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Voice of AI: AI & mental health, responsibility in real time

  • Writer: Ralph Schwehr
    Ralph Schwehr
  • Nov 13, 2025
  • 4 min read

Data centers are springing up everywhere, capital is swirling like a tornado, but the most vulnerable bottleneck lies in the unseen: trust, mental health, fair data practices. This issue spans from 50-billion-dollar projects to copyright rulings and the question of how we build systems that stabilize people rather than overwhelm them . The common thread: scaling is only progress if safety and dignity grow along with it.



Infrastructure & Energy: The pace in gigawatts


Physics becomes a product: Veir, supported by Microsoft, is bringing superconducting low-voltage cables to data centers . The target output is 3 MW per cable system, requiring 20 times less space than copper – a potential solution to the power and heat density demands of modern AI racks. Pilot projects will begin in 2026, with a full launch planned for 2027.


Anthropic plans to invest $50 billion in US data centers , initially in Texas and New York, in partnership with Fluidstack. Hundreds of permanent jobs and thousands of construction jobs are expected starting in 2026. Compute is location policy: energy access, grid expansion, and local value creation determine the speed of AI development, not just model releases.


Data & Commons: Fairness is a feature, not a footnote


Wikipedia to AI companies: Use the paid enterprise API and stop scraping. Behind this request lie server load, the financing of the public good, and respect for the volunteer community. For product teams, this means: attribution belongs in the interface, compensation in the roadmap, and both in governance.


The law sets guidelines: A German court has ruled that training with song lyrics constitutes copyright infringement. This sends a clear message to the industry: Training data is not "free," and licenses are not a mere nice-to-have. Companies must document consent and chains of rights; otherwise, they risk legal and reputational damage.


Capital & Talent: Selection Phase Instead of Hype


SoftBank is selling its entire Nvidia position. Officially, this isn't an anti-AI move, but rather a shift into new bets; nevertheless, markets tremble when the most prominent AI bull realizes profits. The consequence: funding remains, but selectively. Narratives are no longer enough; sound unit economics are what counts.


According to media reports, Yann LeCun is planning his own startup. When a key figure from the deep learning era moves into the startup scene, it's a sign: "World model" research could iterate faster in focused vehicles, and the race for the next generation of models could accelerate.


Product Stacks: From Demos to SLAs


Agents on the front line: Wonderful raises $100 million (Series A) to establish AI agents in customer service with real SLAs, escalation, and human handoff. The shift: “Wow factor” gives way to operational reliability and measurability.


Low-intensity analytics: WisdomAI receives $50 million (including funding from Kleiner Perkins and Nvidia) for a BI stack in which LLMs primarily formulate queries and provide verified enterprise data as responses. This shifts responsibility from the "speaking model" to the curated data layer.



Key messages

  • Mental health is a product criterion: safety mechanisms must cushion peak loads in support, education, and work.

  • Compute is geopolitics : Whoever orchestrates energy, land and networks sets standards.

  • The commons need governance: Paid data access and clean licenses will become product components.

  • Markets test substance: Capital follows reliable roadmaps, not narratives.

  • Agentic systems are becoming operational: SLAs, escalation, and human-in-the-loop are replacing "labs charm".


List of sources


Conclusion

Data centers and returns define the pace, our treatment of people defines the direction. Those building now must simultaneously protect: license data sources, make attribution transparent, and take the psychological burden of AI interactions seriously (keywords: escalation, quiet periods, human handoff, opt-outs).

" Real-time responsibility is not a hindrance, but an engine of innovation." – Ralph Schwehr


Your Next Step (3-point plan) with OAK AI:

  1. Data audit in 14 days: Licensing status, chains of rights, attribution design, logging.

  2. Agent pilot with SLAs: First-line automation including measurable handover to humans; quality gates for sensitive cases.

  3. Infrastructure Roadmap 24–36 months: Energy/cooling strategy (including new transmission technologies), site due diligence, grid risks.


Contact: info@oakai.de We help with audits, pilot designs and infrastructure scoping.

 
 
 

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