The global artificial intelligence (AI) market is primed for accelerated growth at least through 2030, driven by fierce demand in nearly every major vertical, from automotive and manufacturing to healthcare, finance and retail. The world has caught on that smart, well-designed AI solutions offer tremendous value with huge benefits for companies, customers, communities and individuals alike.
But, implementing an effective AI solution can be a complex endeavor, involving a myriad of hardware and software technologies – all of which must interoperate effectively to realize value and speed time to actionable insights. And even beyond meeting your AI goals, the budget requirements of your solution will also have a significant cost impact on capital expenditures and operational expenditures (CapEx and OpEx).
The journey to a solution can be much like solving a mathematical equation:
- Cataloguing each problem element according to its domain.
- Expressing their relationships as a kind of formula.
- Applying the formula to the data to arrive at the most elegant solution.
- Validating the result with repeatable proofs.
For customers who wish to unlock a higher level of AI performance and value, Presidio offers a uniquely holistic approach that simplifies the process of optimization while leveraging the benefits of software and tools for AI from our principal technology ally, Intel . Presidio’s machine learning (ML) and (DL) engineers are highly experienced in using those tools to select the best devices for each unique problem, helping to achieve improved business outcomes.
Assembling the elements of an effective AI solution
Whether your solution incorporates AI, ML or DL, the process begins with defining the problem: what insights are you trying to acquire, and how will you apply them? With a deep understanding of the mission, developing an effective AI solution involves assembling hardware elements that work together most efficiently – including processors, GPUs, accelerators, edge devices and more – along with the right architecture and software.
Changing a single element can introduce a rippling effect that impacts total performance – and the key to success lies in understanding which variables will have the desired impact. For example, some architects might focus solely on performance metrics – like choosing the most powerful processor – without taking into account the trade-offs between speed and cost. Or, they might not appreciate how the right acceleration solution can achieve the desired result with fewer servers and less expensive processors. And even with the right configuration of devices, pairing it with the wrong software can impact performance by as much as 10 percent.
It comes down to the fine art of optimization: coaxing your desired level of performance, value, time to insight, and cost management from the ideal AI solution, with every element working together seamlessly, operating at reduced heating and cooling requirements, and satisfying CapEx and OpEx concerns.
Here’s where Presidio’s holistic approach comes into play.
Deriving the most value from Intel® software and tools for AI
The overarching goal of any AI/ML/DL solution is to achieve the greatest problem-solving efficiency. While some organizations might try to achieve the same goal by throwing more human resources at the problem, Presidio believes that a better approach is to equip fewer people with the best tools from the very start.
Intel shares our “simpler is better” approach of minimizing the number of devices required for AI while increasing their efficiency and lowering costs through the use of Intel software and tools for AI. Two of the principal offerings Intel brings to bear for AI operations include:
- Intel® oneAPI tookits, an assortment of mission-specific tools and libraries that enable developers to be productive across multiple hardware architectures, writing code once and eliminating the need to write to each hardware vendor’s APIs. For developers using frameworks, oneAPI enables them to keep their focus further up the software stack without worrying about the underlying technology – concentrating on the data science, not devices.
Following open industry standards, oneAPI powers common frameworks such as TensorFlow, scikit-learn, PyTorch, Modin and others, transparently surfacing device performance up to the framework level. Although a few extra modifications are required to enable Intel optimizations; Presidio can help with those steps so you can easily derive the most value from the technology.
Based on DPC++, oneAPI is compatible with the most widely used languages and programming models, including C++, Python, SYCL and OpenMP. And, because it’s open source, oneAPI provides a safe, clear path to future devices.
- Intel® Distribution of OpenVINO™ toolkit, designed to translate, re-target and optimize primarily deep learning models trained on one architecture for inferencing on a different device type, helping to accelerate the development of machine learning solutions. Based on convolutional neural networks (CNNs), this toolkit shares workloads across Intel® architecture-based hardware, including accelerators, to maximize performance.
For example, training might take place on an array of GPUs or powerful Intel® Xeon® processors, but the edge device or similar system it’s deployed to run on can be very different; this is the tool that helps translate the model to run on different devices while eliminating the need for developers to program those devices at a low level. OpenVINO can also help achieve full device utilization: a device equipped with both CPU and GPU can be trained to leverage both devices simultaneously for increased throughput.
These are two examples of Intel® technologies from a much larger AI portfolio that Presidio employs to eliminate complexity and speed development for its customers.
Presidio simplifies AI to unlock performance and value
AI done right involves a host of variables that must work together optimally, but identifying that solution can often seem daunting – and that’s where Presidio’s knowledge and holistic approach can help. While some advisors specialize in a single element, such as writing script, Presidio is highly experienced at every stage of development with diversified expertise in AI, ML and DL.
Presidio’s process begins with an in-depth Q&A cycle to identify the precise AI problem to be solved, followed by a detailed assessment of the technology requirements to get there – considering everything from processing and acceleration to cloud instances. At the development phase we apply our experience with Intel’s AI software and tools, including oneAPI, OpenVINO and more to each unique solution. Presidio then creates a model to determine the best solution, applying the formula to confirm that it achieves the customers stated goals.
Case in point: Presidio’s data engineering team can assist with data analytics using a solution we call Machine Learning in a Box (MLiB). With MLiB, customers can access all their data sources to build out ML models that provide insight and predictive decision-making capabilities. MLiB offers a thorough way to leverage AWS architecture, with data engineering and data science expertise to produce fast, functional ML/DL models.
By taking an enterprise approach to a solution, Presidio explores not merely the formula used but also how to apply it to the problem most efficiently – navigating the landscape to identify the most performant, cost-effective and efficient AI solution using Intel software and tools.
Let us help you achieve your full AI potential
Fresh applications for artificial intelligence are growing exponentially across industries, and IT organizations are hard-pressed to keep up – especially given the complexity of getting myriad elements to interoperate most efficiently.
Presidio can bring immense value to the process with a holistic approach that leverages Intel software and tools to streamline development, unlocking performance and value. Contact your Presidio account manager to explore how AI can deliver the meaningful insights that benefit your business.
