· ai
[Paper] Rectifying LLM Thought from Lens of Optimization
Recent advancements in large language models (LLMs) have been driven by their emergent reasoning capabilities, particularly through long chain-of-thought (CoT) ...
-
- · ai
At NeurIPS, NVIDIA Advances Open Model Development for Digital and Physical AI
Researchers worldwide rely on open-source technologies as the foundation of their work. To equip the community with the latest advancements in digital and physi...
- · ai
AI models block 87% of single attacks, but just 8% when attackers persist
One malicious prompt gets blocked, while ten prompts get through. That gap defines the difference between passing benchmarks and withstanding real-world attacks...
- · ai
AI-native 6G: From networks to intelligence fabrics
“Network language models” will coordinate complex interactions among intelligent components, computational infrastructure, access points, data centers, and more...
- · ai
[Paper] HERMES: Heterogeneous Application-Enabled Routing Middleware for Edge-IoT Systems
The growth of the Internet of Things has enabled a new generation of applications, pushing computation and intelligence toward the network edge. This trend, how...
- · ai
Learning, Hacking, and Shipping ML
Vyacheslav Efimov on AI hackathons, data science roadmaps, and how AI meaningfully changed day-to-day ML Engineer work The post Learning, Hacking, and Shipping...
- · ai
[Paper] Integrating Artificial Intelligence and Mixed Integer Linear Programming: Explainable Graph-Based Instance Space Analysis in Air Transportation
This paper analyzes the integration of artificial intelligence (AI) with mixed integer linear programming (MILP) to address complex optimization challenges in a...
- · ai
OpenAGI emerges from stealth with an AI agent that it claims crushes OpenAI and Anthropic
A stealth artificial intelligence startup founded by an MIT researcher emerged this morning with an ambitious claim: its new AI model can control computers bett...
- · ai
[Paper] Revisiting Direct Encoding: Learnable Temporal Dynamics for Static Image Spiking Neural Networks
Handling static images that lack inherent temporal dynamics remains a fundamental challenge for spiking neural networks (SNNs). In directly trained SNNs, static...
- · ai
[Paper] Current Challenges of Symbolic Regression: Optimization, Selection, Model Simplification, and Benchmarking
Symbolic Regression (SR) is a regression method that aims to discover mathematical expressions that describe the relationship between variables, and it is often...
- · ai
[Paper] In-context Inverse Optimality for Fair Digital Twins: A Preference-based approach
Digital Twins (DTs) are increasingly used as autonomous decision-makers in complex socio-technical systems. Their mathematically optimal decisions often diverge...
- · ai
Why AI Alignment Starts With Better Evaluation
You can’t align what you don’t evaluate The post Why AI Alignment Starts With Better Evaluation appeared first on Towards Data Science....