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OpenAI Newly Released SimpleQA Helps Reveal That Generative AI Blatantly And Alarmingly Overstates What It Knows
Important new research shows that generative AI woefully overestimates confidence levels and thus … [+]
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In today’s column, I examine closely a recently released empirical analysis by OpenAI, the maker of ChatGPT, revealing that generative AI severely overstates confidence levels regarding the responses that the AI generates. This means that when AI gives you an answer that the AI portrays for example as fully aboveboard and hunky-dory, the reality is that the response is bound to be a lot shakier than you are being led to believe.
Generative AI is pulling the wool over your eyes. The AI is giving you a snow job. You are being gaslighted by the AI.
Let’s talk about it.
This analysis of an innovative proposition is part of my ongoing Forbes.com column coverage on the latest in AI including identifying and explaining various impactful AI complexities (see the link here).
Dangers Of Dealing With Someone Supremely Overconfident
Before we jump into the AI side of things, I’d like to begin by reflecting on humans and the nature of human behavior associated with someone being supremely overconfident.
You ask a stranger what time it is. Turns out that you don’t have your watch, and you left your smartphone back in your car. So, you are unsure of the exact time. The person says to you in a strong and extremely confident voice that the time is 1:34 p.m. They are emphatic that they have given you the precise time of day as though there is no possible debate or discussion to be had.
Period, end of story.
Another person happens to walk by at that same moment and overhears you asking for the time. This interloper looks intently at their timepiece and tells you that it is 1:48 p.m. Whoa, something isn’t right here. The first given time was said to be 1:34 p.m. on the nose, while the subsequent passerby looked at their watch and noted that it was supposedly 14 minutes later and actually 1:48 p.m.
Upon your gentle questioning of the first person, the one that said they were abundantly irrefutably sure it was 1:34 p.m., they now cave in and admit it was just a guess. But that’s not what they said or intimated when you asked them for the time. They portrayed their answer as though it was golden. You could take that stated time to the bank, as it were.
What gives?
That person might be the type of individual who believes one hundred percent in every utterance they convey. It is their personal style. They never want to seem wimpy or waffling. If they tell you something, by gosh it is the absolute truth of the matter. You aren’t to have even the tiniest doubt in your mind about what they say to you.
Have you ever met such a supremely confident person?
I’m sure that you have. We all have. These types of people act as though they are the chosen ones who can speak with complete certainty. It doesn’t matter whether the topic at hand is big or small. They will take the most trivial aspect and still cling to their certainty. When confronted with alternative perspectives, some will back down, while others might argue until blue in the face about the oddest claims or contentions.
The problem is this.
If you don’t know that a person you are dealing with has that kind of hubris, you can end up in some precarious positions. You take their portrayal of certainty and assume it to be valid. The next thing you know, you have gotten yourself into a pickle because what they said was flimsy and fell apart.
Regrettably, you let their sense of overconfidence mislead you.
Generative AI Deals With Certainty And Uncertainty
Let’s next shift into generative AI mode.
You might not be aware that generative AI makes extensive use of certainty and uncertainty. Under the hood of generative AI, there is a whole bunch of statistical and probabilistic estimations going on, see my detailed explanation at the link here. Every response that AI generates also has a devised level of certainty, which you could say represents essentially a level of uncertainty too (i.e., 60% certainty of something, implying 40% uncertainty of that same something).
Either way, the crux is that the answers by AI are always accompanied by a kind of confidence level concerning how likely the answer is correct or not.
Most users of generative AI are oblivious to this facet. They don’t know it even exists. There’s a reason why they don’t. It is because the AI makers go out of their way to keep it out of view. They want you to have full faith in what AI generates. If the AI continually shows you a certainty or confidence level, this might scare you into thinking that AI is not completely trustworthy.
Of course, the reality is that generative AI is in fact not fully trustworthy. Any answer produced by generative AI deserves your best kind of scrutiny. Double-check the response. Triple-check if the matter is a serious one. Do not believe what the AI tells you. Always assume that there is a solid chance that the AI is wrong or has made an error, including a so-called AI hallucination (see my coverage at the link here).
The bad news then is that the preponderance of users is blindly unaware of this rather significant consideration when using generative AI, namely that the answers are not 100% certain all the time. I would dare say that 100% is a rarity. Yet you are seldom told this explicitly by the AI.
The good news is that you can tell the AI to inform you about the calculated level of confidence. In your prompts, you can directly instruct generative AI to indicate the certainty and/or uncertainty of each response. The prompting technique varies depending upon whether you want this done one-time, often, all the time, or under varying circumstances. See my tutorial on the prompting of generative AI to display confidence levels, at the link here.
There’s something else worth mentioning about this. The default response protocol being used for most of the major generative AI apps such as ChatGPT, GPT-4o, o1, Google Gemini, Anthropic Claude, Meta Llama, and others is customarily going to be to word responses with clues or hints about certainty and uncertainty.
For example, suppose the AI indicated that “the time right now is 2:05 p.m., but please know that I am not connected to a real-time clock.” You are being told two things at once. You are being given a precise time which you would naturally assume to be accurate and timely. The thing is, you would need to read the rest of the response and realize that since the AI is not connected to a real-time clock, the stated time might be off target. The wording though was a bit tricky and didn’t come out straight away and warn you to be suspicious of the claimed time. That’s what should have happened to try and maximize clarity.
Worse Still Is That Generative AI Is Overconfident
Okay, you now know that there is an internal calculation of certainty and uncertainty. That’s a handy pro tip.
I have a twist for you.
Get yourself prepared and find a comfy place to sit down.
Here’s the monumental question at play:
- Do you think that the calculated confidence level matches with the reality of the actual answers being generated and conveyed?
Allow me to elaborate. Suppose the AI calculates that a given response is around a 90% level of certainty. Great, that seems relatively high, and you might be somewhat safe to rely upon the answer, depending upon the consequences of making such a reliance.
What if we compared the generated answer that the AI claims consisted of a 90% confidence level to a real-world answer that we had available to us? It could be that 90% was a pretty solid estimate and we are happy with the calculated certainty. On the other hand, we might discover that the answer should have been given a confidence level of say 40%, much lower than the amount estimated by AI.
Yikes, that’s disconcerting. The AI egregiously missed the mark and woefully misjudged the estimated confidence level. If you had asked the AI to show you the confidence level, and you saw that it was 90%, you might have proceeded under a misleading or false impression. The value should have been 40%.
Maybe this happens once in a blue moon, and you can rest easy. Well, I have a shocker for you. It happens a lot more than you would imagine. A heck of a lot more.
In a recent research study by OpenAI involving a new benchmark coined as SimpeQA that is intended for assessing generative AI apps, the researchers pursued on a kind of secondary basis to explore the confidence level estimations of AI. That wasn’t the mainstay of the effort. I mention this to highlight that you are encouraged to learn more about SimpleQA as a helpful benchmarking capability.
Here, I want to focus for now on the confidence level considerations.
You could say with great confidence that generative AI appears to be supremely overconfident in the responses that are being generated. Oops, that’s not good. Sad face.
Research Results Tell Quite A Story Of Woe
In an OpenAI study published online at the OpenAI official blog site, the paper entitled “Measuring Short-Form Factuality In Large Language Models” by Jason Wei, Nguyen Karina, Hyung Won Chung, Yunxin Joy Jiao, Spencer Papay, Amelia Glaese, John Schulman, and William Fedus, OpenAI Research Paper, October 30, 2024, made these salient points (excerpts):
- “We present SimpleQA, a benchmark that evaluates the ability of language models to answer short, fact-seeking questions.”
- “A factuality benchmark like SimpleQA allows us to measure the scientific phenomenon known as calibration, or whether language models “know what they know.”
- “One way to measure calibration is to directly ask the language model to state its confidence in its answer using a prompt like: “Please give your best guess, along with your confidence as a percentage that it is the correct answer.”
- “Then we can plot the correlation between the stated confidence of the model, and how accurate the model actually was. A perfectly calibrated model would have the same actual accuracy as the stated confidence. For instance, on all prompts where the model stated a confidence of 75%, the accuracy would be 75% for a perfectly calibrated model.”
- “However, the fact that performance is well below the line y=x means that models consistently overstate their confidence. Hence, there is a lot of room to improve the calibration of large language models in terms of stated confidence.”
I will expand upon those above points.
I earlier noted that we would be dismayed if AI said a confidence level of 90% and yet the real-world value ought to be 40%. Any large gap is going to be problematic. We won’t get overly concerned if the gap is small, let’s say if the AI estimated 90% and the real-world value was 85%, we might have a modest amount of heartburn, but not as much in the case of the much lower 40%.
In a chart provided in the above-cited research study, I used some interpolation to gauge how far off on average the AI estimated confidence level was from the desired actual accuracy. My interpolations are only rough gauges since the chart has several generative AI apps shown, thus there are a lot of variabilities involved. Nonetheless, I tried to be relatively fair by using what seemed to be the semblance of the values shown
Here’s what my eyeballing suggested:
- ——Level of 50%————
- AI stated level of confidence: 50%
- Actual accuracy: 10% approximately.
- ——Next level at 70% ————
- AI stated level of confidence: 70%
- Actual accuracy: 20% approximately.
- ——Next level at 80% ————
- AI stated level of confidence: 80%
- Actual accuracy: 40% approximately.
- ——Next level at 95% ————
- AI stated level of confidence: 95%
- Actual accuracy: 60% approximately.
The grim concern is that at a stated 95% level of confidence by AI, the reality is more akin to a 60% confidence level. That’s unnerving. So too is that at 80% the reality seems to be around 40%. Even when you get down to 50% or flip-of-the-coin, the reality is more akin to just 10%.
The hair on the back of your head ought to be standing up.
Why This Is A Big Deal Of Great Importance
I logged into ChatGPT and asked why we ought to be worried about these kinds of results and to provide a few examples.
- My entered prompt: “Give me three examples of what could happen if the AI indicated confidence level is a lot higher than the real value.”
- ChatGPT generated response:
“Certainly, here are three examples that illustrate the potential consequences of overconfident generative AI in different fields.”
“Medical diagnosis: A generative AI tool is used by doctors to suggest possible diagnoses based on symptoms. The AI recommends a rare but severe condition with 95% confidence, but in reality, its accuracy at this confidence level is only 60%. A doctor might rely on this high-confidence suggestion and order unnecessary, costly, or invasive tests, causing patient anxiety and increasing healthcare costs. Worse, if the diagnosis is incorrect, a more likely and treatable condition might be overlooked, endangering the patient’s health.”
“Investment recommendation: A financial advisor uses generative AI to analyze market data and generate investment recommendations. The AI suggests investing heavily in a stock with 95% confidence, based on recent market movements, but its true accuracy at this level is much lower. If the stock’s performance doesn’t align with the AI’s recommendation, investors could face substantial losses.”
“Customer support: A tech support AI chatbot confidently advises users to perform a specific solution to fix a common software issue, rating its response at 85% confidence. In reality, the accuracy is closer to 50%. If the AI’s advice is incorrect, users may follow steps that could worsen their problem, such as misconfiguring settings, corrupting files, or spending hours troubleshooting the wrong issue. This also results in more calls to customer support to undo the AI’s guidance.”
End of ChatGPT response
Those are vivid examples of why you should be supremely careful in getting caught by AI that is supremely overconfident.
I asked ChatGPT to give us humans some overarching advice on the matter.
- My entered prompt: “What can be done about generative AI overstating its level of confidence?”
- ChatGPT generated response: “In practice, this miscalibration can be problematic, especially in high-stakes domains like healthcare, law, or finance, where overconfident but incorrect AI responses could lead to adverse outcomes. To address this, developers are exploring ways to improve confidence calibration, such as by incorporating explicit feedback systems, refining training protocols, and developing post-deployment accuracy testing methods.”
I would also like to add that AI makers and those fielding AI need to be extremely cautious in applying generative AI to domains that have demonstrative consequences.
The medical domain has life-or-death outcomes. The financial domain could be monetarily ruinous to someone. By and large, the AI makers try to cover their liability by stating in their licensing agreements that you aren’t supposed to use their generative AI for those situations, or that if you do then you are making that choice and it isn’t on them, see my analysis of these pronounced AI & Law matters at the link here.
Bottom Line Is Keep Your Wits About You
I said earlier that you ought to not believe generative AI at face value. That goes for the confidence levels too.
You’ve been forewarned.
I should mention that the cited study is only one particular study on a particular set of generative AI apps at a particular point in time. Please do not overgeneralize these results. At the same time, take this as a cold splash of water and a wake-up call. If you are going to ask for confidence levels, be cognizant of how to judge them. Also, the semblance of high confidence conveyed via the wording of the AI responses should be carefully scrutinized. You might be getting tricked or bamboozled.
The last word on the overall dangers of overconfidence goes to the famous astronaut Neil Armstrong: “Well, I think we tried very hard not to be overconfident because when you get overconfident, that’s when something snaps up and bites you.”
I ask that you not let generative AI reach out and bite you. That’s something you won’t relish. It could be utterly disastrous for all concerned.
And you can take that 100% to the bank.
¡Prepárate para montar la ola de suerte y expansión!
El 6 de abril, mientras transmite el signo audaz y ardiente de Aries, el Sol se reunirá con Júpiter en Géminis en un afortunado sextil, creando una oportunidad emocionante para el crecimiento, la prosperidad y los nuevos y audaces comienzos.
Si ha estado ansiando algo nuevo y emocionante, este tránsito podría ser la luz verde que ha estado esperando. Es el momento perfecto para arriesgarse, expandir sus horizontes y celebrar hitos.
El Sol en Aries tiene que ver con la acción, el coraje y el liderazgo. Como el primer signo en el zodiaco, Aries encarna una chispa de iniciación, al igual que su gobernante planetario, Marte. Entonces, con el sol viajando a través de este intrépido signo de fuego, es hora de avanzar y adoptar desafíos con confianza y coraje.
Júpiter, por otro lado, es el planeta de abundancia, optimismo y expansión. En el signo cerebral de Géminis (curiosidad, comunicación y adaptabilidad, Júpiter abre un mundo de posibilidades. Amplifica la necesidad de exploración intelectual, nuevas ideas y conexiones sociales.
Este tránsito nos invita a ampliar nuestras perspectivas, pensar fuera de la caja y sumergirnos en nuevas aventuras que expanden nuestras vidas personales y profesionales.
El sextil del sol a Júpiter el 6 de abril es una poderosa combinación de pasión ardiente y expansión intelectual. Es un momento en que las oportunidades de crecimiento y exploración se sienten abundantes, y el cosmos recompensa a aquellos que están dispuestos a correr riesgos y adoptar el cambio.
Ya sea que esté comenzando un nuevo proyecto, tomando una gran decisión o sentirse inspirado para hacer algo nuevo, este tránsito ofrece el potencial de prosperidad y abundancia.
Siga leyendo para lo que esto significa para su signo del zodiaco.
Aries (del 20 de marzo al 19 de abril)
¡Eres la estrella del espectáculo, Aries! Además de que es su temporada de regreso solar, con el sol encendido por su primera casa, está uniendo fuerzas con Lucky Júpiter … y bueno, ¡eres imparable! Este es el momento perfecto para lanzar un proyecto personal o renovar su imagen. Considere actualizar su marca o presencia en las redes sociales para que coincida con su energía. Este tránsito se trata de ti, poseerlo y brillar.
Tauro (del 19 de abril del 20 de mayo)
Este es un momento para la reflexión y el crecimiento espiritual, Tauro. Aries gobierna su introspectiva casa 12 de patrones subconscientes y la iluminación de Júpiter en su segunda casa de finanzas y valores, lo que le brinda la claridad de liberarse de los viejos patrones mentales que ya no le sirven. Tal vez es hora de dejar de lado esos sistemas de creencias limitantes en torno al dinero o su autoestima. Confíe en que las nuevas y prósperas oportunidades esperan una vez que lo haga.
Géminis (del 20 de mayo al 20 de junio)
¡Es tu día de suerte, Géminis! A medida que el Sol energiza a su 11ª Casa de Asuntos Comunitarios, Júpiter aporta expansión y oportunidad a su letrero (¡y en la puerta de entrada!), Lo que lo convierte en un excelente momento para conectarse con personas influyentes y aquellos que comparten objetivos y sueños similares. Una oportunidad de establecer contactos podría llegar en su camino, o podría unirse inesperadamente a un grupo que se alinee perfectamente con sus valores.
Cáncer (del 20 de junio al 22 de julio)
Alcance las estrellas: su carrera está bajo el centro de atención, el cáncer. A medida que el Sol energiza y revitaliza su décima casa de autoridad pública, Lucky Júpiter lo hace más receptivo y sintonizado con su crecimiento personal y profesional. Esto no solo ofrece ideas espirituales, sino que también te empuja a hacer movimientos audaces en tu vida profesional. El éxito está en el horizonte.
Leo (22 de julio al 22 de agosto)
¡La aventura te espera, Leo! El sol está gobernado por el sol, y mientras enciende su novena casa de expansión filosófica, unirá fuerzas con Lucky Júpiter en su 11ª Casa de Asociaciones, Asuntos Comunitarios y visiones futuras. Ya sea que se trate de un viaje de último minuto, una clase en la que se está inscribiendo o un pasatiempo nuevo que está explorando, su mente y su corazón están abiertos a nuevas experiencias. Carpe Diem.
Virgo (22 de agosto al 22 de septiembre)
Este es un gran problema: confía en que la transformación que está experimentando es para su más alto bien, Virgo. Con el sol sacudiendo su octava casa de intimidad y recursos compartidos, se reunirá con Lucky Júpiter en su décima casa de carrera y reputación pública. Una ganancia inesperada financiera o un profundo avance emocional podría estar en camino, ayudándole a entrar en su poder personal. Estar abierto a lo inesperado.
Libra (del 22 de septiembre al 22 de octubre)
Sus asociaciones y acuerdos contractuales están bajo el foco de este tránsito, Libra. A medida que el sol energiza su sector de relaciones, se reunirá con Audacy Júpiter en un sextil armonioso. Ya sea amor, negocios o amistades, una nueva conexión podría sentirse destinada. Es un buen momento para trabajar con otros en empresas conjuntas o colaboraciones que contribuyen a su crecimiento personal y profesional.
Scorpio (22 de octubre a Nov. 21)
Sus hábitos de salud pueden mejorar drásticamente bajo esta sinergia empoderadora, Scorpio. Si bien el trabajo y los asuntos de salud están a la vanguardia, el sextil de Sun a Júpiter, activando su sexta casa de bienestar y octava casa de empresas conjuntas, podría inspirarlo con la confianza y la energía que necesita para asumir nuevos desafíos. Tal vez es hora de sacudir su rutina o asumir un nuevo objetivo de salud. Una nueva oportunidad de trabajo o reconocimiento podría llegar a su manera, haciendo que sus esfuerzos se sientan más gratificantes.
Sagitario (22 de noviembre al déco de 21)
Sus jugos creativos fluyen, y eso es un eufemismo, Sagitario. Después de todo, no es todos los días que su gobernante planetario de la suerte, Júpiter, une fuerzas con el sol en su quinta casa de amor, pasión y autoexpresión. Aplastar por alguien especial? Ya sea que esté trabajando en un proyecto de pasión, atrapando sentimientos románticos o entrando en el centro de atención con un esfuerzo creativo, su aura está radiante y está listo para brillar. El amor también podría ser espontáneo y emocionante.
Capricornio (del 21 de diciembre al 19 de enero)
El hogar es donde está tu corazón, entonces, ¿por qué no darle el amor que merece, Capricornio? Con el sol que abarca su cuarta casa doméstica del hogar y la familia, mientras que en el flujo de energía armonioso con Júpiter en su sexta casa de mejora, logística y responsabilidad, puede sentirse llamado a mejorar su espacio vital o crear más espacio para sus pertenencias. Tal vez es hora de redecorar, mudarse a un nuevo espacio o incluso fortalecer los lazos familiares.
Acuario (19 de enero de 18 años)
Usa tus palabras sabiamente: son más poderosos de lo que te das cuenta, Acuario. Con el sol energizando su curiosa tercera casa de comunicación, sus pensamientos e intercambios serán clave durante este tiempo. Aún así, a medida que el Sol se armoniza con Júpiter en su quinta casa de fertilidad y expresión creativa, eres igualmente inspirador y seguro en tu enfoque. Es posible que tenga una conversación esclarecedora que lleva su relación al siguiente nivel o provoca una nueva idea para un proyecto.
Piscis (del 18 de febrero al 20 de marzo)
¡El dinero fluye y la abundancia está llamando, Piscis! A medida que el sol energiza su segunda casa de comodidad, finanzas y valores que busca la estabilidad, se reunirá con Júpiter en su cuarta casa del hogar, la familia y los lazos emocionales. ¿Listo para hacer esa inversión en su espacio vital? Otros podían sentirse llamados para gastar un poco de efectivo extra en una excursión familiar. Confía en tu intuición: la prosperidad podría venir de manera sorprendente.
A finales de 2023, escuchamos que Google estaba trabajando en un nuevo asistente digital que evidentemente se planeó debutar en el Pixel 9 en 2024. Evidentemente llamado Pixie, el asistente habría manejado tareas de IA en el dispositivo usando un modelo de Gemini Nano. Pero la IA nunca se materializó. Entonces, ¿qué pasó con Pixie, y lo volveremos a ver?
Bienvenido al compiladorsu resumen semanal de Goings-On. Paso mis días mientras el editor de Google leyendo y escribiendo sobre lo que Google está haciendo a través de Android, Pixel, Gemini y más, y hablo de todo aquí en esta columna. Esto es lo que ha estado en mi mente esta semana.
¿Qué era Pixie?
Según los informes de la información, Pixie estaba destinado a ser un asistente de IA en el dispositivo exclusivo de los teléfonos de Google Pixel, concebido antes de que el chatbot Gemini llegara a la escena (todavía era Google Bard en aquel entonces). Usando un modelo local de Géminis Nano, la IA habría extraído datos de las aplicaciones de Google en su teléfono para ofrecer asistencia más personalizada. La información dijo en 2023 que Pixie podría haber evolucionado “a una versión mucho más personalizada del Asistente de Google”.
Aparentemente, Pixie estaba planeado para asumir las tareas del asistente del Asistente de Google en los teléfonos de Google. Obviamente, eso nunca sucedió, aunque Google ha anunciado oficialmente sus planes para eliminar gradualmente al Asistente Legacy a favor de Gemini en el futuro cercano.
Relacionado
Géminis está reemplazando oficialmente al Asistente de Google, esto es lo que eso significa para ti
Google Assistant se está jubilando este año
¿Qué pasó con Pixie?
La serie Pixel 9 aterrizó el año pasado sin mencionar el asistente de Pixie que se rumoreaba el año anterior. El informe posterior de la información (llamado a nuestra atención por 9to5Google) arroja algo de luz sobre lo que pudo haberle sucedido a Pixie.
Según los informes, el CEO de Google, Sundar Pichai, ordenó personalmente un cambio en la estrategia con Pixie para evitar la competencia con el asistente de IA prioritario de Google, Gemini. La marca Pixie parece estar bien y verdaderamente retirada, pero algunas características de Pixie terminaron llegando al Pixel 9. Capturas de pantalla de Pixel, una característica de IA local impulsada por el modelo Gemini Nano XS, evidentemente comenzó su vida como funcionalidad de Pixie. 9to5Google también ha informado que la extensión de servicios públicos de Gemini que permite a la IA controlar directamente la configuración del dispositivo, la reproducción de medios, las alarmas y más, al mismo tiempo, se planeó ser parte de la experiencia de Pixie.
La información ha informado que estas características aparentemente salieron de Pixie no hacen una experiencia tan similar a lo que Pixie habría sido. Sin embargo, es posible que veamos más de lo que Pixie podría haber sido en el futuro.
Relacionado
La pequeña aplicación de capturas de pantalla de Pixel de Google finalmente me convenció de que AI podría ser un gran problema
Las capturas de pantalla de Pixel pueden ser la forma más clara de Google de demostrar que la IA es útil
¿Podría Pixie regresar?
Con Gemini tan claramente una prioridad para Google, parece poco probable que veamos el lanzamiento de un asistente de inteligencia artificial exclusivo de píxeles que se superpone con el conjunto de funciones de Gemini; de hecho, con Gemini listo para reemplazar el Asistente de Google en la mayoría de los dispositivos en el futuro cercano, Google parece que va en la dirección opuesta. Pero un informe de marzo de Android Authority que hace referencia a “Una fuente dentro de Google” dice que más funcionalidad de Pixie llegará a la serie Pixel 10 en forma de una nueva aplicación llamada Pixel Sense.
Parece que Pixel Sense no competirá directamente con Gemini, sino que intentará proporcionar sugerencias “predictivas” basadas en el contexto de sus aplicaciones de Google conectadas, incluidos Calendar, Chrome, Gmail, Keep, Maps y más. Pixel Sense aparentemente también podrá organizar sus capturas de pantalla en un archivo de búsqueda como lo hace la aplicación de capturas de pantalla Pixel actual, insinuando que puede reemplazar las capturas de pantalla por completo.
Pixel Sense funcionará completamente en el dispositivo; Android Authority cita una fuente diciendo que “sus datos permanecen privados, visibles solo para usted, ni siquiera Google puede verlo”.
Los informes de AA no pintan una imagen completa de cómo funcionará realmente la aplicación Pixel Sense, pero como se describe, parece que podría funcionar de manera similar a la de Google Now, o la función S25 similar de Samsung, ahora breve. Esas características también tienen como objetivo proporcionar información según lo necesite, informado por el contexto de sus cuentas conectadas. Con el acceso a lo que parece esencialmente toda la información almacenada en su cuenta de Google y alimentada por Gemini Nano, Pixel Sense podría hacer un mejor trabajo para ofrecer actualizaciones útiles a medida que las necesita.
Relacionado
Revisión: El Samsung Galaxy S25 es un teléfono pequeño sin grandes ideas
Todavía bastante agradable, aunque
Géminis es tu asistente de IA de Android para lo previsible
El asistente de Pixie probablemente nunca verá la luz del día en su forma inicialmente planificada; Google está poniendo todos sus huevos de asistente en la canasta de Géminis. Pero parece que obtendremos más de la funcionalidad de Pixie en la serie Pixel 10 en forma de la nueva aplicación Pixel Sense. En cuanto a qué es exactamente el sentido de Pixel, tendremos que esperar y ver. Es posible que escuchemos más en Google I/O, que comienza el próximo mes.
After correctly predicting Denny Hamlin to win his first race of the NASCAR Cup Series season, we’re turning to AI to help us predict the winner and full finishing order for the Goodyear 400 at Darlington Raceway today at 3 p.m. ET (FS1).
We asked ChatGPT for its NASCAR at Darlington predictions based on historical data, betting odds, and statistical trends – including its pick to win, best prop bet, and favorite long shot, as well as the results for every driver for today’s 38-car field.
Along with our 2025 Goodyear 400 predictions at Darlington, here are our AI-powered NASCAR best bets and full AI-simulated finishing order:
NASCAR AI picks & predictions for Goodyear 400 at Darlington
We’ve previously used ChatGPT to predict its March Madness bracket, Super Bowl picks, and even its Canada vs. USA predictions, and we’re once again turning to OpenAI’s popular chatbot to predict the winner of today’s Goodyear 400 at Darlington.
We trained ChatGPT’s latest and most advanced AI model to study the latest NASCAR odds, betting history, and relevant trends before predicting this weekend’s winner:
ChatGPT’s pick to win Goodyear 400 at Darlington
ChatGPT predicts Denny Hamlin will win the Goodyear 400 at Darlington. His best odds are +800 via BetMGM, which would turn a winning $10 bet into an $80 profit with an implied win probability of 11.11%.
Here’s why the AI model is predicting Hamlin will win today’s race:
Short-track savvy: Hamlin’s long history on short, punishing tracks gives him the experience needed to navigate Darlington’s notorious “Track Too Tough to Tame,” avoiding the mishaps and attrition that often plague less experienced drivers.
Team excellence & strategy: Joe Gibbs Racing consistently fields strong cars at Darlington, and Hamlin’s ability to manage cautions, fuel strategy, and late-race restarts is a big advantage on this challenging circuit.
Proven consistency: Despite the inherent chaos of Darlington, Hamlin’s track record as a veteran who can execute under pressure makes him a standout in a field where even the favorites have slim win probabilities.
AI confidence level: 
(15% win probability)
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ChatGPT’s best prop bet for Goodyear 400 at Darlington
ChatGPT predicts Chase Briscoe will finish in the top three as its best NASCAR prop bet for Darlington. Briscoe’s best odds to score a top-3 finish are +550 via bet365, which would turn a winning $10 bet into a $55 profit with an implied win probability of 15.38%.
Here’s why the AI model is predicting Briscoe to finish in the top three today:
Strong starting position & package: Briscoe qualified 4th with Joe Gibbs Racing – a team known for building competitive cars at Darlington – and his starting position puts him right in the mix.
Experience on tough tracks: JGR drivers have a good track record at Darlington, and Briscoe’s aggressive yet measured driving style makes him well-suited to navigate Darlington’s unique challenges.
Ability to capitalize on caution-fueled restarts: Darlington is notorious for its unpredictable cautions and restarts. If the leaders are caught up in strategy or on-track incidents, Briscoe’s aptitude for seizing opportunities could see him climbing into the top three.
AI confidence level: (25% chance of top-3 finish)
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ChatGPT’s best long shot to win Goodyear 400 at Darlington
ChatGPT predicts Alex Bowman to win the Goodyear 400 as its best long shot at Darlington. His best odds to win are +5000 via Caesars, which would turn a winning $10 bet into a $500 profit with an implied win probability of 1.96%.
Here’s why the AI model is predicting Bowman as its best long shot today:
Undervalued starting position vs. team quality: Although Bowman qualified 33rd, his Hendrick Motorsports car is typically one of the best on the circuit. A deep starting position can mask his true race pace if his team brings a strong setup for Darlington.
Opportunity in Darlington’s chaos: Darlington’s reputation for attrition, unpredictable cautions, and strategic gambles means that drivers starting deep can climb the order dramatically if they avoid early incidents.
Proven ability to overperform: Bowman has shown in past races that he can make up significant ground when conditions favor his driving style. His experience and skill could allow him to exploit a chaotic race and deliver a surprise win.
AI confidence level: (4% win probability)
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Goodyear 400 AI projections for full finishing order
Here is our predicted Goodyear 400 finishing order and results for every driver based on AI projections. While ChatGPT is a large language model and not specifically designed for predicting sporting events, it can spot trends or insights that NASCAR bettors might overlook.
ChatGPT’s full NASCAR finishing order predictions at Darlington
1. Denny Hamlin 
(No. 11, Joe Gibbs Racing Toyota) – Using his veteran short‐track savvy and ability to manage fuel and cautions, Hamlin pulls away to take the win.
2. William Byron 
(No. 24, Hendrick Motorsports Chevrolet) – Byron’s strong car and clean air from starting first help him finish near the front.
3. Chase Briscoe 
(No. 19, Joe Gibbs Racing Toyota) – A well-handled race by Briscoe capitalizing on strategic restarts secures him a podium finish.
4. Bubba Wallace (No. 23, 23XI Racing Toyota) – Wallace’s aggressive style suits Darlington’s unpredictable nature, keeping him in the top four.
5. Kyle Busch (No. 8, Richard Childress Racing Chevrolet) – Busch’s experience and ability to avoid trouble make him a steady presence in the top five.
6. Joey Logano (No. 22, Team Penske Ford) – Logano overcomes a deeper starting position with a series of strong restarts to climb into the top six.
7. Chase Elliott (No. 9, Hendrick Motorsports Chevrolet) – Despite a mid-pack start, Elliott’s racecraft and Hendrick’s setup allow him to finish strongly.
8. Tyler Reddick (No. 45, 23XI Racing Toyota) – Reddick’s speed and determination help him navigate the short-track mayhem for a top-10 finish.
9. Austin Cindric (No. 2, Team Penske Ford) – Cindric’s consistency and a smart pit strategy keep him in contention among the leaders.
10. Christopher Bell (No. 20, Joe Gibbs Racing Toyota) – Bell capitalizes on clean air and a well-timed move to round out the top 10.
11. Ryan Blaney (No. 12, Team Penske Ford) – Blaney stays in the mix and finishes solidly in the upper group.
12. Kyle Larson (No. 5, Hendrick Motorsports Chevrolet) – Larson’s talent sees him fighting through traffic for a top-12 finish.
13. Todd Gilliland (No. 34, Front Row Motorsports Ford) – In the midst of the short-track chaos, Gilliland manages to keep a respectable position.
14. Ryan Preece (No. 60, RFK Racing Ford) – Preece, starting near the front, is jostled around early and slips to 14th.
15. Michael McDowell (No. 71, Spire Motorsports Chevrolet) – McDowell’s early speed is tempered by the attrition typical of Darlington, landing him mid-pack.
16. Ty Gibbs (No. 54, Joe Gibbs Racing Toyota) – The young gun shows promise but finishes behind the veterans as the race unfolds.
17. Carson Hocevar (No. 77, Spire Motorsports Chevrolet) – Hocevar’s package keeps him in contention, but he ultimately settles in the lower mid-field.
18. Chris Buescher (No. 17, RFK Racing Ford) – Buescher’s RFK setup allows him to cruise steadily, finishing just outside the top 15.
19. Justin Haley (No. 7, Spire Motorsports Chevrolet) – Haley makes a late charge but is held back by traffic, finishing in the upper mid-field.
20. Ross Chastain (No. 1, Trackhouse Racing Chevrolet) – Chastain’s bold moves see him climb significantly – but contact and cautions slow his progress, putting him 20th.
21. Austin Dillon (No. 3, Richard Childress Racing Chevrolet) – Dillon’s car struggles with the track’s relentless demands, dropping him into the lower mid-field.
22. Josh Berry (No. 21, Wood Brothers Racing Ford) – Berry’s knack for close-quarters racing keeps him around the 20th–22nd range.
23. Brad Keselowski (No. 6, RFK Racing Ford) – Keselowski battles through on-track incidents to finish in the low 20s.
24. Zane Smith (No. 38, Front Row Motorsports Ford) – Smith’s less competitive package and a few missteps push him slightly back.
25. A.J. Allmendinger (No. 16, Kaulig Racing Chevrolet) – Allmendinger’s aggressive style yields mixed results, and he ends up mid-pack.
26. Noah Gragson (No. 4, Front Row Motorsports Ford) – Gragson is caught in the frequent Darlington cautions, finishing in the mid-field.
27. John Hunter Nemechek (No. 42, Legacy Motor Club Toyota) – Nemechek’s strategic driving helps him inch forward, but he remains in the lower mid-field.
28. Ricky Stenhouse Jr. (No. 47, Hyak Motorsports Chevrolet) – Stenhouse Jr. is involved in a couple of incidents, dropping him further back.
29. Ty Dillon (No. 10, Kaulig Racing Chevrolet) – With a modest package, Ty Dillon finishes in the latter part of the field.
30. Daniel Suarez (No. 99, Trackhouse Racing Chevrolet) – Suarez’s volatile style sees him struggle with consistency, landing him near the back.
31. Cole Custer (No. 41, Haas Factory Team Ford) – Custer’s car isn’t well-suited for Darlington, resulting in a lower-field finish.
32. Riley Herbst (No. 35, 23XI Racing Toyota) – Inexperience and a lack of track finesse see Herbst fade in the latter half.
33. Alex Bowman (No. 48, Hendrick Motorsports Chevrolet) – Bowman’s pace drops off amid the chaos, and he falls toward the back.
34. Erik Jones (No. 43, Legacy Motor Club Toyota) – Jones is hampered by on-track contact and ends up further down the order.
35. Cody Ware (No. 51, Rick Ware Racing Ford) – With one of the least competitive packages, Ware is forced into a deep back finish.
36. Shane van Gisbergen (No. 88, Trackhouse Racing Chevrolet) – The international star struggles to adapt to Darlington’s brutal demands and falls out of contention.
37. Austin Hill (No. 33, Richard Childress Racing Chevrolet) – Hill’s inexperience on this demanding track sends him near the rear.
38. J.J. Yeley (No. 44, NY Racing Team Chevrolet) – Yeley’s limited Cup experience sees him finish in the final stretch.
NASCAR best bets for Goodyear 400 at Darlington
| Bet | Driver | Odds | Implied win probability |
|---|---|---|---|
| Pick to win |
Denny Hamlin | +800 | 11.11% |
| Best prop bet |
Chase Briscoe (top-3) | +550 | 15.38% |
| Best long shot |
Alex Bowman | +5000 | 1.96% |
How to watch the 2025 Goodyear 400 at Darlington
Race date: Sunday, April 6
Start time: 3 p.m. ET
Track: Darlington Raceway (Darlington, S.C.) TV: FS1 | Streaming: Fox Sports App
Best NASCAR betting sites for Goodyear 400 at Darlington
Looking to bet on the Goodyear 400 at Darlington Raceway? Here are our top-rated NASCAR best sports betting sites as determined by our expert team at Sportsbook Review, along with our best sportsbook promos ahead of today’s race at 3 p.m. ET.
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