Introduction to Green Data Centers

Seagate commissioned a survey and report based upon that survey on the role that digital storage can play in creating more sustainable and efficient data centers. This is particularly important as data centers scale up and new data centers are built to support AI-related businesses.

Survey Findings

The survey gathered responses from 330 data center professionals across 11 markets: Australia, China, France, Germany, India, Japan, North America, Singapore, South Korea, Taiwan, and the United Kingdom. The report indicates that energy usage is now a top concern for 53.5% of business leaders. The press release quotes Goldman Sachs Research as forecasting that global power demand for data centers will increase by as much as 165% by 2030, compared with 2023.

Key Findings

Other key findings are:

• 94.5% of respondents reported increasing data storage needs, with 97% anticipating AI’s growth to further impact storage demand.
• Nearly 95% of respondents are concerned about environmental impact, but only 3.3% prioritize this in their purchasing decisions.
• Top barriers to driving sustainability at data centers are high energy consumption (53.5%), raw material requirements (49.5%), physical space constraints (45.5%), infrastructure costs (28.5%), and acquisition costs (27%)
• 92.2% acknowledge the importance of extending the life cycle of storage equipment, but only 15.5% consider it a top purchasing factor.

Creating Sustainable Data Centers

The full report goes into depth on how reducing the total cost of ownership and achieving sustainability goals can be achieved together. By using less power to store data, storage tiering with less frequently accessed data in less expensive and lower power storage technology, storage device life cycle extension and efficient space use in data centers costs can be controlled while using less energy and generating less greenhouse gases.

Embodied Carbon in Storage Media

Note that the carbon contribution for storage in data centers includes both the embedded carbon in manufacturing, shipping and assembling storage systems as well as the ongoing carbon generated by power generation to use the storage devices in storage systems. The comparison of Seagate’s estimates of the embedded carbon in SSDs versus HDDs and LTO tape shows a significant difference. SSDs and HDDs show a significant difference in the embodied carbon since the semiconductor manufacturing processes used to make the NAND flash die in SSDs take a lot of energy and resources, while HDDs require much less energy and carbon generating resources to manufacture.

Power Consumption of Storage Media

The report also contains a table on estimated operating power for SSDs, HDDs and LTO tape and an estimated power efficiency in W/TB. This table indicates that SSDs for data centers use over 50% more operating power per TB of storage capacity. The LTO tape in the table seems to indicate that it uses more power, but the table is showing the power consumed while writing and reading the tape. With magnetic tape in a tape library the tapes spend most of their time sitting idle in the library, so the actual average power efficiency of the magnetic tape would be much less.

Conclusion

Seagate’s commissioned survey and report indicates that there are ways that data centers can manage more stored data while reducing energy consumption and greenhouse gas emissions by careful choices of digital storage in a storage hierarchy.

FAQs

Q: What is the main concern for business leaders in terms of data centers?
A: Energy usage is now a top concern for 53.5% of business leaders.
Q: How can data centers reduce energy consumption and greenhouse gas emissions?
A: By using less power to store data, storage tiering with less frequently accessed data in less expensive and lower power storage technology, storage device life cycle extension and efficient space use in data centers.
Q: What is the difference in embodied carbon between SSDs and HDDs?
A: SSDs show a significant difference in the embodied carbon since the semiconductor manufacturing processes used to make the NAND flash die in SSDs take a lot of energy and resources, while HDDs require much less energy and carbon generating resources to manufacture.

Innovations in workforce productivity are revolutionizing the way teams work, and AI-driven tools are at the forefront of this transformation. By leveraging these tools, teams can overcome productivity barriers and achieve their goals more efficiently. With the ability to automate repetitive tasks, provide data-driven insights, and enhance collaboration, AI-driven tools are empowering teams to work smarter, not harder.

Understanding Productivity Barriers

Productivity barriers can hinder a team’s ability to achieve their goals, leading to decreased morale, missed deadlines, and lost opportunities. Common productivity barriers include communication breakdowns, lack of clear goals, and inadequate resources. By identifying and addressing these barriers, teams can create a more productive and efficient work environment.

Communication Breakdowns

Communication breakdowns are a common productivity barrier that can lead to misunderstandings, errors, and delays. When team members are not on the same page, it can be challenging to collaborate effectively, leading to decreased productivity and increased stress. AI-driven tools, such as project management software and collaboration platforms, can help teams communicate more effectively and stay organized.

Lack of Clear Goals

A lack of clear goals can make it difficult for teams to focus their efforts and prioritize tasks. Without a clear understanding of what needs to be accomplished, team members may feel uncertain about their roles and responsibilities, leading to decreased motivation and productivity. AI-driven tools, such as goal-setting software and performance metrics, can help teams establish clear goals and track progress.

Inadequate Resources

Inadequate resources, such as outdated technology or insufficient training, can hinder a team’s ability to complete tasks efficiently. When team members lack the necessary tools and support, they may struggle to keep up with demands, leading to burnout and decreased productivity. AI-driven tools, such as automation software and virtual assistants, can help teams access the resources they need to succeed.

How AI-Driven Tools Can Help

AI-driven tools are designed to help teams overcome productivity barriers and achieve their goals more efficiently. By automating repetitive tasks, providing data-driven insights, and enhancing collaboration, these tools can empower teams to work smarter, not harder.

Automation

Automation is a key feature of AI-driven tools, allowing teams to streamline repetitive tasks and focus on higher-level work. By automating tasks such as data entry, bookkeeping, and customer service, teams can free up time and resources to focus on more strategic initiatives. AI-driven tools, such as robotic process automation (RPA) software, can help teams automate tasks and improve efficiency.

Data-Driven Insights

Data-driven insights are essential for making informed decisions and driving business success. AI-driven tools, such as analytics software and business intelligence platforms, can provide teams with real-time data and insights, enabling them to make data-driven decisions and optimize their workflows.

Enhanced Collaboration

Enhanced collaboration is critical for team success, and AI-driven tools can help facilitate communication and cooperation. By providing a shared platform for team members to collaborate, AI-driven tools can help teams work more effectively together, share knowledge and expertise, and achieve their goals.

Best Practices for Implementing AI-Driven Tools

Implementing AI-driven tools requires careful planning and execution to ensure successful adoption and maximum impact. Best practices for implementing AI-driven tools include identifying clear goals and objectives, selecting the right tools and technologies, and providing ongoing training and support.

Identifying Clear Goals and Objectives

Identifying clear goals and objectives is essential for ensuring that AI-driven tools are aligned with business needs and priorities. By establishing clear goals and objectives, teams can ensure that they are using AI-driven tools to drive meaningful outcomes and achieve their desired results.

Selecting the Right Tools and Technologies

Selecting the right tools and technologies is critical for ensuring that AI-driven tools are effective and easy to use. By evaluating different options and selecting the tools that best meet their needs, teams can ensure that they are getting the most out of their AI-driven tools.

Providing Ongoing Training and Support

Providing ongoing training and support is essential for ensuring that team members are comfortable and confident using AI-driven tools. By providing regular training and support, teams can ensure that they are getting the most out of their AI-driven tools and overcoming any challenges or obstacles that may arise.

Real-World Examples of AI-Driven Tools in Action

AI-driven tools are being used in a variety of industries and applications, from customer service and marketing to finance and healthcare. Real-world examples of AI-driven tools in action include chatbots and virtual assistants, predictive analytics and machine learning, and automation and process optimization.

Chatbots and Virtual Assistants

Chatbots and virtual assistants are being used to provide customer support and enhance the customer experience. By using natural language processing (NLP) and machine learning algorithms, these tools can understand and respond to customer inquiries, providing personalized support and resolving issues quickly and efficiently.

Predictive Analytics and Machine Learning

Predictive analytics and machine learning are being used to drive business insights and inform decision-making. By analyzing large datasets and identifying patterns and trends, these tools can provide teams with real-time insights and recommendations, enabling them to make data-driven decisions and drive business success.

Automation and Process Optimization

Automation and process optimization are being used to streamline workflows and improve efficiency. By automating repetitive tasks and optimizing business processes, teams can free up time and resources to focus on higher-level work, driving innovation and growth.

Conclusion

In conclusion, AI-driven tools are revolutionizing the way teams work, providing them with the insights, capabilities, and support they need to overcome productivity barriers and achieve their goals. By automating repetitive tasks, providing data-driven insights, and enhancing collaboration, AI-driven tools can empower teams to work smarter, not harder. Whether you’re looking to improve communication, streamline workflows, or drive business insights, AI-driven tools can help. With the right tools and technologies, teams can achieve their goals and drive success in today’s fast-paced and competitive business environment.

Frequently Asked Questions (FAQs)

What are AI-driven tools?

AI-driven tools are software applications that use artificial intelligence (AI) and machine learning algorithms to automate tasks, provide insights, and enhance collaboration.

How can AI-driven tools help teams overcome productivity barriers?

AI-driven tools can help teams overcome productivity barriers by automating repetitive tasks, providing data-driven insights, and enhancing collaboration.

What are some examples of AI-driven tools?

Examples of AI-driven tools include chatbots and virtual assistants, predictive analytics and machine learning software, and automation and process optimization tools.

How can teams implement AI-driven tools effectively?

Teams can implement AI-driven tools effectively by identifying clear goals and objectives, selecting the right tools and technologies, and providing ongoing training and support.

What are the benefits of using AI-driven tools?

The benefits of using AI-driven tools include improved productivity, enhanced collaboration, and increased efficiency, as well as the ability to drive business insights and inform decision-making.

U.S. government funding for the global database of security flaws, the Common Vulnerabilities and Exposures database, was set to expire on Apr. 16. The not-for-profit organization that runs the database, MITRE, confirmed its contract with the U.S. Department of Homeland Security to operate the CVE Program had not been renewed. However, in an eleventh hour turnaround, the U.S. Cybersecurity and Infrastructure Security Agency said it had extended the contract with MITRE.

What Happened And Why?

MITRE vice president Yosry Barsoum confirmed that U.S. government funding for the CVE database and the Common Weaknesses Enumeration programs will expire, warning that it could be a disaster for security. The news came via a letter on social network BlueSky. Barsoum wrote, “On Wednesday, April 16, 2025, the current contracting pathway for MITRE to develop, operate, and modernize CVE and several other related programs, such as CWE, will expire. If a break in service were to occur, we anticipate multiple impacts to CVE, including deterioration of national vulnerability databases and advisories, tool vendors, incident response operations, and all manner of critical infrastructure.”

Impact of the Funding Cut

The potential end to the CVE program funding was viewed by some experts as part of a cost-cutting drive by the Trump administration. The CVE system is a global reference method for publicly-known security flaws, launched in 1999 and maintained by the U.S. National Cybersecurity FFRDC, operated by The MITRE Corporation, with funding from the U.S. National Cyber Security Division of the U.S. Department of Homeland Security. CVE IDs are listed on MITRE’s system as well as in the U.S. National Vulnerability Database.

Why Is An End To CVE Program Funding Bad?

The CVE database is “critical for anyone doing vulnerability management or security research,” and for “a whole lot of other uses,” security journalist Brian Krebbs wrote on Mastodon. America’s “abrupt pullback” from leadership roles “in this case coordinating the near global issue of CVEs for vulnerabilities” will “place a heavy burden on global cyber defenses,” says Ian Thornton-Trump, CISO at Inversion6. Cutting the CVE program funding would be “a huge blow to the cybersecurity community,” says William Wright, CEO of penetration testing firm Closed Door Security.

The CVE Funding Cut’s Impact On Global Cybersecurity

However, the news might not be quite as bad as it seems. It’s essential to understand that MITRE does not operate the National Vulnerability Database, which is run by the U.S. National Institute of Standards and Technology, says Sean Wright, an independent security researcher. While MITRE does assign CVE IDs, the CVE Naming Authority can also do this. The recent news about MITRE’s contract would likely only affect new vulnerabilities. Historical vulnerabilities should not be affected.

What To Do Next

MITRE said historical CVE records will be available on GitHub, but future CVEs still hang in the balance. Hopefully, another organization will step in to provide the funding, or countries will “band together to offer support,” says Closed Door Security’s Wright. Businesses can prepare by diversifying their threat intelligence sources and monitoring vendor-specific vulnerability feeds, says Jamie Akhtar, CEO and co-founder at cybersecurity outfit CyberSmart.

Conclusion

The potential end to MITRE’s CVE program funding is a worrying move that potentially reduces security for everyone. However, with the contract extension, the CVE program will continue to operate, and the global cybersecurity community can breathe a sigh of relief. It is crucial for organizations to stay vigilant and prepared for any potential changes in the future.

FAQs

Q: What is the Common Vulnerabilities and Exposures (CVE) database?
A: The CVE database is a global database of security flaws that provides a reference method for publicly-known security flaws.
Q: Who operates the CVE database?
A: The CVE database is operated by The MITRE Corporation, with funding from the U.S. National Cyber Security Division of the U.S. Department of Homeland Security.
Q: What would happen if the CVE program funding is cut?
A: If the CVE program funding is cut, it could lead to a deterioration of national vulnerability databases and advisories, tool vendors, incident response operations, and critical infrastructure.
Q: How can businesses prepare for a potential CVE funding cut?
A: Businesses can prepare by diversifying their threat intelligence sources and monitoring vendor-specific vulnerability feeds.
Q: Is the National Vulnerability Database (NVD) affected by the CVE funding cut?
A: No, the NVD is operated by the U.S. National Institute of Standards and Technology and is not directly affected by the CVE funding cut.