Milo for higher education

Frontier intelligence for students. Pedagogical control for professors.

Students use a familiar chat interface with frontier models today. An integrated coding harness is next. Professors set course context, see class-wide patterns, and steer the course without reading private conversations.

Built first for undergraduate and graduate computer science and engineering courses.

CS 40 Faculty view
Last 7 days
Faculty brief

Where students need help

Updated today
Questions 268 Across student conversations
Homework 3 questions 61% Locality: 2.4× Homework 2
Recurring clusters 18 Across course concepts
Top question clusters Share of questions
90° rotation locality45%
Block-major mapping31%
UArray2b indexing16%
Timing experiments8%
Leading pattern Homework 3 drove 2.4× more debugging than Homework 2.

Locality in 90° rotation was the leading issue.

Based on aggregated class-wide patterns

Illustrative faculty view

For students

Real tools, connected to the course.

Milo starts with the open-ended chat interface students already understand. They work directly with frontier models, files, course materials, and pasted code. An integrated coding harness is coming next.

  • Frontier models for explanation, research, and problem-solving
  • Your syllabus, lectures, and assignments in context
  • Files and pasted code in the same conversation
  • Integrated coding harness coming next
HW3 locality resultsCourse context on
Model ▾
Why is my 90° row-major rotation slower than 180° on the same image?
m

A 90° rotation turns each source row into a destination column. With row-major storage, those writes jump through memory and cause more cache misses.

$ ./ppmtrans -row-major -rotate 90 large.ppm4.82s user$ ./ppmtrans -row-major -rotate 180 large.ppm1.31s user90° row-major is 3.7× slower

A 180° rotation keeps row-to-row access. Compare this result with block-major mapping and explain the change in spatial locality.

Ask about your course, upload a file, or paste code…

For professors

See where the course needs attention. Act while it matters.

Milo turns normal student AI work into clear course signals. Use them to clarify a concept, improve an assignment, or add an example before the next assessment.

Find patterns

Find the concepts behind repeated questions and follow-ups.

Improve assignments

Compare question and debugging activity across problems and due dates.

Measure response

See what changes after a clarification or new example.

Private conversations. Useful patterns.

Professors see aggregated trends across the class. They see an individual transcript only when a student shares it.

  • Private by default. Student transcripts stay out of the professor view.
  • No training on pilot conversations. Each institution sets its retention period before students join.
  • Not an AI detector. Milo supports teaching. It does not assign misconduct scores.

Start with one course

Run Milo for four weeks.

Students get the course-aware chat interface. Professors get a weekly brief. After four weeks, Acyclic reviews the results and next steps with you.

Request a 4-week course pilot