Category: Uncategorized
-
Content Creators in the Adult Industry Want a Say in AI Rules
A group that includes sex workers, sex tech businesses, and sex educators has demanded a seat at the table to shape AI regulations that they say could lead to discrimination against them. Read more
-
¿Comprenden los consejos de administración su nuevo papel en la ciberseguridad?
Julie Ragland fue CIO de la empresa de fabricación de vehículos Navistar, y ha ocupado puestos de liderazgo de TI en Adient y Johnson Controls. Para Ragland, que también forma parte de varios consejos de administración de agencias estatales y organizaciones sin ánimo de lucro, una de las mayores responsabilidades de los consejos de administración… Read more
-
Is Unchecked Churn Holding Back Your AI Performance? This AI Paper Unveils CHAIN: Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn
Deep reinforcement learning (DRL) faces a critical challenge due to the instability caused by “churn” during training. Churn refers to unpredictable changes in the output of neural networks for states that are not included in the training batch. This problem is particularly troublesome in reinforcement learning (RL) because of its inherently non-stationary nature, where policies… Read more
-
Le principali tecnologie che sconvolgeranno il mondo del business nel 2025
A volte le tecnologie più promettenti sono proprio davanti ai nostri occhi: basta riconoscere il valore aziendale insito nel loro utilizzo. Per avere un’idea delle più promettenti che le aziende incontreranno nel corso dei prossimi mesi, abbiamo intervistato una serie di leader IT chiedendo loro quali pensano che siano i sistemi che potranno aiutare le… Read more
-
The United Nations Wants to Treat AI With the Same Urgency as Climate Change
A UN report proposes that the organization take a much more active role in the monitoring and oversight of AI. Read more
-
Qwen 2.5 Models Released: Featuring Qwen2.5, Qwen2.5-Coder, and Qwen2.5-Math with 72B Parameters and 128K Context Support
The Qwen team from Alibaba has recently made waves in the AI/ML community by releasing their latest series of large language models (LLMs), Qwen2.5. These models have taken the AI landscape by storm, boasting significant capabilities, benchmarks, and scalability upgrades. From 0.5 billion to 72 billion parameters, Qwen2.5 has introduced notable improvements across several key… Read more
-
SynSUM: A Synthetic Benchmark for Integrating Clinical Notes with Structured Data
Electronic Health Records (EHRs) present a wealth of information, combining structured tabular data and unstructured clinical notes. This valuable resource forms the foundation for training clinical decision support systems and automating diagnosis and treatment planning processes. While large language models (LLMs) can utilize unstructured text, they lack interpretability, an important factor in high-risk clinical applications.… Read more
-
Palmer Luckey Is Bringing Anduril Smarts to Microsoft’s Military Headset
The founder of Oculus VR is returning to headsets—this time for the battlefield. Read more
-
Kyutai Open Sources Moshi: A Breakthrough Full-Duplex Real-Time Dialogue System that Revolutionizes Human-like Conversations with Unmatched Latency and Speech Quality
The field of spoken dialogue systems has evolved significantly over the years, moving beyond simple voice-based interfaces to complex models capable of sustaining real-time conversations. Early systems such as Siri, Alexa, and Google Assistant pioneered voice-activated interactions, allowing users to trigger specific actions through voice commands. These systems, while groundbreaking, were limited to basic tasks… Read more
-
DFDG: Enhancing One-Shot Federated Learning with Data-Free Dual Generators for Improved Model Performance and Reduced Data Overlap
Data-Free Knowledge Distillation (DFKD) methods transfer knowledge from teacher to student models without real data, using synthetic data generation. Non-adversarial approaches employ heuristics to create data resembling the original, while adversarial methods utilize adversarial learning to explore distribution spaces. One-Shot Federated Learning (FL) addresses communication and security challenges in standard FL setups, enabling collaborative model… Read more