resources reinforcement-learning-example 
Unite.AI
MARCH 22, 2024
These LLMs, designed to process and generate human-like text, learn from an extensive array of texts from the internet, ranging from books to websites. This learning process allows them to capture the essence of human language making them general purpose problem solvers. What's Social Learning? Social learning isn't a new idea.
Marktechpost
MAY 7, 2024
Reinforcement learning (RL) is a fascinating field of AI focused on training agents to make decisions by interacting with an environment and learning from rewards and penalties. RL differs from supervised learning because it involves doing rather than learning from a static dataset.
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Marktechpost
MARCH 22, 2024
Reinforcement Learning from Human Feedback (RLHF) enhances the alignment of Pretrained Large Language Models (LLMs) with human values, improving their applicability and reliability. However, aligning LLMs through RLHF faces significant hurdles, primarily due to the process’s computational intensity and resource demands.
Marktechpost
APRIL 16, 2024
Reinforcement Learning (RL) is expanding its footprint, finding innovative uses across various industries far beyond its origins in gaming. Algorithmic Trading: Executing high-speed trades based on learned strategies from vast market data. Smart Cities In urban planning, RL is used to optimize traffic management systems.
Unite.AI
JANUARY 23, 2024
In the domains of artificial intelligence (AI) and machine learning (ML), large language models (LLMs) showcase both achievements and challenges. These techniques are resource-intensive and time-consuming, making them difficult to implement. Trained on vast textual datasets, LLM models encapsulate human language and knowledge.
AWS Machine Learning Blog
APRIL 24, 2024
In this post, we share how we analyzed the feedback data and identified limitations of accuracy and hallucinations RAG provided, and used the human evaluation score to train the model through reinforcement learning. To increase training samples for better learning, we also used another LLM to generate feedback scores.
Marktechpost
FEBRUARY 7, 2024
In recent years, researchers in the field of robotic reinforcement learning (RL) have achieved significant progress, developing methods capable of handling complex image observations, training in real-world scenarios, and incorporating auxiliary data, such as demonstrations and prior experience.
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