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Hugging Face reaches $2 billion valuation to build the GitHub of machine learning

TechCrunch

That consumer bet hasn’t paid off, but the company kept iterating on its natural language processing technology. Due to the success of this libary, Hugging Face quickly became the main repository for all things related to machine learning models — not just natural language processing.

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Four investors explain why AI ethics can’t be an afterthought

TechCrunch

It’s reasonable to ask what role ethics plays in the building of this technology and, perhaps more importantly, where investors fit in as they rush to fund it. So some onus lies on investors to make sure these new technologies are being built by founders with ethics in mind.

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Construction tech startups are poised to shake up a $1.3-trillion-dollar industry

TechCrunch

Allison Xu is an investor at Bain Capital Ventures, where she focuses on investments in the fintech and property tech sectors. As one of the least-digitized sectors of our economy, construction is ripe for technology disruption. A construction tech boom. Technology startups are emerging to help solve these problems.

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Enhancing customer care through deep machine learning at Travelers

CIO

s unique about the [chief data officer] role is it sits at the cross-section of data, technology, and analytics,â?? On the role of the Chief Data Officer: Due to the nature of our business, Travelers has always used data analytics to assess and price risk. Here are some edited excerpts of that conversation. s a unique role and itâ??s

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Venture capital undermines human rights

TechCrunch

The future of technology is determined by a handful of venture capitalists. The world’s 10 leading venture capital firms have, together, invested over $150 billion in technology startups. Europe and China, which in turn are shaping the future of technology. Despite gains, gender diversity in VC funding struggled in 2020.

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Deep Science: AI adventures in arts and letters

TechCrunch

But you can stay tolerably up to date on the most interesting developments with this column, which collects AI and machine learning advancements from around the world and explains why they might be important to tech, startups or civilization. You might even leave a bad review online. Image Credits: Asensio, et.

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V7 snaps up $33M to automate training data for computer vision AI models

TechCrunch

It’s only as good as the models and data used to train it, so there is a need for sourcing and ingesting ever-larger data troves. But annotating and manipulating that training data takes a lot of time and money, slowing down the work or overall effectiveness, and maybe both. V7 even lays out how the two services compare.)

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