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Analysts and experts say that the openness and accuracy of the Llama 3.1 family of models pose an existential threat to providers of closed proprietary large language models.
Data analytics and machine learning can deliver real business value, but too many projects miss their mark. Here are seven mistakes to watch out for, and what to do instead.
Fueled by vibes and with stars in their eyes, enterprises are not taking the time to understand generative AI’s limitations and to create their own rules-based approach.
Acquisition of search and analytics startup in reported seven figure deal is likely OpenAI’s biggest to date.
Smart companies will experiment with small generative AI applications to gain the skills and confidence to try bolder projects.
There is widespread fear in the securities and finance sectors that using generative AI will force companies to rely on giant cloud companies.
Imagine a social network where every post and comment were digitally signed, permanent, irreversible, and verifiable, and where participants who created value were rewarded.
We’re still waiting for a trusted vendor to spare enterprises from the confusion and guesswork of artificial intelligence.
The Kubernetes open source project should serve as the blueprint for the way in which we develop, govern, fund, and support AI projects.
AI agents offer flexibility and autonomy as they plan and complete complex tasks that traditionally require human involvement.