answering complex questions. However, because of their extensive size, LLM models often demand bigger computing resources. This issue generated the need for small language models (SLMs), which can run offline on a phone.

What are Small Language Models (SLMs)?

SLMs are smaller versions of the existing popular Large Language Models (LLMs). Large language models, like OpenAI’s GPT-3, and Google’s Gemini can have hundreds of billions of parameters. For such billions of parameters, LLMs require substantial computational resources for training and conclusions.

Small Language Models (SLMs) have significantly fewer parameters, typically ranging from a few million to a few billion. The AI experts are expecting SLMs to remain in the top AI trends in 2024. A short overview of the advantages of smaller size of LLMs is specified below.

Advantages of SLMs: Efficiency, Speed, Trainability, Interpretability, and Privacy

  • Efficiency: SLMs require less computational power and memory, which makes them suitable for deployment on smaller devices or edge computing. On-device chatbots and personalized mobile assistants are some of the best examples of SLMs.
  • Faster Inference: Due to their smaller size, SLMs can offer quicker response times, which is crucial for real-time applications.
  • Trainability: SLMs can be trained with relatively small datasets. This makes SLMs more accessible for various tasks.
  • Interpretability: Their simplified architectures make Small Language Models easier to understand and analyze.
  • Privacy: SLMs can process data locally, which makes SLMs valuable for situations where privacy and security are more important. Internet of Things (IoT) devices are working with SLMs.

Microsoft developed two new models Phi and Orca with SLMs, which perform at par or even better than LLMs in certain areas. It is a big achievement to get better performance while using fewer computational resources. The ongoing progress in SLMs is expecting more research and innovation.

Multimodal AI: Understanding Text, Image, Audio, and Video.

In general, most LLM models are processing text data, which means the majority of LLMs are trained on text data. However, multimodal models are taking the place of previous models, which can understand the information from text, images, audio, and video. With this capability, multimodal models can give more accurate responses on search engines, app creation, and many more. We are expecting multimodal as in the top AI trends in 2024.

What is Multimodal AI? Understanding Text, Images, Audio, and Video

Multimodal AI can understand, interpret, and generate information across multiple types of input and output data. It can understand texts, images, audio, and videos and can give output in these forms. The object of multimodal AI introduction is to handle multiple information similar to humans.

For example, a multimodal AI can analyze a news article (text), accompanying photos (images), and the reporter’s narration (audio) to understand the story comprehensively. Similarly, it can assist in healthcare by understanding the patient’s verbal descriptions of symptoms (audio), written medical records (text), and diagnostic images (visual) to provide a more accurate diagnosis.

Benefits of Multimodal AI:

1. Multiple Data Understanding: Multimodal models can understand things in-depth and accurately by combining information from various forms like written, visual, and audio.

2. Improved Interaction: Multimodal AI can interact with users in more natural and understandable ways. Such as through voice commands, gestures, and visual cues.

3. Enhanced Learning: Multimodal AI systems can learn from various data sources, which improves their performance and adaptability over time.

4. Greater Flexibility: Multimodal AI can be applied to a broad range of applications. Such as we can apply it to autonomous vehicles, smart homes, education, entertainment, and many more.

Microsoft’s Multimodal AI developments: Copilot and Designer

Microsoft Corporation is seriously working on the development of Multimodal AI systems. For example, Copilot is upgraded with multimodal AI and now it can understand your uploaded images. Copilot can process text, images, and data from Bing searches. For instance, if you upload a photo of a historical place, Copilot can give you useful information about its historical significance.

Microsoft Designer is also using multimodal AI to create images. You can describe what you want, and it will generate an image to match your description.

With these capabilities, multimodals are expected to remain in the Top 2024 AI trends.

Artificial Intelligence (AI) is emerging rapidly in various scientific fields in 2024. AI is affecting various fields of science, including biology, chemistry, physics, and environmental science. Summarizing AI is changing the science now in all niches. Here are some key areas where AI is making significant contributions to science:

AI’s Impact on Various Scientific Fields:

1. Drug Discovery and Development

AI algorithms can analyze large amounts of chemical and biological data to predict how different chemicals behave. This can help us to identify new drugs and reduce the time and cost of drug development. Machine learning models are helping us to understand disease and find potential medicines for curing.

2. Genomics and Genetics

AI is used in genomics to analyze genetic sequences. This helps us to identify genetic variations that may be linked to specific diseases. With AI’s help, we can develop personalized medicine, where treatments are customized to an individual’s genetic nature.

3. Climate Sciences

AI models are used to study climate data, predict climate change, and estimate the effects of various factors on global warming. These models can get vast amounts of data from satellite images, sensors, and historical records for giving output. It helps us to improve weather forecasts, monitor environmental changes, and inform policy decisions relating to climate change.

4. Astronomy and Space Exploration

Scientists use AI to study data, received from telescopes and space missions. AI helps them discover new bodies, understand the universe, and find possible signs of life on other planets. Machine learning algorithms can sort data to identify patterns and anomalies that might be difficult for humans to see.

5. Material Science

In material science, AI helps us to discover and design new materials with the required properties. With the help of AI scientists are developing stronger and more durable materials for use in construction and manufacturing.

6. Environmental Conservation

Scientists are using AI technologies to protect wildlife and the environment. AI can process images captured from camera traps, drones, and satellites to monitor wildlife populations and changes in their habits.

7. Physics and Chemistry

AI-powered models help us understand the basics of physical and chemical processes. In physics, AI can be used to study particles at the quantum level or analyze galaxies’ motion. In the field of chemistry, AI is used to predict chemical reactions, understand molecular structures, and design new catalysts.

1. Drug Discovery and Development:

Microsoft Research Asia is working on predicting protein-protein interactions, which is an essential step in discovering drugs. Microsoft Azure Machine Learning provides a cloud-based platform for researchers to build, train, and deploy AI models.

2. Genomics and Genetics:

Microsoft Genomics AI team is analyzing large-scale genomic datasets to understand complex diseases and identify potential drug targets.

3. Climate Science:

Microsoft Planetary Computer is helping researchers to access and analyze massive datasets related to climate change. Microsoft’s AI for Earth program is supporting researchers who are using AI to study climate challenges.

4. Astronomy and Space Exploration:

Microsoft is collaborating with NASA to analyze data from telescopes and space missions by utilizing Azure Machine learning. This helps in studying celestial objects and searching for exoplanets.

5. Material Science:

Project Bonsai is developing AI systems that can help in designing new materials.

6. Environmental Conservation:

Microsoft’s AI for Sustainability program is developing AI algorithms to track carbon emissions, optimize renewable energy, and manage energy usage.

7. Physics and Chemistry:

Microsoft Quantum is developing quantum computing hardware and software to explore and solve problems in various scientific fields.

AI is expanding the canvas of scientific knowledge, but many challenges like the quality, availability of data, and the ability to explain models are there. Future developments in AI will focus on creating trouble-free systems to help in scientific research. Looking into the top trends of AI in 2024, we expect a lot of advancements in this field.

Keep up with the latest trends and innovations in technology with Vistech and SynerEdge Solutions LLC! We are here to help you stay informed about the newest advancements, like the AI trends in 2024. With Vistech and SynerEdge Solutions, you don’t have to worry about keeping up with the fast-paced tech world. Instead, it becomes an exciting journey of learning and feeling empowered.

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Nadeem Saleh
By Nadeem Saleh

I am the founder and CEO of Syneredge Solutions LLC, a multidisciplinary services-providing company in the IT sector. I am a dynamic executive with over three decades of professional management experience and a proven track record of serving in the industrial sector in Pakistan. As the CEO of SynerEdge Solutions, I’ve witnessed firsthand the challenges professionals face in keeping pace with the rapid advancements in technology. From groundbreaking inventions to the latest software updates, staying informed can feel like a full-time job. Vistech was born from this very need – to create a curated space where professionals can easily access and digest valuable tech knowledge.

7 responses to “Top AI Trends in 2024”

  1. Abdullah says:

    Very informative article

  2. Verdah says:

    Highly informative! Well-written! 👏

  3. Cathy says:

    Well written article

  4. Zahid says:

    Informative and good knowledge sharing..

  5. Amjad says:

    Good content.

  6. Zainab says:

    Such an informative read, thank you!

  7. John says:

    Very informative

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