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The Financial Times recently shed light on the growing need for increased transparency in AI systems. Their article, "AI should not be a black box," raises some thought-provoking points: 📍 Early AI researchers used to share training data, facilitating collaboration and the identification of flaws. Today, tech companies have shifted their approach and now withhold insights into their training data, citing concerns over intellectual property infringement. (This shift has sparked controversy, particularly within the arts industries, where many individuals have attempted to sue, claiming that AI models have utilised their proprietary works without permission.) 📍 The lack of transparency in AI models is a growing concern. The design of a model determines how it interprets inputs and generates language. AI companies view their model's architecture as their unique advantage, keeping it undisclosed to maintain their competitive edge. This lack of transparency poses challenges in evaluating the outputs, limitations, and biases of AI models, making it hard to assess their reliability and fairness. 📍 According to a Stanford University index, even AI leaders like Google, Amazon, Meta, and OpenAI fall short in transparency needed for responsible AI development: https://lnkd.in/ea7KF28 At Boltzbit, we take a different approach: 🤝 Our users have their own models, trained on their private data. This ensures data privacy and control over the learning process.  🤝 Our user-friendly verification tool enables continuous improvement and ensures our models' accuracy.  🤝 We provide precise sourcing for AI-generated answers, offering word-by-word references rather than just links.   👉 To learn more about this topic, check out the link to the Financial Times article below: https://lnkd.in/dAmqZ4mY

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