When Structured Sparse Autoencoders Learn Consistent Concepts Across Modalities
Researchers propose Structured Sparse Autoencoders to help vision-language models learn consistent, non-fragmented concepts across both visual and textual modalities.
Researchers propose Structured Sparse Autoencoders to help vision-language models learn consistent, non-fragmented concepts across both visual and textual modalities.
Amazon Web Services has introduced serverless customization capabilities on SageMaker AI to simplify the fine-tuning of NVIDIA's Nemotron 3 models.
A newly released report on China's venture capital sector highlights a major shift toward hard tech, with embodied AI alone attracting over 65.6 billion yuan in funding.
Hugging Face's chief executive argues that businesses are increasingly shifting away from proprietary AI subscriptions in favor of open-source alternatives.
The study reveals that large language models treat answer correctness and question answerability as two distinct dimensions, suggesting that a single confidence score is insufficient for proper model abstention.
Researchers have released PLURAL, a large-scale dataset based on global survey data designed to help align language models with diverse international value systems.
Despite a surge in South Korean stock indices driven by soaring AI-related profits at Samsung and SK Hynix, historically low valuations present a potential entry point for investors.
DJI has introduced the EV50, its first vertical takeoff and landing fixed-wing cargo drone, which reportedly set an altitude record during a scientific expedition on Mount Everest.
Equinix is planning two new data centers in Amsterdam, though local restrictions will limit construction to a quarter of the permitted development capacity.
SMetric is a scheduling framework designed specifically for agentic workloads, optimizing serving efficiency by prioritizing complete agent responses and leveraging high KV-cache reuse.
Microsoft is integrating artificial intelligence into its Windows 11 update pipeline to identify and patch security vulnerabilities more rapidly.
Huawei has confirmed its upcoming Mate 90 smartphone series will feature HarmonyOS 7 and a new Kirin chip utilizing advanced transistor density technology.
Henry Schein One has deployed an AI-powered quality verification system on Amazon SageMaker to analyze dental X-rays in real time across thousands of clinics.
Chinese artificial intelligence laboratories are increasingly developing proprietary chips to improve hardware-software integration and reduce long-term operational costs despite high upfront financial risks.
AWS has outlined four deployment patterns for running quantized machine learning models optimized by Unsloth on its SageMaker and cloud container infrastructure.
MIT researchers have developed FloatForm, a swarm of small aquatic robots capable of self-assembling into reconfigurable floating structures.
WebSwarm is a recursive multi-agent framework designed to improve the depth and coverage of web search tasks by dynamically orchestrating specialized sub-agents.
Chinese artificial intelligence startup DeepSeek has initiated an in-house chip development project focused on optimizing inference workloads and reducing reliance on Nvidia hardware.
AWS has demonstrated how to implement disaggregated prefill and decode using vLLM on SageMaker HyperPod to optimize large language model inference.
To prevent context window overload in long-horizon multimodal dialogues, this paper introduces an agent architecture that stores visual information in an external memory structure.
The Prismata framework is designed to secure autonomous web agents against cross-site prompt injection attacks by isolating untrusted web content from core agent instructions.
The paper identifies a credit assignment failure in critic-free reinforcement learning for language models and proposes a tail-aware calibration method to address it.
Researchers propose a Representation-as-a-Judge method that leverages the internal representations of small language models to evaluate outputs efficiently without relying on text generation.
This article explores the ongoing debate surrounding the return on investment for massive capital expenditures in the artificial intelligence sector.