Tootfinder

Viven, which builds AI "digital twins" that grant employees access to crucial information when coworkers are unavailable, emerges from stealth with a $35M seed (Marina Temkin/TechCrunch)
https://techcrunch.com/2025/10/15/e…

Eightfold co-founders raise $35M for Viven, an AI digital twin startup for querying unavailable coworkers | TechCrunch
Viven's seed funding was led by Khosla Ventures and Foundation Capital.

Task-Aware Reduction for Scalable LLM-Database Systems
Marcus Emmanuel Barnes, Taher A. Ghaleb, Safwat Hassan
https://arxiv.org/abs/2510.11813 https://arxi…

Task-Aware Reduction for Scalable LLM-Database Systems
Large Language Models (LLMs) are increasingly applied to data-intensive workflows, from database querying to developer observability. Yet the effectiveness of these systems is constrained by the volume, verbosity, and noise of real-world text-rich data such as logs, telemetry, and monitoring streams. Feeding such data directly into LLMs is costly, environmentally unsustainable, and often misaligned with task objectives. Parallel efforts in LLM efficiency have focused on model- or architecture-l…

Queering The Air
Critically engaged queer commentary...
Great Australian Pods Podcast Directory: #GreatAusPods

Poseidon: A OneGraph Engine
Brad Bebee, \"Umit V. \c{C}ataly\"urek, Olaf Hartig, Ankesh Khandelwal, Simone Rondelli, Michael Schmidt, Lefteris Sidirourgos, Bryan Thompson
https://arxiv.org/abs/2510.11166

Poseidon: A OneGraph Engine
We present the Poseidon engine behind the Neptune Analytics graph database service. Customers interact with Poseidon using the declarative openCypher query language, which enables requests that seamlessly combine traditional querying paradigms (such as graph pattern matching, variable length paths, aggregation) with algorithm invocations and has been syntactically extended to facilitate OneGraph interoperability, such as the disambiguation between globally unique IRIs (as exposed via RDF) vs. l…

Queering food in the 21st Century https://call-for-papers.sas.upenn.edu/cfp/2025/12/08/queering-food-in-the-21st-century

Grounding Large Language Models in Clinical Evidence: A Retrieval-Augmented Generation System for Querying UK NICE Clinical Guidelines
Matthew Lewis, Samuel Thio, Richard JB Dobson, Spiros Denaxas
https://arxiv.org/abs/2510.02967

Grounding Large Language Models in Clinical Evidence: A Retrieval-Augmented Generation System for Querying UK NICE Clinical Guidelines
This paper presents the development and evaluation of a Retrieval-Augmented Generation (RAG) system for querying the United Kingdom's National Institute for Health and Care Excellence (NICE) clinical guidelines using Large Language Models (LLMs). The extensive length and volume of these guidelines can impede their utilisation within a time-constrained healthcare system, a challenge this project addresses through the creation of a system capable of providing users with precisely matched informat…

Queering The Air
Critically engaged queer commentary...
Great Australian Pods Podcast Directory: #GreatAusPods

Starcloud, which launched a satellite with a Nvidia H100 chip in November, says the satellite is running and querying responses from Google's Gemma (Pia Singh/CNBC)
https://www.cnbc.com/2025/12/10/nvidia-backed-starcloud-tr…

‘Greetings, earthlings’: Nvidia-backed Starcloud trains first AI model in space as orbital data center race heats up
The company's Starcloud-1 satellite is running Gemma, an open model from Google, marking the first time in history that an LLM has been trained in outer space.

On the Expressiveness of Languages for Querying Property Graphs in Relational Databases
Hadar Rotschield, Liat Peterfreund
https://arxiv.org/abs/2510.07062 https://

On the Expressiveness of Languages for Querying Property Graphs in Relational Databases
SQL/PGQ is the emerging ISO standard for querying property graphs defined as views over relational data. We formalize its expressive power across three fragments: the read-only core, the read-write extension, and an extended variant with richer view definitions. Our results show that graph creation plays a central role in determining the expressiveness. The read-only fragment is strictly weaker than the read-write fragment, and the latter is still below the complexity class NL. Extending view d…

The Hybrid Multimodal Graph Index (HMGI): A Comprehensive Framework for Integrated Relational and Vector Search
Joydeep Chandra, Satyam Kumar Navneet, Yong Zhang
https://arxiv.org/abs/2510.10123

The Hybrid Multimodal Graph Index (HMGI): A Comprehensive Framework for Integrated Relational and Vector Search
The proliferation of complex, multimodal datasets has exposed a critical gap between the capabilities of specialized vector databases and traditional graph databases. While vector databases excel at semantic similarity search, they lack the capacity for deep relational querying. Conversely, graph databases master complex traversals but are not natively optimized for high-dimensional vector search. This paper introduces the Hybrid Multimodal Graph Index (HMGI), a novel framework designed to brid…