Apple engineer killed in Tesla crash had previously complained about autopilot
I avoid new technology, exactly because I&#x27;m an engineer.<p>I wonder if that is just me, but when new technology is introduced and hyped, I usually take a quick look at implementations, research, and talks just to get an idea of what the state of the art really is like.<p>As a result, I have become the late adopter among my group of friends because the first iteration of any new technology usually just isn&#x27;t worth the issues.<p>You know this effect when you open a new book and immediately spot a typo? I felt that way looking at state of the art AI vision papers.<p>The first paper would crash, despite me using the same GPU as the authors. Turns out they got incredibly lucky not to trigger a driver bug causing random calculation errors.<p>The second paper converted float to bool and then tried to use the gradient for training. That&#x27;s just plain mathematically wrong, a step function doesn&#x27;t have a non-zero gradient.<p>The third paper only used a 3x3 pixel neighborhood for learning long-distance moves. Doesn&#x27;t work, I cannot learn about New York by waking around in my bathroom.<p>That gave me the gut feeling that most people doing the research were lacking the necessary mathematical background. AI is stochastical gradient descent optimization, after all.<p>Thanks to TensorFlow, it is nowadays easy to try out other people&#x27;s AI. So I took some photos of my road and put them through the state of the art computer visible AIs trained with KITTY, a self-driving car dataset of German roads. All of them couldn&#x27;t even track the wall of the house correctly.<p>So now I&#x27;m afraid to use anything self-driving ^_^