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The Download: metric weaknesses and AI elephant warnings

View original at technologyreview.com
MIT Technology Review - Ai Research Title: The Download: metric weaknesses and AI elephant warnings Date: 2026-06-29 12:10 Source: https://www.technologyreview.com/2026/06/29/1139834/the-download-metric-weaknesses-ai-elephant-warnings/ <p><em>This is today’s edition of </em><a href="https://forms.technologyreview.com/n…
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  • Google capping Meta's access to Gemini AI compute has disrupted and delayed some Meta AI projects.

    60% confidence
  • Powerful AI capable of altering the landscape of cyberwarfare cannot remain solely in American hands; Chinese AI firms must match US capabilities.

    60% confidence
  • There have been some 3,000 human casualties from human-elephant conflicts in India in the last five years, and over 1,000 elephant deaths since 2014.

    60% confidence
  • Research shows Gen Z are more likely to believe and pass on misinformation when they feel a sense of common identity with the person who shared it, with social media shifting credibility from community to identity-based authority.

    60% confidence
  • India is home to about 60% of the world's wild Asian elephants, with around 80% of their habitat outside protected areas, leading to deadly human-wildlife conflicts.

    60% confidence
  • Security researchers say Zhipu AI is poised to reset the AI race after its model matched Anthropic's Mythos in finding security bugs.

    60% confidence
  • Android phones gave Venezuelan earthquake victims between seconds and up to two minutes of advance notice before the seismic events struck.

    60% confidence
  • US restrictions on AI models have sparked alarm that they are boosting China's AI progress.

    60% confidence
  • Zhipu AI's model still cannot match Anthropic or OpenAI on general tasks despite matching Mythos in security bug detection.

    60% confidence
  • Chipmakers are profiting off AI at the expense of everyone else.

    60% confidence
  • Severe weather is now the leading cause of loss for data centers, as extreme heat puts AI-heavy data centers under significant operational pressure.

    60% confidence
  • Appropriate safeguards are now in place for the release of Anthropic's Mythos 5 model to trusted organizations.

    60% confidence
  • External metrics and data can never capture what is truly important; worse, they inevitably redefine one's core sense of what is important, whether or not one is aware of the trap.

    60% confidence
  • A new study suggests 6.4 to 7.8 hours of sleep is the optimal range; too much sleep may be as harmful as too little.

    60% confidence
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What we're seeing
AI Funding Surge: Capital Floods Fintech, Foundation Models, and Autonomous Systems
A concentrated burst of AI-linked funding on 2026-08-28 pushed well over $1.5B into companies spanning fraud/identity fintech (Socure, which also acquired Fravity), foundation models (Stability AI), AI agents and enterprise tooling (Instinct, Generalist AI, Emerald AI, Owner), and AI-adjacent autonomous/aerospace ventures (Gatik, Regent Craft). The breadth and simultaneity of these rounds signal that investor appetite for AI is not concentrated in a single vertical but is broadening into applied and infrastructure-adjacent domains, with consolidation (Socure-Fravity) beginning alongside fresh capital formation.
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EPKINLY Regulatory-Clinical Success Cascade
High probability of expanded label indications, additional combination approvals, and competitive positioning strength in follicular lymphoma market. Predicts positive commercial uptake and potential accelerated review for related indications.
Patterns we're watching ›
Where sources disagree
Morgan Stanley & Co. LLC
The same metric (eps) for the same entity (Morgan Stanley & Co. LLC) reported for the identical fiscal period (Q1 2026) and observation date (2026-03-31) has two conflicting values: 3.43 USD_per_share vs 3.08 USD. This is not a temporal change — both observations claim to measure the same point in time. The ~10% discrepancy (0.35 USD difference) is material for a financial metric.
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