Noticias
Which AI Is Smarter And More Useful?
Generative AI has been with us for over two years now, with most major tech companies trying to take a piece of the action. OpenAI’s ChatGPT may be the product more people know about thanks to its early market advantage, but Microsoft Copilot has the immense power of a multi-trillion dollar company behind it. Seems like a fair enough fight, right? So, with OpenAI and Microsoft both touting their flagship AIs, which one is actually the better bot when it comes to everyday usefulness?
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I’ve been putting AIs to the test against one another for a while now. Last year, when pitting ChatGPT against Google Gemini, the latter stole the crown — but only barely. Can Copilot pull off a similar victory? I’ve devised a gauntlet of tests for these AIs, with questions designed to be difficult for large language models. Simply put, the goal is to push these AIs outside of their comfort zones to see which one has the widest range of usability and highlight their limitations.
First, some parameters. I performed all these tests on the free version of both platforms, as that’s how the majority of users will experience them. If you’re one of the people paying $200 a month for the most premium version of ChatGPT, for example, your experience will differ from these results. Two, I used the main chat function for each test unless otherwise stated.
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What are Copilot and ChatGPT?
You’re likely familiar with OpenAI ChatGPT, and by extension, Microsoft Copilot. They’re AI chatbots that can have conversations, answer questions, and more. On a more technical level, both Copilot and ChatGPT are large language model (LLM) AIs. They are trained on large amounts of text scraped from a variety of sources using a transformer model that calculates the relationships between words.
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On the user-facing side, they generate text in response to user-submitted prompts by guessing the probability of each word they output. To heavily oversimplify, they’re kind of like your phone keyboard’s next-word prediction feature, but far, far more complex.
OpenAI makes ChatGPT, while Microsoft makes Copilot. However, Microsoft is a major investor in OpenAI, and because Copilot uses AI models from OpenAI, it has a lot of overlap with ChatGPT. That’s not to say they’re the same thing — Microsoft uses some proprietary models in Copilot (specifically, its Prometheus model) in addition to a custom assortment of OpenAI models, but there’s a lot of ChatGPT under Copilot’s hood. Nevertheless, Microsoft does its own tuning to balance all the different AI gremlins under that hood, so it is distinct enough as a product to merit a head-to-head comparison between the two.
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OpenAI, meanwhile, retains a massive user base on ChatGPT, which gives it a big competitive advantage since the more users there are, the more the AI is getting used and trained. Neither company actually turns a profit on AI – OpenAI head Sam Altman says the company is losing money even on $200/month subscribers – but OpenAI remains the market leader by a wide margin. ChatGPT is built into everything from Copilot to Apple’s Siri these days, and it’s widely considered the industry standard.
Copilot is all up in your business
The largest difference between ChatGPT and Copilot is that Microsoft has been cramming Windows and Office products to the gills with its AI. Microsoft was legally ruled a monopoly in the PC operating system market a quarter of a century ago, and things haven’t changed much since then. Windows is by far the most dominant OS on the planet, which means the ability to simply blast a firehose of Copilot features into all of its products is a huge advantage. From your taskbar to your Word documents, Copilot is digging roots deep into the Microsoft ecosystem.
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This strategy hasn’t translated into very many users for Copilot, though, and ChatGPT retains by far the largest user base in the AI market. With 28 million active Copilot users in late January compared to over 300 million monthly active users for ChatGPT at the end of 2024, it’s an absolute blowout for OpenAI. Things get even more bleak for Copilot when you realize how many of its users are likely to be using it only because it’s the tool built into their computer by default.
For the rest of this comparison, we’ll focus on the capabilities of each chatbot. Still, the truth is that you can do more with Copilot than you can with ChatGPT, at least if you have a Windows computer that supports it. Both AIs have desktop apps you can run, but Copilot can manipulate your Excel spreadsheets, Word documents, PowerPoint slides, Outlook inbox, and more from directly within those apps.
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Basic questions
One of the most common uses for AI is searching up the answers to basic, everyday questions that you’d usually ask Google. Both AIs are pretty good at this, but pretty good is rarely good enough. AI remains prone to hallucinations — confidently stating falsehoods as facts — which can undermine their usefulness. If you have to double check an AI’s answers on Google, you might as well just use Google in the first place.
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In any case, I started this head-to-head comparison by prompting both AIs to “Tell me some fun facts about Google Android.” The similarity of the two responses is a clear demonstration of just how much of ChatGPT’s DNA is baked into Copilot. Both told me Android was originally built to run on digital cameras (true), that Google acquired Android in 2005 for $50 million (true), that the first Android-powered phone was the HTC Dream (true – SlashGear covered it at the time), that the original Android logo was a much scarier robot, and that the one we know and love was inspired by bathroom signs (both true).
However, both AIs also made mistakes. Both told me the Android mascot is named Bugdroid. That’s not true. Google officially calls it The Bot, while Bugdroid is a fan-created nickname. Similarly, the Dream was indeed the first consumer Android phone, but the first was a Blackberry-style prototype, something which only ChatGPT pointed that out.
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It’s easy to spot such errors when you’re asking about something you know a lot about, but if I’d been asking about something outside my expertise, I’d need to double check everything. In other words, a pretty good rate of accuracy isn’t good enough when it comes to this tech. Both AIs performed decently, but there’s plenty of room for improvement.
Logical reasoning
Reasoning has been a major area of focus for all of the major players in the AI space recently. ChatGPT and Copilot have both implemented new reasoning capabilities that supposedly allow the AIs to think more deeply about questions. This language is a bit misleading — AI doesn’t “think,” it just calculates probability based on which words are most closely related in its training data. However, the bots can now show their work, so to speak.
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I decided to be a bit glib here. I’ve noticed that AI has trouble answering questions that are very close to common logic puzzles but which differ by being much simpler.
I turned reasoning on in both Copilot and ChatGPT, then asked, “A farmer needs to cross a river to bring his goat to the other side. He also has a pet rock with him. The rock will not eat the goat, but the rock is very significant to the farmer on an emotional level. How can the farmer get himself, the goat, and the rock across in the fewest number of trips?” Human readers will note that there is actually no puzzle here. Since I’ve added no real constraints, the farmer can clearly bring both across in one trip. However, neither AI clued into that fact.
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Max Miller/SlashGear
Because it resembles more complex puzzles, Copilot and ChatGPT assumed the problem must be more challenging than it is. They invented a constraint not present in my question — that the boat must not be able to hold both the goat and the rock – and told me that it would take three trips to bring both across. Earning the slight advantage, Copilot ultimately noted that if the boat were larger the farmer could cross the river in one trip.
Max Miller/SlashGear
Creative copy
One of the main selling points for large language models like ChatGPT and Copilot has been the generation of creative copy — writing. Well, I happen to have an advanced degree in putting words one after another, so I’ll be the judge of that. In last year’s Gemini versus ChatGPT showdown, I enjoyed making the bots write from the perspective of a little kid asking their mom to let them stay up late and eat cookies. I reused a very similar prompt here, but added a new wrinkle. “My mom says I can have a cookie before bed if I go right to sleep. I want to stay up and have a cookie. Write a letter persuading my mom to let me have both.”
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Here, the two chatbots took different tacks. While ChatGPT gave a bullet-pointed list of reasons why our put-upon child should be allowed to have his cookie and stay up, too, Copilot was less didactic. It kept things in all prose, adhering closer to a traditional letter writing style. However, both AIs gave more or less the same argument, claiming that they’d be more well behaved and go to bed without fuss if they got what they wanted. However, ChatGPT did a bit better here, at least in logical terms, because it offered the hypothetical mom something in exchange — the promise of spending that extra time awake as mom-kid quality time.
Max Miller/SlashGear
Max Miller/SlashGear
Copilot gets points here for more closely embodying the perspective of the child in its response, while ChatGPT gets a cookie for using slightly better logic. Ultimately, though, neither of these letters felt persuasive enough to be very convincing to any actual parent.
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The haiku test
When I compared ChatGPT to Google Gemini almost a year ago, I pointed out their limitations by asking both to write a haiku. As a result of the way LLMs work, neither AI could do so correctly. AI doesn’t actually know anything about the words it spits out, and that means they don’t know what a syllable is. Consequently, they can’t write a haiku, which follows a five-seven-five syllabic verse pattern So, has anything changed a year later?
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Maybe someone at OpenAI saw that comparison, or at least I’d like to think so. When prompted to “write a haiku about Slashgear.com,” ChatGPT did so with no problem, writing the following:
“Tech news on the rise,
gadgets, cars, and future dreams,
SlashGear lights the way.”
It’s not going to win any awards, but it qualifies as a haiku, and that’s progress. I’m no AI developer, so I have no clue what changed behind the scenes to enable haiku writing here. Either way, it’s good to see improvement.
Copilot stalled out when I gave it the same prompt. It wouldn’t write its haiku until I signed out of my Microsoft account and reloaded the page, at which point it gave me this:
“Gadget whispers loud,
Innovation on the rise,
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SlashGear guides the way.”
It’s interesting to see how both AIs repeat phrases here, such as “on the rise” and “lights/guides the way.” I’d guess that Copilot defaults to ChatGPT for this, and that’s why the poems are similar. Neither poem was particularly beautiful or evocative, but both bots passed this test, and both showed a basic understanding of what SlashGear is, which was integral to the prompt.
Problem solving
As you may have heard, AIs can often pass the bar exam. However, they can’t be lawyers, as lawyers who’ve tried to use them have found out the hard way. So, with those mixed results in mind, how do ChatGPT and Copilot do with logistically complex problem solving puzzles of the kind that routinely stump LSAT test takers?
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Rather than using actual LSAT practice questions, which are copyrighted and have probably already been scraped to train the AIs, I came up with a few of my own. The first was, “Fred is a used car salesman. One day, a family comes in looking to buy a car he hasn’t had time to inspect, but he tells them there’s nothing wrong with it. After all, none of the cars he’s sold ever had issues in the past. What is the fallacy in Fred’s logic, if any?” ChatGPT and Copilot both correctly identified that Fred has fallen victim to the hasty generalization fallacy.
The next question was, “On the way home from Fred’s dealership, the brakes fail in the car he sold, and several people are killed in a collision. Fred claims he’s not at fault, since his cars are sold as is and become the owner’s responsibility once paperwork is signed. The surviving family member claims he is at fault, since the family would not have purchased the vehicle had they known the brakes were faulty. Based only on logic, who is right?”
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The responses to this more subjective question differed, with Copilot asserting that both parties have strong claims, while ChatGPT sided with the family, pointing out that Fred’s position relies on “contractual technicalities,” while the family can prove causality.
Max Miller/SlashGear
Max Miller/SlashGear
Code writing
One of the more useful applications of AI is thought to be coding. Especially when it comes to the common but tedious chunks of code that developers routinely find themselves writing, it’s been posited that it’s much easier to offload that work to an AI, leaving the human coder with more time to write the new and complex code for the specific project they’re working on. I’m no developer, so take this particular test with a grain of salt. At the same time, though, these tools should supposedly lower the barrier to entry for coding noobs like me.
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Common wisdom dictates that writers should have their own websites, but I’ve been putting off the creation of one. With that in mind, I asked both AIs to, “Generate HTML for a personal website for a writer named Max Miller. Give the website a retro aesthetic and color scheme, with an About Me section with a headshot and text field, a Publications section where I can link out to published work, and a Contact section where I can add social media and email links.”
At this point, I found out ChatGPT now has a code editing suite called Canvas. It allowed me to play with and preview the code right in my browser. Taste is subjective, but ChatGPT also generated what I would argue is the better looking website, using nicer looking margins and a dark mode style color scheme. Both, however, fulfilled the prompt more or less to a T, each generating a very similar page layout. Have a look for yourself below.
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Max Miller/SlashGear
Max Miller/SlashGear
Real-time information
When I tested ChatGPT against Google Gemini last year, only the latter could give me up to date information on recent events such as sports scores. I asked both how my local hockey team, the Colorado Avalanche, are doing this season, and both gave me an overview that appears to be correct. Both ChatGPT and Copilot provided me with current rankings and a few highlights from the season, but ChatGPT was more detailed. It told me some player stats that Copilot didn’t bother with.
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I followed up by asking who they’re playing next. Both AIs correctly understood the “they” in my question to mean the Avalanche. I’m writing this section at 5:00 p.m. on Friday, February 28, and both AIs informed me about tonight’s game, which takes place against the Minnesota Wild at Ball Arena in Denver two hours from the time of this writing. Interestingly, Copilot attached a Ticketmaster advertisement to the end of its response. ChatGPT, meanwhile, gave me much more useful information by showing me the upcoming schedule for not only tonight’s game but several thereafter. It also appended a link to the official Avalanche website.
Things got far more stark when I asked about breaking news. As of this writing, authorities are investigating the shocking deaths of legendary actor Gene Hackman and his wife. When I asked, “What’s the latest on the investigation into Gene Hackman,” Copilot gave me the basics of the story and told me autopsy and toxicology tests are still pending. ChatGPT, on the other hand, had no idea what I was talking about.
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Image based prompting
Using multimodal AI — the ability of an AI to work with multiple forms of media — both ChatGPT and Copilot can incorporate user submitted pictures and other files into a prompt. I decided to start simple for this test. On my bed, I arranged a Samsung Galaxy S23 Ultra, a Samsung portable SSD, a Swiss army multitool, lip balm, hand cream, a eyeglass case, a beaded bracelet, Samsung Galaxy Buds, and my wallet. I then took a photo of the assortment and uploaded it to both AIs with the prompt, “Identify the objects in this photo.”
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Both AIs did okay here, but ChatGPT blew Copilot away by a country mile. Whereas Copilot misidentified the SSD as a power bank and the glasses case for deodorant, ChatGPT identified everything accurately.
Max Miller/SlashGear
Max Miller/SlashGear
It was time to up the stakes. I took a photo of a generic Prilosec pill and asked both AIs, “What kind of pill is this?” If these AIs misidentified the medication, that could have dire effects for an overly trusting user. Thankfully, both AIs declined to make a guess when faced with the blank, red pill. Sometimes, it’s better to be useless than wrong.
Lastly, I took a photo of two rows on my bookshelf, containing 78 books, and ensuring all the text in the photo was legible, then asked the AIs, “Which of these books should I read if I have an interest in dystopian fiction?” Again, ChatGPT strong armed Copilot into submission. Neither impressed me, though. Whereas Copilot suggested “Agency” by William Gibson, ignoring everything else and hallucinating a book I don’t own, ChatGPT identified “Agency,” “The Parable of the Sower” by Octavia Butler, and “Appleseed” by Matt Bell. However, it hallucinated several more titles not on the shelf.
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Max Miller/SlashGear
Max Miller/SlashGear
Mobile apps
Lastly, both Copilot and ChatGPT are available in mobile form, with apps available in the Apple App Store and Google Play Store. On the surface, both apps look pretty similar, with a text field at the bottom and buttons to enter a voice mode. Since both apps are quite similar, it makes sense to focus this comparison on where they differ — which is in exactly one way
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Copilot’s standout mobile app feature is Copilot Daily, an AI news summary. It begins with a fun fact before launching into the daily news, presumably summarizing the articles it cites as sources in the bottom of the screen for each item. Based on my knowledge of the events it summarized, it seems relatively accurate. However, it’s not as if there’s a shortage of news summary features created by actual journalists. You can find them from every major news outlet.
However, the apps are otherwise nearly carbon copies of their web interfaces. Both apps are essentially just wrappers for that interface, since it’s not as if your phone has the power to run these models locally. Unless you’re very excited to hear a robot read the news to you, the ChatGPT app is the better option simply because ChatGPT has more built in features within its interface.
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Conclusion: ChatGPT beats Copilot by a hair, but neither AI is great
If you absolutely had to choose either Microsoft Copilot or ChatGPT, the latter remains the better option for most people. While Copilot isn’t exactly like its more popular peer, it’s using enough of OpenAI’s models that you’re better off with the original flavor. Copilot is a lot like Bing — doing basically the same thing as the bigger name brand, but just a little bit worse.
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With that said, it’s a stretch to call either of these chatbots smart or useful. Frankly, with hundreds of billions of dollars now sunk into these two AIs alone by both OpenAI and Microsoft, how is it that Copilot and ChatGPT still can’t nail the basics? Microsoft plans to spend $80 billion on AI data centers this year, while OpenAI is seeking up to $7 trillion for new projects.
Yes, that’s trillion with a T to fund a technology that can’t get basic facts right or understand how boats work. When competitors like DeepSeek are doing the same things for a microscopic fraction of that investment cost, these products feel deflatingly unimpressive in comparison. Markets aren’t a consumer concern, it’s true, but some perspective feels necessary here.
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Look, if all you need is a robot that can quickly write you an email, both ChatGPT and Copilot will happily crank out slop copy that anyone can tell was written by AI. If you need a smart thesaurus, or sports scores, or a bit of simple code, they’ve got you covered. In a tight race, ChatGPT does a few things marginally better than Copilot. Still, for any task where accuracy matters, neither are reliable enough to count on.
Gemini acaba de elevar el listón con el lanzamiento de su muy esperada característica,Lienzo. Este nuevo espacio de trabajo interactivo permite a los usuarios crear, refinar y compartir sus ideas como nunca antes.
Canvas se basa en el conjunto de herramientas en evolución de Gemini, que ya incluye características potentes como Investigación de Gemini Deepuna herramienta diseñada para ayudar a los usuarios a profundizar en temas complejos con ideas con IA. Con una investigación profunda, los usuarios de Gemini pueden realizar investigaciones en profundidad, analizar grandes conjuntos de datos y generar informes completos.
Ahora, con la adición de lienzo, Gemini lleva las cosas un paso más allá al ofrecer un espacio perfecto para la colaboración en tiempo real y la exploración creativa.
Ya sea que esté redactando estrategias de divulgación de influencia, ideas de contenido de lluvia de ideas o interfaces de software de codificación, Canvas proporciona una plataforma integrada para refinar borradores y generar código.
Esta actualización fortalece las capacidades de Gemini, ofreciendo un entorno robusto para todo, desde una lluvia de ideas inicial hasta salidas finales pulidas. Con el lienzo, puede mejorar su proceso creativo en múltiples disciplinas, todo dentro de un espacio de trabajo unificado.
Desatar una nueva era de creatividad con lienzo
El lienzo de Gemini no es solo otra actualización de características, es una forma completamente nueva de trabajar.
Con el lienzo, Gemini da un paso más al convertir al asistente de IA de una herramienta en un poderoso espacio de trabajo de colaboración para escribir y codificar. Este espacio dinámico está diseñado para permitirle crear y editar a la perfección documentos o código mientras ofrece actualizaciones en vivo sobre cada cambio realizado.
https://www.youtube.com/watch?v=4leardp_agc
Desbloqueo de posibilidades interminables con lienzo: desde el aprendizaje hasta la creatividad
En la página de lienzo, Gemini explica los casos de uso de la herramienta.
Aquí hay un desglose rápido de cómo se puede usar el lienzo en diferentes campos:
- Aprendizaje interactivo: Los estudiantes pueden crear juegos de estudio, cuestionarios y simulaciones, lo que hace que los temas complejos sean más fáciles de entender.
- Visualización del código: Cree modelos de trabajo de algoritmos o visualice conceptos de codificación, ayudando a los estudiantes a comprender y aprender la programación de manera más interactiva.
- Entregables de negocios: Genere rápidamente borradores pulidos para informes comerciales, propuestas o notas de reuniones, ahorrando tiempo en la creación de contenido.
- Prototipos: Diseñar prototipos comerciales interactivos, desde sistemas de gestión hasta interfaces de usuario, con actualizaciones en tiempo real.
- Exploración creativa: Experimente con la generación de mundos 3D o juegue juegos de memoria interactiva para provocar creatividad y participar en proyectos divertidos e imaginativos.
Ya sea para estudiantes, trabajaro divertidoEl lienzo reúne todos estos elementos en una plataforma flexible, ofreciendo interminables formas de participar e innovar.
Poner el lienzo a la prueba
El lienzo no es solo para escribir o codificar, es una herramienta de IA que cambia el juego para los especialistas en marketing. Al proporcionar un espacio donde se unen el desarrollo de la estrategia de campaña, la creación de contenido y el análisis en tiempo real, el lienzo simplifica el proceso de transformación de sus ideas de marketing en campañas efectivas.
Con solo algunas indicaciones, puede generar esquemas de campaña, redactar informes y crear publicaciones en redes sociales. Más importante aún, Canvas le permite ver los resultados de inmediato visualizando cómo se verá su contenido en diferentes plataformas.
Queríamos probar el lienzo y ver lo que puede hacer para los especialistas en marketing en marketing de influencers. Decidimos solicitar la herramienta para crear Una campaña de influencers de Instagram. Entonces le pedimos a Gemini que redactara un calendario de contenido y un campo de influencia. Es seguro decir que el resultado nos impresionó mucho.
Al observar los resultados, Gemini comenzó dándonos los conceptos básicos, como el nombre de la campaña, su objetivo, público objetivo y la duración.
Lienzo seguido redactando un detallado calendario de contenido para nuestro imaginario Campaña de Instagram.
El calendario incluye varios tipos de publicaciones, como exhibiciones de funciones de productos, testimonios de clientes e incluso un evento en vivo para un lanzamiento de productos. Cada entrada está bien estructurada, con el Tipo de contenido, tema/temay Mensaje clave/llamada a la acción claramente descrito.
Además, el calendario proporciona notas relevantes para Optimización del contenidocomo usar audio de tendencia para carretes o incorporar elementos interactivos como encuestas para historias de Instagram.
A continuación, Géminis creó un completo Plantilla de lanzamiento de influencer. Esta plantilla se adapta a alentar a los influencers a colaborar en la campaña, detallando el tipo de contenido que crearían, los objetivos de la campaña y los beneficios de la colaboración.
Incluye Consejos de personalizacióncomo cómo mencionar las cualidades únicas del influencer y por qué su audiencia se alinea con la marca. La plantilla también sugiere compensación y otras ventajas, asegurando que el influencer vea el valor total de la participación.
Finalmente, Gemini sugirió un claro llamado a la acción para el tono del influencer, lo que facilita que el destinatario responda. El campo concluye con una solicitud profesional y concisa para programar una llamada, asegurando que el influencer sepa exactamente cómo proceder si están interesados en la colaboración.
El tono es educado y atractivo, enfatizando el potencial de una asociación fructífera. Este cierre simple pero efectivo asegura que el tono permanezca abierto al tiempo que fomenta una respuesta rápida.
Con el lienzo, los especialistas en marketing pueden ir más allá de la planificación tradicional y, en cambio, disfrutar de un enfoque dinámico y práctico para refinar y optimizar sus campañas.
Pero no se detiene allí. Hacer cambios también se hace perfecto gracias a su función de edición incorporada. ¿Necesita ajustar la copia, ajustar hashtags o actualizar las pautas visuales? Pregúntele a Gemini, y actualizará el contenido en tiempo real.
Por ejemplo, le pedimos a Gemini que modifique las fechas de inicio y finalización de la campaña, el público objetivo y el objetivo de la campaña. Gemini actualizó el plan de campaña en tiempo real.
Nota: Canvas admite una función de exportación que le permite exportar cualquier cosa que le pida a Google Docs.
Cómo acceder al lienzo Géminis
Comenzar con el lienzo es muy fácil. Todo lo que necesita hacer es abrir la aplicación Gemini en su web o dispositivo móvil, seleccione “Lienzo“Desde la barra rápida y comienza a crear.
Ya sea que esté en un escritorio o en la marcha, se puede acceder a lienzo a través de las versiones web y móviles de Gemini.
El lienzo es Disponible para todos los suscriptores avanzados de Géminis y Géminis en todo el mundo. Actualmente es compatible con el inglés, con más idiomas que se espera que se desplome pronto. Simplemente toque el “+ +“icono en el móvil o elija”Lienzo“En la web para comenzar a usar esta nueva herramienta poderosa.
El futuro de la creatividad, la colaboración y el código
Gemini Canvas está listo para revolucionar la forma en que abordamos la escritura, la codificación y la colaboración. Ya sea que esté refinando una propuesta comercial, construyendo un prototipo de aplicaciones web o elaborando una herramienta de aprendizaje interactiva, el lienzo le brinda la flexibilidad, la velocidad y la colaboración necesarias para convertir sus ideas en realidad.
Al combinar escritura, codificación y diversión, Géminis ha creado un espacio donde la creatividad no conoce límites. Listo para bucear? Abra Gemini hoy y experimente el futuro de la productividad y la colaboración.
Sobre el autor
Escritor
Kalin Anastasov desempeña un papel fundamental como gerente de contenido y editor en Influencer Marketing Hub. Aplica expertos su experiencia en SEO y escritura de contenido para mejorar cada pieza, asegurando que se alinee con nuestras pautas y ofrece una calidad inigualable a nuestros lectores.
Key takeaways
- To generate crypto market insights via ChatGPT, collect accurate historical and real-time data on prices, trading volumes and market capitalization.
- Organize data into clear formats, such as tables with consistent date formats and labeled columns, to help ChatGPT identify patterns and trends.
- Use precise and focused prompts to guide ChatGPT in generating actionable insights, enhancing the relevance and clarity of its responses.
- Cross-check ChatGPT’s outputs with up-to-date information from reputable sources before making trading decisions to account for potential inaccuracies.
Predicting crypto market trends can feel like navigating a storm — unpredictable and fast-changing. Prices can spike or crash unexpectedly due to investor sentiment, regulatory changes or sudden events such as exchange hacks. For traders, staying ahead means finding reliable ways to analyze these movements and make informed decisions.
This is where ChatGPT can help.
By analyzing historical data and recognizing patterns, ChatGPT offers insights that can support better decision-making. But for AI tools to deliver meaningful results, especially when using ChatGPT for crypto investments, it’s essential to follow the right process. Combining well-structured data, clear prompts and effective risk management can improve the accuracy and usefulness of its insights.
This article explores practical ways of how to use ChatGPT for crypto market analysis — from collecting and organizing data to crafting effective prompts that help the model generate actionable insights.
How to harness ChatGPT for crypto market analysis
While predicting crypto trends will always have its challenges, using data-driven insights with ChatGPT can make market behavior easier to understand. With the right strategy, ChatGPT becomes a powerful tool to identify patterns, highlight emerging trends, and support smarter trading decisions.
Using ChatGPT effectively for crypto analysis involves four key steps:
- Step 1: Gathering data for analysis
- Step 2: Formatting data for analysis via ChatGPT
- Step 3: Writing clear and effective prompts
- Step 4: Caution! Verify ChatGPT insights before drawing conclusions
Step 1: Gathering data for analysis
When it comes to predicting crypto trends, data is everything. Without reliable data, even the most advanced tools like ChatGPT can deliver unreliable insights. Crypto markets are notoriously volatile, and understanding the patterns behind price movements, whale activity and investor sentiment requires trustworthy information from the right sources.
The type of data required depends on the kind of analysis being performed. For example:
- Price analysis requires accurate records of past prices, volume and market cap trends.
- Whale activity analysis focuses on large investor movements and wallet behavior.
- Sentiment analysis relies on tracking social media discussions, influencer mentions and crowd sentiment shifts.
Did you know? A study found that higher X post engagement generally correlates negatively with cryptocurrency prices, indicating that increased social media activity may precede price declines.
Step 2: Formatting data for analysis via ChatGPT
To predict crypto trends with ChatGPT, data must be structured in a way that highlights patterns, trends and key events. Poorly formatted data can lead to incomplete or incorrect outputs, so investing time in proper organization is crucial.
Structuring data for analysis
When formatting price data, focus on key points that reflect market trends. Include the date open price, close price and volume in chronological order to capture market movement. This article uses the Bitcoin (BTC) price data below to illustrate the process.
Gaps in data are common, especially in volatile markets. Filling missing entries with estimated values, such as moving averages, can improve continuity and make analysis more accurate.
For technical indicators, like the relative strength index (RSI) or the moving average convergence divergence (MACD), aligning the data with consistent timestamps is key.
Sentiment data tends to be unstructured, which can make it challenging to analyze. To improve its clarity, combine sentiment scores with key dates and relevant events. For example:
Data cleaning and preparation
To maximize the accuracy of ChatGPT insights, take these steps:
- Ensure date formats are consistent (e.g., YYYY-MM-DD) to prevent misalignment.
- Remove duplicates to avoid skewed data patterns.
- Fill missing values by interpolating trends or forward-filling where necessary.
- Label data clearly to provide the necessary context for ChatGPT’s interpretation.
Did you know? A study found that ChatGPT’s sentiment analysis of news headlines can effectively predict daily stock returns, outperforming traditional methods.
Creating well-structured prompts is key to unlocking meaningful insights from ChatGPT, especially for ChatGPT crypto analysis. Poorly written prompts can confuse the model, resulting in incomplete or irrelevant responses. Clear prompts guide ChatGPT in focusing on the right data points and generating actionable insights.
Step 3: Writing clear and effective prompts
Effective prompts are built around three core principles: clarity, purpose and focus. The illustrations and prompts used in this article were experimented with using ChatGPT-4o.
Also, please note that ChatGPT outputs only show trimmed versions for illustration purposes. The original outputs are too long to display in full, but they provide detailed insights into each RSI dip, including exact price movements, duration and trader takeaways.
- Clarity: Use precise language that defines exactly what is needed. Avoid vague requests like:
“Is Bitcoin bullish?”
Instead, provide clear instructions with relevant details: “Analyze Bitcoin’s RSI and MACD data between December 2024 and January 2025. Identify points where both indicators aligned with bullish breakouts.”
- Purpose: Be specific about the outcome you expect. For example:
“Summarize how Bitcoin’s social sentiment changed in December 2024 and highlight its impact on price movement.”
- Focus: Include relevant conditions, such as timeframes, data sources or key indicators, to ensure the analysis is targeted and relevant. For instance:
“Identify instances where Bitcoin’s RSI dipped below 50 between December 2024 and January 2025. Describe how long each dip lasted and explain the resulting price movement.”
Prompt examples for crypto market trend analysis
Here are examples of effective prompts tailored for different types of crypto insights:
- Technical analysis prompt: “Analyze Bitcoin’s RSI dips below 30 from 2024 onward. Identify how long it typically took for the price to recover.”
- Sentiment analysis prompt: “Summarize Bitcoin sentiment trends on Reddit and Twitter throughout 2024. Identify patterns linked to price surges.”
- Strategy development prompt: “Create a trading strategy for Bitcoin using RSI, MACD, and whale accumulation data. Identify optimal entry and exit points.”
How to improve prompt quality
If ChatGPT’s response lacks detail or produces irrelevant insights, improving the prompt structure can enhance the outcome. Instead of rephrasing the same request, focus on adjusting the prompt’s depth, scope or context. Try these approaches for better results:
- Add more data references: Refer to RSI, MACD or other indicators to improve precision.
- Define the timeframe more clearly: Limiting the analysis period often provides sharper insights.
- Request comparative analysis: Asking ChatGPT to compare conditions across different timelines or trends can reveal more meaningful insights.
When tested on GPT-4o, a refined prompt produced significantly better results. The basic prompt, “Analyze Bitcoin RSI data,” returned vague and incomplete insights.
In contrast, an enhanced prompt — “Analyze Bitcoin’s RSI dips below 50 between December 2024 and January 2025. For each dip, identify the exact dates, duration, and the corresponding price movement. Explain whether the dips signaled trend reversals, corrections, or further declines. Additionally, provide insights in simple language, focusing on how traders can interpret these RSI movements for better decision-making in market entries and exits. Prepare a structured table summarizing each dip, including columns for date, RSI value, duration, price movement, and key insights for traders” — generated clear, actionable insights in contrast to previous output, as seen above.
The below table summarizes key differences in the outputs of Prompt 1 and Prompt 2:
As observed, taking the time to write clear, targeted prompts significantly improves ChatGPT’s ability to provide meaningful and actionable insights for crypto market analysis.
However, results may vary as ChatGPT may not yield the same outputs all the time due to differences in prompt wording, data interpretation and inherent variability in AI-generated responses. Also, traders should cross-check insights with real-time data and multiple sources for informed decision-making.
Step 4: Caution! Verify ChatGPT insights before drawing conclusions
Insights generated by ChatGPT can provide useful guidance, but verifying those insights is crucial before making investment decisions. Crypto markets are volatile, and relying solely on AI crypto market predictions without cross-referencing data may lead to poor outcomes.
Verifying ChatGPT insights
To confirm the accuracy and relevance of ChatGPT’s insights:
- Cross-check with trusted data sources: If ChatGPT highlights a bullish signal based on RSI trends, compare this finding with live data from platforms like TradingView, CoinGecko or Glassnode to confirm the signal’s validity.
- Review key market conditions: Market behavior often depends on broader economic events, news or geopolitical factors. If ChatGPT identifies a pattern, check if major events align with the prediction.
- Test insights on a demo account: Before applying any suggested strategy, test it in a risk-free environment using demo trading platforms to assess its effectiveness.
Applying verified insights
Once insights are verified, applying them effectively is essential:
- Set clear entry and exit points: If crypto trading with ChatGPT suggests a bullish breakout pattern, establish specific price points to minimize risk and secure profits.
- Use stop-loss orders: Protect investments by setting stop-loss points that limit potential losses if the trend reverses unexpectedly.
- Diversify approach: Even when ChatGPT identifies promising trends, combining insights from multiple data sources helps reduce reliance on a single prediction.
Did you know? A survey by Mercer Investments in 2024 revealed that 54% of investment managers have already integrated AI into their investment processes, while over 90% are either currently using or planning to adopt AI tools.
Limitations of using ChatGPT for crypto market predictions
While ChatGPT can be a valuable tool for analyzing market trends, it has several limitations:
- Lack of real-time data: ChatGPT does not have live access to market prices, trading volumes or real-time sentiment. External data sources are needed for up-to-date analysis.
- No predictive accuracy guarantee: ChatGPT analyzes historical patterns and sentiment but cannot predict future price movements with certainty. Market conditions can change rapidly due to unforeseen factors.
- Data quality dependence: The accuracy of insights depends on the quality of the input data. If outdated or biased information is provided, the analysis may be misleading.
- Limited understanding of market manipulation: ChatGPT cannot detect wash trading, pump-and-dump schemes or other forms of market manipulation that can influence crypto prices.
- No personal financial advice: ChatGPT does not provide personalized investment recommendations. Traders should combine AI-generated insights with technical analysis, fundamental research and risk management strategies.
As the saying goes, “Past performance is not indicative of future results.” AI tools like ChatGPT can support decision-making, but they should never replace critical thinking. Thus, always cross-check AI-driven insights with reliable market research before making any trading decisions.
The future of ChatGPT in predicting crypto market trends
As AI technology continues to evolve, using ChatGPT for crypto forecasting is expected to become more refined and integrated with real-time data platforms. Future developments could include:
- Enhanced data integration: While ChatGPT cannot access live market data directly, integrating it with financial data providers like Finnhub or Polygon.io via APIs may allow real-time data retrieval.
- Improved prediction models: AI models are rapidly improving their ability to identify complex patterns, potentially enhancing prediction accuracy.
- Automated trading strategies: Future updates may enable traders to automate strategies based on ChatGPT insights, with alerts for optimal entry and exit points.
While ChatGPT is already a valuable tool, its capabilities will likely expand further as AI continues to develop, providing crypto traders with even more effective analysis and strategic insights
This article does not contain investment advice or recommendations. Every investment and trading move involves risk, and readers should conduct their own research when making a decision.
Google Slides es una herramienta poderosa, pero crear una presentación completa puede llevar mucho tiempo. Recientemente, Google introdujo la integración de Gemini en diapositivas y todas las aplicaciones del espacio de trabajo. Ahora, solo necesita indicaciones de texto para crear presentaciones atractivas e imágenes de alta calidad para sus diapositivas. Tuve que verlo yo mismo, y decidí experimentar con Géminis y lo encargué con la construcción de una presentación completa.
En esta publicación, comparto mi viaje y revelo cómo Gemini manejó el desafío y si ofrece la promesa de presentaciones sin esfuerzo.
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Google Gemini: Todo lo que necesita saber sobre la IA multimodal de próxima generación de Google
Google Gemini está aquí, con un enfoque completamente nuevo para la IA multimodal
Acceso a Géminis en las diapositivas de Google: requisitos
Antes de encender las hojas de Google en la web, repasemos los requisitos. Si bien varios modelos Gemini son gratuitos de descargar y usar, pagará más para desbloquear el asistente de IA en las aplicaciones de productividad de Google.
Debe comprar el plan avanzado de Gemini a $ 20 por mes. Después de eso, la opción Géminis aparece en Docs, Hojas, Gmail, Google Drive y Slides. Google también ofrece un mes de prueba gratuita para usuarios elegibles.
Dado que Google Slides es una solución web, puede explorar la integración de Gemini en escritorios de Windows, Mac y Chromebooks.
Explorando Géminis en las diapositivas de Google
Genere diapositivas utilizando un mensaje de texto
Después de habilitar Gemini en Google Slides, es hora de verificarlo en acción. En el siguiente ejemplo, crearé una presentación sobre los beneficios de un estilo de vida saludable. Mi objetivo es cubrir los beneficios de la nutrición, el ejercicio regular, el bienestar mental y el manejo del estrés. Siga los pasos a continuación.
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Inicie las diapositivas de Google en la web e inicie sesión con los detalles de su cuenta de Google. Comience con una presentación en blanco.
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Abra Géminis desde la esquina superior derecha y escriba un aviso.
Escribir un aviso es una parte crucial de su proceso de presentación. Dado que es un tema amplio y adaptable, sea lo más descriptivo posible. En nuestro caso, escribiré un aviso a continuación para mi diapositiva de introducción.
Genere una diapositiva con el título “Los beneficios de un estilo de vida saludable”. Agregue una definición breve de un estilo de vida saludable, enfatizando el equilibrio del bienestar físico, mental y nutricional.
Esto es lo que se le ocurrió a Géminis. Puede volver a intentarlo si no está satisfecho con los resultados y haga clic en Insertar para agregarlo.
Ahora, haga clic + + Para agregar una nueva diapositiva y continuar escribiendo indicaciones para generar nuevas diapositivas para su presentación.
Cree una diapositiva titulada “Nutrición: alimentar su cuerpo”. Agregue información sobre la importancia de las frutas y verduras.
A diferencia de Copilot en PowerPoint, no puede crear múltiples diapositivas a la vez. Debes describir cada diapositiva por separado. Por lo tanto, asegúrese de planificar el esquema de su presentación.
Después de eso, creé cuatro diapositivas nuevas utilizando las indicaciones de texto a continuación.
Cree una diapositiva titulada, “Ejercicio: moverse para un usted más saludable”. Agregue información sobre la cantidad recomendada de ejercicio por semana.
Crea una diapositiva titulada, “Bienestar mental: encontrar tu paz interior”. Agregue puntos de bala en buenos hábitos de sueño.
Genere una diapositiva que enumere los beneficios de un estilo de vida saludable, que incluye un aumento de la energía, un mejor estado de ánimo y un mejor sueño.
Cree una diapositiva de conclusión con pasos prácticos para adoptar un estilo de vida más saludable. Incluir puntos de bala orientados a la acción.
Hubo algunos casos en los que no estaba satisfecho con los resultados. Entonces, le pedí a Gemini que recreara esas diapositivas. Además, no te sorprenderá con diseños de diapositivas llamativas y animaciones. Debe agregarlos manualmente y completar su presentación.
En cualquier momento, puede escribir @Nombre del archivo Y solicite a Gemini que se refiera a un documento de su cuenta de Google Drive. Por ejemplo, si escribió una dieta vegetariana en un documento, puede pedirle a Gemini que se refiera a ella para sus diapositivas de presentación.
Estás usando diapositivas generadas por AI. La precisión puede recibir un éxito cuando se trata de temas complejos como IA, fotografía computacional, aprendizaje automático y más. Compruebe dos veces antes de compartir la presentación con otros.
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Google Gemini: 5 maneras de usar el asistente a día a día de Google con IA
Puede hacer que muchas tareas cotidianas sean mucho más fáciles
Crear e insertar imágenes con Gemini
No tenía idea de que Géminis podía crear imágenes basadas en indicaciones de texto. Es un gran ahorro de tiempo, ya que no necesita buscar imágenes en la web para obtener imágenes adecuadas para su presentación. Generé un par de imágenes relevantes utilizando las indicaciones de texto a continuación.
Una imagen de una placa equilibrada con proteína magra, granos integrales y verduras.
Una fotografía de primer plano de un vaso de agua con rebanadas de limón y pepino.
Gemini le ofrece cuatro opciones de imagen para sus diapositivas. Puede verlos e insertarlos en sus diapositivas.
Géminis hizo mis diapositivas
Géminis en Google Slides abrió mis ojos al potencial de la IA en la creación de presentación. Si bien no es un reemplazo perfecto para la creatividad humana y el pensamiento estratégico, es una herramienta poderosa para racionalizar el proceso, especialmente para elaborar borradores iniciales y imágenes llamativas.
Aún así, la supervisión humana es crucial, pero si tiene plazos ajustados o desea explorar nuevas formas de crear diapositivas atractivas, pruebe a Gemini. Gemini Advanced desbloquea el asistente de IA de Google en otras aplicaciones de productividad como Google Sheets. Así es como puedes aumentar tus hojas de cálculo con Gemini.
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