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Texas Just Shook Up the AI Boom. Dallas-Fort Worth Is Feeling the Pressure

A historic election has raised new questions about billions in planned data-center investments. But the biggest fight is over who pays for the infrastructure.

Texas Just Shook Up the AI Boom. Dallas-Fort Worth Is Feeling the Pressure

We haven't written up this one. Inc. has the full story — the link below goes straight to it.

Read the original at inc.com →

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AI-Generated Movie Heading Theaters

Artificial intelligence is moving from experimental videos to the big screen. Fable Studio CEO Edward Saatchi says a team of just 30 people spent nine months creating Gods Don’t Give Gifts, an…

Come Code, IDE e Wiki di osFoundry rendono revisionabile il lavoro di più agenti AI in parallelo

Sono le 16 e da dopo pranzo tre agenti di coding lavorano sullo stesso repository. Uno ha sistemato l'arrotondamento del totale del carrello, uno ha aggiunto un codice sconto, uno ha scritto i test.

  • osFoundry unifica chat, agenti AI, file e strumenti in una singola finestra
  • Sistema consente assegnazione di task a più agenti AI contemporaneamente
  • Funzionalità di revisione facilitano la collaborazione e riducono conflitti

LLM Returns Invalid JSON Once in a While: Structured Outputs vs Validate-and-Retry

TL;DR: If json.loads() on model output fails only occasionally, there are three distinct causes: truncation, stray prose or code fences around the JSON, and schema drift (valid JSON, wrong shape).

  • LLM JSON parsing failures can stem from truncation, extraneous text, or schema mismatches.
  • Structured outputs and typed models help eliminate extraneous text and schema mismatches.
  • Validation-and-retry approach with logging raw responses is recommended for handling failures.

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