The most advanced ML Observability platform
We’re super excited to share that Aporia is now the first ML observability offering integration to the Databricks Lakehouse Platform. This partnership means that you can now effortlessly automate your data pipelines, monitor, visualize, and explain your ML models in production. Aporia and Databricks: A Match Made in Data Heaven One key benefit of this […]
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We’re excited 😁 to share that Forbes has named Aporia a Next Billion-Dollar Company. This recognition comes on the heels of our recent $25 million Series A funding and is a huge testament that Aporia’s mission and the need for trust in AI are more relevant than ever. We are very proud to be listed […]
The concept of responsible AI describes how a specific organization approaches the challenges surrounding artificial intelligence (AI) from both an ethical and a legal perspective.
Responsible AI is intended for use by any organization considering how to build ethical and lawful AI systems. In order to make AI responsible, companies must design, develop, and deploy AI in a way that empowers employees and businesses, and impacts customers and society fairly. This practice will engender trust and enable companies to scale AI with confidence.
Organizations can take meaningful action on important issues like fairness, safety, security, accountability, and transparency by implementing the right measures. Using this framework, organizations can commit to responsible AI practices. This process explains how general ethical frameworks (such as the Asilomar Principles) can be applied to specific organizational AI systems, such as self-driving cars or hospital software. As a result, it helps organizations understand how general legal frameworks (such as GDPR in the EU) can apply to particular AI systems, such as self-driving cars and hospital software.
Learn more about responsible AI here.
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