Our artificial intelligence omnibus brings together all of the valuable, informational content we have published on the topic. Read on.
Interest and research into Artificial Intelligence (AI) are rising, with significant breakthroughs such as new categories happening all the time.
Over the years, we have published a lot of content on AI and related topics. This omnibus aims to bring you all of those valuable, informational content together so that you can access it all from a one-stop solution. Each section is linked to a detailed blog where you can find more information about the said topic. Here's what you need to know about artificial intelligence. Let's start from the basics.
Artificial Intelligence and Cloud Computing
If both cloud computing and artificial intelligence are optimizing and bracing for rapid growth then it is evident that they are more compatible than originally expected. The power of the cloud has played an important role in advancing artificial intelligence and machine learning within the modern landscape of technology. Artificial intelligence needs the power of cloud computing. It gives businesses the power to access data sets that would otherwise be impossible without the power of the cloud. It also helps businesses scale up or down depending on the unique needs of a business. This works to help artificial intelligence seamlessly integrate into workflows where it could not be done.
As mentioned, Artificial intelligence and cloud technology work in a mutually beneficial manner – AI systems power cloud, and cloud works as an engine increasing the scope and market of AI. More and more businesses and organizations, both big and small, are adopting both technologies to amplify their growth. Overall, we see that cloud computing is democratizing the tech landscape for small and medium organizations to benefit from high-grade technologies such as AI. Now let us take a look at some of the said benefits.
- More efficiency with SaaS-AI integration
- Self-managing clouds
- Enhancing data management capabilities
AI Infrastructure Market: Upcoming Trends
“Artificial Intelligence is the new electricity,” said the famous computer scientist Andrew Ng. As with electricity in the past century, AI is revolutionizing the way we live and the world we live in. The major growth drivers of the AI Infrastructure Market are:
- The growth in networking infrastructure
- Many organizations experienced in the AI industry are broadening their infrastructure and related requirements
- Many countries around the world and their governments are now heavily investing in AI ecosystems.
- Automation is happening in many end-user industries. In terms of upcoming trends, businesses and organizations are recognizing the importance and convenience of having AI-powered systems in their daily operations. Automation improves efficiency and cuts costs and resources in most cases. An example of this would be AI-powered chatbots interacting with customers in real-time and solving the most common problems. Another key trend is that AI Infrastructure powered solutions are constantly demanding the latest hardware & software integration. This trend almost goes without saying, but AI Infrastructure is very much necessary for innovation, research, & development. The next key trend in the AI Infrastructure is creating a suitable infrastructure for AI development. Furthermore, AI Infrastructure in Europe is projected to witness significant growth in the next five years.
AI in Finance
Financial institutions such as banks are now on a path of digital transformation, even though some of the core systems in the more established enterprises are still on traditional systems. The implementation of ML and AI in finance has three immediate results to show – reduce human intervention in operations, improve security, and foster more resources for innovations. Furthermore, here are some of the use cases and applications that exist currently and are on a growth trajectory.
- Automation in documentation
- Risk assessment and management
- Customer assistance
Preparing Data Centers for AI
The specific demands of artificial intelligence, machine learning, and deep learning applications test data center performance, dependability, and scalability. It is even more challenging as engineers imitate the design of public clouds to simplify the shift to hybrid cloud and on-premise deployments. Data centers need to evolve to cater to workloads associated with AI.
Let's take a look at some of the best practices that will prepare a data center for heavy workloads from AI, ML, and DL:
- Map out scalability plans
- Clustering GPUs
- Identify bottlenecks
- Parallel file systems
4 Artificial Intelligence Categories to Discover
Interest and research into Artificial Intelligence (AI) are rising, with significant breakthroughs such as new categories happening all the time. We are yet to see the point when AI transforms to superintelligence though. In this context, here is a look at the four main types of AI.
- Limited memory machines
- Reactive AI
- Theory of mind
- Self-aware AI
Since artificial intelligence is such a huge topic, there are even more ways of classification. Here are three more types of AI to learn about.
- Weak AI
- General AI
- Strong AI
Difference between AI, Machine Learning and Deep Learning
Artificial intelligence, machine learning, and deep learning have often been used interchangeably even though this could not be further from the truth. Although they do go together they are not the same. To better understand Deep Learning and Machine Learning we need to start at the beginning.
AI, also known as machine intelligence, gives machines the ability to think like humans. It is able to study the various ways in which programs and machines solve problems and learns to replicate this behavior. This machine-based intelligence is remarkable because it typically displays processes that are usually akin to human intelligence.
ML is a subset of AI that focuses on helping machine systems learn and improve through machines. It makes those machines become better at a specific task without explicit programming. Although it is not identical to AI, it is an important part of a wider ecosystem surrounding it.
DL, also known as deep neural learning, is a further subset of artificial intelligence and machine learning. It takes advantage of artificial neural networks in a way that is very similar to the human neural system.
VEXXHOST Cloud Solutions
AI is a highly beneficial tool for users with specific requirements and is growing rapidly. At VEXXHOST, we provide close to limitless possibilities in creating and managing cloud environments, with three foundational components of infrastructure – bare metal, virtual machines, and Kubernetes.
As a reputed IaaS provider, we ensure that our clients get the best type of cloud storage services for their data. Our storage services include all the styles – object storage, block storage, and file storage, using an open source platform, removing vendor-lock-ins. At VEXXHOST, we provide cloud solutions for a multitude of clients worldwide. We provide OpenStack-based clouds, including public clouds and dedicated and highly secure private cloud environments, ensuring utmost security and agility.
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