Innovation in AI Product Development - Shemer Steinlauf
In this interview, Shemer Steinlauf, a Senior Product Manager at Microsoft, shares his journey, experiences, and the strategic approaches he employs to ensure the Azure Video Indexer not only meets but exceeds expectations in a rapidly changing market.
What we talk about below
- How does Microsoft manage the quality-speed tradeoff in a new product?
- How has Microsoft used beta and client testing in Steinlauf’s AI-led Azure Video Indexer?
- How does Steinlauf see the strategic incentives for Azure Indexer?
From Developer to Product Manager
Shemer Steinlauf's career at Microsoft spans nine years, with five of those dedicated to product management. His journey began as a developer, eventually transitioning to a technical advisor role for Azure support, and finally to his current position managing the Azure Video Indexer.
"I started as a developer and then moved into solution building," Shemer explained. "This background allows me to understand the needs and challenges of developers, which is crucial in my role as a product manager."
Steinlauf’s background also helped him appreciate how important developer experience is, something he placed a lot of emphasis on.
“'I’m sure that everybody that knows a bit about Microsoft remembers Steve Ballmer, the former CEO, on stage shouting, developers, developers, developers, The essence is, right, Microsoft is a dev, first developer, first company. We invented.net we're providing Azure services, we are providing developers and solution developers with a lot of tools, a lot of tools to work with.”
Azure Video Indexer: Empowering Users Through Data
Azure Video Indexer is an AI tool designed to extract data from video content. It offers a range of features, including face detection, celebrity recognition, object identification, and topic extraction.
"Our goal is to allow users to extract as many data points from video content as possible," Shemer said. "We aim to empower users to achieve more with our product, whether they're in media, manufacturing, or retail."
The standout feature of Azure Video Indexer is its ability to turn unstructured video data into structured insights, which can aid automation and quality control efforts in addition to the obvious applications for video search. For instance, in manufacturing, the tool can be used to monitor production lines and ensure quality control by identifying defects in real-time. In retail, it can analyze customer behavior to optimize store layouts and improve the shopping experience.
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Balancing Quality and Growth
Since the launch of ChatGPT in 2022, AI businesses have been scrambling to claim a stake in a market moving very quickly. Given how important it seemed to get the software out quickly, I wanted to ask Shemer about the tradeoff between speed and quality.
"Quality is number one," Shemer said. "We strive for the best quality because it directly impacts the trust our customers have in us. Trust and quality are prioritized over growth, even if it means sacrificing expansion opportunities."
Safeguards for product release, Shemer told me, include automated and manual testing, peer reviews, and continuous monitoring of product performance.
"At Microsoft, we have a long-standing commitment to quality and trust," Shemer explained. "We have Responsible AI Standard that helps ensure that Microsoft’s AI systems achieve a set of goals that map to our core principles. It provides product teams with the tools and resources necessary to meet these goals and track progress over time. "
Are clients involved in the quality process, I asked.
"We involve our customers from the early stages through private previews," Shemer explained. "This allows us to gather valuable feedback and ensure that we're meeting their needs while maintaining high standards of quality."
This collaborative approach has proven to be highly effective. By engaging with customers directly, Shemer and his team can identify potential issues early and address them before the product reaches a broader audience. This not only enhances the quality of the product but also fosters a strong relationship with customers, who feel their input is valued and impactful.
"During periods of rapid growth, it's crucial to maintain a strong focus on quality," Shemer explains. "We use private previews and beta testing to ensure that our products are thoroughly tested and refined before they reach a wider audience."
The Future of Azure Video Indexer
Looking ahead, Shemer is focused on expanding the capabilities of Azure Video Indexer, particularly in integrating generative AI technologies and extending the product's reach to the edge.
"We're continuously innovating to provide state-of-the-art AI tools to our users," Shemer says. "Our goal is to make AI accessible and valuable to an even wider range of industries and use cases."
As Azure Video Indexer continues to evolve, Shemer is excited about the potential for new applications and innovations. He envisions a future where the tool is not only a leader in video analysis – but one in which video data enables process optimisation and improvement as it couldn’t before.
"Our vision is to make Azure Video Indexer an indispensable tool for businesses across different sectors," Shemer says. "By continuously innovating and expanding our capabilities, we aim to provide our users with the best possible tools to extract valuable insights from their video content."
Conclusion
Shemer Steinlauf's insights offer a glimpse into the meticulous planning and strategic thinking that underpin successful product management at Microsoft. His dedication to quality, trust, and customer collaboration sets a high standard for innovation and growth in the tech industry. As Azure Video Indexer continues to evolve, Shemer's leadership will undoubtedly guide it toward even greater achievements.
With a steadfast commitment to quality and an unwavering focus on customer needs, Shemer Steinlauf exemplifies the qualities of a successful product manager in today's fast-paced technological landscape. His work with Azure Video Indexer not only showcases the potential of AI-driven video analysis but also highlights the importance of maintaining trust and quality in the pursuit of innovation and growth.
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