30 results for "ai experiment"
Let the AI Do the Experimenting
Using autoresearch to optimise marketing campaigns under budget constraints The post Let the AI Do the Experimenting appeared first on Towards Data Science .…
Google launches Ask YouTube, a conversational AI search "experiment" that generates pages with videos and text summaries, for Premium users in the US aged 18+ (Jay Peters/The Verge)
Jay Peters / The Verge : Google launches Ask YouTube, a conversational AI search “experiment” that generates pages with videos and text summaries, for Premium users in the US aged 18+ — ‘Ask YouTube’ …
An experimental cafe run by AI opens in Stockholm
The cafe has only been open for a week but already draws between 50 and 80 curious customers a day. Read more at straitstimes.com. Read more at straitstimes.com.…
Show HN: SuperVoiceMode dictation experiment became an AI voice interface
Talk to your Mac. Free AI-corrected dictation forever, plus a voice assistant for Claude, Codex, and local LLMs. Fully on-device — nothing ever leaves it.…
Humanoid robots to become baggage handlers in Japan airport experiment
Japan Airlines will introduce the robots for trial run at a Tokyo airport amid country’s surge in inbound tourism and worsening labour shortages Japan’s famously conscientious but overburdened baggage…
Google transforms YouTube into Search with new experimental AI mode
Is this really the future?…
Fast experiment on T4 GPU. Self play training on Dark Hex (Colab notebook) [P]
Case-Specific Rubrics for Clinical AI Evaluation: Methodology, Validation, and LLM-Clinician Agreement Across 823 Encounters
Objective. Clinical AI documentation systems require evaluation methodologies that are clinically valid, economically viable, and sensitive to iterative changes. Methods requiring expert review per sc…
Cloudless-Training: A Framework to Improve Efficiency of Geo-Distributed ML Training
Geo-distributed ML training can benefit many emerging ML scenarios (e.g., large model training, federated learning) with multi-regional cloud resources and wide area network. However, its efficiency i…
RCSB PDB AI Help Desk: retrieval-augmented generation for protein structure deposition support
Motivation: Structural Biologists have contributed more than 245,000 experimentally determined three-dimensional structures of biological macromolecules to the Protein Data Bank (PDB). Incoming data a…
Representation Homogeneity and Systemic Instability in AI-Dominated Financial Markets: A Structural Approach
This paper investigates how similarity in the informational representation of market states among Artificial Intelligence (AI) trading agents can generate systemic instability in financial markets. We…
PivotMerge: Bridging Heterogeneous Multimodal Pre-training via Post-Alignment Model Merging
Multimodal Large Language Models (MLLMs) rely on multimodal pre-training over diverse data sources, where different datasets often induce complementary cross-modal alignment capabilities. Model mergin…
MAE-Based Self-Supervised Pretraining for Data-Efficient Medical Image Segmentation Using nnFormer
Transformer architectures, including nnFormer,have demonstrated promising results in volumetric medical image segmentation by being able to capture long-range spatial interactions. Although they have …
Would AI in 2011 Have Shaped the Modern Web?
Would AI in 2011 Have Shaped the Modern Web? Let’s run a thought experiment: What if AI...…
How well does S3 checkpointing hold up when running Airflow on spot?
This article explores what actually happens when Apache Airflow runs on spot instances, using real experiments to simulate node preemption across both control plane and worker nodes. It walks through …
YouTube Tests AI-Powered 'Ask YouTube' Conversational Search Feature
YouTube is testing a new search feature that it says is meant to feel more like a conversation than a search interface. Users are able to ask complex questions in natural language, receive results tha…
AI prefers resumes written by itself: Self-preferencing in Algorithmic Hiring
As artificial intelligence (AI) tools become widely adopted, large language models (LLMs) are increasingly involved on both sides of decision-making processes, ranging from hiring to content moderatio…
An Intelligent Fault Diagnosis Method for General Aviation Aircraft Based on Multi-Fidelity Digital Twin and FMEA Knowledge Enhancement
Fault diagnosis of general aviation aircraft faces challenges including scarce real fault data, diverse fault types, and weak fault signatures. This paper proposes an intelligent fault diagnosis frame…
CAP-CoT: Cycle Adversarial Prompt for Improving Chain of Thoughts in LLM Reasoning
Chain-of-Thought (CoT) prompting has emerged as a simple and effective way to elicit step-by-step solutions from large language models (LLMs). However, CoT reasoning can be unstable across runs on lon…
Constraint-Based Analysis of Reasoning Shortcuts in Neurosymbolic Learning
Neurosymbolic systems can satisfy logical constraints during learning without achieving the intended concept-label correspondence; this is a problem known as reasoning shortcuts. We formalize reasonin…
When AI reviews science: Can we trust the referee?
The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the same time, modern large language models (LLMs) of…
Modeling Induced Pleasure through Cognitive Appraisal Prediction via Multimodal Fusion
Multimodal affective computing analyzes user-generated social media content to predict emotional states. However, a critical gap remains in understanding how visual content shapes cognitive interpreta…
MarketBench: Evaluating AI Agents as Market Participants
Markets are a promising way to coordinate AI agent activity for similar reasons to those used to justify markets more broadly. In order to effectively participate in markets, agents need to have infor…
LLM-Augmented Traffic Signal Control with LSTM-Based Traffic State Prediction and Safety-Constrained Decision Support
Traffic signal control is a critical task in intelligent transportation systems, yet conventional fixed-time and rule-based methods often struggle to adapt to dynamic traffic demand and provide limite…
Representational Curvature Modulates Behavioral Uncertainty in Large Language Models
In autoregressive large language models (LLMs), temporal straightening offers an account of how the next-token prediction objective shapes representations. Models learn to progressively straighten the…
CT-FineBench: A Diagnostic Fidelity Benchmark for Fine-Grained Evaluation of CT Report Generation
The evaluation of generated reports remains a critical challenge in Computed Tomography (CT) report generation, due to the large volume of text, the diversity and complexity of findings, and the prese…
XGRAG: A Graph-Native Framework for Explaining KG-based Retrieval-Augmented Generation
Graph-based Retrieval-Augmented Generation (GraphRAG) extends traditional RAG by using knowledge graphs (KGs) to give large language models (LLMs) a structured, semantically coherent context, yielding…
Google is testing AI chatbot search for YouTube
Google is trying out an AI Mode-like search experience for YouTube. The company is now testing "a new way to search on YouTube that feels more like a conversation," with results pulling in things like…
AI reality check: Here's what three companies learned building wallets, homes, and games
Executives from Citi, Home Depot, and Capcom describe early work with AI agents While AI agents have moved from experimental tools to customer-facing workers in a matter of months, the next challenge …
Got OpenAI's privacy filter model running on-device via ExecuTorch
Been experimenting with running OpenAI's privacy filter model on mobile through ExecuTorch. Sharing in case it's useful to others working on similar problems. Setup: - Runtime: ExecuTorch - Memory foo…