Maria Diaz/ZDNET
Even though OpenAI’s most recently launched model, GPT-4o, significantly raised the ante on large language models (LLMs), the company is already working on its next flagship model, GPT-5.
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Leading up to the spring event that featured GPT-4o’s announcement, many people hoped the company would launch the highly anticipated GPT-5. To curtail the speculation, CEO Sam Altman even posted on X, “not gpt-5, not a search engine.”
not gpt-5, not a search engine, but we’ve been hard at work on some new stuff we think people will love! feels like magic to me.
monday 10am PT. https://t.co/nqftf6lRL1
— Sam Altman (@sama) May 10, 2024
Now, just two weeks later, in a blog post unveiling a new Safety and Security Committee formed by the OpenAI board to recommend safety and security decisions, the company confirmed that it is training its next flagship model, most likely referring to GPT-4 successor’s, GPT-5.
“OpenAI has recently begun training its next frontier model and we anticipate the resulting systems to bring us to the next level of capabilities on our path to AGI [artificial general intelligence],” said the company in a blog post.
Although it may be months if not longer before GPT-5 is available for customers — LLMs can take a long time to be trained — here are some expectations of what OpenAI’s next-gen model will be able to do, ranked from least exciting to most exciting.
Better accuracy
Following past trends, we can expect GPT-5 to become more accurate in its responses — because it will be trained on more data. Generative AI models like ChatGPT work by using their arsenal of training data to fuel the answers they provide. Therefore, the more data a model is trained on, the better the model’s ability to generate coherent content, leading to better performance.
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With each model released thus far, the training data has increased. For example, reports said GPT-3.5 was trained on 175 billion parameters while GPT-4 was trained on one trillion. We will likely see an even bigger jump with the release of GPT-5.
Increased multimodality
When predicting GPT-5’s capabilities, we can look at the differences between every major flagship model since GPT-3.5, including GPT-4 and GPT-4o. With each jump, the model became more intelligent and boasted many upgrades, including price, speed, context lengths, and modality.
GPT-3.5 can only input and output text. With GPT-4 Turbo, users can input text and image inputs to get text outputs. With GPT-4o, users can input a combination of text, audio, image, and video and receive any combination of text, audio, and image outputs.
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Following this trend, the next step for GPT-5 would be the ability to output video. In February, OpenAI unveiled its text-to-video model Sora, which may be incorporated into GPT-5 to output video.
Ability to act autonomously (AGI)
There is no denying chatbots are impressive AI tools capable of helping people with many tasks, including generating code, Excel formulas, essays, resumes, apps, charts and tables, and more. However, we have been seeing a growing desire for AI that knows what you want done and can do it with minimal instruction — artificial general intelligence, or AGI.
With AGI, users would ask the agent to accomplish an end goal, and it would be able to produce the result by reasoning what needs to be done, planning how to do it, and carrying the task out. For example, in an ideal scenario where GPT-5 had AGI, users would be able to request a task such as “Order a burger from McDonald’s for me,” and the AI would be able to complete a series of tasks that include opening the McDonald’s site, and inputting your order, address, and payment method. All you’d have to worry about is eating the burger.
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The Rabbit R1 startup is trying to accomplish the same goal, creating a gadget that can use agents to create a frictionless experience with tasks in the real world, such as booking an Uber or ordering food. The device has sold out multiple times despite not being able to carry out the more advanced tasks mentioned above.
As the next frontier of AI, AGI can completely upgrade the type of assistance we get from AI and change how we think of assistants altogether. Instead of relying on AI assistants to tell us, say, how the weather is, they will be able to help accomplish tasks for us from start to finish, which — if you ask me — is something to look forward to.