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Apparently AI hasn’t gotten the memo that AWD can be optioned for the 2025 Hybrid Maverick.
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AI - Don’t believe everything you read on the internet 🧐
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As someone who used to do research in libraries. World Book and Britannica had errors. Because of a changing world a lot of the errors were out of date errors.
I won't even go into the errors that were in Newsweek, Time, Life, National Geographic.
Life and the world isn't perfect neither is AI.
I'm going to go out on a limb here and say that, most who dismiss, misunderstand or trash AI. Are shall we say long in the tooth. As a realist I'm going to tell you AI is not going away. Just like the old farts, that bemoned fuel injection and automatic transmissions. Both are here and they're here to stay. The world is a dynamic imperfect place.
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The more basic LLMs used for quick searches and summaries are not the best gauge of the technology.
Just yesterday I was using gpt-5 to troubleshoot a piece of enterprise hardware (a newer Dell server) with proprietary fault codes for something I had never seen before, and I was pretty shocked at how accurate it summarized conclusions using a Dell internal service manual linked to a fault code that possibly no one had ever queried it for yet. I could not open a support case with Dell because it was for riser and expansion cards not in the original configuration, yet I was pretty sure the answer given was as good or better than tier 1 support.
Just yesterday I was using gpt-5 to troubleshoot a piece of enterprise hardware (a newer Dell server) with proprietary fault codes for something I had never seen before, and I was pretty shocked at how accurate it summarized conclusions using a Dell internal service manual linked to a fault code that possibly no one had ever queried it for yet. I could not open a support case with Dell because it was for riser and expansion cards not in the original configuration, yet I was pretty sure the answer given was as good or better than tier 1 support.
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I have found that upon questioning the AI response, I have actually gotten more accurate answers.
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Don't necessarily believe anything anyone says on this site either.
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I find reactions to AI to be very similar to reactions to BEVs. They are both Rorshach tests that say a lot about the person doing the reacting. And reactions tell me a lot about how deeply read an individual is on either subject. Some are deeply read, understand the pros and cons, and understand the trajectory of progress. Others have read a few clickbait stories and regurgitate them. Still others have one good or bad experience and draw a conclusion from that experience.
The thing about BEVs is that they are taking over the world. The timeline is unclear. But at some point soon all vehicles will be BEV. Period. End of discussion. It's just a question of when.
Similarly, AI capabilities are currently improving exponentially. Some voices (like Nobel Prize winners) say that that LLMs are a dead end, while still expressing astonishment and delight at their capabilities (read "The Bitter Lesson" essay). AI accuracy and speed are currently improving exponentially every few months now, as we throw larger and better training data sets at them. We just don't know what the limit of the LLM architecture is. What's a little freaky is that the rate of improvement is approaching infinity.
One of my favorite things about LLMs is that the teams managing them don't know what the capabilities of any LLM will be until it is trained. They are constantly surprised by emergent behavior that they didn't expect.
All that said, the OP is right. AIs have a lot of issues today. They also do some amazing things. And nobody really knows if they're about to hit a hard limit, or if they're about to go vertical on us. It reminds me just a little bit of the first atomic test - when the scientists weren't totally sure they weren't about to set the Earth's atmosphere on fire. They were pretty sure it was cool, but there was this little niggling doubt...
Edit. I just re-read this. Boy I sound pretentious and pontificating. Sorry about that. Not my intention.
The thing about BEVs is that they are taking over the world. The timeline is unclear. But at some point soon all vehicles will be BEV. Period. End of discussion. It's just a question of when.
Similarly, AI capabilities are currently improving exponentially. Some voices (like Nobel Prize winners) say that that LLMs are a dead end, while still expressing astonishment and delight at their capabilities (read "The Bitter Lesson" essay). AI accuracy and speed are currently improving exponentially every few months now, as we throw larger and better training data sets at them. We just don't know what the limit of the LLM architecture is. What's a little freaky is that the rate of improvement is approaching infinity.
One of my favorite things about LLMs is that the teams managing them don't know what the capabilities of any LLM will be until it is trained. They are constantly surprised by emergent behavior that they didn't expect.
All that said, the OP is right. AIs have a lot of issues today. They also do some amazing things. And nobody really knows if they're about to hit a hard limit, or if they're about to go vertical on us. It reminds me just a little bit of the first atomic test - when the scientists weren't totally sure they weren't about to set the Earth's atmosphere on fire. They were pretty sure it was cool, but there was this little niggling doubt...
Edit. I just re-read this. Boy I sound pretentious and pontificating. Sorry about that. Not my intention.
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AI is only really as good as the source it's given. I've found Gemini (Google AI) sometimes finds wrong info on websites and regurgitates it. They likely have a bunch of really smart people paid a lot of money trying to figure out how to weigh source truth.
Where it really shines is when given a bunch of known good information - feed it a couple of user manuals and service manuals and it'll be able to use the data from those conversationally. Much quicker way to search and learn.
Always good to keep a critical eye when reading AI generated responses. But as Scott said, it's only getting better.
Where it really shines is when given a bunch of known good information - feed it a couple of user manuals and service manuals and it'll be able to use the data from those conversationally. Much quicker way to search and learn.
Always good to keep a critical eye when reading AI generated responses. But as Scott said, it's only getting better.
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I feel like a lot of people miss the point that a LANGUAGE model never knows anything, it can't reason well and totally sucks at math, it just regurgitates what is statistically likely to come next to words or terms you query it about.
If you found google too hard to use in the past, you are probably getting absolute garbage out of LLMs and not even realizing. LLMs aren't that smart, just a lot of people are worryingly dumber than them, the easily fooled are easily fooled.
If you found google too hard to use in the past, you are probably getting absolute garbage out of LLMs and not even realizing. LLMs aren't that smart, just a lot of people are worryingly dumber than them, the easily fooled are easily fooled.
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AI informs me. The word regurgitate is an overused word used by folks explaining AI shortcomings.
Those “smart people” who are figure out what is “true” should be questioned also.
AI is like Wikipedia on steroids when it comes to answering queries. Useful on some topics - not so much on others.
When AI can start asking original questions and start discovering unknown/undiscovered “truths” - then it will get interesting.
I’m waiting for AI to develop their own “Turing Test” - am I talking to a human or AI. They will get nervous when a human approaches their level?
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Agreed - Oversight and transparency is important and not talked about enough these days. I think questions like "Does the 2025 Hybrid Maverick have a AWD option" or "what's the torque for X" have straight forward answers.
Anything historical or political is much harder as many different levels of bias come into play. But that's not really what we are discussing on this truck forum lol.
AI is already being used extensively in the automotive sector. From design and simulation to adaptive cruise control and self driving.
AI is used to determine optimum torque in modern engines & motors - not just tell us what the humans came up with
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From the sources I see shown there - it appears some dealer's info could be updated and differentiated better too.
Some dealer's sites are pretty bad, they don't seem to updated from Ford's site - which is strange to me on both sides.
I'd think Ford would demand that to be a dealer, I'd think the dealer would want accurate info on what they can sell.
Some dealer's sites are pretty bad, they don't seem to updated from Ford's site - which is strange to me on both sides.
I'd think Ford would demand that to be a dealer, I'd think the dealer would want accurate info on what they can sell.
This is AI’s answer to the question “is AI used in automotive sector?” Grok AI:
“Yes, AI is extensively used in car design across various stages of the process. Here’s a concise overview:
1. **Concept and Styling**: AI tools, like generative design algorithms, help designers explore thousands of aesthetic and functional design variations based on parameters like aerodynamics, weight, and material strength. Tools like Autodesk’s generative design or NVIDIA’s AI-driven rendering platforms assist in creating optimized shapes.
2. **Engineering and Simulation**: AI is used in finite element analysis (FEA) and computational fluid dynamics (CFD) to simulate structural integrity, crash performance, and aerodynamics. Machine learning models predict material behavior and optimize components for weight, cost, and durability.
3. **Autonomous Driving Systems**: AI, particularly deep learning, is critical for developing self-driving car technologies. Neural networks process sensor data (LiDAR, radar, cameras) to enable features like lane detection, object recognition, and path planning.
4. **Manufacturing Optimization**: AI streamlines production by optimizing assembly lines, predicting maintenance needs, and improving quality control through computer vision to detect defects.
5. **User Experience**: AI enhances in-car systems, such as voice assistants, infotainment personalization, and driver behavior analysis for safety features like adaptive cruise control or fatigue detection.
6. **Sustainability**: AI aids in designing electric vehicles (EVs) by optimizing battery performance, thermal management, and energy-efficient components. It also supports eco-friendly material selection.
Major automakers like Tesla, Ford, Volkswagen, and Toyota, along with tech firms like NVIDIA and Waymo, integrate AI into their design workflows. For example, Tesla uses AI for both vehicle design and its Full Self-Driving (FSD) system, while startups like Lightyear leverage AI for efficient EV designs.
In short, AI is transforming car design by accelerating development, improving performance, and enabling smarter, safer, and more sustainable vehicles.“
“Yes, AI is extensively used in car design across various stages of the process. Here’s a concise overview:
1. **Concept and Styling**: AI tools, like generative design algorithms, help designers explore thousands of aesthetic and functional design variations based on parameters like aerodynamics, weight, and material strength. Tools like Autodesk’s generative design or NVIDIA’s AI-driven rendering platforms assist in creating optimized shapes.
2. **Engineering and Simulation**: AI is used in finite element analysis (FEA) and computational fluid dynamics (CFD) to simulate structural integrity, crash performance, and aerodynamics. Machine learning models predict material behavior and optimize components for weight, cost, and durability.
3. **Autonomous Driving Systems**: AI, particularly deep learning, is critical for developing self-driving car technologies. Neural networks process sensor data (LiDAR, radar, cameras) to enable features like lane detection, object recognition, and path planning.
4. **Manufacturing Optimization**: AI streamlines production by optimizing assembly lines, predicting maintenance needs, and improving quality control through computer vision to detect defects.
5. **User Experience**: AI enhances in-car systems, such as voice assistants, infotainment personalization, and driver behavior analysis for safety features like adaptive cruise control or fatigue detection.
6. **Sustainability**: AI aids in designing electric vehicles (EVs) by optimizing battery performance, thermal management, and energy-efficient components. It also supports eco-friendly material selection.
Major automakers like Tesla, Ford, Volkswagen, and Toyota, along with tech firms like NVIDIA and Waymo, integrate AI into their design workflows. For example, Tesla uses AI for both vehicle design and its Full Self-Driving (FSD) system, while startups like Lightyear leverage AI for efficient EV designs.
In short, AI is transforming car design by accelerating development, improving performance, and enabling smarter, safer, and more sustainable vehicles.“
AI is busy designing the Hybrids. It is not focusing on listing stats anymore. AI says “read the manual”Apparently AI hasn’t gotten the memo that AWD can be optioned for the 2025 Hybrid Maverick.
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