Epsom Derby - AI Preview
From ChatGPT above.
"His pedigree, being by Dubawi out of the Breeders’ Cup Mile winner Tepin, suggests he has the class and stamina to handle the Derby's 12-furlong distance."
This breeding suggests he doesn't get the derby trip. Not he has the stamina in rain softened ground. Weird the conclusions AI comes to..... anyway.
Winner out of Australia. Out of Galileo......
It is good for drawing all the threads together but it's still about picking the important bones and down weighting the less relevant. imo
"His pedigree, being by Dubawi out of the Breeders’ Cup Mile winner Tepin, suggests he has the class and stamina to handle the Derby's 12-furlong distance."
This breeding suggests he doesn't get the derby trip. Not he has the stamina in rain softened ground. Weird the conclusions AI comes to..... anyway.
Winner out of Australia. Out of Galileo......
It is good for drawing all the threads together but it's still about picking the important bones and down weighting the less relevant. imo
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ShaunWhite
- Posts: 10353
- Joined: Sat Sep 03, 2016 3:42 am
Yes you need to specifically tell it that you don't want assumptions or a copy/paste response and then it starts to do the job properly. It's tuned for min impact on their servers so defaults to the easy answer.
That's the advice I got from OpenAI support anyway.
why has dubawi progeny not won the derby?
"Dubawi has been an incredibly successful sire, producing numerous top-class racehorses, but his progeny have yet to secure a victory in the Derby. One possible reason is that Dubawi himself was more suited to middle distances rather than the extreme stamina test of the Derby. In the 2005 Derby, Dubawi finished third behind Motivator, showing that while he had class, the mile-and-a-half distance may not have been his strongest suit.
Many of Dubawi's offspring have excelled over shorter distances or in races that require a blend of speed and stamina rather than pure staying ability. His progeny have won prestigious races like the 2000 Guineas, Prix Jacques Le Marois, and Dubai World Cup, but the Derby demands a specific type of horse—one with both stamina and tactical speed. While Dubawi has sired winners of the Deutsches Derby (German Derby) and other major races, his bloodline may not be perfectly suited to the unique test of Epsom.
That said, breeding trends evolve, and it's always possible that one of his descendants could break the pattern in the future. Would you like to explore some of his most successful progeny?"
Its a bit weird that it can come up with this though....... after what it came up with earlier.....
"Dubawi has been an incredibly successful sire, producing numerous top-class racehorses, but his progeny have yet to secure a victory in the Derby. One possible reason is that Dubawi himself was more suited to middle distances rather than the extreme stamina test of the Derby. In the 2005 Derby, Dubawi finished third behind Motivator, showing that while he had class, the mile-and-a-half distance may not have been his strongest suit.
Many of Dubawi's offspring have excelled over shorter distances or in races that require a blend of speed and stamina rather than pure staying ability. His progeny have won prestigious races like the 2000 Guineas, Prix Jacques Le Marois, and Dubai World Cup, but the Derby demands a specific type of horse—one with both stamina and tactical speed. While Dubawi has sired winners of the Deutsches Derby (German Derby) and other major races, his bloodline may not be perfectly suited to the unique test of Epsom.
That said, breeding trends evolve, and it's always possible that one of his descendants could break the pattern in the future. Would you like to explore some of his most successful progeny?"
Its a bit weird that it can come up with this though....... after what it came up with earlier.....
is ai based on gazzaninga experiments left brain interpreter?
ChatGPT said:
AI, as it exists today, is not directly based on Michael Gazzaniga's left brain interpreter experiments — but his work has influenced thinking in neuroscience, psychology, and by extension, artificial intelligence.
What was Gazzaniga’s "left brain interpreter"?
Michael Gazzaniga studied split-brain patients, people who had their corpus callosum severed (usually to treat epilepsy). This structure connects the brain's two hemispheres. In these patients:
The left hemisphere (typically responsible for language) would often try to create explanations for behaviors initiated by the right hemisphere (which it no longer communicated with).
Gazzaniga called this explanatory mechanism the "left brain interpreter."
It suggests that the human brain constructs coherent narratives even from limited or contradictory data — not necessarily accurate, just plausible.
Is modern AI based on this?
No — but:
AI does construct narratives or explanations, especially in models like ChatGPT, which generate coherent text from patterns in data — somewhat analogous to the interpreter mechanism.
Gazzaniga's work has inspired theories about modular cognition, self-awareness, and narrative-building — all of which influence cognitive architectures in AI research.
AI models like ChatGPT are language-dominant and also can "rationalize" or create plausible-sounding responses, which superficially resembles the interpreter idea.
Key Differences
Feature Left Brain Interpreter Modern AI (e.g., ChatGPT)
Based in Human brain's modular biology Artificial neural networks
Mechanism Post-hoc rationalization by the left hemisphere Pattern-based next-word prediction
Awareness Arises from embodied consciousness No consciousness or awareness
Motivation Coherence in behavior and self-perception Statistical coherence of language
In summary, Gazzaniga’s "left brain interpreter" is not a blueprint for AI, but it offers insights into how humans process and generate meaning — and those insights inspire AI researchers to build systems that appear more human-like in reasoning or communication.
ChatGPT said:
AI, as it exists today, is not directly based on Michael Gazzaniga's left brain interpreter experiments — but his work has influenced thinking in neuroscience, psychology, and by extension, artificial intelligence.
What was Gazzaniga’s "left brain interpreter"?
Michael Gazzaniga studied split-brain patients, people who had their corpus callosum severed (usually to treat epilepsy). This structure connects the brain's two hemispheres. In these patients:
The left hemisphere (typically responsible for language) would often try to create explanations for behaviors initiated by the right hemisphere (which it no longer communicated with).
Gazzaniga called this explanatory mechanism the "left brain interpreter."
It suggests that the human brain constructs coherent narratives even from limited or contradictory data — not necessarily accurate, just plausible.
Is modern AI based on this?
No — but:
AI does construct narratives or explanations, especially in models like ChatGPT, which generate coherent text from patterns in data — somewhat analogous to the interpreter mechanism.
Gazzaniga's work has inspired theories about modular cognition, self-awareness, and narrative-building — all of which influence cognitive architectures in AI research.
AI models like ChatGPT are language-dominant and also can "rationalize" or create plausible-sounding responses, which superficially resembles the interpreter idea.
Key Differences
Feature Left Brain Interpreter Modern AI (e.g., ChatGPT)
Based in Human brain's modular biology Artificial neural networks
Mechanism Post-hoc rationalization by the left hemisphere Pattern-based next-word prediction
Awareness Arises from embodied consciousness No consciousness or awareness
Motivation Coherence in behavior and self-perception Statistical coherence of language
In summary, Gazzaniga’s "left brain interpreter" is not a blueprint for AI, but it offers insights into how humans process and generate meaning — and those insights inspire AI researchers to build systems that appear more human-like in reasoning or communication.
This....
It suggests that the human brain constructs coherent narratives even from limited or contradictory data — not necessarily accurate, just plausible.
And.....
AI models like ChatGPT are language-dominant and also can "rationalize" or create plausible-sounding responses, which superficially resembles the interpreter idea.
Anyway back to the real world!!
It suggests that the human brain constructs coherent narratives even from limited or contradictory data — not necessarily accurate, just plausible.
And.....
AI models like ChatGPT are language-dominant and also can "rationalize" or create plausible-sounding responses, which superficially resembles the interpreter idea.
Anyway back to the real world!!
I let Ai on chatgpt analyse screen shots from charts a few races turned out ok and some didnt but gave a good response to the charts
Conclusion:
Joli Travail appears the most likely to win based on market sentiment, as shown by:
The strong and consistent price shortening.
High trading volume.
Clear support from the market relative to the other two.
If you’re looking to follow money trends or scalping strategies, Joli Travail is currently the standout.
Most Likely Winner (Based on Market Sentiment):
Statuario – strongest price move pre-race (4.1 → 3.6), indicating strong confidence.
Alternative: Stans The Man – gaining support late with most money at current price.
If you’re trading, Statuario for early move, and Stans The Man for late momentum/back-to-lay are the angles.
Most Likely Winner (Based on Chart Data):
Conclusion:
Joli Travail appears the most likely to win based on market sentiment, as shown by:The strong and consistent price shortening.
High trading volume.
Clear support from the market relative to the other two.
If you’re looking to follow money trends or scalping strategies, Joli Travail is currently the standout.
Most Likely Winner (Based on Market Sentiment): Statuario – strongest price move pre-race (4.1 → 3.6), indicating strong confidence.
Alternative: Stans The Man – gaining support late with most money at current price.If you’re trading, Statuario for early move, and Stans The Man for late momentum/back-to-lay are the angles.
Most Likely Winner (Based on Chart Data):