Why It’s Important
This move could challenge the dominance of closed source models in the generative AI market and could have an impact on companies like OpenAI, whose models are already available on Azure. Meta AI acknowledged that its tests are not yet comprehensive enough and that the benchmarks may not include enough diversity, which could lead to biases.
Similar to any other generative AI model for critical applications, enterprises should exercise caution when adopting Llama 2 to mitigate potential risks. Thorough evaluation and testing of the model’s performance in diverse real-world scenarios are essential. Organisations must also consider employing advanced filtering mechanisms and moderation tools to ensure the generated outputs meet acceptable standards. It is crucial to recognise the Western bias in the model’s results. To address this, it is necessary to make an effort to promote data representation and incorporate localised training datasets that are specific to different regions and cultures.
Who’s Impacted
- CEO
- AI developers
- IT teams
What’s Next?
- To ensure responsible AI practices, enterprises should collaborate with AI ethics experts, use explainable AI techniques, and establish strong monitoring and feedback systems. This will help assess and adapt the model’s behaviour, with a focus on fairness and transparency.
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