AI stack attack: Navigating the generative tech maze

by | Jul 8, 2024 | Technology

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In mere months, the generative AI technology stack has undergone a striking metamorphosis. Menlo Ventures’ January 2024 market map depicted a tidy four-layer framework. By late May, Sapphire Ventures’ visualization exploded into a labyrinth of more than 200 companies spread across multiple categories. This rapid expansion lays bare the breakneck pace of innovation—and the mounting challenges facing IT decision-makers.

Technical considerations collide with a minefield of strategic concerns. Data privacy looms large, as does the specter of impending AI regulations. Talent shortages add another wrinkle, forcing companies to balance in-house development against outsourced expertise. Meanwhile, the pressure to innovate clashes with the imperative to control costs.

In this high-stakes game of technological Tetris, adaptability emerges as the ultimate trump card. Today’s state-of-the-art solution may be rendered obsolete by tomorrow’s breakthrough. IT decision-makers must craft a vision flexible enough to evolve alongside this dynamic landscape, all while delivering tangible value to their organizations.

Countdown to VB Transform 2024

Join enterprise leaders in San Francisco from July 9 to 11 for our flagship AI event. Connect with peers, explore the opportunities and challenges of Generative AI, and learn how to integrate AI applications into your industry. Register Now

Credit: Sapphire Ventures

The push towards end-to-end solutions

As enterprises grapple with the complexities of generative AI, many are gravitating towards comprehensive, end-to-end solutions. This shift reflects a desire to simplify AI infrastructure and streamline operations in an increasingly convoluted tech landscape.

When faced with the challenge of integrating generative AI across its vast ecosystem, Intuit stood at a crossroads. The company could have tasked its thousands of developers to build AI experiences using existing platform capabilities. Instead, it chose a more ambitious path: creating GenOS, a comprehensive generative AI operating system.

This decision, as Ashok Srivastava, Intuit’s Chief Data Officer, explains, was driven by a desire to accelerate innovation while maintaining consistency. “We’re going to build a layer that abstracts away the com …

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We want to hear from you! Take our quick AI survey and share your insights on the current state of AI, how you’re implementing it, and what you expect to see in the future. Learn More

In mere months, the generative AI technology stack has undergone a striking metamorphosis. Menlo Ventures’ January 2024 market map depicted a tidy four-layer framework. By late May, Sapphire Ventures’ visualization exploded into a labyrinth of more than 200 companies spread across multiple categories. This rapid expansion lays bare the breakneck pace of innovation—and the mounting challenges facing IT decision-makers.

Technical considerations collide with a minefield of strategic concerns. Data privacy looms large, as does the specter of impending AI regulations. Talent shortages add another wrinkle, forcing companies to balance in-house development against outsourced expertise. Meanwhile, the pressure to innovate clashes with the imperative to control costs.

In this high-stakes game of technological Tetris, adaptability emerges as the ultimate trump card. Today’s state-of-the-art solution may be rendered obsolete by tomorrow’s breakthrough. IT decision-makers must craft a vision flexible enough to evolve alongside this dynamic landscape, all while delivering tangible value to their organizations.

Countdown to VB Transform 2024

Join enterprise leaders in San Francisco from July 9 to 11 for our flagship AI event. Connect with peers, explore the opportunities and challenges of Generative AI, and learn how to integrate AI applications into your industry. Register Now

Credit: Sapphire Ventures

The push towards end-to-end solutions

As enterprises grapple with the complexities of generative AI, many are gravitating towards comprehensive, end-to-end solutions. This shift reflects a desire to simplify AI infrastructure and streamline operations in an increasingly convoluted tech landscape.

When faced with the challenge of integrating generative AI across its vast ecosystem, Intuit stood at a crossroads. The company could have tasked its thousands of developers to build AI experiences using existing platform capabilities. Instead, it chose a more ambitious path: creating GenOS, a comprehensive generative AI operating system.

This decision, as Ashok Srivastava, Intuit’s Chief Data Officer, explains, was driven by a desire to accelerate innovation while maintaining consistency. “We’re going to build a layer that abstracts away the com …nnDiscussion:nn” ai_name=”RocketNews AI: ” start_sentence=”Can I tell you more about this article?” text_input_placeholder=”Type ‘Yes'”]

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