Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities
Many industry sectors have been pursuing the adoption of Industry 4.0 (I4. 0) ideas and
technologies, which promise to realize lean and just-in-time production through digitization …
technologies, which promise to realize lean and just-in-time production through digitization …
A review on reinforcement learning algorithms and applications in supply chain management
Decision-making in supply chains is challenged by high complexity, a combination of
continuous and discrete processes, integrated and interdependent operations, dynamics …
continuous and discrete processes, integrated and interdependent operations, dynamics …
Reasoning with language model is planning with world model
Large language models (LLMs) have shown remarkable reasoning capabilities, especially
when prompted to generate intermediate reasoning steps (eg, Chain-of-Thought, CoT) …
when prompted to generate intermediate reasoning steps (eg, Chain-of-Thought, CoT) …
The debate over understanding in AI's large language models
We survey a current, heated debate in the artificial intelligence (AI) research community on
whether large pretrained language models can be said to understand language—and the …
whether large pretrained language models can be said to understand language—and the …
Training language models to follow instructions with human feedback
Making language models bigger does not inherently make them better at following a user's
intent. For example, large language models can generate outputs that are untruthful, toxic, or …
intent. For example, large language models can generate outputs that are untruthful, toxic, or …
Foundational challenges in assuring alignment and safety of large language models
This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …
language models (LLMs). These challenges are organized into three different categories …
Minigrid & miniworld: Modular & customizable reinforcement learning environments for goal-oriented tasks
We present the Minigrid and Miniworld libraries which provide a suite of goal-oriented 2D
and 3D environments. The libraries were explicitly created with a minimalistic design …
and 3D environments. The libraries were explicitly created with a minimalistic design …
Compute trends across three eras of machine learning
Compute, data, and algorithmic advances are the three fundamental factors that drive
progress in modern Machine Learning (ML). In this paper we study trends in the most readily …
progress in modern Machine Learning (ML). In this paper we study trends in the most readily …
Foundation models for decision making: Problems, methods, and opportunities
Foundation models pretrained on diverse data at scale have demonstrated extraordinary
capabilities in a wide range of vision and language tasks. When such models are deployed …
capabilities in a wide range of vision and language tasks. When such models are deployed …
Self-play fine-tuning converts weak language models to strong language models
Harnessing the power of human-annotated data through Supervised Fine-Tuning (SFT) is
pivotal for advancing Large Language Models (LLMs). In this paper, we delve into the …
pivotal for advancing Large Language Models (LLMs). In this paper, we delve into the …