An IBM Institute for Business Value study on the state and impact of the generative artificial intelligence (AI) market evaluates the priorities and challenges CEOs face in the age of artificial intelligence.
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Oracle leverages generative AI in Oracle Fusion Cloud HCM to boost productivity by enabling automated content generation, intelligent recruiting, and data summarization.
Databricks hosted Microsoft CEO Satya Nadella at its customer event, and the two companies explained how they’re working on trustworthy AI and serving joint customers.
Generative AI will play an increasing role in graphic design. Learn how graphic designers can capitalize on AI to enhance their work while working around its limitations.
With the release of its first large language model, Stability AI serves as an open-source alternative to OpenAI’s ChatGPT.
Now is the time to sit down with your marketing and sales leaders to understand the potential and pitfalls of generative AI for your organization. Here are five emerging generative AI use cases to consider.
At Snowflake Summit, the Cloud Data leader details innovations in LLMs, generative AI, and app development functionality.
The speed of AI innovation is outpacing companies’ ability to understand, let alone manage, the risk. This is where leaders can take control.
Aaron Back offers his thoughts on new announcements and products launched at this week’s Salesforce AI Day.
Get a preview of “Selling to the New Executive Buying Committee,” an Acceleration Economy Course on top business and tech drivers of AI.
While Oracle has embedded AI into its Fusion apps, the company has yet to make any major announcements in terms of its generative AI strategy.
By understanding the significance of explainable AI, businesses can make informed decisions and benefit from increased transparency.
Low-code/no-code tools positively impact software agility and automation, but AI presents another viable option to deliver similar benefits.
Without explainability, organizations risk facing challenges of the black box problem. Practitioner analyst Toni Witt shares enterprise-friendly ways to boost explainability.
This guidebook will help you see how generative AI can benefit your business while avoiding the pitfalls that come with adoption, all backed by practitioner guidance.
While generative AI can bring much value to an organization, prompt engineering will be a vital skill to get the most of the technology.
By addressing transparency, accountability, fairness, and privacy, healthcare organizations can harness generative AI’s transformative power while upholding the highest standards of ethical conduct.
The black box problem, which refers to a lack of explainability, can have major implications for companies using AI systems.
Understanding why ethical AI and explainable AI are foundational elements to generative AI is critical to moving forward.
Organizations must understand how to optimize both non-generative and generative AI to unlock value across operations.