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OS-Genesis: A Novel GUI Data Synthesis Pipeline that Reverses the Conventional Trajectory Collection Process
Designing GUI agents that perform human-like tasks on graphical user interfaces faces a critical obstacle: collecting high-quality trajectory data for training. Existing methods depend on expensive and time-consuming human supervision or on generating synthetic data, which can hardly reflect the diversity and dynamics in the real world. Those constraints significantly limit the GUI agents’ scalability…
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Meta AI Introduces EWE (Explicit Working Memory): A Novel Approach that Enhances Factuality in Long-Form Text Generation by Integrating a Working Memory
Large Language Models (LLMs) have revolutionized text generation capabilities, but they face the critical challenge of hallucination, generating factually incorrect information, particularly in long-form content. Researchers have developed Retrieved-Augmented Generation (RAG) to address this issue, which enhances factual accuracy by incorporating relevant documents from reliable sources into the input prompt. While RAG has shown promise,…
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REDA: A Novel AI Approach to Multi-Agent Reinforcement Learning That Makes Complex Sequence-Dependent Assignment Problems Solvable
Power distribution systems are often conceptualized as optimization models. While optimizing agents to perform tasks works well for systems with limited checkpoints, things begin to go out of hand when heuristics tackle multiple tasks and agents. Scaling dramatically increases the complexity of assignment problems, often NP-hard and nonlinear. Optimization methods become the white elephants in…
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Meet Android Agent Arena (A3): A Comprehensive and Autonomous Online Evaluation System for GUI Agents
The development of large language models (LLMs) has significantly advanced artificial intelligence (AI) across various fields. Among these advancements, mobile GUI agents—designed to perform tasks autonomously on smartphones—show considerable potential. However, evaluating these agents poses notable challenges. Current datasets and benchmarks often rely on static frame evaluations, which provide snapshots of app interfaces for agents…
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This AI Paper Introduces LLM-as-an-Interviewer: A Dynamic AI Framework for Comprehensive and Adaptive LLM Evaluation
Evaluating the real-world applicability of large language models (LLMs) is essential to guide their integration into practical use cases. One key challenge in assessing LLMs is their tendency to exploit fixed datasets during testing, leading to inflated performance metrics. Static evaluation frameworks often fail to determine a model’s ability to adapt to feedback or provide…
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iOS 18.2 was killing my iPhone’s battery until I turned off this feature
If your battery life has worsened since you upgraded to iOS 18, here’s how I fixed the problem after weeks of tweaking my phone’s settings.
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USB-C Is Now the Law of the Land in Europe
Apple has already pulled devices to comply with the European Commission’s new Common Charger Directive.
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A Book App Used AI to ‘Roast’ Its Users. It Went Anti-Woke Instead
One year-end summary from Fable, a social app where people share what books the read, told the user “Don’t forget to surface for the occasional white author, OK?”
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Meet Josh Patterson, a 2024 BigDATAwire Person to Watch
We live in a world of big data and big compute. But what about big query engines? One of the startups developing software to keep up with big data and big compute is Voltron Data, which is headed by Josh Patterson. Patterson co-founded Voltron Data in 2021 with pandas creator Wes McKinney (a 2018 Person…
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Financial Services Struggle to Align Data with AI Goals
In a data-driven world, financial services organizations are racing to harness the transformative power of AI. However, this journey is not without challenges. We know AI has a data problem. Without the right data in the right place, even the most sophisticated AI strategies fall short. IT leaders in the financial services sector understand that…