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Translated’s DVPS: Context Meets Cognition

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Manage episode 499875358 series 3498549
Content provided by Eddie Arrieta and MultiLingual Media. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Eddie Arrieta and MultiLingual Media or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

On July 3, 2025, at Translated’s unique “PI Campus” in Rome—eight luxury villas retrofitted into pools‑and‑massages‑equipped offices—The Translated team kicked off Project DVPS (Diversibus Vis Plurima Solvo). Backed by a €29 million EU grant, DVPES unites 70+ top AI researchers from EPFL, Oxford, ETH Zurich, FBK Trento and more to build the next generation of multimodal foundation models.

By fusing language with handwriting, audio, video, sensor data and beyond, and by moving from sequential “chain‑of‑thought” to real‑time “learn‑by‑doing” reasoning, the project aims to shatter today’s context, reasoning and continual‑learning limitations in LLMs—and push toward truly grounded, human‑level AI.

  continue reading

644 episodes

Artwork
iconShare
 
Manage episode 499875358 series 3498549
Content provided by Eddie Arrieta and MultiLingual Media. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Eddie Arrieta and MultiLingual Media or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

On July 3, 2025, at Translated’s unique “PI Campus” in Rome—eight luxury villas retrofitted into pools‑and‑massages‑equipped offices—The Translated team kicked off Project DVPS (Diversibus Vis Plurima Solvo). Backed by a €29 million EU grant, DVPES unites 70+ top AI researchers from EPFL, Oxford, ETH Zurich, FBK Trento and more to build the next generation of multimodal foundation models.

By fusing language with handwriting, audio, video, sensor data and beyond, and by moving from sequential “chain‑of‑thought” to real‑time “learn‑by‑doing” reasoning, the project aims to shatter today’s context, reasoning and continual‑learning limitations in LLMs—and push toward truly grounded, human‑level AI.

  continue reading

644 episodes

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