04 Oct Which Cloud Service WorkS Best For Your AI Project!!
What are Cloud Services/Servicing?
Cloud servicing or services refers to the use of remotely provided services which are hosted by cloud computing service providers through the Internet. Cloud services serve as an alternative solution to organizations or individuals who would rather not cater for the costs of maintaining on premise infrastructure, while enjoying the benefits of cloud servicing which include, uninterrupted accessibility, seamless operations, and risk mitigation.
Only a few decades ago, most companies had their servers and equipment on premise, but they soon began to realize how cost inefficient it was owning and maintaining these equipment. First of all, the cost of procuring these equipment stood at extremely exorbitant prices, thereby causing strains on the budgetary allocations annually. This was an especially grim reality for most startups.
If/when they finally succeeded in procuring these equipment, these organizations would have to employ mostly specialized staff (creating new functional departments) to operate the new equipment and also foot the cost of maintenance. These problems associated with organizations purchasing, and maintaining their own servers, voice communication systems and internet facilities on their premises led to the intervention of cloud servicing.
With Cloud servicing, company owners no longer have to worry about the cost of procuring and maintaining servers; as the cloud services providers do all that already. All they need to do is to pay for the services (at a lot cheaper rate than they would have if they were to purchase the equipment themselves) and then have access to these services on demand. This presents a win-win scenario for both the service providers and users.
Artificial Intelligence refers to the branch of computer science that tries to mimic and incorporate the intelligence of humans into machines. Humans are the most intelligent beings alive, at least that we know of for now. The aim of artificial intelligence is to produce machines that can function intelligently and without supervision just like human beings do. The different fields of artificial intelligence aim at perfecting specific human functions. For example, the area of speech recognition tries to imitate the auditory communication, computer vision performs the same function of the human eye, robotics imitate human movement, etc.
Other fields of artificial intelligence include Deep learning, machine learning, pattern recognition, NLP, NN, image processing, etc. Artificial Intelligence came about as a result of computer scientists who felt that human intelligence “can be so precisely described that a machine can be made to simulate it”
Artificial Intelligence is beneficial for the following reasons:
- They make work easier, and can mitigate the difficult work which may be to tasking and boring for humans to do.
- It saves time and energy expended. It’s also important for time maximization as you get to do more work in a shorter time span.
- Machines don’t get tired like humans do. This means they can be used anytime and anyway, for long hours to achieve maximum output.
Like every other component of technological advancement, artificial intelligence has its own peculiar disadvantages:
- They are costly to acquire and maintain
- There is the constant fear of high grade artificial intelligence falling into the wrong hands, as the Kaizen nature of AI ensures continuous improvement which exhibits levels of intelligence that can be a threat to humanity.
- They contribute to increased unemployment rates because they can do the work of a lot of humans at a time and can be used to replace skilled personnel.
Cloud Services to employ for your AI project
Now that we fully understand what cloud services and artificial intelligence are, you may need information on the best cloud services available for your artificial intelligence projects. We have taken the time to outline and analyze these services for your benefit.
Generally, cloud computing services could be grouped into four categories. They are:
- Infrastructure as a service (IaaS)
- Platform as a Service (PaaS)
- Software as a Service( SaaS)
- Data as a Service (DaaS)
The best cloud services for your AI project include
- Oracle Cloud: The oracle corporation is a common name among tech-enthusiasts as a topnotch provider of quality cloud services. Oracle Cloud has the storage, servers, applications, and network, among others that you need to build your complete your AI project. Oracle Cloud provides convenient services in all cloud computing groups, such as, the oracle data cloud which is powered by the oracle ID graph to aid customer data analysis. As a result, if your AI projects are data oriented (DaaS), there’s no better cloud service for you than Oracle Cloud. This may be further iterated by Oracle’s ability to stitch together a number of stacks, providing an integrated stack for its users. This implies that AI project which may require such features are mostly better off with Oracle cloud.
Oracle Corporation works in collaboration with other leading tech companies like Microsoft, IBM, and SAP to provide the most convenient, easy to use software for your AI projects. Their applications include SaaS analysis, Supply Chain Management, Customer Experience and a host of other well-developed apps.
Oracle Cloud platform offers you the opportunity to manage your data, develop your own apps, engage in content collaboration and business analytics. They also provide one of the best storage, computing, and networking services worldwide.
- Amazon Web Services: The endearing factor thing with regards to Amazon Web Services is how easy they are to operate, even for beginners. If you are working on your AI project for the first time, you would most likely work best with Amazon Web Services. This is because they provide educational and instructional training and materials in a bid to ensure that you understand how best to utilize their services.
AWS also provides the best machine learning and deep learning facilities which enables you to build the best AI projects. It provides you with features that help you build your own functionalities to your taste and satisfaction, making AWS the best cloud service for the implementation of Web based projects (APIs)
- Google Cloud: Google Cloud is arguably the most popular cloud computing service provider out there, but it just doesn’t stop at being popular. Its features are second to none. Like Amazon services, it is also beginner-friendly and provides personalized packages for its users. It is also relatively cheap to use. Google Cloud is best known for its prowess in data analysis and management. Thus, AI projects which may require large dependencies on data analysis and management, may opt for google cloud. Google Cloud also provides features such as out of the box algorithms, and enterprise sharing capabilities in a bid to keep up communication with internal developers and users. Google cloud vision also comes as an additional feature on Google cloud, ensuring that projects which are based on facial recognition patterns thrive, especially if the project is based on Google cloud.
- Microsoft Azure: Microsoft is another well-known name in the tech industry. It represents one of the best when it comes to speech recognition and language analysis, facial recognition, handwriting and text analysis.
In addition to the aforementioned features of Azure, it is a cost effective solution for most AI projects with strict budgets. It also aids budgetary concerns with regards to risk mitigation based on issues such as security, and scalability. With Microsoft Azure, AI projects with smaller budgets and little room for error can thrive effectively. Finally, and most importantly, Azure allows a flexibility with regards to framework, languages and tools.
- IBM: IBM has engaged and completed a series of projects which are designed to help you build a standard AI infrastructure, an example would be, “summit,” which is widely acclaimed to be the fastest supercomputer in the world. Summit has features incorporated in it that helps you to build your own quality AI project. IBM also offers one of the best storage features for AI-based projects in this category, as well as a truly seamless accessibility standard. Also, with features such as as-a-service, IBM allows you to determine your level of control, and ensures that remote teams can collaborate more efficiently. IMB’s Watson for instance offers an entire image based search engine. With a major size of 10MB and pixel density of 32×32, IBM projects prospects for facial recognition based AI projects.
You can also feel free to explore and research about other cloud services and choose the one that is best suited for you. You should, however, follow these guidelines to ensure that you’re making the right choice concerning your proposed service provider.
- Check that your provider complies with all statutory and regulatory guidelines, and are not defaulting in any way. All topnotch service providers adhere strictly to industry rules and regulations. If a service provider defaults in complying with these standards, the chances are that the reason may be because they can’t provide you with the kind of services you need to facilitate your project.
- Check that your provider has an impeccable information security system. You can’t go around making use of providers that cannot ensure that your data is kept private and secure.
- If possible do a quick research on the projects that are running on your choice of cloud with enough proof. You don’t want to spend a lot of time to just make model work on the cloud and try to fix the API connection.
- Always read through the terms and services to ensure that relevant clauses for indemnity, intellectual rights protection, warranties, etc. are available to your satisfaction. Don’t settle if they don’t meet your expectations