Aporia is a new Israeli startup which offers an AI observability platform. This is a platform which oversees the information inputted to a machine for the purpose of teaching it to learn to think on its own. The company just raised $5 million in a seed round from Vertex Ventures and TLV Partners.
The future is in artificial intelligence. People fear this because they see examples of AI run amok in science fiction like the Terminator movies and the Matrix films. But in reality AI just means letting computers figure things out for themselves. This means that they can be more helpful whether for making medical diagnoses or determining a proper course of action in engineering or software design.
Aporia declares that it empowers data scientists to take control of their machine learning models’ performance in production. “With a robust, friendly monitor builder,” says the company, “the Aporia platform allows them to quickly create, update and maintain ML monitors that track and detect various types of performance issues and data drift. When an issue occurs, Aporia reports it on various channels and provides context for further investigation.”
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A machine learning model, as explained by Microsoft, is a file that has been trained to recognize certain types of patterns. You train a model over a set of data, providing it an algorithm that it can use to reason over and learn from those data. Once the model has been trained a user can use it to reason over data that it hasn’t seen before, and make predictions about that data.
Aporia boasts that it is the first company to offer deep customization capabilities for model monitoring with full support for public cloud and managed-on-prem, allowing data science teams to build the exact monitors they need for their use cases. Aporia is used by multi-billion dollar companies for monitoring billions of daily predictions and maintaining data integrity. Founded in 2020, Aporia is backed by TLV Partners and Vertex Ventures.
“AI needs guardrails. Companies need to have confidence in their machine learning models, and the only way to get there is by robust monitoring to ensure they’re doing what they’re supposed to do,” says Aporia CEO Liran Hason. “Aporia makes monitoring simple, fast and secure, bringing engineering and DevOps best-practices into the new field of MLOps and ensuring that data science teams can keep their models performing accurately and fairly.”
Hason explained the difference between AI and traditional tech to Tech Crunch. “AI is a super powerful technology,” he said. “But unlike traditional software, it highly relies on the data. Another unique characteristic of AI, which is very interesting, is that when it fails, it fails silently. You get no exceptions, no errors. That becomes really, really tricky, especially when getting to production, because in training, the data scientists have full control of the data.”