Top 8 Latest Tech Trends You Must Know in 2024

In this article, we will discuss the 2024 tech trends that you must know would shake things up this year. This year is about embracing many different trends that involve the utilization of Artificial intelligence in various industries. Additionally, we will discuss how these AI advancements are now being used for practical purposes. Here they are:

1. MLOps: The Future of AI and Machine Learning
2. Working Out Spatial Computing
3. Advancements in Satellite Technology
4. Progress in Quantum Computing
5. Data Security through Intelligent Systems
6. Platform Engineering Model in Cloud
7. AI-Powered Development
8. Boom of GenAI

8. Boom of GenAI

This year, a significant surge in the usage of Artificial Intelligence, especially GenAI is anticipated in multiple industries. GenAI already sparked the world last year with ChatGPT and Stable Diffusion Image Generation AI, but this time there is more. We can expect to find more and more AI Enterprises coming up, engaging in more and more real-world GenAI activities. We can also expect the usage of AI in the medical industry, to tackle specific healthcare challenges.

As we move into 2024, we will find AI enterprise projects that will reach new levels of maturity we never imagined in their early phases. This might sound like all sunshine and rainbows, but there’s a kicker. As GenAI takes the spotlight, there going to be a bit of skill issues within the IT sector. Meaning, this boom is going to create a gap that screams for more specialized IT training within companies.

Brace yourself, the GenerativeAI dialogue will shift from theory to practice very soon.

7. AI-Powered Development

AI-powered development has been revolutionizing the software development industry for the past few months. You can expect new AI software that takes development productivity to a whole new level in the coming months. This innovation is going to help developers spend more time on bringing their ideas into the market, and spend less time on debugging tedious errors.

With AI-augmented tools, the role of developers and necessary skills are going to change drastically. These changes would require them to adapt and upskill to stay relevant to the development industries. But the good part is, that developers can now focus more on creative ideas and tasks. Meaning, we leave the mundane, robotic tasks to the AI tools.

Integrating AI into their work may bring certain challenges. Developers would now need to stay updated on the new technologies, constantly adapting it them and finding ways to use them to their advantage.

Software development is going to become more robust than ever, with streamlined workflows and increased productivity. Developers will now be able to build better products in no time. We have already seen similar AI-powered development software in use last year. It’s only going to get better this year.

6. Platform Engineering Model in the Cloud

In today’s dynamic work environment, we rely on cloud-hosted apps and software more than ever. Building a well-organized cloud team is crucial and cloud platform engineering creates the perfect environment to do it. Imagine all the different development teams with various development tools and services. Without clear rules and structure, there is only chaos you could get out of this.

Platform Engineering defines these clear structures and rules in workflows, making developments much more smooth and organized. Platform Engineering is all about creating an environment for developers of different teams to share their tools and collaborate in building awesome software and apps with no mess whatsoever.

This year, more companies will switch to the Platform Engineering model to provide the right infrastructure and management to build cloud platforms. The focus would be especially on deployment(CI/CD) and constructing a sustaining Internal Development Platform (IDP). In addition to this, platform teams are adopting new automated solutions powered by AI to solve cloud problems. Overall, cloud platforms will become more robust, building products with improved quality.

5. Data Security through Intelligent Systems

Cybersecurity has been growing important through recent years. The advancements in the field of AI and technology brings in new and unique security concerns that must be addressed proactively. The role of intelligent automated systems is to provide data security in supply chains.

This year, we will see notable improvements in terms of development and usage in intelligent systems to prevent cyber mishaps or attacks. From threat detection to predictive analytics, we will see these systems being used in protecting important data in the coming years.

As new machine learning solutions with enhanced diagnostic capabilities come up, the role of intelligent systems in handling cyber accidents becomes crucial. These automated solutions can offer wide-ranged detection and forecast potential threats on a large scale. These intelligent systems take in large amounts of data and efficiently handle them by detecting problems, enhancing the overall supply chain.

With intelligent systems evolving, human involvement would still be necessary to make it truly intelligent. The systems will be constantly judged and evaluated to guide their development and deployment.

Knowing how this data is consumed, stored, and processed can increase its efficiency. This is called Data Governance. These intelligent systems, when combined with robust data governance and ongoing human assessment would make an efficient system that detects cyber threats.

4. Progress in Quantum Computing

Quantum computing stands as a revolutionary technology that has transformed conventional computing to become extremely powerful, fast, and robust. Derived from our understanding of Quantum Science, these computers can solve heavy problems that would probably take an eternity for normal computers to solve.

This year, there will be advancements in the field, where we will take a software-based approach that works along with conventional systems to protect important/confidential data from future quantum attacks. This will be done by adopting something called the Post-Quantum Cryptographic (PQC), which will be adopted in browsers and operating systems. PQCs will also make an entry into tech companies and enterprises to ensure data security in the post-quantum world.

Another trend can be expected to grow in the next 4-5 years. Quantum networking is expected to allow users to collaborate and communicate in quantum computers for more scalable quantum solutions. The concepts of quantum entanglement and superpositions are now used in technology to make this possible. With great demands for data security in today’s world, quantum networking, along with quantum computing is expected to see exponential growth and investments in the next few years.

3. Advancements in Satellite Technology

The concept of phones connecting to satellite has been around for quite a while now, although we only use it for emergencies. This year, many companies are trying to implement this concept on a much wider scale. In the sense that you can communicate with people in other parts of the world by making phone calls or receiving text messages. This technology can be expected to be implemented in a few years, although companies like Apple, Amazon, and SpaceX are already on it, launching satellites into space.

Elon Musk’s Starlink was able to reach a crucial milestone by successfully launching 2 test satellites into space and establishing a stable high-speed data connection between them. Amazon aims to build its satellite-based broadband service in the coming years.

Earlier this month, SpaceX launched a rocket that carried Starlink’s first set of satellites. This project aimed to end “Dead Zones” once and forever all. Starting with text messages, the project will scale up to Voice and data services, available in the most remote areas.

Wireless service providers from all over the globe such as KDDI(Japan), Optus(Australia), and Rogers(Canada) will collaborate with SpaceX’s exciting project. With all these companies working hard on satellite projects, the satellite and communication industry would likely experience a significant evolution.

2. Working Out Spatial Computing

Spatial computing is an advanced human-computer interaction that seamlessly merges the digital and physical realities. Imagine you get rid of your keyboard and mouse, and use hand gestures and physical movements to manipulate digital content. One of the most famous technologies that uses spatial computing is Virtual Reality Headsets(VR).

Although this year might not be the year of boom for VR headsets, or anything related to spatial computing, we will see notable advancements in this field of technology in the coming years. Companies like Apple, Google, and Samsung are already working on it. Apple has announced the upcoming release of their new mixed-reality headset this very year.

The cost of these headsets is becoming increasingly affordable. Additionally this year, we will most likely get a glimpse of Apple Vision Pro and Meta Quest 3. Along with this, it won’t be too long before we find ourselves using smart glasses embedded with virtual assistants that use this very technology. The preliminary version of this technology is already out, with Hamann’s AI Pin and Meta’s Ray Ban Glasses

With companies working so hard to make spatial computing more economical and flawless, there is no doubt this technology is not too far in the future.

1. MLOps: The future of AI and Machine Learning

MLOps refers to the development and analysis method of building Machine learning models. Models usually produce predictions that do not stay the same, and sometimes it reduce drastically. Moreover, to stay relevant to the recent trends, models usually need to take in data now and then, along with training and analyzing the results. This is efficiently done by using Machine Learning Operations (MLOps). The purpose of MLOps is the provide the developers with core functions necessary to take their machine learning model to production with fast development, deployment, and scalability.

Implementing AI solutions has become much more easy and practical due to the use of MLOps. This is why, developers now try to use this to refine and deploy their models in their businesses. This year, due to the increasing popularity of Artificial Intelligence and Machine learning, the usage of this seamless technology has become more common than ever.