Use Cases

Steps

1. 1.Visit Deep Research or Genspark
2. 2.Enter the research topic and report framework requirements
3. 3.AI automatically searches and integrates information

Steps

1. 1.Upload PDFs to a designated folder
2. 2.Configure filesystem MCP to read files
3. 3.Let AI extract key information and structure it

Steps

1. 1.List target competitors
2. 2.Agent automatically visits official websites, App Store reviews, and social media
3. 3.Analyze product feature matrix and differentiation advantages

Steps

1. 1.Enter the target company name and research focus areas
2. 2.Agent automatically searches the company website, Crunchbase, and LinkedIn
3. 3.Analyze funding rounds, valuation trends, and investors

Steps

1. 1.Define target patent scope and keywords
2. 2.Download USPTO/EPO patent documents via fetch MCP
3. 3.Analyze patent claims and technical solutions with Claude

Steps

1. 1.Collect student information: target exam, current level, daily available study time
2. 2.AI breaks down the exam syllabus and generates a knowledge point map with priorities
3. 3.Push daily learning tasks and corresponding resources

Steps

1. 1.Check whether the teacher model satisfies two core conditions: thought pattern compatibility (high initial overlap rate) and possessing new capabilities that the student lacks (e.g., additional RL training).
2. 2.If the teacher's conditions are insufficient, prioritize models from the same family that have undergone additional RL training, or use multi-teacher OPD to integrate multiple expert capabilities.
3. 3.In the existing RL framework, replace the advantage function with the reverse KL divergence of the log ratio between teacher and student, enabling single-line code integration of OPD.