Pith. sign in

The impact of the AI revolution on asset management

1 Pith paper cite this work. Polarity classification is still indexing.

1 Pith paper citing it
abstract

Recent progress in deep learning, a special form of machine learning, has led to remarkable capabilities machines can now be endowed with: they can read and understand free flowing text, reason and bargain with human counterparts, translate texts between languages, learn how to take decisions to maximize certain outcomes, etc. Today, machines have revolutionized the detection of cancer, the prediction of protein structures, the design of drugs, the control of nuclear fusion reactors etc. Although these capabilities are still in their infancy, it seems clear that their continued refinement and application will result in a technological impact on nearly all social and economic areas of human activity, the likes of which we have not seen before. In this article, I will share my view as to how AI will likely impact asset management in general and I will provide a mental framework that will equip readers with a simple criterion to assess whether and to what degree a given fund really exploits deep learning and whether a large disruption risk from deep learning exist.

citation-role summary

background 1

citation-polarity summary

fields

cs.CV 1

years

2025 1

verdicts

CONDITIONAL 1

roles

background 1

polarities

unclear 1

representative citing papers

Total-Editing: Head Avatar with Editable Appearance, Motion, and Lighting

cs.CV · 2025-05-26 · conditional · novelty 6.0

Total-Editing is a unified 3D head avatar framework that separately controls appearance, motion, and lighting through an intrinsically decomposed neural radiance field, and reports stronger identity, expression, pose, and LPIPS metrics than reenactment baselines on VFHQ.

citing papers explorer

Showing 1 of 1 citing paper.

  • Total-Editing: Head Avatar with Editable Appearance, Motion, and Lighting cs.CV · 2025-05-26 · conditional · none · ref 77 · internal anchor

    Total-Editing is a unified 3D head avatar framework that separately controls appearance, motion, and lighting through an intrinsically decomposed neural radiance field, and reports stronger identity, expression, pose, and LPIPS metrics than reenactment baselines on VFHQ.