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’ …
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]
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…
Show HN: AI memory with biological decay (52% recall)
Most RAG setups fail because they treat memory like a static filing cabinet. When every transient bug fix or abandoned rule is stored forever, the context window eventually chokes on noise, spiking to…
New data center will be partially powered by human brain cells for the first time
A startup is experimenting with data centers powered by lab-grown human neurons, testing whether living cells can offer a more efficient alternative to traditional computing.…
Pressure on DOJ to prosecute Anthony Fauci grows after adviser indicted—with days left to charge COVID ‘lies’
Just two weeks remain before the five-year legal deadline to indict Fauci for denying under oath that he funded "gain of function" experiments that modified bat coronaviruses in the same city where th…
Visualizing Loss Landscapes of Neural Networks [P]
Hey r/MachineLearning , Visualizing the loss landscape of a neural network is notoriously tricky since we can't naturally comprehend million-dimensional spaces. We often rely on basic 2D contour analo…
Infisical (YC W23) Is Hiring Full Stack Software Engineers (Remote)
Infisical https://infisical.com/ is looking to hire exceptional talent to join our teams in building the open source security infrastructure stack for the AI era. We're building a generational compan…
Celebrating 20 years of Google Translate: Fun facts, tips and new features to try
Google’s sharing 20 fun facts to celebrate Google Translate turning 20, from its roots as a 2006 AI experiment to supporting almost 250 languages today.…
Higher glass transition temperatures reduce thermal stress in cryopreservation
Cryopreservation by vitrification could transform fields ranging from organ transplantation to wildlife conservation, but critical physical challenges remain in scaling this approach from microscopic …
HeLa-Mem: Hebbian Learning and Associative Memory for LLM Agents
Long-term memory is a critical challenge for Large Language Model agents, as fixed context windows cannot preserve coherence across extended interactions. Existing memory systems represent conversatio…
LLMs Corrupt Your Documents When You Delegate
Large Language Models (LLMs) are poised to disrupt knowledge work, with the emergence of delegated work as a new interaction paradigm (e.g., vibe coding). Delegation requires trust - the expectation t…
A/B Testing Pitfalls: What Works and What Doesn’t with Real Data
Why Most “Winning” Experiments Fail in Production and How Top Companies Avoid It…