Algorithmia Blog

Emergent // Future: Rethinking Human-Computer Interaction, Data Science Platforms for Enterprise, and more

Issue 51

This week we check out who Microsoft tapped to change the way humans interact with machines, learn why every data science team needs a centralized platform for their work, what we’re reading, and some things to try at home.

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Rethinking Human-Computer Interaction at Microsoft

Microsoft’s new head of research has spent his career building powerful, safe AI.

Now, Eric Horvitz gets to fundamentally change the way humans interact with machines, from flying a plane to designing a virtual personal assistant that lives outside his office.

Horvitz is tasked with harnessing the AI expertise across several Microsoft research labs into core products, as well as establishing a dedicated AI initiative at the Redmond campus.


There’s A (Data Science) Platform For That

Sharing, reusing, and running data science models at scale is not typically part of the data scientist’s workflow and this inefficiency is amplified in a corporate environment where data scientists need to coordinate every move with IT, continuous deployment is a mess, and code reusability is low.

That’s why a data science platform is a necessity for every data science team, big or small.

By centralizing everything except the training, you can focus on building a registry of your models, showing the lineage of how they progressed from one version to the next by making them available as self-contained artifacts that are ready to be plugged into any data pipeline.

This reduces duplication of efforts across teams, identifies and surfaces the best internal and external models, and creates the capability for an AI strategy.

Learn more about how to collaborate with internal stakeholders to build a better data science and machine learning platform.


What We’re Reading


Things to Try at home

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