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What we're seeing
Enterprise AI Agent Rollout Outpaces Data Trust and Readiness
Enterprise adoption of agentic AI is accelerating fast — Siemens deepening its NVIDIA partnership for self-verifying agentic AI in chip design, Manulife expanding its Microsoft AI-governance partnership, and a wave of infrastructure launches (NVIDIA GPU-accelerated data processing, Dell exascale storage, new AI chip generations) — even as a new Google Cloud survey shows the underlying data foundation isn't ready: companies have AI access to only 45% of their data on average, data laggards see access fall to 30% or less, and only about half of organizations trust their AI agents' decisions. Meanwhile, insider selling at enterprise-AI bellwether C3.ai (CEO Thomas Siebel offloading $4.8M in shares) hints at investor caution layered under the adoption hype.
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Signals we're tracking
Satellite-Terrestrial Network Integration Acceleration
Increased investment and launches in hybrid satellite-cellular networks across telecom industry; competitive responses from other carriers; regulatory activity around satellite spectrum; expansion of emergency/rural connectivity use cases
Patterns we're watching ›
Where sources disagree
JPMorgan Chase & Co.
Both facts report JPMorgan Chase & Co.'s revenue for the same fiscal period (FY 2025) with the same observation date (2025-12-31), but with different values: $182.447 billion vs. $185 billion. The ~1.4% difference ($2.553 billion) is too large to be explained by rounding alone and represents conflicting data for the identical time period.
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Press releaseGlobeNewswire· March 24, 2026

0G Labs Trained World's Largest Decentralized AI Model at 107B Parameters in 2025 - Eight Months Before This Week's Industry Headlines

View original at globenewswire.com
0G Labs Trained World's Largest Decentralized AI Model at 107B Parameters in 2025 - Eight Months Before This Week's Industry Headlines San Francisco, CA, March 24, 2026 (GLOBE NEWSWIRE) -- While the crypto industry celebrated Bittensor's Covenant-72B this week as a breakthrough in decentralized AI training, 0G Labs had…
Opening lines of the source · GlobeNewswire · short snapshot — read the full document at the original

What we drew from this source

The claims Via News extracted from this document. We point to the source; we don't replace it.

  • While the industry celebrated Bittensor's 72B model this week, 0G had already trained 107B parameters in July 2025 - 48% larger, 8 months earlier

    60% confidence

  • This isn't about breaking records, it's about building AI as a public good

    60% confidence

  • We proved decentralized infrastructure can train a 107 billion parameter model in 2025, before anyone else

    60% confidence

  • 0G's approach achieves approximately 95% cost reduction compared to centralized GPU cluster training

    60% confidence

  • This week's headlines celebrating 72 billion parameters as a milestone missed that 0G had already operated at significantly larger scale

    60% confidence

  • 0G set the benchmark for decentralized AI training on standard consumer bandwidth

    60% confidence

  • The industry is finally paying attention to decentralized AI

    60% confidence

  • Distributed, open-source AI training is complementary to centralized approaches and will play a growing role in frontier model development

    60% confidence

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