What the work actually looks like
An honest account of building AI systems in industry, including the parts that are unglamorous and the parts nobody puts in a course description.
Speaking topic
For a room deciding what to do with their careers, from somebody doing the work they are deciding whether to go into, who can still remember what it is like to not know where to begin.

Student conferences, faculty and departmental events, orientation and careers weeks, hackathon opening and closing sessions.
What it covers
Rewritten for each audience, so the order and the examples change. These are the subjects it covers.
An honest account of building AI systems in industry, including the parts that are unglamorous and the parts nobody puts in a course description.
He took an unusual path, and he talks about it as one route among several, which is more useful to a room of students than a template.
The parts worth investing in when the specific frameworks have a short half-life.
Usually the half the students remember. Budget real time for it.

Demystifying AI, hands-on
“Machine learning isn't magic. It's math.”
The same math that pinpoints your phone on a map trains today's AI. He teaches it from first principles, often with Pepper, a humanoid robot, taking the audience's questions.
For students, developers and technical teams
He has run university sessions and speaks regularly to student audiences, and he is close enough to the start of his own career to answer the questions students actually ask.
On this subject
Questions
Rates are agreed per event and are not published. Put the institution and the budget in the enquiry and he gives you a straight answer.
Yes. A talk plus a smaller hands-on session is a common shape for a university booking and makes better use of the travel.
Send your date.
Tanmay replies himself, availability first.
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