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Using AI to critique your photos


I agree with Tesla but the real world is not easily simulated. That is why I mentioned "immersion" for AGI. By the way autonomous driving in any environment is largely linked to AGI due to how challenging of a problem it is.
But for the math problems you are wrong, it didn't solve them with calculations it solved them with reasoning that's why it was so impressive.
As for chess you are right, although you are missing a crazy point. The computers who learnt to defeat humans and redefined whole chess openings from scratch were trained by playing only with themselves only by knowing the set of rules and nothing more. They also achieved it in half an hour. From zero to mastery. That goes beyond computations. This is mind-blowing
 
AI side note:

My wife searched "reindeer" in Mac Photos and this came up...our Yorkie wearing a Christmas sweater sporting antlers.

Close, but...

 
It sounds like you're using AI as a search engine for the most part, and as such it's certainly an outstanding one. I partly use it that way as well. And of course it's not human, which is as it should be, and why it's such an effective co-conspirator; It doesn't get tired, frustrated, distracted or drunk like humans do. (And that's also why autonomous vehicles are already safer than human drivers even though the systems are in their infancy.) Use AI with the prompt "Are autonomous vehicles safer than vehicles driven by humans, and if so, why. Please cite your sources."

Alan Edward Klein said:
It's not innovative or creative because it doesn't really have a mind.
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I suppose someone is about to break out their dictionary and look up these words but my experience has been that AI is both wildly innovative and creative. It creates. It innovates. It doesn't need a mind for that, even though it can't do its tasks without you and leveraging outside resources. You, as the human interpreter and managing partner, can use its output to steer it and yourself to accomplish goals. You may not experience this if your use of AI is basically a super-search engine, but if you branch out from there I imagine you will.
 
koraks said:
We may have to discuss what 'reasoning' is - and what isn't. Not all association is reasoning in my book. If you said "association", then I would have agreed.
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Very good point as usual.
It is not associations but I see what you mean it is not reasoning in the sense that they know what they are doing or applying logic as humans do.
It is more a “closed system” you give it the formal rules and then by applying them it can lead to conjectures or theorems sort of as called “symbolic reasoning”
 
Alan Edward Klein said:
But it can't drive a Tesla without getting into an accident?
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The same might be said by the population of human drivers that have already tried, and definitely failed.
 
The tesla lacks the appropriate sensors for it to really drive autonomously. AI is the least of its problems.
 
Pieter12 said:
The tesla lacks the appropriate sensors for it to really drive autonomously. AI is the least of its problems.
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We have autonomous Waymo Jaguars running around the city now. It’ll be interesting to see how well they do. Here It’s chaotic driving for sure. Anarchy, really. It will be a good test for a Waymo.
 
warden said:
We have autonomous Waymo Jaguars running around the city now. It’ll be interesting to see how well they do. Here It’s chaotic driving for sure. Anarchy, really. It will be a good test for a Waymo.
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We have had Waymos for quite a while here. The biggest problem (besides all the noise at the charging depot) is they pretty much strictly obey traffic rules unlike human drivers, often holding up traffic to make a left turn--they won't go into an intersection if the car hasn't determined it can safely clear it before the light turns red.
 

But they don't drive safer, and they've been at it for years. And driving seems to be less than trying to create something or be innovative, where AI has to "think" outside given parameters, as there are with driving.
 
warden said:
We have autonomous Waymo Jaguars running around the city now. It’ll be interesting to see how well they do. Here It’s chaotic driving for sure. Anarchy, really. It will be a good test for a Waymo.
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Do they run on rainy or snowy days when the street lines are covered? Night? Are there other limitations of where, when etc they can;t run?
 
Alan Edward Klein said:
Do they run on rainy or snowy days when the street lines are covered? Night? Are there other limitations of where, when etc they can;t run?
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Well, with the recent major blackout in San Francisco, they all came to a halt. Seems they couldn't deal with traffic lights being out among other things. And as of now, they aren't on the freeways except with a driver behind the wheel.
 
Pieter12 said:
Well, with the recent major blackout in San Francisco, they all came to a halt. Seems they couldn't deal with traffic lights being out among other things. And as of now, they aren't on the freeways except with a driver behind the wheel.
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What about when it rains or snows?
 
Pieter12 said:
Rain is no problem. Can’t say about snow, it doesn’t snow here.
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Well it snows in a big part of the country. What happens there? Can these programs navigate with obscured lane lines, crosswalks, low visibility, etc? Or do you need a dog sled?
 
Alan Edward Klein said:
Well it snows in a big part of the country. What happens there? Can these programs navigate with obscured lane lines, crosswalks, low visibility, etc? Or do you need a dog sled?
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It could well maybe able to manage snow OK. And if not, it certainly isn’t supposed to be for everyone everywhere.
 

Regardless of the learning principles based on which examples and their order remain the same. AI can only be as good as its learning material and order of its presentation.
 
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Sirius Glass said:
Regardless of the learning principles based on which examples and their order remain the same. AI can only be as good as its learning material and order of its presentation.
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There is a small truth to that in the old saying in the AI world “garbage in-garbage out” but the misconception that it is only as good as its data seems to linger even in many of my programmer colleagues.

Let’s do a small test. I asked the free non latest version of ChatGPT the following:

“Can you imagine a photo camera that works with a new technology neither analog nor digital?”

I assume that this was not present or formulated in the data as it is and it had to be some new original synthesis among the patterns. Here was the output (sorry for its length):



The “Cognitive Camera”
  • Capture principle: Instead of using film or pixels, the camera records light and spatial information as patterns of neural-encoded thought — essentially storing how the scene feels and interacts with attention.
  • Image formation: The photographer “frames” the scene with intention and gaze, and the camera interprets the visual field along with context, emotion, and conceptual focus.
  • Output: The resulting image is not a static photo but a dynamic projection: the captured scene can shift depending on who is viewing it, highlighting details differently for each observer, almost like a living photograph.
  • Controls: No shutter speed or ISO; instead, you “tune” your mental focus, adjust conceptual parameters (contrast of ideas, emotional depth), and the camera interprets these inputs into the light-matter interaction.
  • Special feature: The camera can merge multiple photographers’ perspectives, combining their intentions into a composite “multi-conscious” photograph — almost like a collaborative dream image

Why it’s plausible (science-fiction-meets-future-tech)
  1. Quantum / light field sensing: Could theoretically measure phase, polarization, and coherence patterns of light beyond classical imaging.
  2. AI / brain-computer interface: Could integrate intentional patterns from a human mind to guide image formation.
  3. Dynamic display: Using augmented reality, holography, or light-field projection, the “photo” could respond to the observer, unlike any analog or digital still image
 

Ask it what sources it used to make these conclusions. Maybe these have already been suggested in the literature it was trained on.
 
Pieter12 said:
It could well maybe able to manage snow OK. And if not, it certainly isn’t supposed to be for everyone everywhere.
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But the idea is that AI will be more advanced than special humans, certainly at least as good as regular humans. If it can't drive in the snow, or in other street conditions we run into ordinarily, what do you get with AI?
 
Alan Edward Klein said:
If it can't drive in the snow, or in other street conditions we run into ordinarily, what do you get with AI?
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Safety. Sobriety. Efficiency. Lack of road rage. Presence of 360 degree vision. Scanning for hazards better and faster than two elderly human eyes looking ahead. No macular degeneration or cataracts. Faster reflexes. Lack of distracted driving while checking your phone. More skill than the average 16 year old with a fresh license. Lack of drag racing. Lack of tailgating. An inability to run from the cops. Inability to drive while fatigued or fall asleep behind the wheel.

should I go on? Is your question even serious, Alan?
 

Many of those things are lacking or not up to par. Here's AI's opinion.https://www.google.com/travel/flights?client=ms-android-verizon-us-rvc3&hs=BRTU&sca_esv=31db8cbb946c4eae&tbm=flm&sxsrf=ANbL-n7P4-snY40mit6so4CyCeYAHCZoqw:1768071951940&source=lnms&ved=1t:200715&ictx=111&q=What issues do automatic driving cars have



Automatic driving cars currently face a variety of significant issues spanning technology, safety, regulation, and social impact
. These challenges are hindering their widespread, fully autonomous deployment.

Technological and Safety Limitations
  • Sensor and Software Errors: Cars rely on complex sensor and perception systems that can experience software glitches or errors, leading them to do the wrong thing at the wrong time.
  • Difficulty with Complex Environments: Autonomous vehicles struggle with real-world complexities and "edge cases" such as construction zones, unclear lane markings, and unexpected obstacles or detours that human drivers might navigate easily.
  • Adverse Weather Conditions: Snow, ice, and heavy rain can interfere with sensors, reducing the car's ability to detect its surroundings accurately.
  • "Phantom Braking" and Detection Issues: Vehicles may perform abrupt, unnecessary stops (known as "phantom braking") in response to non-existent objects, which can cause rear-end collisions with human drivers. They also have issues correctly detecting pedestrians and cyclists, especially at dawn or dusk.
  • Interaction with Unpredictable Human Behavior: Autonomous systems typically predict average behavior and struggle with the "not-average" and sometimes aggressive maneuvers of human drivers, which can lead to misjudgments in traffic.
  • Need for Human Intervention: Many current systems are semi-autonomous and require the human driver to remain attentive and ready to take control. A false sense of security can lead to driver distraction and fatal accidents when a rapid transition of control is needed.

Cybersecurity, Legal, and Regulatory Issues
  • Vulnerability to Hacking: As connected computers on wheels, self-driving cars are vulnerable to cybersecurity threats. A breach could allow remote control of the vehicle or access to personal data, with catastrophic consequences.
  • Lack of Clear Regulation: There is currently no consistent and comprehensive federal, state, or local regulatory requirement for companies to prove their cars are reasonably safe before deployment. This uncertainty slows development and makes accountability difficult.
  • Liability and Insurance Questions: In the event of an accident, it is often unclear who is at fault—the manufacturer, software developer, vehicle owner, or a passenger. This complicates legal processes and insurance frameworks.

Societal and Economic Concerns
  • Job Displacement: The widespread adoption of autonomous vehicles could disrupt entire industries, leading to significant job losses for professional drivers, such as truckers, taxi, and rideshare operators.
  • Equity and Access: The initial cost of the technology may mean benefits are exclusively available to the wealthy, potentially worsening existing transportation inequities.
  • Increased Travel: By making commuting time more productive (e.g., allowing work or leisure during travel), AVs might actually encourage longer commutes and increase total vehicle miles traveled, potentially exacerbating congestion and environmental pollution unless paired with clean energy mandates.







Additional inquiries:

What progress is being made on the legal and regulatory front for autonomous vehicles?
What technologies are being developed to improve self-driving car performance in bad weather?
Explain more about 'phantom braking'
Potential Problems with Self-Driving Cars
 
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Your link opens a page for Google travel services. I’m going to take a break from this thread.
 
Back on topic, it seems the one thing that AI has not scraped is any actual information on proper critiquing of photograph. Rather than using a model such as "Criticizing Photographs by Terry Barrett they seem to have taken scraped information like might be found on Flickr or here as examples of critique.
What is worse, it really does seem that AI writing seems to be becoming normalized and is having an impact on human authored work.
Up here in Canada, a lawyer who was arguing to get his privileges re-instated after revocation, used AI legal references which turned out to be entirely fictitious. He apologized stating he had no way of noting that AI output was other than reliable.
I have just finished reading Yousuf Karsh: Life & Work and, in my uninformed opinion, it reads like it might have been written to mimic AI assisted work. I am sure that is not true.
It does seem however that opinion is being increasingly presented as fact, in the absence of proof.
 
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