NetApp Is Committed To Helping Entities Build Their Own AI Factories
Posted: Tuesday, Oct 22
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NetApp Is Committed To Helping Entities Build Their Own AI Factories

So much is going on with NetApp according to Jeff Baxter, Vice President of Product Marketing at NetApp. Baxter provided details about the latest NetApp product announcements and the future trajectory of artificial intelligence (AI) and cybersecurity within the industry.

Understanding ONTAP: The Foundation of Data Management

The introduction to ONTAP, NetApp’s unified operating system. As the NetApp Executive explained, ONTAP was developed over 30 years ago and has since progressed to unify customers’ data estates across data centres and major cloud platforms, including Amazon, Microsoft, and Google. The platform supports various applications and workloads, serving as a backbone for efficient data management.

Product Announcements

NetApp has divided its recent announcements into four key areas:

  1. Enterprise storage
  2. Cloud storage
  3. Cybersecurity
  4. AI

On the enterprise storage front, Baxter introduced the ASA series models, which promise to offer simplicity, power, and affordability for customers seeking optimal solutions for block storage.

In cloud storage, NetApp rolled out numerous innovations catering to various cloud providers, while the cybersecurity and AI announcements featured advancements poised to shape the future of these domains.

The Future of AI: Serious Applications in Enterprises

2024 is the year when AI will be taken seriously within enterprise use cases. While consumer applications of AI have seen substantial growth, widespread adoption in enterprises has lagged. Baxter predicted that businesses will begin leveraging AI to generate tangible business results by applying large language models to their proprietary data.

The potential risks associated with AI, such as hallucination and misuse. NetApp aims to tackle these challenges by ensuring data governance and sanitisation, thereby reducing inaccuracies while recognising the collective efforts needed to address such risks.

Small Language Models: Tailored AI Solutions

Acknowledging the growing trend of small language models (SLMs), especially within government organisations. The importance of providing versatile tools that can adapt to specific data sets, whether through small or large language models.

“So whether it’s a small language model, whether it’s using large language models but doing training and fine tuning on them with retrieval augmented generation, to be very focused on your specific private dataset.” Added Baxter.

NetApp is committed to either helping entities build their own AI factories or fine-tune existing large-scale models to cater to unique needs, illustrating a tailored approach to AI implementation.

Bridging the AI Skills Gap: Infrastructure-Level Solutions

Many customers, primarily those operating at the infrastructure level, express concerns about the complexities of AI adoption. Baxter reassured these customers by highlighting NetApp’s efforts to abstract and automate the AI process, thereby simplifying its integration into enterprises. This approach mirrors the evolution of technological innovations, where initial complexity gives way to more user-friendly solutions.

“Today, AI is very much like, the dawn of many other technological innovations where you’re stringing everything together. You go back to the invention of the world wide web, and we’re writing HTML by hand.” Added Baxter.

Cybersecurity Focus: Ransomware Resilience

NetAppโ€™s focus on enhancing cyber resiliency. Ransomware has become a pressing concern, and NetApp positions itself as the last line of defence within a zero-trust security model. Baxter detailed how NetApp builds anti-ransomware technologies directly into their storage solutions, employing AI/ML models to detect and block sophisticated ransomware attacks effectively.

Customer Insights and Future Directions

Baxter shared insights from interactions with customers, who prioritise cost efficiency in an increasingly data-intensive environment. The advent of AI has led businesses to retain more data, recognising its potential for future training models. This trend drives the need for cost-effective storage solutions.

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