2022 Predictions for MLOps and the Industry

MLOps has moved fast in the last year. What will 2022 be like in the MLOps ecosystem? Reah from Arize AI comes on to talk to us about what he expects for the new year. Arize AI is looking for design partners that will provide feedback and get free access to Arize. If interested, here's how to tell them https://arize.com/mlops-signup/!

Take-aways

Predictions include: AI fairness and bias issues will get worse before they get better Enterprises will stop shipping AI blind The citizen data scientist will rise The ML infra ecosystem will get more crowded/complex We will finally unlock the power of unstructured data ML models will become robust to changes 10 members of MLops community will get free Arize for a year (just reach out)

In this episode

Reah Miyara

Senior Product Manager, Arize AI

Reah Miyara is Senior Product Manager at Arize AI, a leading ML monitoring and observability platform counted on by top enterprises to track billions of predictions daily. Reah joins Arize from Google AI, where he led product strategy for the Algorithms and Optimization organization. His experience as a team and product leader is extensive, touching a broad cross-section of the AI technology landscape. Reah played pivotal roles in ML and AI initiatives at Google, IBM Watson, Intuit, and NASA Jet Propulsion Laboratory and his work have directly contributed to many important innovations and successes that have moved the broader industry forward. Reah also co-led the Google Research Responsible AI initiative, confronting the risks of AI being misused and taking steps to minimize AI’s negative influence on the world.

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Demetrios Brinkmann

Host

Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.