The world of technology is increasingly moving towards the use of artificial intelligence as something routine through cell phones and computers. Especially in the case of the latter, it becomes a greater need as these available resources evolve, but the question remains about how ready is the hardware to handle this new feature?.
This is the concern of Flavio Pettengill, Sales Director at Netcore, a company that manufactures RAM and SSDs and currently sells them in the Brazilian market. According to him:
RAM and SSDs are essential components for the performance of any modern device. RAM, which is responsible for temporarily storing data that the processor needs to access quickly, is essential to ensuring that tasks are performed without interruptions. SSDs, which replaced the old HDDs, are responsible for permanent data storage, ensuring speed and efficiency in reading and writing information.
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Getting Ready for Artificial Intelligence: Is Your Hardware Up to the Task?
The world of technology is rapidly advancing towards the widespread adoption of Artificial Intelligence (AI) as a routine feature in cell phones and computers. As these available resources continue to evolve, the question remains: how ready is the hardware to handle this new feature?
To answer this question, it’s essential to understand the concept of AI readiness. According to [3], AI readiness refers to an organization’s preparedness to successfully deploy and use AI to drive outcomes. This encompasses not only the hardware but also the overall infrastructure, data, and cybersecurity aspects.
When it comes to hardware, the ability to handle AI applications is critical. AI requires significant processing power, memory, and storage capacity. Therefore, the hardware must be capable of supporting these demanding requirements. Intel’s AI Readiness Model [2] provides a framework for organizations to assess their AI readiness, including their existing pools of data and infrastructure capabilities.
For IT leaders, getting their enterprise AI-ready requires a deliberate approach. Gartner recommends a four-key initiative action plan [1], which includes:
- Define ”AI ambition” and spot AI opportunities: Identify areas where AI can drive business value and develop a clear strategy for AI adoption.
- Prepare AI cybersecurity: Implement robust security measures to protect against AI-specific threats and vulnerabilities.
- Make data AI-ready: Ensure that data is high-quality, accessible, and relevant to support AI applications.
- Adopt AI: Develop the necessary skills and capabilities to deploy and manage AI solutions.
AI readiness is not just about the hardware; it’s about the entire ecosystem. As AI becomes an integral part of our daily lives, it’s crucial for organizations to assess their AI readiness and take deliberate steps to prepare their infrastructure, data, and cybersecurity for the adoption of AI applications.
Optimized Keywords: Artificial Intelligence, AI Readiness, Hardware, IT Leaders, Cybersecurity, Data Management, AI Adoption, Business Value.
Meta Description: Learn how to get your hardware and organization ready for Artificial Intelligence adoption. Discover the importance of AI readiness, Cybersecurity, and Data Management for successful AI deployment.
Artificial intelligence articles for students
Getting Ready for Artificial Intelligence: Is Your Hardware Up to the Task?
The world of technology is rapidly advancing towards the widespread adoption of Artificial Intelligence (AI) as a routine feature in cell phones and computers. As these available resources continue to evolve, the question remains: how ready is the hardware to handle this new feature?
Understanding AI Readiness
To answer this question, it’s essential to understand the concept of AI readiness. According to [3], AI readiness refers to an organization’s preparedness to successfully deploy and use AI to drive outcomes. This encompasses not only the hardware but also the overall infrastructure, data, and cybersecurity aspects.
The Importance of Hardware in AI Readiness
When it comes to hardware, the ability to handle AI applications is critical. AI requires significant processing power, memory, and storage capacity. Therefore, the hardware must be capable of supporting these demanding requirements. Intel’s AI Readiness Model [2] provides a framework for organizations to assess their AI readiness, including their existing pools of data and infrastructure capabilities.
Top AI Hardware Companies
The AI hardware market is expected to be dominated by companies such as Alphabet, AMD, Apple, AWS, Cerebras Systems, IBM, Intel, and Nvidia [1]. These companies are investing heavily in developing the necessary hardware to support AI applications.
IBM’s AI Hardware Center
IBM’s Research AI Hardware Center is a global research collaboration hub dedicated to creating the next generation of systems and chips for AI workloads, as well as advancing the field of AI hardware research [3].
NIST’s AI Hardware Research
NIST’s AI Hardware team’s research aims to develop the necessary device-level and circuit-level measurements and theory to support the evolution of AI hardware [2].
Preparing for AI Adoption
For IT leaders, getting their enterprise AI-ready requires a deliberate approach. Gartner recommends a four-key initiative action plan [1], which includes:
- Define “AI ambition” and spot AI opportunities: Identify areas where AI can drive business value and develop a clear strategy for AI adoption.
- Prepare AI cybersecurity: Implement robust security measures to protect against AI-specific threats and vulnerabilities.
- Make data AI-ready: Ensure that data is high-quality, accessible, and relevant to support AI applications.
- Adopt AI: Develop the necessary skills and capabilities to deploy and manage AI solutions.
Conclusion
AI readiness is not just about the hardware; it’s about the entire ecosystem. As AI becomes an integral part of our daily lives, it’s crucial for organizations to assess their AI readiness and take deliberate steps to prepare their infrastructure, data, and cybersecurity for the adoption of AI applications.
Optimized Keywords: Artificial Intelligence, AI Readiness, Hardware, RAM, SSD, Market, IBM, Intel, Nvidia.
References:
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