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Axios · Amy Harder

What it's like inside the data centers powering the AI boom

ASHBURN, Va. – A test server hall tucked inside America's "data center alley" offers a rare firsthand look inside the AI boom. Why it matters: Seeing how AI is physically made helps sharpen our understanding of the unprecedented data center buildout that is becoming increasingly unpopular around…

LatamList · Araceli Dominguez

Braven raises $4.6M seed round to expand AI insurance infrastructure platform

Braven, an insurance infrastructure startup founded by a Colombian team, raised a $4.6M seed round led by Collide… The post Braven raises $4.6M seed round to expand AI insurance infrastructure platform appeared first on LatamList.

LatamList · Araceli Dominguez

Draiven raises $600K and acquires Rabt Automation

Brazilian AI startup Draiven raised $600K in a round led by Asterismus Capital and acquired Rabt Automation, a… The post Draiven raises $600K and acquires Rabt Automation appeared first on LatamList.

Rest of World · Rina Chandran and Michael Beltran

The AI-powered World Cup runs on thousands of data workers

Human annotators in Brazil, Cambodia, and the Philippines are tracking every movement in the football tournament for teams, broadcasters, and the betting industry.

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Bloomberg Technology · Mie Dahl, Andreina Itriago

Israeli AI Startup Eyes Expansion in Trump-Aligned Latin America

An Israeli artificial intelligence startup is betting that election victories by Trump-aligned leaders across Latin America will boost demand for its government-focused cybersecurity products.

arXiv NLP · Alaina Brandt

Can an Old Dog Be Taught New Tricks? Taking LLMs Beyond Sentence Level Translation

arXiv:2607.14040v1 Abstract: Automatic translation systems, from CAT tools to MT, overwhelmingly treat translation as a sentence-by-sentence act. This paper asks whether LLMs can be moved beyond that paradigm through whole-document, corpus-informed translation.

arXiv NLP · Weicheng Ma, John Guerrerio

Scalable and Culturally Specific Stereotype Dataset Construction via Human-LLM Collaboration

arXiv:2607.07895v1 Abstract: Research on stereotypes in large language models (LLMs) has largely focused on English-speaking contexts, due to the lack of datasets in other languages and the high cost of manual annotation in underrepresented cultures.

arXiv NLP · Dhruv Agarwal, Anya Shukla

PLURAL: A Global Dataset for Value Alignment

arXiv:2607.08034v1 Abstract: Large language models (LLMs) are used worldwide, yet disproportionately reflect Western values, limiting their ability to represent diverse value systems.

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