Machine Learning, AI, and All-Flash Arrays: Leave Performance Tuning in the Past!

Whether you realize it or not, we’re exposed to artificial intelligence and machine-based learning every day. The virtual assistants on our smartphones, the smart speaker in your living room, your social media account, and even your favorite TV-streaming platform all use artificial intelligence and machine learning for optimum performance and personalized user experiences.

Machine Learning, AI, and All-Flash Arrays: Leave Performance Tuning in the Past!

September 30, 2020

Whether you realize it or not, we’re exposed to artificial intelligence and machine-based learning every day. The virtual assistants on our smartphones, the smart speaker in your living room, your social media account, and even your favorite TV-streaming platform all use artificial intelligence and machine learning for optimum performance and personalized user experiences.

The use of this kind of technology is experiencing a period of exponential growth. Artificial intelligence is expected to grow from a $1.4 billion industry in 2016 to a $59.8 billion industry by 2025.

The reason for this dramatic increase in the adoption of artificial intelligence and machine learning is the partnership of this technology with the power of big data analytics. Artificial intelligence is seemingly inseparable from its pairing with big data. But all this data has to go somewhere, and with outdated infrastructure, this can weigh your entire system down.

...Unless you have an all-flash array. Let’s learn more about how machine-based learning, artificial intelligence, and all-flash arrays make for a perfect trio.

How Machine Learning, AI, and All-Flash Arrays Work Together

Machine learning and artificial intelligence (AI) are two terms that tend to be used interchangeably, but they do serve different purposes, and both get the support of better performance by running from an all-flash system. We hear about machine learning and AI when it comes to big data analytics, which is a phenomenon that is sweeping the business world with all the possibilities that it opens up, but both machine learning and AI have applications that extend to virtually every industry.

Artificial Intelligence

Artificial intelligence is a broad idea of machines carrying out tasks “smartly.” It refers to a whole umbrella of technology that includes machine learning, deep learning, and other ways to enable technology to work for us. Besides machine learning, AI extends to all kinds of uses and applications that make our lives easier:

  • Process automation
  • Sales and business forecasting
  • Recommendations and content curation
  • Customer segmentation
  • Product recommendations
  • Spam filters
  • Smart email categorization

Machine Learning

Machine learning is one application of AI. It’s based on the concept of giving information and data to machines (technology) and letting the machines process it on their own and learn for themselves. There are countless examples of machine learning, and it has been used for all kinds of things, including medical diagnoses, music creation, and information-based decision-making in the financial sector. Some credit card companies use machine learning for fraud detection, and Google has even created a machine that can mimic human thoughts.

All-Flash Arrays

All-flash systems refer to high-speed storage technology. They’re electronically programmable, easily scalable, and they process requests quickly. All-flash arrays are also rewritable, which makes it ideal for data that changes frequently, which can happen with machine learning and AI. All-flash arrays support the high-performance needs of AI and machine learning with lightning-fast responses by writing data and completing input and output requests in record time.

How All-Flash Arrays Enable AI and Machine Learning

As you can imagine, artificial intelligence and machine learning consume an incredible amount of data and need a system that can process it all and keep up. Data sets have grown considerably since the widespread adoption of AI and machine learning. In fact, 90 percent of data to ever be created has been created in the last two years alone, and as a society, we create 2.5 quintillion bytes of data each daily.

The problem is that all of this data needs to go someplace. Because there is so much data to handle, traditional methods of storage aren’t quite the right fit. For some time, the only solution was performance tuning, which refers to the improvement of how well your system performs. As the system holds more and more data and takes on an increased load, the system’s performance decreases. To offset this issue systems had to be continually modified to handle a higher load. This is known as performance tuning.

Performance tuning involves optimizing and homogenizing the design of database files and organizing into indexes in the database’s environment. But this requires time-intensive managing from IT workers who can fully optimize the system. It’s labor-intensive, and only moderately helpful, as it needs to be done regularly. It’s a stop-gap solution, not a permanent fix.

On the other hand, all-flash arrays can accurately predict future capacity and performance needs. This means your database will optimize your virtual memory placement on its own, for autonomous management and better performance with little or no performance tuning.

Do You Need an All-Flash System for Machine Learning or AI?

Can you manage machine learning and AI programs within your enterprise without an all-flash system? Flash really enables you to do all the things that you want to accomplish with AI and machine learning; it’s the best solution on the market to handle your data needs.

How does this happen? Flash has high availability, low latency, and high throughput, which makes it the most optimum solution for running AI and machine learning. Disk arrays have latencies somewhere around tens of milliseconds. But all-flash arrays are considerably faster. Their latency is only tens of microseconds, which makes it about one thousand times faster.

With an all-flash system, you don’t have the limits you find in outdated architecture that can slow down your processing speeds. Sending large amounts of data through older architecture like a SAS interface creates a bottleneck. But with an all-flash array, you free up the bottleneck, and gain access to the maximum performance for machine learning and AI.

Flash arrays can also be packed together much more densely than rotating drives, which means that you can have up to an entire petabyte of storage in just a single rack-mount enclosure. Also, flash consumes less power, which means that when you are operating on a large scale, you’ll notice a considerable decline in the cost of powering your system.

If you’re just dipping your toe into the machine learning and AI pool, or if you’re looking to maximize the performance of your existing system, the best way to do so is with an all-flash array.

Ready to unleash the power of artificial intelligence and machine learning with an all-flash system? Palmiq can make it happen for you with first-rate all-flash storage technology at a wildly affordable price, and we’ll give you the best system to handle machine learning and artificial intelligence to take your system to the next level

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