Chris Traganos

New for Business Insider: AWS’ capacity+performance issues cost real money w/ some AI customers (eg. Epic Games, Thomson Reuters, Figma) moving workloads to Google and Anthropic, an internal document shows. Highlights the financial toll of AWS’s capacity crunch. https://lnkd.in/gxZUhNe8 #Amazon #AWS

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"While the project began during the pandemic as a joint effort between Seattle and Google.org, developers recognized its greater potential; the system moved to civic tech firm Exygy for broader deployment in 2023." https://lnkd.in/gNaDT8yV

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How do newsrooms thrive when traditional revenue models shift? The Local Media Association (LMA) found a path forward by empowering publishers to secure philanthropic funding. The results of their Lab for Journalism Funding are a testament to the community's desire for quality news: 194 local publishers were equipped with the tools to build pitch decks and write grant applications. Collectively, these organizations raised $35 million in philanthropic revenue. Georges Media Group in Louisiana expanded from 3 to 25 philanthropy-funded reporter positions. By identifying and pursuing these new revenue streams, these publishers are securing their future and the health of their local information ecosystems. Read more in the 2025 Google News Impact Report. https://lnkd.in/eV-ZNVus

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In Amazon's recent financial results report, it was exciting to see two major delivery initiatives spotlighted to improve customer convenience, speed, and accessibility across the U.S. 🚚 Expanding fast delivery in rural areas: Over the past four months, we’ve increased the number of rural communities with access to Amazon’s Same-Day and Next-Day Delivery by 60%, expanding Amazon’s reliable, rapid delivery service to even more locations. 🥬 Scaling grocery delivery: Customers in over 1,000 towns and cities across the U.S. can now add fresh groceries to their Same-Day orders for delivery within hours. And, we’re on track to reach 2,300+ locations by the end of 2025. Every Amazon delivery represents a partnership between advanced technology and the people who make it possible across Transportation tech, business, and operations teams, as well as delivery partners. I’m excited to see these programs continue to scale and reach even more communities as we grow them further into 2026.

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Technology should expand opportunity—especially for people and communities that have too often been left out of new innovation. Today, Meta is launching the AI Glasses Impact Grants to support U.S.-based organizations using AI glasses to drive real-world societal and economic value—from accessibility and education to health, community support, and veterans’ services. I’m especially encouraged by the practical, “in-the-moment” ways wearables can help people stay present while getting what they need—hands-free, in real time. We’ve already seen examples like: Farmers accessing real-time insights about their crops Athletic trainers capturing injury notes hands-free on the field Universities making filmmaking and collaboration more accessible for students If your organization is building (or scaling) work like this—or you know someone who is—I hope you’ll apply and share. Applications are open now and close March 9, 2026. https://lnkd.in/dnw_53Nq https://lnkd.in/dRWaVXZi

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This Scale AI story might matter more than you think. Meta just invested $14.3B to take a 49% stake in Scale AI — and brought Scale’s CEO into its internal “superintelligence” unit. On the surface, it looks like a major bet on data. But look a little deeper, and it’s a shift in how control is consolidating across the AI value chain. Why it matters: – Scale was one of the few trusted, neutral data providers for labeling and evaluation – Now that neutrality is in question, contracts are reportedly getting pulled by OpenAI and Google – Startups and enterprises alike are suddenly reconsidering where their training signal comes from What comes next: – A surge of boutique data providers — decentralized, domain-specific, and more transparent – Startups reframing data control as part of their moat: “We don’t just use models — we own the context” – Infra teams re-evaluating dependencies — either proactively, or reactively when vendor dynamics shift As training data usage becomes more regulated and controlled — moving away from the wild west of early foundation model training — the pressure to secure differentiated data pipelines only increases. When we talk about defensibility in AI, it’s tempting to focus on model IP or feature differentiation. But data leverage — how it’s sourced, labeled, evaluated, and governed — is becoming a more important part of the strategic equation. It’s not quite infrastructure. But it’s no longer a commodity either. It’s a layer of increasing consequence — and one worth watching closely. Are you rethinking your data leverage yet? https://lnkd.in/gx9GPefp

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