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AI is everywhere in our apps and our work, but it still hasn't made the jump into the physical products we use every day. In this video, I break down where AI hardware is right now, where I think it's going, and what holds it back. I talk through the "Jarvis" ideal: one AI brain that runs across your phone, home, car, and computer. Then I cover today's AI wearables like smart glasses, rings, and recorders, and how they feed context into ChatGPT or Claude. I also explain the two big problems that stop us from getting there: integrations and distribution. Do you agree with my take or not? Let me know in the comments.
CHAPTERS: 0:00 AI Is Booming, But Not in Physical Products 1:04 Where AI Hardware Is Now and Where It's Going 1:15 Sponsor: Rumble Wallet 2:30 The Jarvis Ideal: One AI Brain Across All Your Devices 2:53 Why Cars Lead in AI-Enabled Hardware 3:25 Where We Are Now: AI Hardware That Gives AI More Context 3:44 AI Wearables: Smart Glasses, Rings, and AI Recorders 4:19 How More Integrations Make Your AI Assistant Smarter 4:48 The Gap Between Jarvis and Today's AI Hardware 5:02 Problem 1: Integrations (Context Capture and Smart Home Actions) 5:42 Problem 2: Distribution and the Missing AI Ecosystem 6:18 What Meta and Apple Are Doing in AI Hardware 6:37 Privacy Concerns and the "Her" Movie Future 7:08 Predictions: Physical AI in the Next 1 to 2 Years 7:50 Final Thoughts
------------------- Clips channel @jonlawclips
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So AI is one of the most transformative technologies of all time, and we see all this talk about
this exponential progress, AGI, super intelligence.
And just in the past two weeks at the time when I'm recording this video, there's been
something like a model launch a day that's frontier on either cost or performance.
But all of this has happened in the digital world, and AI just hasn't made that jump into
physical products that you and I, as a consumer, use every day in our lives.
Maybe we have a new app or new ways of doing things online for our jobs, or an assistant
that makes our life easier, right?
But there is no physical hardware beyond cars, which I'll put in a separate category, but
standard consumer hardware that is fundamentally AI native.
And I think this revolution is just around the corner of a whole host of hardware devices
that are built with AI that replace a lot of the existing incumbent technologies that
we use to live our lives.
And I want to talk through where this space is at, where it's going, and then what the
problems that are holding the space back right now are.
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I think the physical embodiment of AI-enabled hardware, as it actually affects our lives,
is something like Jarvis, like you see in the Iron Man movies, which is one AI brain
that permeates throughout all of the regular devices that you use to live your life.
A lot of that is home tech, just things like your lights, and speakers, and the TV, your
phone, your computer, and then your car.
And a car is the area in which we've seen the most progress with AI-enabled hardware.
But beyond that, in the consumer space, there's not a lot of things that are regularly used
by people or are very fundamentally enabled by one AI brain that's yours and that works
with you as a partner of sorts to make your life better and to make you more efficient
and productive.
So again, that's what I think we're trending toward and what's going to happen and be really
transformative over the next one or two years.
And what we're seeing now is the early stage of that.
And I want to touch on in a minute the spread between that Jarvis ideal and where we're
at.
But basically, where we're at now is AI hardware that gives AI, or the intelligent brain, so
to speak, more context about you and your life so it can help you better.
For example, I've done a lot of reviews on this channel of all of that frontier AI hardware.
That's things like glasses, and rings, and bracelets, and recorders that sit on your
body somewhere.
And what all of those do is record video or audio and then feed that in as an MCT layer
to your existing Jack2BT, Clawed, Muse, whatever it is that you use.
And by recording everything all the time, whether video or audio, you make those personal
assistants, those agents, that AI smarter so it can do more things for you.
And as the number of integrations increase, so your Clawed can access your Gmail, your
Drive, and then just extrapolating that out, it can now serve you better.
It has more context, more integrations through hardware, and then it can, again, just do
more for you.
And that is useful, right?
If your local models and your Jack2BT or your Clawed goes to every meeting for you or remembers
what your kid said they wanted this morning before you go to work, whatever it may be,
it can help you more efficiently just because it knows more about you.
But again, there's a big difference between that Jarvis ideal and then where we're at
currently.
And I think you can categorize those issues as one, the integrations, and number two,
the distribution.
And by integrations, I mean there are devices now that can capture context, again, with
video or audio, but they typically don't capture everything.
That's number one.
That's integrations on the information inflow side of things.
And then you have integrations on the side of what the agents can do with that information.
And that's things like a smart home and a suite of devices to make your home smart once
the AI has the information to regulate your home on your behalf if you want it to, your
car as well, so your physical life, and then also your digital life, being able to communicate
on your behalf, book things with your credit cards, and so on.
Now that's part of the issue when I think where things are improving.
And then the other side of it, again, is distribution, which is you don't want to have this super
fragmented layer, ideally, or at least you want kind of a cornerstone product, like a
cornerstone Jarvis-style product, because you do need to sync across the board everything.
And there is an MCP-style approach where you can kind of keep things fragmented, but you
need some ecosystem, right?
You need the app store from which apps are built.
And we're not fully there yet, and we don't have one of the big companies that can push
an ecosystem like that that has really made a step into that area.
You're seeing things on the assistant side a little bit from Facebook now.
Apple is working on home AI-enabled smart tech, but there's not really been this fusion
of those things or a way to fuse together just different companies' products in a way
that really nicely benefits you.
Now is all of this kind of dystopic?
Yes, completely.
Are there privacy concerns that have to get figured out?
Also a big yes.
In fact, if you've seen the movie Her, I think that's what we're going to get to in the next
one, two years.
And what Her basically is in that movie is just an assistant that knows everything about
you that can do everything on your behalf.
The problem is that's actually really, really useful, which is why I think it will be so
transformative once you crack it.
But it hasn't been cracked for those two reasons of integration and distribution.
I talked a little bit through where we're at currently as far as that frontier tech
goes, and I make lots of videos on this channel about those specific products.
And that I think it'll be an exciting, kind of weird, but definitely a very exciting two
years in this space.
And we're going to see this whole, you know, the last six years of change with AI from
Jack2BT onward has been in the digital space, apart from self-driving, which is just kind
of its own thing.
But now we're going to see that real fusion into the physical world.
And that's when a lot of this talk about how good models are or intelligence is becomes
very tangible because it'll actually interface with you all the time in your life.
And for a lot of people make their lives better.
Those are my thoughts on the subject.
Let me know if you agree or you don't.
Either way, I hope it's some food for thought.
I appreciate you being here and I will see you in the next one.
Cheers.