At the same time, companies must ensure they enact best practices when storing data, whether for AI or in general. Those who do not properly adjust their technology and adopt AI risk falling behind. Successfully incorporating AI will be a critical part of remaining competitive in the future. Other prevention methods include prioritizing cybersecurity education while onboarding new team members, regular checkups on infrastructure and testing data-recovery scenarios with hacker simulations. Most of the security industry focuses on intrusion prevention and detection, but it’s a losing battle because the vulnerabilities are not just technical-they depend on people never making a mistake, and that’s not likely.Ĭompanies must ensure that their employees are regularly receiving training on cybersecurity best practices. They get tricked into giving out their credentials or into installing malware. It can’t be overstated that the majority of ransomware attacks occur because of human error. Most importantly, if a system is breached by bad actors, an immutable copy of AI data in the cloud cannot be attacked, deleted or compromised. The cloud has a unique advantage here over storing data on-premise, as it is not connected to user accounts, which is where most hacks take place. This way, in the case of a ransomware attack, the back-up copy is safe from the threat of a breach and cannot be tampered with. Store a second, immutable copy of the data. Because of this, here are two tips to ensure data is safe and accurate: 1. Unfortunately, as technology continues to grow and evolve, so does the threat of cyberattacks. Since AI is still a burgeoning technology, companies must tread cautiously with it and regularly check that no breaches or threats have occurred. Further, when these AI mistakes are finally realized, companies will have to spend time correcting the failures, which results in lost productivity time. When data is tampered with, companies risk working with incorrect information that can have serious consequences for their business. Once AI, or any other next-gen technology, is implemented, however, it is critical that the information it utilizes is secure and untampered with. The cloud can also store insights that AI is able to glean, making it even more useful for organizations that utilize it.
Enterprises can increase or decrease their cloud storage depending on their demands, making AI simple to adjust and implement for different aspects of the company. When data is properly stored in the cloud, businesses can customize AI to their own specific needs for the technology. While these vendors also offer storage, less expensive storage from specialty vendors are beginning to chip away (registration required) at the hyperscalers’ market share. The “hyperscalers”-i.e., Amazon, Google and Microsoft-are all offering AI platforms in the cloud. Most AI applications, such as ChatGPT, are already running in the cloud. The confluence of declining storage prices and the availability of very high-powered CPU resources based on chips by Nvidia, AMD and others is promoting the boom in AI applications. Like most semiconductor products, prices will continue to drop as volumes increase. The price of solid-state storage has been dropping more quickly than the price of hard drives, and SSDs will probably begin to displace hard drives within the next few years. Luckily, the cost of data storage has been dropping dramatically, especially “hot storage,” which is based on hard drives or SSDs. Right now, the surging cloud storage presence can really make its mark in supporting such next-gen deployments like AI. In fact, recent data from my company, Wasabi, found that 84% of enterprises expect to increase the amount of data stored in the public cloud in the next 12 months.
The Convergence Of Cloud Storage And AIĭata storage has grown into a $77.5 billion industry and, even amid the tech slowdowns that we’ve seen this year, the demand for cloud storage has not wavered. None of this would be possible without data.
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