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Technologies to Enable Artificial Intelligence (AI) in Higher Education

Learn how AI is reshaping higher education and which technologies can best support any current and future AI initiatives at your institution.

AI in Higher Education Takeaways

  • AI has the potential to revolutionize teaching and learning, operations, and research at higher education institutions.

  • Types of AI used in higher ed include machine and deep learning, generative AI, and computer vision.

  • Students, faculty, administrators, staff, and researchers use AI for a variety of purposes, including data science.

  • AI is used to accelerate academic research, equip students with skills for the future, and improve operations.

  • Intel offers hardware and software technologies, course content, and student programs to advance AI in higher education.



Why AI in Higher Education?

The purpose of higher education around the world is to educate and enlighten students in new ways of thinking and problem-solving as well as to equip them with the knowledge and skills needed as they transition to the workforce. The recent advancements in AI have the potential to revolutionize nearly all aspects of our world. This is especially true for students who are soon-to-be members of the workforce entering an AI-fueled digital economy.

In alignment with the global adoption of AI, AI is being integrated into all aspects of higher education—teaching, learning, researching, and administrative tasks—to help students better prepare for an evolving, tech-based future.

Intel is steadfastly committed to expanding access to AI curricula, programming, and resources for higher education institutions around the world. As AI evolves at your higher education institution, we are here to maximize your success with guidance, expert insights, and a technology portfolio designed for AI initiatives of all sizes.

AI in Higher Ed Use Cases

From students building advanced technical skills to faculty members educating tomorrow’s innovators to researchers pursuing breakthrough scientific discoveries—AI is quickly becoming prevalent on higher education campuses and applied in new and evolving ways.

Accelerating AI-Powered Scientific Research

University research is vital to advancing scientific discoveries and innovation; strengthening local, regional, and national economies; and addressing the world’s most perplexing challenges. This research is often costly, requires massive amounts of compute power, and is extremely time consuming—sometimes taking years or decades to reach a conclusion or achieve desired results. AI is emerging as a viable solution to drastically accelerate the research process, saving researchers time, lowering costs for universities, and ultimately bringing the impact of revolutionary research results to the real world sooner.

Teaching the Next-Generation of Innovators

The demand for graduates with AI skills is expected to rapidly grow over the next three years. A 2021 survey of higher education educators and IT decision-makers found that 69 percent of all respondents sensed increasing demand from employers for graduates with AI technical skills. That’s why there has been an industry-wide shift to create new AI offerings, bolster existing curricula, and increase the overall accessibility of AI instruction to a wider variety of students.

To help community colleges in the US expand their AI programming, in 2020 Intel created the AI for Workforce program to provide colleges with over 500 hours of AI content and prepacked courses, professional development for instructors, and implementation guidance for faculty.

Building Student Skill Sets for a Digital Economy

Today’s students are looking for opportunities to translate their academic success into career success. In the current digital economy, that means students must be equipped with new AI technical skills that they can use to solve complex problems with innovative solutions in fast-moving industries such as healthcare and life sciences and financial services.

Intel is empowering students to expand their learning, elevate their skills, and get on the fast track to becoming an AI leader through three programs:

Using AI to Improve Daily Life

Nearly everyone is already connected to AI through their everyday go-to tools, websites, and products like social media, online shopping recommendations, online search engines, and smartphones. With new AI advancements being released almost daily, your students and staff are turning to more-complex and compute-intensive applications to help enhance their lives and augment their teaching and learning. Some of the more advanced, compute-heavy tools you may need to support include AI-powered personal assistants; video- or voice-based content creator apps for digitizing lectures, conferences, and guides; curricula and resource planning programs; and personalized learning solutions.

How You Can Best Support AI Initiatives at Your University

A key factor to the success of any AI-related project is having the right foundational technology in place that provides the ideal balance of performance, advanced security features, and costs. We know it can be challenging to select the exact solution needed to match the needs of every person on campus and their unique use-case technology specifications. To help you with planning, we’ve gathered advice from our experts on the steps you can take to better understand and support the needs of your diverse higher education community.

Determine the Type of AI Being Used or Taught

No matter the size or type of higher ed institution your IT team supports, determining which technologies will best support your user base begins with an understanding of the type of AI being used or taught.

AI is a broad term that is often used instead of describing the more complex types—or subsets—of AI. However, broadly labeling initiatives as an “AI project” can make selecting the right supporting technology even more difficult. Each AI subset requires a unique combination of hardware, software, and security based on the project’s end goal. Let’s explore the types of AI that are either being used at your institution already or will be soon.

  • Classical machine learning (ML): Uses models, or algorithms, to analyze data sets, identify patterns, and make predictions without human intervention. This type of AI is often the first type students learn about when beginning their college career. ML also powers many popular tools used by everyone on campus, such as Gradescope, Grammarly, Consensus, Elicit, and ResearchRabbit.
  • Deep learning: Teaches computers to process data in a way that is inspired by the human brain, using models that can recognize complex patterns in pictures, text, sounds, and other data to produce accurate insights and predictions. This type of AI is an advancement of classical ML and used when working with massive data sets that have numerous parameters or when a high level of accuracy is required.
  • Computer vision: Trains computers to make sense of the overwhelming amount of visual data collected to locate, identify, and track objects or specific actions. This type of AI combines cameras, edge computing, cloud-based computing, software, and AI to enable systems to “see” data collected from cameras and videos. In addition to researchers using computer vision to aid their pioneering work, it’s often used by campus security and administration professionals to help ensure campus safety. Computer vision can also enhance student engagement in distance learning, enable automated proctoring for online exams, and help spot plagiarism in handwritten student exams.
  • Generative AI: Generates new content when provided with a prompt by an end user. Generative AI creates this content based on the massive sets of data and machine learning AI algorithms it was trained on. This type of AI is integrated with language AI, also known as natural language processing (NLP), which allows it to process and understand human language. When used together, generative AI and NLP can understand a prompt and generate an appropriate response via text, video, imagery, or audio. Generative AI is a relatively new tool that higher ed students and professionals are enthusiastically adopting and experimenting with to accelerate research, boost productivity, enhance curriculum development, and maximize learning outcomes.

Pick Technologies Based on the Complexity and Scale of AI Projects

For students, faculty, administrators, and researchers to fully harness the power of AI, they need to be equipped with and supported by the hardware and software technologies that maximize performance, minimize costs, and provide enhanced security features to help keep sensitive information and data safe and secure.

Choose Hardware Solutions That Can Keep Up with AI Complexity

When considering hardware technology options, it’s important to remember the computational requirements for AI initiatives will vary greatly based on the number of parameters involved in the data. However, typically the less complex the data set being used in the project is, the less compute performance will be needed to deploy the AI model. This table provides common ways students use AI across subjects and majors—from simple tasks like productivity tools to highly complex, multicomponent projects like building robots with computer vision—and how the computational requirements increase as projects scale in size and complexity. Additionally, this table illustrates how IT can best align Intel® Core™ processors to student uses.

For student devices, the amount of processing power required depends on how the device will be used.

This concept of matching compute performance to the level of workload complexity should also be applied when selecting hardware for professors teaching AI skills and for research professionals. To meet the performance needs of professors and researchers, consider deploying Intel® Xeon® Scalable processors or Intel® Xeon® W processors that are purpose-built for high-performance workstations in specialized labs and feature built-in accelerators for demanding AI workloads. If you find researchers need even more performance and scalability for their work in generative AI or large language models (LLMs), Habana® Gaudi®2 processors may be the right option.

With our vast portfolio of CPUs and accelerators—and new innovations always in the works—we are dedicated to making it easier for you to enable AI in higher education. For example, our upcoming Meteor Lake processors will offer a dedicated inference accelerator optimized for low power and the ability to run AI workloads across the CPU and integrated GPU.

Select Software Solutions and Resources That Support High-Quality Teaching and Learning

The right software solutions and resources are essential for AI in higher education initiatives to succeed—no matter if someone is teaching about it, learning about it, or using it every day for work. We’ve gathered our top programs that you and your IT team can leverage to better support all those in the higher ed community.

For University Researchers and Developers

Intel offers numerous resources for researchers, data scientists, and developers that can help improve performance and increase productivity during AI model training and deployment. We offer framework optimizations for those working in PyTorch, scikit-learn, and TensorFlow, as well as a comprehensive portfolio of libraries and tools to enable faster development, training, and deployment of machine learning solutions.

For Faculty and Staff

As an ardent supporter of educators, we’ve developed a comprehensive collection of classroom-ready resources, teaching kits, and tools that professors can modify to fit their curriculum needs. Intel® academic courses are designed to help expedite course design and development with ready-to-use lesson plans, videos, labs, and other content.

Discover more information about Intel® academic courses and AI programs for students and learn how other educational institutions are implementing our AI in higher education resources.

For Students

In addition to our student programs discussed earlier, students can access our free, cloud-based development sandbox, the Intel® Developer Zone, for class assignments, personal projects, or general experimentation. For the most-ambitious students up for new challenges, we offer free, self-paced AI courses; on-demand webinars; and certification programs they can take advantage of to get a jump-start on their future careers.

Seek Solutions with Integrated, Hardware-Based Security Features

When working with sensitive data in regulated industries, such as higher education, protecting devices from cyberattacks is of the utmost importance. However, this can be difficult for higher ed IT leaders to achieve for several reasons:

  • Little control of networked devices, both university- and student-owned, means every device is a potential entry point for attackers and malware.
  • Students and faculty often travel and complete work off campus, which raises the risk of theft and device tampering.
  • Users are typically the weak links in security infrastructures because of bad or shared passwords, infrequent updates, or sharing sensitive data on the network with unsecured personal devices.

For these reasons, additional security measures and increased due diligence are required. Hardware-based security features, like those running on Intel® processors and the Intel vPro® platform, can help everyone better protect their devices and data by offering enhanced protection at all computing layers.1 Learn more about our vast collection of integrated security technologies and how they work in concert to provide foundational security, workload and data protection, and software reliability.

Better Support Your University’s AI Initiatives with Purpose-Built Solutions from Intel

Intel offers a portfolio of hardware and software tools that can help you support newly emerging, changing, or legacy AI efforts at your university. Our solutions are built to help you deliver the right levels of performance and security to users while keeping costs and future interoperability in mind.

Discover our full suite of software and hardware technologies for all your AI in higher education needs.

Frequently Asked Questions

AI is being used in higher education institutions in a variety of ways, ranging from students building their AI knowledge and skill sets through experimentation to faculty members enhancing their course content faster and easier to researchers uncovering world-changing insights. AI is also widely used by administrators to streamline processes, improve staff efficiency, and lower costs.

The benefits of AI in higher education can vary widely depending upon the type of AI being used and how it’s being applied to a particular project or initiative. However, typical benefits of using AI in higher education institutions include:

  • Increases efficiency for faculty and staff through automation of repetitive work.
  • Enhances student learning experiences with more-engaging and personalized course content.
  • Frees up professors from time-consuming tasks so they can focus on maximizing instruction time and directly supporting students.
  • Accelerates the development and deployment of AI solutions used by academic researchers.
  • Improves and streamlines administrative processes and operations, helping to reduce overall educational costs.
  • Better prepares students for a digital workforce and economy.