Bridging
DeepSeek-Prover-V2: Bridging the Gap Between Informal and Formal Mathematical Reasoning
While DeepSeek-R1 has significantly advanced AI’s capabilities in informal reasoning, formal mathematical reasoning has remained a challenging task for AI. This is primarily because producing verifiable mathematical proof requires both deep conceptual understanding and the ability to construct precise, step-by-step logical arguments. Recently, however, significant advancement is made in this direction as researchers at DeepSeek-AI…
Bridging philosophy and AI to explore computing ethics
During a meeting of class 6.C40/24.C40 (Ethics of Computing), Professor Armando Solar-Lezama poses the same impossible question to his students that he often asks himself in the research he leads with the Computer Assisted Programming Group at MIT: “How do we make sure that a machine does what we want, and only what we want?” At…
Bridging Reasoning and Action: The Synergy of Large Concept Models (LCMs) and Large Action Models (LAMs) in Agentic Systems
The advent of advanced AI models has led to innovations in how machines process information, interact with humans, and execute tasks in real-world settings. Two emerging pioneering approaches are large concept models (LCMs) and large action models (LAMs). While both extend the foundational capabilities of large language models (LLMs), their objectives and applications diverge. LCMs…