OpenAI's Roadmap, Bringing Pixar's Lamp to Life, & More

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THEWHITEBOX

TLDR;

Today, we analyze OpenAI’s announced roadmap, their “discovery” that proves DeepSeek was right, the strong yet concerning state of SuperMicro, the dangers of flirting AIs, the first on-device LLM app, and Apple’s first robotics endeavor: bringing back Pixar’s lamp to life by proposing our trend of the week: ‘emotion-displaying robots.’

FRONTIER RESEARCH

OpenAI’s Roadmap

In a viral tweet, Sam Altman explained OpenAI’s roadmap for the upcoming weeks and months. First, he announced that Orion, the secretive model thought to be the key behind o3, is now called GPT-4.5 and will be released next. He also stated that it would be their ‘last non-reasoning-model release.’

But what does he mean by that? Well, they’ve decided that the next release after GPT-4.5, GPT-5, will consolidate all models into a single offering; there will be no more model dropdowns.

In other words, he announced GPT-5, a system of models, including o3. In summary, they want to create a single point of contact with the user who can handle various tasks, dynamically and autonomously switching between models depending on the typology of the user’s request.

Some considerations. What Sam means by GPT-4.5 (Orion) not being a reasoning model is that it’s a pre-trained model trained to compress trillions of words (and probably images, video, audio…) of knowledge into its weights. It's a new update of GPT-4, the base model underpinning all ChatGPT models for the last two years (probably even including o3-mini, although we know they post-trained it with Orion data).

But what is the difference between a non-reasoning GPT-4.5 and a reasoning model like o3?

TheWhiteBox’s takeaway:

The funny thing is that, behind closed doors, non-reasoning and reasoning models aren’t that different, as the base of reasoning models is a non-reasoning model. However, there’s a stark difference in how they approach problem-solving: one takes its time, taking a multi-step approach, and the other responds automatically, without hesitation.

I always find the System 1 / 2 theory of mind by Daniel Kahneman (Thinking fast and slow), consistently referenced by these AI labs, as a great way to difference both models: non-reasoning models are akin to human intuition (or System 1 thinking); they are fast and automatic, they commit to a particular response with no “second thoughts.“ On the other hand, reasoning models are slow and deliberate, they take their time to answer and can reflect, backtrack, or search for better solutions in real-time, akin to humans engaging their prefrontal cortex to solve a complex task (System 2 thinking).

Of course, choosing one or the other depends on the task type. If the user asks for a creative poem, this is instinctive for someone trained in the art of poetry (as GPT-4.5 will be); thus, thinking fast is the way to go. Furthermore, if they ask questions requiring knowledge if the model knows the answer, it just knows it, so there is no need to think for longer about it.

But if the user asks to solve a complex maths…

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