Streamlit nabs $35M Series B to expand machine learning platform

StreamLit

As a company founded by data scientists, Streamlit may be in a unique position to develop tooling to help companies build machine learning applications. For starters, it developed an open source project, but today the startup announced an expanded beta of a new commercial offering and $35 million Series B funding.

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Kite launches Team Server to extend its code-completion ML assistant to enterprises

The ML-based code completion tool Kite launched its Team Server today, complementing its existing offerings for individual developers with an enterprise-grade version for entire teams of them.
Kite’s Team Server builds on its original coding assistant through deploying GPUs within enterprises’ internal networks, enabling them to create custom-trained models from their proprietary code to meet internal standards, and providing security features like its SSH tunnel proxy for encryption.

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Tips for applying an intersectional framework to AI development

y now, most of us in tech know that the inherent bias we possess as humans creates an inherent bias in AI applications — applications that have become so sophisticated they’re able to shape the nature of our everyday lives and even influence our decision-making. The more prevalent and powerful AI systems become, the sooner the industry must address questions like: What can we do to move away from using AI/ML models that demonstrate unfair bias?

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Spotify open-sources Klio, a framework for AI audio research

This week at the 2020 International Society for Music Information Retrieval Conference, Spotify open-sourced Klio, an ecosystem that allows data scientists to process audio files (or any binary files) easily and at scale. It was built to run Spotify’s large-scale audio intelligence systems and…

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The problem of underrepresented languages snowballs from data sets to NLP models

Just how comprehensively do natural language processing (NLP) pipelines support widely spoken languages? A recent study coauthored by researchers at Clarkson University and Iona College sought to investigate the degree to which NLP tools understand eight dialects.

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