OpenAI Releases GPT-4.5, Blazing-Fast LLMs, and a Robotics' Breakthrough

TLDR;

This week, we cover 👾OpenAI’s GPT-4.5 debut with a focus on emotional intelligence rather than groundbreaking advancements, raising concerns over its steep pricing. Meanwhile, 🚄Inception Labs has introduced Mercury Coders, pioneering diffusion-based LLMs that generate text faster than traditional models.

Moving on, we look at Amazon and Hume AI. The former has 🏠revamped Alexa with Claude-powered AI, aiming to dominate the smart home market, while the latter has launched 🎵Octave, a voice model integrating deep emotional expression.

We then move into 🕸️Poe Apps that enable rapid AI-driven app creation, excelling in prototyping, a close look at NVIDIA earnings report and what I believe is missing and, lastly, we discuss in more detail Figure AI’s 🤖Helix, a multi-robot control system mimicking human cognition, a clear robotics breakthrough.

FRONTIER RESEARCH

Finally, OpenAI Releases GPT-4.5

Weeks after Sam Altman announced their intentions, GPT-4.5 has finally arrived. And the results are, well, interesting. From the live stream, it was clear that the model’s EQ, which stands for Emotional Quotient, would be the main protagonist, not new intelligence frontiers.

In other words, they emphasize that the model seems more emotionally aware, more concise in its responses, and more likely to understand human intent and feelings, but not necessarily “frontier” in the sense that it would not be crushing other models in complex benchmarks, with Sam Atlman himself acknowledging this.

Surprisingly, the model doesn’t seem to be a huge improvement (OpenAI acknowledged removing ‘GPT-4.5 is a frontier model’ from the system card), which makes it even more daunting given its astronomical prices: $75/million input tokens and $150/million output tokens. For reference, that’s x250 and x500 times more expensive than OpenAI’s cheapest model, GPT-4o-mini.

Yes, those numbers are actually genuine.

But what does all this tell you about OpenAI’s future? Why are they releasing a model they acknowledge isn’t “frontier”? Are OpenAI’s days long gone? Is this terrible news for NVIDIA? What other insights can be concluded based on the release?

Overall, it’s safe to say that people are underwhelmed. But I believe they are misusing the model and, crucially, not seeing the bigger picture. In fact, I’ll go so far as to say that this model was never meant to be used for anything other than a declaration of intentions. This Sunday, we’ll cover all the details from architecture, training techniques, compute, evaluations, and, crucially, what OpenAI’s real plans are.

FRONTIER RESEARCH

Meet the Mercury Family, the First Powerful dLLMs

Inception Labs, a startup started by professors at different top AI universities, has come out of stealth to present the Mercury Coder family. At first, this seems just like any other AI coding model release.

However, they have gone viral, which should signal you that it’s not.

As you may have realized from the video above, Mercury Coders represent a fundamentally different approach to AI models that makes them blazing fast. They are diffusion large language models (dLLMs) instead of autoregressive LLMs, the traditional approach exemplified by all frontier models (ChatGPT, Grok, Claude, Gemini…, etc.).

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