IBM and Salesforce team up to help customers adopt AI

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1. IBM and Salesforce team up to help customers adopt AI

IBM and Salesforce have announced a strategic partnership to expedite the integration of intelligent technologies in customer relationship management. IBM Consulting will play a key role in guiding clients through the maze of advanced technologies. Matt Candy, IBM Consulting’s global managing partner for generative AI, stated the collaboration would "empower enterprise clients to scale and accelerate the adoption of generative AI."

Salesforce has a history of incorporating advanced technologies like Einstein, Sales Cloud, Service Cloud, and Marketing Cloud. The company's CEO, Mark Benioff, highlighted Salesforce's ambition to become the "No. 1 intelligent CRM," backed by recent quarterly results. This partnership aims to streamline the integration of Salesforce's diverse technology suite.

The collaboration comes amid industry uncertainty about the effective use of generative AI. A recent study showed that 62% of executives feel ill-equipped to deploy such technology. This partnership could serve as a model for other companies, filling a knowledge gap in an industry fraught with uncertainty.

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2. X to use public data to train AI models

Elon Musk's X has updated its privacy policy, revealing plans to use publicly available data to train machine learning models. The policy aligns with Musk's broader ambitions through another venture, xAI, which aims to "understand the true nature of the universe."

Although X has no public goals in intelligent systems, its data collection could benefit Musk's other projects, including xAI. Musk has also hinted at a rivalry with LinkedIn, possibly explaining the collection of job and education data. However, the specifics remain unclear.

The policy change has sparked ethical concerns about using public data for machine learning training. As the industry wrestles with privacy issues, X's new policy could serve as either a model or a cautionary tale. Given Musk's influence, this venture could significantly shape the landscape of intelligent technologies.

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3. South Dakota Schools prepare for AI in classrooms

South Dakota is taking steps to integrate intelligent technologies into its educational system. The School Administrators of South Dakota are planning workshops to educate key stakeholders about the pros and cons of using advanced technologies in education.

Superintendent Jarod Larson emphasized the need for a balanced approach to implementing intelligent systems in classrooms. His district is exploring how to use these technologies effectively and safely over the next year.

The workshops have garnered significant interest, with hundreds of registrations already received. This reflects the urgency among educators to understand and harness the potential of intelligent technologies, as they seek to modernize teaching methods and curricula.

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4. SAP appoints Microsoft's Walter Sun as Global Head of AI

SAP has strategically appointed Walter Sun as its global head of intelligent technologies. Formerly of Microsoft, Sun brings a wealth of experience in applied AI for business applications.

Sun's appointment comes at a time when the market for intelligent technologies in business software is increasingly competitive. His expertise could be a significant asset for SAP as it seeks to expand its initiatives in this sector.

The move highlights SAP's strategic focus on becoming a dominant player in the intelligent technologies market. With Sun leading the way, SAP is well-positioned to enhance its product offerings and gain a competitive edge in this rapidly evolving landscape.

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5. A new framework for prioritizing AI projects

The persistent GPU shortage is hampering progress in the intelligent technologies sector. The rise of large language models like GPT-4 has further strained the already limited supply of high-end GPUs.

A new framework, focusing on "Contribution per GPU," offers a solution for allocating scarce resources. By identifying key metrics and calculating each GPU's contribution, companies can make more informed decisions about project prioritization.

While the framework offers a robust solution, it's not universally applicable. Leaders must adapt the approach based on the strategic importance of specific projects. In a resource-constrained environment, this framework could be a significant asset for companies looking to maximize ROI.

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