challenges of autonomous driving

the world is messy—robo-taxies would be confused

It seems like an increasing trend to do data argumentation with generative approaches.

safety standards

ISO 26262

how to do it , instead of what to do

• functional safety standard
• methods about testing and processes

ISO 21448

intended functionality

• scenario based analysis of hazardous situations—“triggering conditions” => “mitigations” shown below
• identification and mitigation of functional insufficiencies
• (requires?) the discovering of unknown unknowns with mitigations

Safety and AI

the actual safety challenges

Challenge of speech anonymization: cannot develop a model which both preserves speech features well but also effectively anonymizes the speech.

Methodology

• Separate content and speech encoders
• Results in highly concentrated + effective speech content, but with very widespread voiceprint

Demo day

• No value add for demo-day winner
• Competition makes you want to prepare more
• “this much budget for an enriching experience”

Mentor Conversations

None yet

Integration

• Integration into soundscape

Hiring

Need help designing a PCB

sample space \(S\) is the set of all possible outcomes of an experiment. It could be continuous or distinct.

equally likely outcomes

Some sample spaces have equally likely outcomes:

• coin flip
• flipping two coins
• rolling a fair die

If we have equally likely outcomes, \(P(outcome)\) = \(\frac{1}{S}\).

If your sample space has equally likely outcomes, the probability is juts counting:

\begin{equation} P(E) = \frac{count(E)}{count(S)} \end{equation}

Whenever you use this tool, you have to think about whether or not your outcomes are equally likely. For instance, the “sum of two dice rolling” is NOT equally likely.