The artificial intelligence (AI) race is in full swing, and Big Tech is investing heavily to come out on top. After being in the making for decades, the AI revolution is finally unfolding across the technology spectrum. The year 2023 is undoubtedly the year of AI, as every week, there’s news about ambitious projects from tech giants.
With generative AI crossing platforms and changing how people work, adopting the technology is a ‘now or never’ consideration. From Meta Platforms Inc., the parent company of Facebook, to IBM Corp., a leading enterprise infrastructure manufacturer, the industry's most prominent names are spending millions of dollars to prepare their infrastructure for AI workloads.
Data centers are at the core of the wave of AI solutions, as, in one way or another, the success of AI projects hinges on the hardware. Major tech companies realize the importance of upgrading their data centers to support AI computing.
In May 2023, Meta revealed its plans for a powerful supercomputer to handle AI research powered by a proprietary chip. More importantly, it unveiled a new data center design equipped with AI-friendly hardware.
The company expects its computing needs to grow exponentially as it delves into AI-powered solutions. With a host of widely-used applications like Facebook and Instagram under its umbrella, it anticipates heavy use of AI workloads. Therefore, it's transforming its infrastructure to support those ambitions.
It announced the Meta Training and Inference Accelerator (MTIA), a custom chip for running AI training and inference workloads. It is supposedly packed with tremendous computing power and efficiency, designed for particular processes, such as deep learning.
It’s the company’s first step in microprocessor design. Several companies in the recent past have developed their own proprietary chips, with Apple Inc. being the most prominent.
The powerful chip announcement came with the unveiling of phase two of Meta’s Research SuperCluster AI supercomputer. Designed to train new AI models, the machine is slated to be one of the fastest in the world, with 16,000 GPUs.
Meta is going all out with its efforts to build advanced infrastructure. In that regard, it also revealed a new data center design to support AI workloads better. By adopting liquid cooling and AI-optimized architecture, it’s prepping its data center that is efficient yet cost-effective for building AI training clusters and video transcoding applications.
Manufacturers of IT equipment are also spending top dollar on innovative solutions that leverage AI. From critical devices, such as servers, to purpose-specific peripherals, such as access points, hardware is getting an AI makeover.
Cisco Systems Inc., the world’s leading network equipment maker, recently announced acquiring Armorblox, an AI company. With this acquisition, the company aims to revolutionize its security offerings. They plan to use Armorblox’s generative AI models to realize high-level security measures, such as attack prediction and policy enforcement. The resulting product would be an AI-First Security Cloud.
While the product details are unclear, Cisco has been working on Cisco Security Cloud. These innovations cement its position in the cybersecurity landscape, closely linked to hardware.
AI has made inroads into data security, and with Cisco’s acquisition, it’s clear that the technology will likely become common for managing cloud security in the coming years.
Two of the biggest name in the technology industry, Dell Inc. and Nvidia Corp., are partnering to create on-premise generative AI solutions for enterprises. The initiative is called Project Helix and will combine both companies' software and hardware expertise to enable generative AI at scale.
The project aims to provide every aspect of the process, from infrastructure to model training. It will be based on Dell’s PowerEdge series servers and Nvidia’s H100 Tensor GPUs. Enterprises can use this equipment with storage, such as Dell PowerScale.
Another important element is Nvidia’s AI Enterprise software suite, which has been instrumental in developing generative AI models behind recent chatbots. Furthermore, security and privacy will be built into the basic components of the infrastructure.
In 2022, the two companies launched an AI-powered, security-focused solution for data centers in the shape of Dell PowerEdge servers equipped with Nvidia DPUs, GPUs, and VMware vSphere 8.
With AI in the headlines, it’s clear that the industry is heading toward a future where this technology will be ubiquitous. AI will be highly prevalent in data center facilities as they form the backbone of tech companies, corporations, and government agencies.
Whether it’s a small on-premise private data center or something akin to the hyperscale service providers, AI adoption is inevitable. Data centers will not just have to adopt AI for their day-to-day operations but also for the sake of business, as their servers will need to handle AI workloads.
Here’s how data centers will change.
Legacy equipment may not be suitable to handle AI applications' complex, data-hungry computing needs. Data centers will gradually need to replace old equipment with new ones designed to handle workloads, such as machine learning.
This means that any investment for AI adoption and handling will need to go toward hardware. Fortunately, the market for such equipment is rapidly growing, so these devices will not be as expensive as they are currently.
Leveraging software-defined solutions, such as SD-WAN (networking) and SDS (storage), will improve performance significantly. Software-defined solutions offer better use of resources and intuitive management, which is vital for making any data center AI-friendly.
Besides upgrading equipment and software to handle AI workloads, data centers will rely heavily on technology for security. Generative AI solutions can predict and detect threats more accurately and quickly.
Data breaches are a common pain point for the industry, and they all too often target data centers. So using AI to prevent such attacks is not just going to be an option but an essential need.
By combining AI-driven hardware and software solutions, data centers will use smart models to predict attacks and prevent them just in time. These models may also be used to enforce data protection regulations and avoid hefty non-compliance fines.
Any enterprise with a data center wanting to move with the times must prioritize AI. As the technology spreads throughout the industry, more and more applications will be running workloads such as deep running that demand reliable processing power.
In other words, any data center that doesn’t want to risk downtime or slow performance will need to update its infrastructure to match the demands of AI.
This is where PivIT comes in with its procurement expertise. Whether you’re scaling up or restructuring infrastructure entirely, PivIT can supply the hardware that will form the core of your AI-supporting data center.
More importantly, procuring with PivIT can result in savings as high as 60%. You can find the latest equipment with short lead times from major manufacturers, such as Cisco, Dell, and Juniper, leading the production of AI-focused hardware.
Learn more about hardware procurement with PivIT!