This month, IBM had a severance pay for the AI energy platform, which is currently used by over 40,000 users. This may not seem a lot, but because the failures of artificial intelligence exceed the number of AI's successes, it is important to look at companies that ensured successful AI implementation and IBM has been aggressively working and demonstrating artificial intelligence for several decades.
Currently, most artificial intelligence is launched in the cloud, with a small, but growing amount operating on the edge and a larger portion of moving to local. In the case of most of these implementations, the issue is that they are inefficiently hybrid, because this model was accepted according to the plan, not out of necessity. In other words, the hosting preferences of implementation caused decisions, not the needs of the company.
IBM wants to change this, providing a growing number of solutions that optimize artificial intelligence to operate in the most efficient, reliable and productive hybrid environment dictated by the company's needs, and not the limitations of any AI supplier.
AI hybrid problem
The problem we have at the moment is that most of the artificial intelligence is launched in the cloud, because there you can get the easiest access to the highest variety of AI models. The cloud is not the most economical, reliable or the highest place to run AI, because it is a remote service, not something that it has full control over. Because we are increasingly relying on artificial intelligence to run our companies, there is also a growing need to control the infrastructure on which AI instances operate, so that we know that they are safe, that our confidential and reserved information do not leak, and that we can better provide critical levels of services.
This does not mean that the cloud is bad. It has advantages, such as a common cost model, cloud data centers are usually able to better serve most weather events, and in the future most can be powered by nuclear. But today they are still harassed with enough unknown in terms of safety, exhibition, staff, power and delays that they are not ideal for efforts related to automatic decisions in real time.
For example, if artificial intelligence monitors and triggers operations, and the cloud decreases, it takes a chance for automated alleviation, because AI will fail with the service. If it was local or fully hybrid (with an emergency switching), he would be able to respond to a failure and limit the influence of end users.
Why choose Power IBM for AI
The advantage that Power has over x86 for artificial intelligence is that it is less used, so the number of potential attackers who understand the platform is reduced. This is a completely different architecture, which means that most of the existing malware may not work well if at all. It comes from IBM, which was much more oriented to safety and ethics than the companies that appeared after him.
That is why banks and many healthcare providers
Brave ibm. If security, reliability and availability are extremely high priorities, IBM is usually at the top of the biddorder list. According to the comprehensive focus of IBM on infrastructure and perfection, he was able to introduce some of the safest and most accurate platforms on the market, and remains one of the few companies that can still ensure mainframe solutions that still achieve ancestors in these three critical areas.
That is why it is sensible to look at IBM for artificial intelligence, taking into account its advantages and experience in this segment, and the ability to help in designing solutions that are less ad hoc and more adapted to the best use of hybrid requirements that surround them.
Wrapping
IBM will never be the cheapest, but considering artificial intelligence, focusing on the cheapest suppliers, many of which it is very difficult to understand, not to mention the implementation of artificial intelligence, it is best to focus, especially in the early years, on companies that are experts in subjects. Thanks to Power and Watsonx, IBM is one of the most experienced AI suppliers currently on the market, and he works very much with NVIDIA, thanks to which IBM is one of the better choices, looking for the implementation of hybrid artificial intelligence.
