Is Bigger Better? Why The ChatGPT Vs GPT-3 Vs. GPT-4 ‘Battle’ Is Just A Family Chat

GPT-4, the next-generation large language model, a step up from the one that took the world by storm in the form of ChatGPT, is out. Powered by the latest Llama 4 model, the app is designed to “get to know you” using the conversations you have and information from your public Meta profiles. It’s designed to work primarily with voice, and Meta says it has improved responses to feel more personal and conversational. There’s experimental voice tech included too, which you can toggle on and off to test — the difference is that apparently, full-duplex speech technology generates audio directly, rather than reading written responses. If you are disappointed about not having a text-to-video generator, don’t worry, it’s not a completely new concept.

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The gains shown by GPT-4.5 are the result of advancements OpenAI made in unsupervised learning. With unsupervised learning, a machine learning algorithm is given an unlabeled data set and left to its own devices to find patterns and insights. GPT-4.5 doesn’t “think” like the company’s state-of-the-art reasoning models, but in training the new model OpenAI made architectural enhancements and gave it access to more data and compute power. “The result is a model that has broader knowledge and a deeper understanding of the world, leading to reduced hallucinations,” the company says. OpenAI released a paper last week detailing various internal tests and findings about its o3 and o4-mini models. The main differences between these newer models and the first versions of ChatGPT we saw in 2023 are their advanced reasoning and multimodal capabilities.

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Well, the multi-modality is one of the unavoidable progressions that we will see in the soon-coming GPT-4, as it has been mentioned by the OpenAI CEO Sam Altman in his speech. At the same time, Altman has broken the rumor of the model having 100 Trillion parameters. Although the new GPT-4.1 models will not be available within the ChatGPT model picker, the latest version of GPT-4o in the chatbot includes many of the same improvements, as seen in the changelog description for the March 27 update. Last week, OpenAI CEO Sam Altman teased that he was dropping a new feature. Paired with reports and spottings of new model art, many speculated it was the long-awaited release of the GPT-4.1 model.

It can write beautifully, is very creative, and is occasionally oddly lazy on complex projects.Feels like Claude 3.7 while Claude 3.7 feels like GPT-4.5. Industry observers, many of whom had early access to the new model, have found GPT-4.5 to be an interesting move from OpenAI, tempering their expectations of what the model should be able to achieve. Given the huge costs of GPT-4.5, though, it is very hard to justify many of the use cases. One of the constant trends we have seen in recent years is the plummeting costs of inference, and if this trend applies to GPT-4.5, it is worth experimenting with it and finding ways to put its power to use in enterprise applications.

• However, information regression appears to be a completely new problem never seen before with the service.
• Based on their model of how language works, they guess what the masked token is, and according to whether the guess was right or wrong, they adjust and update the model.
• To ask the same question to GPT-3.5 through the ChatGPT free research preview as I did, gets you not only the correct answer but also a detailed explanation of the mathematical process.

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It felt like the water that rises all boats, where everything gets slightly improved by 20%. So it is with that expectation that I went into testing GPT4.5, which I had access to for a few days, and which saw 10X more pretraining compute than GPT4. Everything is a little bit better and it’s awesome, but also not exactly in ways that are trivial to point to. Still, it is incredible interesting and exciting as another qualitative measurement of a certain slope of capability that comes “for free” from just pretraining a bigger model. Critically, this masking process does not require the training data to be labelled. This is unlike the deep learning systems trained on massive datasets like ImageNet, where each image has been labelled by humans.

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GPT-4 is a multimodal language model AI, which means it can understand text and other media, like images. This might sound familiar if you’re had a go with Stable Diffusion AI art generation, but it’s more capable than that, as it can respond to images and queries. This has led to some exciting uses, like GPT-4 creating a website based on a quick sketch..

GPT-4 can generate text (including code) and accept image and text inputs — an improvement over GPT-3.5, its predecessor, which only accepted text — and performs at “human level” on various professional and academic benchmarks. Like previous GPT models from OpenAI, GPT-4 was trained using publicly available data, including from public web pages, as well as data that OpenAI licensed. The model is a significant advance on any previous natural language processing system. On the day that a London Futurists Podcast episode dedicated wholly to OpenAI’s GPT-4 system dropped, the Future of Life Institute published an open letter about the underlying technology.

Speaking of reduced hallucinations, OpenAI measured how much better GPT-4.5 in that regard. Obviously, the new model doesn’t solve the problem of AI hallucinations altogether, but it is a step in the right direction. In one example shared by OpenAI, a person tells ChatGPT they’re going through a hard time after failing a test. Where the company’s previous models, including GPT-4o and o3-mini, might commiserate with the individual before offering a long list of unsolicited advice, GPT-4.5 takes a different tact. “Want to talk about what happened, or do you just need a distraction? I’m here either way,” the chatbot says when powered by GPT-4.5. GPT-4 Turbo is the latest language model to be released by ChatGPT owner OpenAI.

Artificial Intelligence

That trend ends today — the company has launched the Meta AI app and it appears to do everything ChatGPT does and more. Another test used by researchers was a chain-of-thought technique, in which they asked GPT-4 Is 17,077 a prime number? Not only did GPT-4 incorrectly answer no, it gave no explanation as to how it came to this conclusion, according to researchers. Many people have reported noticing a significant degradation in the quality of the model responses, but so far, it was all anecdotal. OpenAI’s GPT-4 announcement followed an address from Andreas Braun, CTO of Microsoft Germany, last week, in which he said GPT-4 would be coming soon and would allow for the possibility of text-to-video generation. We haven’t heard much about GPT-5 in recent days, but given the speed at which OpenAI has been releasing new models this year, no release date would surprise us.