<div dir="ltr"><div dir="ltr"><div dir="ltr"><br><div>Hi Jason and Bill,</div><div><br></div><div><br></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, Sep 17, 2025 at 8:12 AM BillK via extropy-chat <<a href="mailto:extropy-chat@lists.extropy.org" target="_blank">extropy-chat@lists.extropy.org</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr">On Wed, 17 Sept 2025 at 14:43, spike jones via extropy-chat <<a href="mailto:extropy-chat@lists.extropy.org" target="_blank">extropy-chat@lists.extropy.org</a>> wrote:<br>> Jason, perhaps this is tangential to your point: I wondered how that was done (car-bots reading traffic lights based on color.) <br>><br>> My source tells me they don’t. It knows the position of the lights: red above, yellow in middle green below, and can tell which one is emitting light.<br>><br>> spike <br>> _______________________________________________</div><div dir="ltr"><br></div><div dir="ltr"><br></div><div dir="ltr"><div style="font-family:arial,sans-serif;font-size:small;color:rgb(0,0,0)">Hi Spike</div><div style="font-family:arial,sans-serif;font-size:small;color:rgb(0,0,0)">The system probably varies between different brands of robo cars.</div><div style="font-family:arial,sans-serif;font-size:small;color:rgb(0,0,0)">But, asking an AI how it does it -----</div><div style="font-family:arial,sans-serif;font-size:small;color:rgb(0,0,0)">BillK</div><div style="font-family:arial,sans-serif;font-size:small;color:rgb(0,0,0)"><br></div><div style="font-family:arial,sans-serif;font-size:small;color:rgb(0,0,0)">Phind AI:</div><div style="font-family:arial,sans-serif;font-size:small;color:rgb(0,0,0)">Self-driving vehicles use sophisticated computer vision systems to reliably detect and classify traffic signals among various environmental light sources. This complex process involves multiple layers of detection and verification to ensure accurate signal recognition.<br><br>### Core Detection Methods<br><br>1. **Visual Processing Pipeline** - High-resolution cameras capture detailed images of the scene<br> - Advanced algorithms detect circular shapes characteristic of traffic lights<br> - Color analysis distinguishes between red, yellow, and green signals<br> - Multiple frames are analyzed to confirm consistent readings<br></div></div></div></div></div></blockquote><div><br></div><div>Yes, both humans and AI systems do this processing to clean up the data from the sensors. The final result of both perception systems is to render cleaned up models of what is being perceived, which are then engineered to be used for decision making. It's just that the model produced by the artificial system renders words (like 'red' or '0xFF0000' which can be distinguished from 'green' or '0x00FF00') into its knowledge while our knowledge is made up of color qualities, like redness which can be distinguished from greenness. This is obviously designed or engineered by nature to use redness for things that should stand out to us. We can engineer things to use different qualities or different words, like using color inversion glasses and so on. The bottom line is, this is an engineering decision that must be made, in order for some conscious entity to be 'like something' in particular.</div><div><br></div><div>Similarly, we can model more than the visible region of the electromagnetic spectrum, like an AI does, using words and numbers to represent what our sensors are detecting. Both aren't like anything. We can 'color map' or 'false color' these regions into our visible light range, to use the same color qualities we use for light. Again, this is all an engineering decision. It's not enough to ask if something is conscious, you need to also ask, what is it engineered to be like. And if it isn't engineered to be like anything, it isn't sentient or conscious, in my book. It is just equally or more intelligent.</div><div><br></div><div>The Turing test can't tell you if something is conscious, that is unless you ask it a question like: "What is redness like for you?"</div><div><br></div><div><br></div><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div style="font-family:arial,sans-serif;font-size:small;color:rgb(0,0,0)">2. **Signal Verification Techniques** - Position tracking: Traffic lights appear in predictable locations<br> - Pattern recognition: Known shapes and arrangements of signals<br> - Motion analysis: Traffic lights remain stationary<br> - Contextual understanding: Relationship to intersections and roads<br><br>### Safety Measures<br><br>1. **Multiple Confirmation Systems** - Requires agreement between multiple detection methods<br> - Implements voting systems among different sensors<br> - Maintains historical context of signal states<br> - Continuously verifies detections<br><br>2. **Error Prevention** - Regular software updates<br> - Sensor calibration checks<br> - Weather condition monitoring<br> - Fallback procedures for uncertain situations<br><br>The reliability of these systems comes from their multi-layered approach, combining visual detection with contextual awareness and sensor fusion. By verifying traffic signals through multiple independent methods, autonomous vehicles can maintain safe operation even in challenging environmental conditions.</div><div style="font-family:arial,sans-serif;font-size:small;color:rgb(0,0,0)">--------------------</div></div></div>
</div>
</div>
_______________________________________________<br>
extropy-chat mailing list<br>
<a href="mailto:extropy-chat@lists.extropy.org" target="_blank">extropy-chat@lists.extropy.org</a><br>
<a href="http://lists.extropy.org/mailman/listinfo.cgi/extropy-chat" rel="noreferrer" target="_blank">http://lists.extropy.org/mailman/listinfo.cgi/extropy-chat</a><br>
</blockquote></div></div>
</div>