The immovable opacity of AI meets the irresistible force of privacy
If an AI operator cannot account for personal data generated inside a large language model, then it is possible activist privacy regulators might find the technology to be unsafe.
If an AI operator cannot account for personal data generated inside a large language model, then it is possible activist privacy regulators might find the technology to be unsafe.
Smartphones are increasingly about foundational models, generative AI features and the ability to leverage AI locally. The latest example is Samsung's Galaxy S24 launch, which also served as a showcase for Google's Gemini Pro and Imagen 2 on Vertex AI.
The plan for Google is to get Gemini into as many developer workflows as possible.
With enterprises still kicking the tires on large language models (LLMs), use cases and generative AI applications, vendors are big on providing choice, bring-your-own-models and the ability to mix and match foundations.
Generative AI and large language models (LLMs) have received plenty of buzz, but enterprises need to stay focused on how domain-specific models develop. Why? That's where the returns will be.