Cloud-as-a-service was once the talk of the data science world. Discourse is shifting to AI — the tech tool with unlimited potential. This change does not mean the cloud will become a figment of the past. AI’s popularity will change it for the better.
The cloud will become the most advanced tech in history as AI improves efficiency, security, and scalability. Unpack how they synergize to bring computing into a new era for data science professionals.
What Does AI Bring to the Cloud?
AI helps the cloud by:
- Offering new products, services, and tools to customers.
- Assisting customers and corporations in undergoing big data processing.
- Normalizing the democratization of AI access.
- Creating personalized experiences based on customer habits.
- Increasing workplace productivity by boosting process efficiency.
- Automating tedious tasks.
Its relevancy to cloud computing provides these boons and more.
Transforming Data Center Infrastructure
Cloud infrastructure takes up a deceptive amount of physical space despite filling up digital areas. Data centers are massive and data professionals are noticing shifts in how the buildings adapt to AI incorporation. Some are going through massive overhauls to optimize for more virtual machines.
Data centers will need specialty equipment like tensor processing units. Google has specifically designed TPUs for neural network processing, which is one example of how these organizations had to get creative when melding AI with the cloud.
Companies running enormous data centers like Microsoft, Google, and Amazon are kickstarting their AI-powered cloud platforms, like Azure. To tend to customers, they need better facilities.
A demand spike is the first concern. More people utilize cloud services now because of AI integration, meaning data centers have to scale up or fall behind. Workloads are heavier and more diverse, especially with remote environments adding to the stress. The upgrades manifest in countless ways, from finding more adaptable ways to keep server rooms cooler than 90° Fahrenheit to installing new GPUs to handle the AI-cloud infrastructure combo.
Enhancing Scalability and Flexibility
AI-powered cloud computing offers every sector a chance to grow. From graphic design platform Canva to fintech giant Plaid, they only experienced the scaling they did by incorporating AI into their cloud. Savvy marketing efforts and lucrative business partnerships yielded increases in their customer bases, and they needed computational power to facilitate them and their new AIs.
An AI model can track traffic and automatically allocate resources based on usage. It saves money because it does not push machinery into overload or use too much energy. These financial savings allow companies to expand their product and service offerings with AI attachments because it is already curated for the employing enterprise.
AI contains countless bytes of sensitive data and cloud providers have to boost security to protect it all. How much protection is enough, and are there even enough measures in the current landscape to cover such diverse and valuable data? Questions like this must motivate cybersecurity and data professionals to instill novel defenses to protect citizens.
Presently, many cloud providers use cybersecurity methods to protect their infrastructure. Most follow the ISO guidelines 27017 and 27018, which govern cloud computing and storing personally identifiable information in public housing.
When using cloud data to train a model, professionals must encrypt and use data anonymization to strip identification from information. Doing so can help the organization utilizing the AI avoid legal hot water. However, are these measures enough to quell privacy and breach concerns from cloud users knowingly or not contributing to AI learning?
Bringing Ethical Discussions to the Forefront
Cloud infrastructure remains a hot topic among compliance and regulatory agencies. There is a lot to unpack with concerns over privacy and third-party accountability. Adding AI into the mix makes matters even more muddled, but it makes the discourse more critical.
How businesses and data scientists use AI with cloud storage may lead to privacy and ethical concerns. To what degree do cloud computing businesses need to be transparent about their AI? How will governments regulate potentially toxic influences like bias, or defend against dangers like cyber criminals?
The consequences of AI and cloud computing malpractice could be severe. Talks about standards and frameworks for responsible AI incorporation with the cloud will solidify a more positive relationship between the technologies.
How AI Reimagined Cloud Services
AI did not simply fall into the cloud and immediately optimize. Companies had to adjust and scale with innovative solutions to meet customer needs. Seeing these adjustments is revolutionary for data science because it clarifies how novel AI technologies will impact physical and digital landscapes.
When considering project developments and competitive advantages, data and cloud professionals must prioritize AI’s boom. If they do, it will encourage the research and development necessary for uncovering the true power behind this dynamic duo. Consider investing in merging AI and the cloud soon to unlock the benefits early.
Article by Ellie Gabel.