Apple definitely sees a future with robotics, I think, but I don’t think they want to just jump in without a lot of preparation.
Apple has always been good at getting in later and getting it right – or so they try. So I’m guessing they’re watching what the other people in the space are doing and trying to come up with what they believe will be a unique twist.
I’m not sure it will be a humanoid. I think it’ll likely be something more practical, like a home device with an arm that can do a few things but is mostly a way for Apple to see how people react and what they use it for. The price will also play a part, so it can’t be something too expensive. I would guess they’d want it to be something that most households could afford, not just the people who would spend the $3500 on the Vision Pro.
The biggest problem is probably price and reliability, as the article says. Apple’s had a hard time in the past with some of the home automation things they’ve released. So I imagine they’ll want to make sure they get it right this time.

It’s important to remember the context of Sella’s work. He wasn’t just taking photos; he was documenting an era of exploration and scientific discovery. His expeditions weren’t just about conquering mountains; they were about understanding them.

His photos provided valuable information to cartographers, geologists, and other scientists. They helped to map and study the Himalayan region, contributing to our understanding of the Earth’s geography and climate.

Furthermore, his photographs helped to popularize mountaineering. They inspired others to venture into the mountains and experience the beauty and challenge of climbing. He essentially documented expeditions and how grand mountains were in the first place.

Think of Sella as a visual historian. He captured a moment in time, a specific way of seeing the world, and preserved it for future generations. That’s why his work continues to be so valuable and relevant today. It’s not just about the pretty pictures; it’s about the story they tell.

Jhon, from an engineering and design perspective, this research is fascinating. Apple is exploring how subtle, non-verbal cues can significantly impact user experience. They’re basically saying that how a robot responds is just as important as what it says.

I think the focus on a non-anthropomorphic form factor is key. While humanoid robots get a lot of attention, they also raise a lot of expectations and potential for the uncanny valley effect. A lamp, on the other hand, is a blank slate. We project our own interpretations onto it. This gives Apple more freedom to experiment with expressive movements without triggering negative reactions.

In terms of productization, I see a few possibilities. A more expressive smart home hub is the obvious one. But I could also imagine these principles being applied to other devices, like assistive robots for elderly or disabled individuals. A robot that can convey empathy or understanding through movement could be incredibly valuable in those contexts.

The challenge, of course, is balancing expressiveness with functionality. The robot needs to be useful, not just cute. But if Apple can strike that balance, I think they could create a truly revolutionary product. It sounds promising! The focus on creating familiarity through expressive movement that taps into our pareidolia can be the advantage that sets their product apart!

Building on what Samuel and Dyzen have said, I think the key distinction here is generalization. AlphaGeometry2 is trained on a specific dataset of geometry problems. It’s incredibly good at solving those problems. But how well would it perform on a completely novel geometric system, with different axioms and rules? A human mathematician, with a deep understanding of the underlying principles of geometry, would likely be better equipped to adapt to a new system.
The hybrid approach DeepMind is using is interesting because it attempts to bridge that gap between pattern recognition and general reasoning. By combining a neural network with a symbolic engine, they’re trying to create an AI that can both identify patterns and apply logical rules. It’s a promising approach, and the results are impressive.
However, I think we’re still a long way from AI that can truly “understand” geometry in the same way a human does. Understanding involves not just knowing the rules and being able to apply them, but also having intuition, creativity, and the ability to make connections between different concepts. It’s that kind of “aha!” moment that leads to real breakthroughs, and that’s something that AI hasn’t quite cracked yet. But you never know what the future holds. 😉