Next upDPTV HighlightsEpisode 1 · From SF Tech Week to TechCrunch DisruptTue, Oct 27 · 10:00 AM PDT

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Next upDPTV HighlightsEpisode 1 · From SF Tech Week to TechCrunch DisruptTue, Oct 27 · 10:00 AM PDT

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Practical articles, technical explainers and digests on AI and data. Explore engineering decisions, real use cases and lessons from building solutions.

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Article
DumBO: The simplest Bayesian optimizer
Learn the basic concepts of Bayesian optimization by building a simplistic optimizer.
Manning Publications · Apr 26, 2023
Papers
BloombergGPT: A Large Language Model for Finance
BloombergGPT is a 50 billion parameter language model that is trained on a wide range of financial data. It is validated on standard LLM benchmarks,…
Dmytro Spodarets · Apr 25, 2023
Papers
S-NeRF: Neural Radiance Fields for Street Views
In this paper, the authors propose a new street-view NeRF (S-NeRF) that considers novel view synthesis of both the large-scale background scenes and…
Dmytro Spodarets · Mar 27, 2023
Papers
Universal Guidance for Diffusion Models
Typical diffusion models cannot be conditioned on other modalities without retraining. This work presents a universal guidance algorithm that enables…
Dmytro Spodarets · Mar 17, 2023
Article
AI with Metaverse will change the world in 2030
Integrating AI with the Metaverse is expected to revolutionize how we interact with technology and each other. In 2030, this synergy is projected to…
Hemachandran K · Mar 16, 2023
Papers
3D Generation on ImageNet
In this paper, the authors develop a 3D generator with Generic Priors (3DGP): a 3D synthesis framework with more general assumptions about the…
Dmytro Spodarets · Mar 7, 2023
Papers
3D-aware Conditional Image Synthesis
This paper describes a 3D-aware conditional generative model for controllable photorealistic image synthesis. It integrates 3D representations with…
Dmytro Spodarets · Mar 5, 2023
Papers
SinMDM: Single Motion Diffusion
This paper presents a Single Motion Diffusion Model, dubbed SinMDM, a model designed to learn the internal motifs of a single motion sequence with…
Dmytro Spodarets · Mar 2, 2023
Digest
Data Phoenix Digest - ISSUE 5.2023
Special event "Startup’s Guide to Success in Central and Eastern Europe" at NVIDIA GTC, scaling media ML at Netflix, how to transform time series for…
Dmytro Spodarets · Mar 1, 2023
Papers
LEGO-Net: Learning Regular Rearrangements of Objects in Rooms
LEGO-Net is a data-driven transformer-based iterative method for LEarning reGular rearrangement of Objects in messy rooms. Results demonstrate that…
Dmytro Spodarets · Feb 23, 2023
Papers
OmniObject3D
OmniObject3D is a large vocabulary 3D object dataset featuring massive high-quality real-scanned 3D objects that can be used to facilitate the…
Dmytro Spodarets · Feb 19, 2023
Papers
MEGANE: Morphable Eyeglass and Avatar Network
Megane is a 3D compositional morphable model of eyeglasses that incorporates high-fidelity geometric and photometric interaction effects. To support…
Dmytro Spodarets · Feb 14, 2023