Navigating the Risks and Opportunities of Generative AI for Future-Proofing Your Brand.

The rapid growth of artificial intelligence (AI) models like Dall-E and GPT-4 comes at a cost to society and the planet. The downsides include the environmental toll of mining rare minerals, the human costs of the labor-intensive process of data annotation, and the escalating financial investment required to train AI models as they incorporate more parameters. The digital divide in the AI community is also widening between those who can train cutting-edge models and those who can't. The environmental impact of training large language models (LLMs) is significant, with estimates suggesting that training a 2019 model called BERT emitted 280 metric tons of carbon emissions, equivalent to the emissions from five cars over their lifetimes.
- The mounting human and environmental costs of generative AI Ars Technica
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- Accenture Technology Lead: “You cannot stop AI. I don't think that makes sense” CTech
- The open questions about openAI and generative AI Economic Times
- 5 considerations that'll help future-proof your brand for the next decade Fast Company
- View Full Coverage on Google News
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