In front of us lies a challenging and “cloudy” year. Artificial intelligence has been reshaping the course of technology and its advancement for years, as well as its usage worldwide. It seems that in 2024, all of this will be completely shocking. The word “shocking” can be interpreted positively or negatively. Some will welcome it, while those who may lose their jobs due to technological advancements may not take it very well.
The information that is important to people in the technology sector, according to Precedence Research, is that investments in computer infrastructure through the Cloud will exceed 1 trillion dollars by 2028. That’s why we said that the year 2024 will be ‘cloudy,’ or better said, dominated by the ‘cloud’.
Why?
Because artificial intelligence has opened up a range of new platforms and services, which bring time savings, cost reduction, resource optimization, and migration to the cloud.
Again the question arises, why? Haven’t we saved enough time and achieved enough success?
In the business world, numbers have no end. There is always a striving to surpass the number from the previous year. If it weren’t for this, technology wouldn’t have advanced so much. That never ends is what led us to artificial technology, cloud computing, and a host of other life-improving technologies.
So, saving time, money, resources, and storing large amounts of data are necessary for innovation and success.
We started this topic with the mentioned tools that facilitate business operations and simplify everyday life, but they also carry additional risks such as compromised security and data protection.
Where do organizations store their data?
According to Explodingtopics.com (include hyperlink
https://explodingtopics.com/blog/corporate-cloud-data):
- Approximately 60% of corporate data is stored in the cloud.
- The amount of corporate data stored in the cloud has at least doubled since 2015.
- More than 50% of companies store business records in public cloud.
- 89% of companies use multi-cloud access.
Probably after the year 2024, we will be able to state that every organization is working with the cloud, and it’s no wonder because it facilitates mass storage, backup and data recovery, data security, unlimited services, and software solutions.
Google, Microsoft, IBM, Amazon, and many other globally service-oriented platforms are actively working on implementing new cloud trends to provide users with more economical and streamlined experiences.
Let’s start with these trends:
- AI and ML
- Multi and Hybrid Cloud Deployment
- Blockchain
- Game Cloud Computing
- Automation
AI and ML
Many users still haven’t learned everything about artificial intelligence and its abbreviation AI, and now the abbreviation ML is also emerging. Do we even know the difference and meaning of these two terms? What is artificial intelligence or AI, and what is machine learning or ML? How are AI and ML connected?
Google says that “artificial intelligence is a broad field that refers to the use of technologies to build machines and computers that have the ability to mimic cognitive functions associated with human intelligence, such as the ability to see, understand, and respond to speech or written language, analyze data, provide recommendations, and more.”
And for machine learning, Google says that it is “a subset of artificial intelligence that automatically enables a machine or system to learn and improve from experience. Instead of explicit programming, machine learning uses algorithms to analyze large amounts of data, learns from it, and then makes informed decisions.”
AI and ML, although closely related, are not the same thing. AI is a broader concept enabling a machine or system to perceive, think, act, or adapt like a human. ML is an application of AI that allows machines to extract knowledge from data and learn autonomously from it.
So, artificial intelligence mimics human intelligence, whereas machine learning cannot because its goal is to teach a specific machine how to perform a specific task and provide accurate results by identifying patterns.
To simplify even further.
Let’s say you ask a device, “How long does it take to travel from New York to Chicago today?” – This means that you’ve posed the question to a machine which gives you an answer, likely approximate but mostly accurate. The device has successfully completed the task, and you didn’t need to further investigate through other search engines. It identified a pattern and provided the requested data. He cannot go beyond the framework that has been set for him and provide more information.
In contrast to machine technology, we have artificial intelligence that works with all types of data, mimicking human intelligence to solve problems, whether structured, semi-structured, or unstructured. In doing so, it utilizes logic and decision trees for learning, reasoning, and self-correction.
Thus, when inquiring about “How long does it take to travel from New York to Chicago?” today, you might receive a response like this through CHATgpt, representing a form of artificial intelligence:
“The journey from New York to Chicago today typically takes about 1 hour and 45 minutes by plane, around 19-20 hours by car, or about 20 hours by train. The exact travel time may vary depending on many factors, including mode of transportation, road conditions, or weather conditions. If you need precise information about current travel time, I recommend using tools such as Google Maps or similar applications that can provide real-time travel information.”
From this, you can conclude that it involves the exchange of a large amount of data, because imagine how many queries related to CHATgpt arrive today alone, and these technologies are economical but require high computational power and storage for data collection and training.
That’s why the cloud is an ideal solution for this.
The Geeks for Geeks page (hyperlink: [Geeks for Geeks](https://www.geeksforgeeks.org/cloudcomputing-trends/)) states:
“The main trends that will develop in this sector in the coming years are self-automation, self-learning, personalized cloud, high data security, and privacy. Many cloud service providers like Amazon, Google, IBM, etc. are investing heavily in artificial intelligence and machine learning. Amazon’s AWS DeepLens camera and Google Lens are two examples of their machine learning based products.”
You can learn more about AI and ML in the following video: https://www.youtube.com/watch?v=J4Qsr93L1qs
Hybrid And Multi-Cloud
We’re returning to the main premise of every trend or innovation, which is reducing costs and increasing flexibility in business while aiming for security and space for today’s complexity in data management and their integration with legacy systems.
Organizations are finding ways to store data or applications, and one such way is Hybrid and Multi-Cloud. However, there’s one key difference between hybrid and multi-cloud environments. Hybrid Cloud is related to a private form, while Multi-cloud is related to public cloud services, and they may or may not involve a private cloud component. In a multi-cloud environment, an enterprise uses multiple public cloud services, usually from different cloud service providers.
Example of Multi-Cloud: An organization may host its web application on AWS and host its Exchange servers on Microsoft Azure. Enterprises use AWS for data storage, Google Cloud Platform for development and testing, and Microsoft Azure for disaster recovery. By using MultiCloud, organizations provide better IT service and try to avoid dependency on a single cloud service provider, while also giving them the opportunity to choose the one that offers the lowest price at a given time.
The difference is that it’s more difficult to implement security for the public cloud form compared to the hybrid cloud.
According to a Flexera survey, 74% of enterprises have a multi-cloud strategy.
Eviden, predicts that in 2024, the expected growth of multi-cloud and distributed cloud services amongst cloud customers would be ~40%. Further they expect a growth of up to 20% with sovereign cloud solutions.
You can learn more about Hybrid and Multi-Cloud in the following video: https://www.youtube.com/watch?v=qkj5W98Xdvw
Blockchain
If you can imagine a massive knot of a computer network and a vast distribution of databases, then you’re talking about Blockchain technology, most famously known for cryptocurrency systems. It consists of a growing list of records, called blocks, which are cryptographically linked.
The advantage is that there is no centralized transaction record, but the transaction transfer is secure and unrestricted. It’s harder to hack decentralized data compared to traditional data storage in one location. Bitcoin entered the market in 2009, making a grand entrance as the first and most well-known cryptocurrency, after which the technology and use of Blockchain exploded.
Later, applications for decentralized finance (DeFi) and non-fungible tokens (NFTs) emerged.
As Blockchain is a much more secure system for storing and collecting data, its applications in the cloud are linked to the Cloud of Things (CoT), i.e., the interconnectedness of physical devices and objects with the internet. This includes everything from connected cars and wearable devices to industrial equipment and household appliances.
It’s predicted that CoT will have the ability to generate a huge amount of data ready for storage, processing, and analysis. Many industries leveraging the benefits of CoT will use it for asset tracking or inventory management. Statista predicts that the number of IoT devices worldwide will reach 29 billion by 2030.
Certainly, the use of blockchain in cloud computing can help companies better manage this data and ensure its security. The cloud can store significant data reserves, confirming the importance of CoT.
You can learn more about Blockchain in the following video: https://www.youtube.com/watch?
v=yubzJw0uiE4
Cloud Gaming
The method of playing video games located on remote servers is actually Cloud Gaming, i.e., video games are no longer run locally on gaming devices (PC, console, mobile phone, etc.), but rather, the games are run on a remote server in the cloud. Essentially, the user streams the video game on their device via the Internet.
Data from the Global Cloud Gaming Market Cap Forecast indicate that around 21.7 million subscribed users spent approximately $1.5 billion on cloud gaming in 2021, and in 2024, it is predicted that the number of subscribed users will exceed 50 million, with their spending reaching 6 billion.
The gaming industry is experiencing rapid and accelerated growth, as the chip shortage has redirected the market towards console production. Exploding Topics website (hyperlink https://explodingtopics.com/blog/cloud-computing-trends) states that Samsung and LG have announced support for Google Stadia (Google’s cloud gaming platform) on their smart TVs.
Furthermore, another piece of data tells us that cloud gaming is the future, as Amazon Web Service Inc. invested $35 billion between 2011-2020 in a data center in Virginia, which enables seamless gaming with low-latency experiences.
For more simplified information on Cloud Gaming, you can watch the following video:
https://www.youtube.com/watch?v=MdnoW1ylP_4
Automation
If we go back to the beginning and remember artificial intelligence, hybrid and multi-clouds, then the logical sequence for us is cloud automation. Reducing manual efforts is crucial for accelerating business processes and reducing operating costs. Automation offers workload management without burden. This can be connected to the services provided by an Apple phone. Every photo you take, if the option for file transfer to iCloud is enabled, will be automatically captured and stored. Similarly, organizations can notice cloud automation whether it’s in a hybrid or multi-cloud environment.
What the automation process eliminates is inefficiency and errors that can occur during manual processes and interventions, but there is no universal automation tool. It’s always a set of different tools and platforms used for automating one or more tasks.
Examples of automation services provided by the public Multi-Cloud:
– AWS Config, AWS CloudFormation, AWS EC2 Systems Manager;
– Microsoft Azure Resource Manager, Azure Automation;
– Google Cloud Composer, Cloud Deployment Manager; and
– IBM Cloud Orchestrator.
You can learn more about Automation in the following video: https://www.youtube.com/watch?
v=gO5ItcaIUrY
The list of trends and the battle for data storage methods in 2024 is extensive; according to Gartner from 2022, 40% of organizations in developed countries are evaluating and planning Cloud strategies. Among companies with more than 2,500 employees, half are planning or evaluating Cloud strategies, as well as 41% of those with 1,000 to 2,500 employees.
In the end, we are left to follow these trends because it will be interesting to see how companies will reconcile the need to increase cloud usage with the need to optimize cloud costs.
According to Eviden conclusion, about Cloud Technology Trends and Predictions for 2024, cloud technology will continue to evolve and shape the future of cloud computing, driving innovation, efficiency, and business value for organizations across the globe.