Noticias

What’s The Difference & Which AI Is Smarter?

Published

2 meses ago

1 marzo, 2025

Max Miller/SlashGear

It can be hard to keep track of Google’s products, which are often here one day and virtually gone the next. When it comes to rapidly evolving fields like AI and personal assistants, things are getting even more confusing. Case in point: Google Gemini is being pushed out to consumers while Google Assistant still exists. That means the search giant currently has two bots with a whole lot of overlapping functionality, leading many to wonder what the difference is between the two.

Both Google Gemini and Google Assistant are forms of AI, but the former is the newer form of generative AI that’s been dominating headlines. However, while Assistant was specifically designed as a phone and smart home assistant, Gemini was designed as a general purpose AI more akin to ChatGPT. So, whereas Assistant is very good at specialized, device-focused tasks, general web searches, and not much more, Gemini is a jack of all trades but arguably a master of none.

I’ve been testing both side-by-side for over a year, and while Gemini wasn’t ready to replace your phone assistant just a year ago, it’s come a long way. Today, it comes as the default assistant app on new Android phones like the Samsung Galaxy S25 series. But Assistant isn’t gone yet. It can still be enabled on Android, and is also found on a wide variety of smart devices. So, let’s break down the differences between each AI to figure out which tasks are best suited to each, and which Google AI is the smartest in 2025.

How is Gemini different from Google Assistant?

Google Gemini running on tablet and Google Assistant running on phone

Max Miller/SlashGear

Google Assistant was first introduced in 2016 as a direct competitor to Apple’s Siri and Amazon’s Alexa. It can be found on most Android smartphones and tablets, newer Chromebooks, supported smart speakers and displays, and more. It is built on an older form of machine learning AI that can handle a limited range of natural language but is still rather keyword dependent (i.e. you have to be rather specific with your commands rather than speaking as you would to another human).

Gemini, by contrast, is Google’s new, flagship large language model, a generative AI that Google hopes can become the all-encompassing, friendly, personal assistant that capital-A Assistant could never be. However, the trade off for being in some ways smarter is that it’s much more unstable. Whereas Assistant required somewhat precisely worded commands to work correctly, Gemini is far more able to interpret more natural human language, which means users theoretically don’t have to spam their phone. However, it is also more prone to misinterpretations or getting things wrong.

By default, Gemini does not have many of Assistant’s most helpful capabilities, such as being able to set reminders, change device settings, or control smart homes. Google has added these features as extensions. For example, there is an Assistant extension that outsources things like reminders, and a Google Home extension to which Gemini will hand smart home requests. Unlike Assistant, Gemini is available not only as a phone assistant but also in a browser on desktop or mobile.

Google Assistant is more useful for answering common questions

Tada Images/Shutterstock

Let’s say you’re in the middle of cooking dinner and you need to know what temperature salmon should be cooked at. If you ask Google Assistant for the answer, it will search online, then give you an answer from a source Google’s algorithms determine to be trustworthy (supposed trustworthiness is based on Google’s internal heuristics to which the public is not privy). In this example, Google Assistant told me salmon should be baked at 400 degrees Fahrenheit, a fact it sourced from a site called Fine Dining Lovers. It gave the same answer on a second ask.

When I asked Gemini the same question with the same phrasing — “What temperature to cook salmon at?” — the AI spit back a long, bullet-pointed answer that told me to cook salmon at 350 degrees and gave me suggested times to cook different sizes of fillet. However, it did not tell me where it got the information. For that, I’d have needed to tap the Google logo at the bottom of the answer, which would have had the AI double check its output against internet sources. When I asked a second time, Gemini changed its answer from 350 degrees to 400 degrees, more closely matching Assistant’s answer.

This illustrates the issue Gemini still faces when responding to basic Internet queries: it builds its own knowledge graph, but seems unable to interface with Google’s actual Knowledge Graph in the same way Assistant is innately capable of. Last month, when I gave it a picture of my pantry and asked which foods would help with heartburn, it told me to eat the toilet paper stored there. While Gemini will undoubtedly continue to improve, Assistant remains the most reliable tool for getting quick, actionable answers to everyday questions.

Gemini can provide more information on uncommon questions

Nwz/Shutterstock

As noted above, generative AI like Gemini is still outclassed by Google Assistant’s ability to do a simple web search for information like cooking, weather, and so forth. On the other hand, for queries that stray off the beaten path of everyday life and can’t be answered by an encyclopedic definition, Gemini is often the far more robust tool. To illustrate this, let’s say I wanted to understand an economic concept like shoe leather cost. Assistant tells me the Wikipedia definition (“The cost of time and effort … that people expend by holding less cash to reduce the inflation tax that they pay on cash holdings when there’s high inflation”) and gives some examples, like walking to the bank to withdraw cash. That’s a decent explanation, but let’s say I need to understand it in less academic terms. I asked Gemini to explain it like I’m five, and the AI came up with the example of a monster stealing from a piggy bank, which isn’t a one-to-one comparison but makes the concept more accessible than my econ professor managed to back in the day.

Of course, as with all generative AI responses, you’ll need to double check what Gemini tells you. In this example, I’m asking about a concept I already understand, so it’s easy for me to tell that Gemini is correct in its explanation. But if I didn’t know what shoe leather cost means, I’d have no way of knowing whether Gemini explained it correctly. Thankfully, Gemini includes an option at the bottom of each response to double check with Google. If Gemini finds Internet sources that seem to correspond with its output, it will link to them, allowing you to check for yourself.

Gemini defaults to extensions for many tasks

The Utilities extension in Gemini for Android

Max Miller/SlashGear

If you use Gemini as your phone assistant on Android, it will outsource a large number of tasks through the Gemini extensions. Things like timers and device settings were until recently handled by a Google Assistant extension, but more recently that’s been replaced by a Utilities extension. Meanwhile, a Google Home extension is used for smart home tasks. In my testing, I found the current implementation to work reasonably well most of the time. However, it can easily get confused in edge cases. When I asked Gemini to tell me what summers are like in Paraguay, it told me, “I cannot set timers longer than one minute.” Not only is that a non-sequitur, it’s a bald-faced lie. It absolutely can set timers for far longer, and routinely does so when it’s not hallucinating.

Meanwhile, Google has spent years integrating those functions directly into Assistant. If you tell it to set a timer, it does so every time. Ask it to add a calendar appointment, call your mom, or turn on your phone’s flashlight, and it complies without hesitation. Gemini, by contrast, has a decently high chance of trying to tell me the history of calendars or explaining — incorrectly — the electric circuit that makes up a flashlight.

However, for more abstract tasks, Gemini becomes much more useful. I know that I type a certain number of words per-minute, so I asked Gemini to figure out how long it would take me to type three pages, then told it to set a timer for that length. It fought me initially, telling me it couldn’t “set timers for dangerous activities.” But after I reminded it writing is only occasionally dangerous, it admitted to having its “wires crossed” and did as requested.

Gemini is getting better at smart home tasks

Melnikov Dmitriy/Shutterstock

Only about a year ago, Gemini could not control smart home devices, at least in my testing. However, it has made tremendous progress in that time thanks to the dedicated Google Home extension, and now seems quite reliable, at least in my relatively dense smart home environment. Dozens of lights, smart sensors, thermostats, locks, and more all work seamlessly when I command them using Gemini on my phone or tablet.

However, Assistant remains a hair faster for these tasks. Using a stopwatch and accounting for reflex time, I measured that it took roughly 2 seconds longer for my lights to respond to commands given using Gemini, with a 1.17-second delay for Assistant and a 3.24-second delay for Gemini. My assumption is that the extra time comes from Assistant processing the command and recognizing that it needs to turn the task over to the Google Home extension. Once it invokes the extension, the lights switch on more or less instantly.

Beyond voice commands, there are slight differences in how the two bots present smart home interfaces. For queries like, “Is my front door locked,” Gemini sent me to the control page for that lock in the Google Home app, whereas Assistant told me, “The Front Door – Lock is locked,” and gave me an embedded control switch for that device. However, when controlling the lights as described above, both bots gave me embedded controls.

Gemini has limited device support compared to Assistant

Max Miller/SlashGear

One of the biggest limitations of Gemini compared to Google Assistant at time of writing is its lack of device support. Google built so much of its smart device ecosystem on the back of Assistant, and the older bot is consequently baked into everything from Google Nest speakers and displays to even third party devices. I control much of my smart home from a Google Assistant equipped JBL speaker located in my bedroom, for example, and have Nest Mini speakers dotted around the rest of my apartment. None of those devices are capable of running Gemini, and it would be shocking if they ever were.

Partially, this is because Google didn’t really plan on releasing much of the tech that became Gemini to the public until its hand was forced by the release of OpenAI’s ChatGPT. We know Google had been experimenting with generative AI for years before the current craze, but instead of dumping entire models before the public eye, it had instead been slowly trickling more useful features into its products. For example, the Magic Eraser photo editing tool which uses generative fill to remove things from photos was launched in 2021, far before ChatGPT was made public.

It’s unclear whether everyone locked into Google’s smart ecosystem will eventually have to toss out their current Assistant-equipped speakers in favor of some as yet unannounced replacement product. Given what has happened to other depreciated Google products like Stadia and Google Play Music, such a scenario would be unsurprising.

Gemini is way better for conversations

A person uses Gemini Live on a Pixel device

Rokas Tenys/Shutterstock

It’s clear that Assistant is best for certain phone and smart home related tasks simply because it was built with them in mind. However, one thing Assistant (and other smartphone assistants like Siri) has never been good at is conversation. Sure, you can prompt it to tell you a joke, a fun fact, or to play a parlor game — you can even ask follow up questions, like asking about the height of a basketball player and then asking how many points they’ve scored this season — but that’s as far as things go. Gemini, on the other hand, will happily chat away with you all day.

Of course, you can use Gemini like any other large language model chatbot, asking it follow up questions or switching topics as frequently as you like. There are limitations, of course, since Gemini will sometimes decline to talk directly about politics (strangely, it will balk even at requests to talk about past politics — it wouldn’t tell me what Barack Obama’s biggest legislative accomplishments were, for instance), and you cannot discuss other taboo topics relating to criminal activity, prurient interest, and so on.

Gemini also has a live conversation feature called Gemini Live, which is basically like being on a phone call with Google’s AI. You can have real time, free-flowing conversations. This feature works for the most part, although common AI frustrations are no less present. You’ll encounter plenty of false statements (talk to it about your field of expertise and see for yourself), and although Gemini is getting better at remembering context, it still sometimes forgets what you’re talking about mid-conversation or goes off on a bizarre, unrelated tangent.

Gemini is becoming agentic

Press release for Gemini 2 displayed on iPhone

Koshiro K/Shutterstock

The big AI buzzword of 2025 is “agentic AI,” and if you haven’t heard the term thrown around yet, prepare yourself. Simply put, an agentic AI can do things on your behalf, autonomously. Gemini 2.0 is the company’s agentic model, and it’s out now. As an example of what agentic AI enables, you can tell Gemini 2.0, “Find a recipe for chicken teriyaki and put it in a note for me.” The AI will happily create a note along those lines. However, you need to be careful here. After I got a recipe that vaguely resembled chicken teriyaki but didn’t seem quite right, Gemini confirmed it had created a Frankensteinian teriyaki recipe using multiple different food blogs. I asked again, specifying, “Do not use multiple sources. Just use a single, highly ranked recipe online and copy it verbatim into a note.” This time, it worked, though I’m now left wondering how the owner of that food blog feels about having their recipe intercepted by AI, which causes them to miss out on the ad revenue I would have provided by visiting the website myself.

In any case, there are uses for agentic AI in Gemini which don’t involve dubious uses of scraped Internet data. If you’re on some of the newest Android devices, such as the Samsung Galaxy S25 series, you can hook Gemini into your calendar, Gmail, Spotify, and more for agentic tasks. It’s as hit and miss as anything else, though. When I asked it to find the closest coffee shop to me and set a 3pm meeting with a friend there, Gemini didn’t invite the friend to the meeting, and it humorously labeled the location as “Coffee Shop” rather than finding an actual place to meet up.

The bottom line: a solid past or an unstable future

Max Miller/SlashGear

When it comes down to choosing between these two Google smart assistants, Google Assistant represents the stable past, while Gemini harkens toward a shaky future. The question is whether you’d rather have a smart assistant that’s very reliable for a small set of everyday tasks, or one that’s a jack of all trades but a master of none. Blue pill, or slightly weirder, bluer pill. At least for the time being, most users probably don’t want to be constantly surprised by Gemini’s madcap interpretations of their requests, and if you’re among them, you should probably stick with Assistant. Frankly, the error rate on Gemini is still too high for this writer, who just wants to get things done and keep on moving.

On the other hand, if you’re the sort of person who loves to embrace the bleeding edge of tech, no matter how experimental, then you’ll love playing around with the infinite possibilities enabled by Gemini. From the ability to have long conversations on a wide range of subjects to agentic capabilities that will let you accomplish multi-step tasks with a single command, Gemini is far more powerful when it actually works. If you can put up with the error rate, and if you’re willing to double check that the information it gives you is accurate, Gemini does indeed feel like the future of digital assistance AI. However, given the pace at which it’s progressed in just the past year, expect Gemini to keep on getting better. Even if you stick with Assistant for now, it’s worth checking out Gemini every so often, just to see if it’s finally ready for you.

Noticias

Géminis, mayo de 2025: Su horóscopo mensual

Published

4 horas ago

1 mayo, 2025

Sergio Villanueva

Para Gemini carismático, adaptable y curioso: esto es lo que puede esperar disfrutar, trabajar y recibir durante todo el mes de mayo.

Nuestras mentes subconscientes son más perceptivas a los cambios inminentes de lo que nuestras mentes conscientes podrían darse cuenta. Al igual que los temblores antes de un tsunami, las partes más profundas de nuestros corazones y mentes a menudo pueden sentir cuando está a punto de tener lugar un cambio significativo. Ese ciertamente parece ser el caso para usted este mes, Géminis, ya que su pronóstico comienza con un cuadrado desafiante entre la luna creciente de la depilación y su planeta gobernante, Mercurio. Iniciar un plan de acción preciso puede ser más difícil. La niebla cerebral y la falta general de motivación son igualmente probables culpables. Tome nota de lo que le ha estado molestando y mantenga esos registros en un lugar donde pueda acceder fácilmente a ellos. Incluso las molestias o ansiedades aparentemente menores pueden ser guías útiles al navegar por el cambio celestial principal de este mes.

Esa transición tiene lugar el 4 de mayo, cuando Plutón se retrógrado, un largo período celestial que afectará los pronósticos cósmicos en los próximos meses. A pesar de la inmensa distancia de este planeta enano desde nuestro punto de vista terrenal, la influencia de Plutón sobre nuestras mentes subconscientes, la transformación social, los tabúes, la muerte y el renacimiento lo convierten en un retrógrado notable. Si otros períodos retrógrados molestos como los de Mercurio son los sutiles susurros de los vientos que atraviesan las grietas en una pared, Plutón retrógrado es el tornado que derriba toda la estructura. Las transformaciones de Plutón son vastas y duraderas. Se pertenecen a aspectos de la existencia que trascienden nuestras vidas individuales mientras afectan cada parte de ellos.

Varios días después, el 7 de mayo, Mercurio forma una potente conjunción con Quirón en Aries. Quirón es un planeta enano que gobierna nuestras vulnerabilidades y heridas emocionales. Influye en la forma en que transformamos nuestro dolor en algo más útil y positivo, ya sea que sea sabiduría que podamos usar o el conocimiento que podemos compartir con los demás. La destreza comunicativa de Mercurio y el intelecto agudo se prestan a una mejor comprensión y, a su vez, el procesamiento de duelos pasados. Nunca es demasiado tarde para aprender de un viejo error, Géminis. Hacerlo puede ser la diferencia entre que esa herida emocional sea una costra dolorida y una cicatriz sutil. No puedes cambiar lo que ya ha pasado. Pero puedes cambiar a donde vayas a continuación.

Su planeta gobernante pasa a Tauro gobernado por la Tierra el mismo día que forma una oposición directa a la luna gibrosa. El mercurio en Tauro promueve la firmeza, la confianza y la estabilidad. También puede conducir a la terquedad, la ingenuidad y la alienación. Tenga cuidado de cómo ejerce esta energía cósmica, Stargazer. El enfrentamiento celestial de Mercurio con la luna gibosa de depilación crea conflicto entre la persona en la que se encuentra en este mismo momento y la persona que tiene el potencial de ser. La luna gibosa de depilación lo llama para evaluar su progreso hasta ahora. Si tuviera que mantener este mismo camino, ¿dónde estaría bajo el brillo de la luna llena en unos días? Si no estás contento con la respuesta, ahora es el momento de redirigir.

Tendrá la oportunidad de calificar sus respuestas, por así decirlo, cuando la luna llena alcanza su máxima fuerza en Scorpio el 12 de mayo. Una luna llena en Scorpio puede sonar intimidante (lo siento, Scorpios, pero su reputación le precede). Sin embargo, no seas tan rápido para asumir lo peor. Scorpio es un dominio celestial que bloquea el enfoque en la dinámica de poder, la mente subconsciente y los temas tabú u opaco como la sexualidad, la identidad, el propósito de la vida, la fe y lo que significa ser exitoso y contenido. Bajo el resplandor revelador de la luna llena, el Cosmos lo dirigirá hacia el tema que más ha estado sopesando mucho en su mente. El flujo de energía estará abierto durante este tiempo, Géminis. Capitalizar la oportunidad de perfeccionar su fuerza.

Un cambio tangible hacia el descanso y la recalibración comienza el 16 de mayo. En este día, la luna gibrosa disminuyendo forma un trígono armonioso con mercurio. La disminución de la luna gibosa nos empuja a liberar viejos comportamientos, ideas o incluso relaciones que ya no nos sirven como antes. Dos días después, Mercurio y Marte forman una plaza desafiante. Esta alineación envía un mensaje claro: ahora no es el momento de actuar. Habrá muchas posibilidades de afirmarse en el futuro. En este momento, las estrellas te instan a que atiendan tus propias necesidades y deseos.

El sol ingresa a su dominio celestial, iniciando la temporada de Géminis, el 20 de mayo. Además de fortalecer su sentido general de sí mismo y propósito, la ubicación del sol promueve el pensamiento flexible y una identidad maleable. Para ser claros, esto no es lo mismo que perderse por completo, Stargazer. Es simplemente una oportunidad para explorar otras partes de ti mismo que podría haber pensado que no existía. Llevas multitudes. Incluso en los últimos días de su vida, aún habrá profundidades inexploradas. Eso es lo que hace que esta información sea tan satisfactoria y la vida tan gratificante. Descubrir nuevas facetas de su identidad no es un castigo, a pesar de la mayor carga de trabajo emocional y mental. La oportunidad de mirar a tu sí mismo siempre es una bendición.

Las estrellas continúan priorizando el cambio y la innovación a medida que Mercurio y Urano se unen bajo Tauro. Urano podría tener una mala reputación por ser caótico y rebelde. Pero con Mercurio en la mezcla, esta alineación parece ser más audaz e innovadora que destructiva. Explore las posibilidades ante usted y absorbe lo que pueda. La luna nueva en su dominio celestial el 27 de mayo (que también se reúne con su planeta gobernante) ofrece el momento perfecto para reflexionar sobre el Intel que reunió. ¿Cómo se comparan las viejas y nuevas versiones de ti mismo? ¿Contraste? Equilibrio entre los dos mentiras en las respuestas a cualquier pregunta.

May será un momento especialmente tumultuoso en el cosmos, pero al menos terminaste en una buena base. El 27 de mayo también marca el comienzo de un trígono entre Plutón y Mercurio, que es seguido de cerca por la conjunción del Sol con su planeta gobernante el 30 de mayo. Se está produciendo un cambio importante, y todos los signos cósmicos apuntan a que sea para mejor. Abraza las mariposas en tu estómago, Géminis. Grandes cosas están en camino.

Así concluye sus aspectos más destacados mensuales. Para análisis celestiales más específicos, asegúrese de leer su horóscopo diario y semanal también. ¡Buena suerte, Géminis! Nos vemos el próximo mes.

Noticias

How Would I Learn to Code with ChatGPT if I Had to Start Again

Published

4 horas ago

1 mayo, 2025

Sergio Villanueva

Coding has been a part of my life since I was 10. From modifying HTML & CSS for my Friendster profile during the simple internet days to exploring SQL injections for the thrill, building a three-legged robot for fun, and lately diving into Python coding, my coding journey has been diverse and fun!

Here’s what I’ve learned from various programming approaches.

The way I learn coding is always similar; As people say, mostly it’s just copy-pasting.

When it comes to building something in the coding world, here’s a breakdown of my method:

Choose the Right Framework or Library
Learn from Past Projects
Break It Down into Steps
Slice your project into actionable item steps, making development less overwhelming.
Google Each Chunk
For every step, consult Google/Bing/DuckDuckGo/any search engine you prefer for insights, guidance, and potential solutions.
Start Coding
Try to implement each step systematically.

However, even the most well-thought-out code can encounter bugs. Here’s my strategy for troubleshooting:

1. Check Framework Documentation: ALWAYS read the docs!

2. Google and Stack Overflow Search: search on Google and Stack Overflow. Example keyword would be:

site:stackoverflow.com [coding language] [library] error [error message]

site:stackoverflow.com python error ImportError: pandas module not found

– Stack Overflow Solutions: If the issue is already on Stack Overflow, I look for the most upvoted comments and solutions, often finding a quick and reliable answer.
– Trust My Intuition: When Stack Overflow doesn’t have the answer, I trust my intuition to search for trustworthy sources on Google; GeeksForGeeks, Kaggle, W3School, and Towards Data Science for DS stuff

3. Copy-Paste the Code Solution

4. Verify and Test: The final step includes checking the modified code thoroughly and testing it to ensure it runs as intended.

And Voila you just solve the bug!

Photo by Stephen Hocking on Unsplash

Isn’t it beautiful?

But in reality, are we still doing this?!

Lately, I’ve noticed a shift in how new coders are tackling coding. I’ve been teaching how to code professionally for about three years now, bouncing around in coding boot camps and guest lecturing at universities and corporate training. The way coders are getting into code learning has changed a bit.

I usually tell the fresh faces to stick with the old-school method of browsing and googling for answers, but people are still using ChatGPT eventually. And their alibi is

“Having ChatGPT (for coding) is like having an extra study buddy -who chats with you like a regular person”.

It comes in handy, especially when you’re still trying to wrap your head around things from search results and documentation — to develop what is so-called programmer intuition.

Now, don’t get me wrong, I’m all for the basics. Browsing, reading docs, and throwing questions into the community pot — those are solid moves, in my book. Relying solely on ChatGPT might be a bit much. Sure, it can whip up a speedy summary of answers, but the traditional browsing methods give you the freedom to pick and choose, to experiment a bit, which is pretty crucial in the coding world.

But, I’ve gotta give credit where it’s due — ChatGPT is lightning-fast at giving out answers, especially when you’re still trying to figure out the right from the wrong in search results and docs.

I realize this shift of using ChatGPT as a study buddy is not only happening in the coding scene, Chatgpt has revolutionized the way people learn, I even use ChatGPT to fix my grammar for this post, sorry Grammarly.

Saying no to ChatGPT is like saying no to search engines in the early 2000 era. While ChatGPT may come with biases and hallucinations, similar to search engines having unreliable information or hoaxes. When ChatGPT is used appropriately, it can expedite the learning process.

Now, let’s imagine a real-life scenario where ChatGPT could help you by being your coding buddy to help with debugging.

Scenario: Debugging a Python Script

Imagine you’re working on a Python script for a project, and you encounter an unexpected error that you can’t solve.

Here is how I used to be taught to do it — the era before ChatGPT.

Browsing Approach:

Check the Documentation:

Start by checking the Python documentation for the module or function causing the error.

For example:
– visit https://scikit-learn.org/stable/modules/ for Scikit Learn Doc

2. Search on Google & Stack Overflow:

If the documentation doesn’t provide a solution, you turn to Google and Stack Overflow. Scan through various forum threads and discussions to find a similar issue and its resolution.

3. Trust Your Intuition:

If the issue is unique or not well-documented, trust your intuition! You might explore articles and sources on Google that you’ve found trustworthy in the past, and try to adapt similar solutions to your problem.

You can see that on the search result above, the results are from W3school – (trusted coding tutorial site, great for cheatsheet) and the other 2 results are official Pandas documentation. You can see that search engines do suggest users look at the official documentation.

And this is how you can use ChatGPT to help you debug an issue.

New Approach with ChatGPT:

Engage ChatGPT in Conversations:

Instead of only navigating through documentation and forums, you can engage ChatGPT in a conversation. Provide a concise description of the error and ask. For example,

“I’m encountering an issue in my [programming language] script where [describe the error]. Can you help me understand what might be causing this and suggest a possible solution?”

2. Clarify Concepts with ChatGPT:

If the error is related to a concept you are struggling to grasp, you can ask ChatGPT to explain that concept. For example,

“Explain how [specific concept] works in [programming language]? I think it might be related to the error I’m facing. The error is: [the error]”

3. Seek Recommendations for Troubleshooting:

You ask ChatGPT for general tips on troubleshooting Python scripts. For instance,

“What are some common strategies for dealing with [issue]? Any recommendations on tools or techniques?”

Potential Advantages:

Personalized Guidance: ChatGPT can provide personalized guidance based on the specific details you provide about the error and your understanding of the problem.
Concept Clarification: You can seek explanations and clarifications on concepts directly from ChatGPT leveraging their LLM capability.
Efficient Troubleshooting: ChatGPT might offer concise and relevant tips for troubleshooting, potentially streamlining the debugging process.

Possible Limitations:

Now let’s talk about the cons of relying on ChatGPT 100%. I saw these issues a lot in my student’s journey on using ChatGPT. Post ChatGPT era, my students just copied and pasted the 1-line error message from their Command Line Interface despite the error being 100 lines and linked to some modules and dependencies. Asking ChatGPT to explain the workaround by providing a 1 line error code might work sometimes, or worse — it might add 1–2 hour manhour of debugging.

ChatGPT comes with a limitation of not being able to see the context of your code. For sure, you can always give a context of your code. On a more complex code, you might not be able to give every line of code to ChatGPT. The fact that Chat GPT only sees the small portion of your code, ChatGPT will either assume the rest of the code based on its knowledge base or hallucinate.

These are the possible limitations of using ChatGPT:

Lack of Real-Time Dynamic Interaction: While ChatGPT provides valuable insights, it lacks the real-time interaction and dynamic back-and-forth that forums or discussion threads might offer. On StackOverflow, you might have 10 different people who would suggest 3 different solutions which you can compare either by DIY ( do it yourself, try it out) or see the number of upvotes.
Dependence on Past Knowledge: The quality of ChatGPT’s response depends on the information it has been trained on, and it may not be aware of the latest framework updates or specific details of your project.
Might add extra Debugging Time: ChatGPT does not have a context of your full code, so it might lead you to more debugging time.
Limited Understanding of Concept: The traditional browsing methods give you the freedom to pick and choose, to experiment a bit, which is pretty crucial in the coding world. If you know how to handpick the right source, you probably learn more from browsing on your own than relying on the ChatGPT general model.
Unless you ask a language model that is trained and specialized in coding and tech concepts, research papers on coding materials, or famous deep learning lectures from Andrew Ng, Yann Le Cunn’s tweet on X (formerly Twitter), pretty much ChatGPT would just give a general answer.

This scenario showcases how ChatGPT can be a valuable tool in your coding toolkit, especially for obtaining personalized guidance and clarifying concepts. Remember to balance ChatGPT’s assistance with the methods of browsing and ask the community, keeping in mind its strengths and limitations.

Final Thoughts

Things I would recommend for a coder

If you really want to leverage the autocompletion model; instead of solely using ChatGPT, try using VScode extensions for auto code-completion tasks such as CodeGPT — GPT4 extension on VScode, GitHub Copilot, or Google Colab Autocomplete AI tools in Google Colab.

As you can see in the screenshot above, Google Colab automatically gives the user suggestions on what code comes next.

Another alternative is Github Copilot. With GitHub Copilot, you can get an AI-based suggestion in real-time. GitHub Copilot suggests code completions as developers type and turn prompts into coding suggestions based on the project’s context and style conventions. As per this release from Github, Copilot Chat is now powered by OpenAI GPT-4 (a similiar model that ChatGPT is using).

Github Copilot Example — image by Github

I have been actively using CodeGPT as a VSCode Extension before I knew that Github Copilot is accessible for free if you are in education program. CodeGPT Co has 1M download to this date on the VSCode Extension Marketplace. CodeGPT allows seamless integration with the ChatGPT API, Google PaLM 2, and Meta Llama.
You can get code suggestions through comments, here is how:

Write a comment asking for a specific code
Press cmd + shift + i
Use the code

You can also initiate a chat via the extension in the menu and jump into coding conversations

As I reflect on my coding journey, the invaluable lesson learned is that there’s no one-size-fits-all approach to learning. It’s essential to embrace a diverse array of learning methods, seamlessly blending traditional practices like browsing and community interaction with the innovative capabilities of tools like ChatGPT and auto code-completion tools.

What to Do:

Utilize Tailored Learning Resources: Make the most of ChatGPT’s recommendations for learning materials.
Collaborate for Problem-Solving: Utilize ChatGPT as a collaborative partner as if you are coding with your friends.

What Not to Do:

Over-Dependence on ChatGPT: Avoid relying solely on ChatGPT and ensure a balanced approach to foster independent problem-solving skills.
Neglect Real-Time Interaction with Coding Community: While ChatGPT offers valuable insights, don’t neglect the benefits of real-time interaction and feedback from coding communities. That also helps build a reputation in the community
Disregard Practical Coding Practice: Balance ChatGPT guidance with hands-on coding practice to reinforce theoretical knowledge with practical application.

Let me know in the comments how you use ChatGPT to help you code!
Happy coding!
Ellen

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About the Author

I’m Ellen, a Machine Learning engineer with 6 years of experience, currently working at a fintech startup in San Francisco. My background spans data science roles in oil & gas consulting, as well as leading AI and data training programs across APAC, the Middle East, and Europe.

I’m currently completing my Master’s in Data Science (graduating May 2025) and actively looking for my next opportunity as a machine learning engineer. If you’re open to referring or connecting, I’d truly appreciate it!

I love creating real-world impact through AI and I’m always open to project-based collaborations as well.

Noticias

Lo que dice el acuerdo de OpenAI del Washington Post sobre las licencias de IA

Published

6 horas ago

1 mayo, 2025

Sergio Villanueva

Los primeros 100 días de Trump luchando contra la prensa, el cambio de los medios de comunicación a los videos de podcasts y más.

La evolución de la licencia de contenido de IA ofertas

El Washington Post se ha convertido en el último editor importante en llegar a un acuerdo de licencia con Openai, uniéndose a una cohorte creciente que ahora abarca más de 20 organizaciones de noticias.

Es parte de un patrón familiar: cada pocos meses, Openai bloquea otro editor para reforzar su tubería de contenido. Pero los términos de estos acuerdos parecen estar evolucionando en silencio, alejándose sutilmente del lenguaje explícito en torno a los datos de capacitación que definieron acuerdos anteriores y planteando nuevas preguntas sobre lo que ahora significan estas asociaciones.

El acuerdo del Washington Post se centra en surgir su contenido en respuesta a consultas relacionadas con las noticias. “Como parte de esta asociación, ChatGPT mostrará resúmenes, citas y enlaces a informes originales de la publicación en respuesta a preguntas relevantes”, se lee el anuncio el 22 de abril sobre el acuerdo de la publicación con OpenAI. En contraste, el pasado se ocupa de editores como Axel Springer y Time, firmado en diciembre de 2023 y junio de 2024 respectivamente, explícitamente incluyó disposiciones para la capacitación de LLM de OpenAI en su contenido.

El acuerdo de OpenAI de The Guardian, anunciado en febrero de 2025, tiene una redacción similar al anuncio del Washington Post y no se menciona los datos de capacitación. Un portavoz de Guardian se negó a comentar sobre los términos de acuerdo con OpenAI. El Washington Post no respondió a las solicitudes de comentarios.

Estos cambios algo sutiles en el lenguaje de los términos podrían indicar un cambio más amplio en el paisaje de IA, según conversaciones con cuatro Expertos legales de medios. Podría indicar un cambio en cómo los acuerdos de licencia de contenido de IA están estructurados en el futuro, con más editores que potencialmente buscan acuerdos que prioricen la atribución y la prominencia en los motores de búsqueda de IA sobre los derechos para la capacitación modelo.

Otro factor a tener en cuenta: estas compañías de IA ya han capacitado a sus LLM en grandes cantidades de contenido disponible en la web, según Aaron Rubin, socio del grupo estratégico de transacciones y licencias en la firma de abogados Gunderson Dettmer. Y debido a que las compañías de IA enfrentan litigios de compañías de medios que afirman que esto era una infracción de derechos de autor, como el caso del New York Times contra OpenAI, si las compañías de IA continuaran pagando a los datos de licencia con fines de capacitación, podría verse como “una admisión implícita” que debería haber pagado para licenciar esos datos y no haberlo escrito de forma gratuita, dijo Rubin.

“[AI companies] Ya tienen un billón de palabras que han robado. No necesitan las palabras adicionales tan mal para la capacitación, pero quieren tener el contenido actualizado para respuestas [in their AI search engines]”, Dijo Bill Gross, fundador de la empresa de inicio de IA Prorata.ai, que está construyendo soluciones tecnológicas para compensar a los editores por el contenido utilizado por las compañías generativas de IA.

Tanto las compañías de IA como los editores pueden beneficiarse de esta posible evolución, según Rubin. Las compañías de IA obtienen acceso a noticias confiables y actualizadas de fuentes confiables para responder preguntas sobre los eventos actuales en sus productos, y los editores “pueden llenar un vacío que tenían miedo que faltaran con la forma en que estas herramientas de IA han evolucionado. Estaban perdiendo clics y globos oculares y enlaces a sus páginas”, dijo. Tener una mejor atribución en lugares como la búsqueda de chatgpt tiene el potencial de impulsar más tráfico a los sitios de los editores. Al menos, esa es la esperanza.

“Tiene el potencial de generar más dinero para los editores”, dijo Rubin. “Los editores están apostando a que así es como las personas van a interactuar con los medios de comunicación en el futuro”.

Desde el otoño pasado, Operai ha desafiado a los gigantes de búsqueda como Google con su motor de búsqueda de IA, búsqueda de chatgpt, y ese esfuerzo depende del acceso al contenido de noticias. Cuando se le preguntó si la estructura de los acuerdos de Operai con los editores había cambiado, un portavoz de OpenAI señaló el lanzamiento de la compañía de la compañía de ChatGPT en octubre de 2024, así como mejoras anunciadas esta semana.

“Tenemos un feed directo al contenido de nuestro socio editor para mostrar resúmenes, citas y enlaces atribuidos a informes originales en respuesta a preguntas relevantes”, dijo el portavoz. “Ese es un componente de las ofertas. La capacitación posterior ayuda a aumentar la precisión de las respuestas relacionadas con el contenido de un editor”. El portavoz no respondió a otras solicitudes de comentarios.

No está claro cuántos editores como The Washington Post no se pueden hacer de OpenAI, especialmente porque puede surgir un modelo diferente centrado en la búsqueda de ChatGPT. Pero la perspectiva para los acuerdos de licencia entre editores y compañías de IA parece estar empeorando. El valor de estos acuerdos está “en picado”, al menos según el CEO de Atlantic, Nicholas Thompson, quien habló en el evento Reuters Next en diciembre pasado.

“Todavía hay un mercado para la licencia de contenido para la capacitación y eso sigue siendo importante, pero continuaremos viendo un enfoque en entrar en acuerdos que resultan en impulsar el tráfico a los sitios”, dijo John Monterubio, socio del grupo avanzado de medios y tecnología en la firma de abogados Loeb & Loeb. “Será la nueva forma de marketing de SEO y compra de anuncios, para parecer más altos en los resultados al comunicarse con estos [generative AI] herramientas.”

Lo que hemos escuchado

“No tenemos que preocuparnos por una narración algo falsa de: las cookies deben ir … entonces puedes poner todo este ancho de banda y potencia para mejorar el mercado actual, sin preocuparte por un posible problema futuro que estuviera en el control de Google todo el tiempo”.

– Anónimo Publishing Ejecute la decisión de Google la semana pasada de continuar usando cookies de terceros en Chrome.

Números para saber

$ 50 millones: la cantidad que Los Angeles Times perdió en 2024.

50%: El porcentaje de adultos estadounidenses que dijeron que la IA tendrá un impacto muy o algo negativo en las noticias que las personas obtienen en los EE. UU. Durante los próximos 20 años, según un estudio del Centro de Investigación Pew.

$ 100 millones: la cantidad Spotify ha pagado a los editores y creadores de podcasts desde enero.

0.3%: La disminución esperada en el uso de los medios (canales digitales y tradicionales) en 2025, la primera caída desde 2009, según PQ Media Research.

Lo que hemos cubierto

Las demandas de AI destacan las luchas de los editores para impedir que los bots raspen contenido

La reciente demanda de Ziff Davis contra Operai destaca la realidad de que los editores aún no tienen una forma confiable de evitar que las compañías de IA raspen su contenido de forma gratuita.
Si bien han surgido herramientas como Robots.txt archivos, paredes de pago y etiquetas de bloqueo AI-AI, muchos editores admiten que es muy difícil hacer cumplir el control en cada bot, especialmente porque algunos ignoran los protocolos estándar o enmascaran sus identidades.

Leer más aquí.

¿Quién compraría Chrome?

El ensayo antimonopolio de búsqueda de Google podría obligar a Google a separarse del navegador Chrome.
Si lo hizo, OpenAi, Perplexity, Yahoo y Duckduckgo podrían ser algunos de los compradores potenciales.

Lea más sobre el impacto potencial de una venta masiva de Chrome aquí.

Tiktok está cortejando a los creadores y agencias para participar en sus herramientas en vivo

Tiktok está tratando de demostrar el potencial de ingresos de sus herramientas en vivo.
La plataforma de redes sociales dice que sus creadores ahora generan colectivamente $ 10 millones en ingresos diariamente a través de la transmisión en vivo.

Lea más sobre el tono de Tiktok aquí.

¿WTF son bots grises?

Los rastreadores y raspadores de IA generativos están siendo llamados “bots grises” por algunos para ilustrar la línea borrosa entre el tráfico real y falso.
Estos bots pueden afectar el análisis y robar contenido, y las impresiones publicitarias impulsadas por la IA pueden dañar las tasas de clics y las tasas de conversión.

Lea más sobre por qué los bots grises son un riesgo para los editores aquí.

¿Facebook se está convirtiendo en un nuevo flujo de ingresos nuevamente para los editores?

Los editores han sido testigos de un reciente pico de referencia de Facebook, y es, algo sorprendentemente, coincidiendo con una afluencia de ingresos del programa de monetización de contenido de Meta.
De los 10 editores con los que Digay habló para este artículo, varios están en camino de hacer entre seis y siete cifras este año del último programa de monetización de contenido de Meta.

Lea más sobre lo que reciben los editores de Facebook aquí.

Lo que estamos leyendo

Las ambiciones de video de los podcasts de los medios de comunicación destacan el movimiento del formato de audio a la televisión

Los medios de comunicación como el New York Times y el Atlantic están poniendo más recursos en la producción de videos de los populares programas de podcast para aprovechar el público más joven de YouTube, informó Vanity Fair.

La perplejidad quiere recopilar datos sobre los usuarios para vender anuncios personalizados

El CEO de Perplexity, Aravind Srinivas, dijo que la perplejidad está construyendo su propio navegador para recopilar datos de usuarios y vender anuncios personalizados, informó TechCrunch.

El presidente Trump apunta a la prensa en los primeros 100 días

El presidente Trump apunta a las compañías de medios tradicionales en sus primeros 100 días, utilizando tácticas como prohibir los puntos de venta de que cubren los eventos de la Casa Blanca hasta el lanzamiento de investigaciones en las principales redes, informó Axios.

SemAFOR probará suscripciones

SemaFor “probará” suscripciones en “Due Time”, el fundador Justin Smith dijo al Inteligencer de la revista New York en una inmersión profunda en la empresa de inicio de noticias centrada en el boletín.