IBM, an early AI pioneer, is adapting to the changing landscape of artificial intelligence by focusing on smaller, reliable AI tools tailored for specific uses. As major companies invest heavily in large foundation models, IBM's approach has started to gain traction, especially following the release of an efficient open-source model by DeepSeek. Their recent earnings report showed a 10% increase in bespoke AI software sales, leading to a 12% rise in stock value. CEO Arvind Krishna views the success of smaller models as a potential validation of this strategic pivot.
IBM's strategy, focusing on smaller AI tools for reliability and specific use cases, is gaining traction amidst debate over AI's economic gains compared to larger models.
The company has zeroed in on building smaller AI tools with a focus on reliability, helping clients apply them to specific use cases.
The recent rise in IBM's bespoke AI software sales reflects a potential shift in the AI landscape, where smaller models may outperform costly, large-scale AI.
Smaller models, with less compute, can be successful, indicating a promising future for companies that prioritize tailored AI solutions.
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