Kind: captions
Language: en
here's the new pixel 6 pro from google
you're now seeing the result of it
running a computationally intensive
neural network in real time that i put
on there for testing purposes it's using
tensorflow lite and the new tensor chip
that is optimized for ai
i am
unboxing this ai
because uh as a robotics and ai person
i'm interested in seeing how innovation
in ai hardware and software is
increasingly taking over the
smartphone space
also unboxing ai makes me think of
pandora's box the myth that serves as
the metaphor for the mystery and the
power of ai
i know this is just a phone
but let's pause for a second to think
this computer has over
200 000 times the processing power of
the computer that first landed humans on
the moon and over 2 million times the
ram
we are engineering our way to super
human intelligence one phone at a time
one small step for phone
and soon enough
one giant leap for uh
hybrid
of
machine and mankind
let's talk about the specs here's the
comparison of the pixel 6 to the pixel 6
pro across various specs highlighting
what to me are the key differences in
yellow and in green what are the key
similarities so key differences 300 in
price
also the pixel 6 pro has a slightly
higher display slightly higher
resolution and a 120 hertz refresh rate
versus the 90 hertz refresh rate though
honestly i've been using both phones for
almost a week now and i don't feel any
difference between them the key
similarity to me on the ai and the
computational side is that they both
have the same soc system on a chip the
google tensor
to me the ram and storage are very
important but once you get to a certain
threshold it really doesn't matter 12
gigabytes feels the same as 8 gigabytes
and the same goes for the storage
both phones have a
50 megapixel wide angle
now that produces a 12 megapixel image
because google combines the 2x2 pixel
groups into single effective pixel to
cut noise and improve color and dynamic
range
there's also the 12 megapixel ultrawide
that's used to decrease noise
for both the photos and the videos
and the pro has a 48 megapixel telephoto
lens
which results in one key difference i
think it provides a 4x optical zoom plus
a 20x digital zoom via machine learning
via their super resolution algorithm
the rest to me is pretty much the same
both phones feel amazing in my hand but
of course me being who i am i care
mostly about what's on the inside and
that's the google tenser
now let's talk about the tensor chip my
main flagship phone for machine learning
applications this year has been the
samsung galaxy s21 ultra 5g pictured
here with the pixel 6 and the pixel 6
pro
the galaxy brain is powered by
snapdragon 888 the pixel brain is
powered by the new tensor chip both are
truly amazing machines
i think ai innovation in both hardware
and software will be what matters in
flagship smartphones over the next
decade this is where the battle is
let's now look at the details of the
technical specs of the tensor system on
a chip and also the philosophical vision
behind its architecture
the key components of the architecture
of the tensor system on a chip are the
cpus the gpu isp tpu contacts hub and
the titan m2
depending on the application various
components of this chip can be used at
the same time leading to what google is
calling heterogeneous computing
for the cpu there is
two big cpu cores
with the cortex x1 there's two medium
cpu cores with the a76 and there's
four
small cpu cores with the a55
this is in contrast with the most common
design for the flagships which is one
big cortex x1 core and three medium a78
cores
it's funny that google says that having
one big cpu core is good for benchmarks
but uh not good for the experience
it's funny because as you'll see in the
benchmarks the pixel 6 actually performs
really well on the single core
geekbench 5 test
performance wise the benefit of having
two cortex x1
is that you can distribute a thermal
budget across them so there's less
overheating on intensive tasks like
4k 60fps video so in the initial test
there's a lot less overheating so you'll
be able to shoot video for much longer
besides the cpus there's the gpu there's
an upgrade in that there's the isp image
signal processor that's optimized for
image and video processing in terms of
machine learning and then there's the
more general machine learning engine
that's the tensor processing unit the
context hub does ultra low power ambient
computing
and the titan m2 does hardware security
like i said i've been using the galaxy
s21 ultra with the snapdragon 88 for
many months now and so it's nice to take
a look at some benchmarks for the cpu
gpu and mpu for these two flagship chips
now the big caveat here as you probably
know is that benchmarks often don't
reflect real-life performance so
arguably that don't actually matter but
the main takeaway story here is that
these are both amazing chips
in geekbench 5 cpu benchmark
pixel 6 outperforms the galaxy s 21 on
single core test
and uh the galaxy s21 out performs pixel
6 on the multi-core test for the
geekbench machine learning benchmark the
snapdragon wins on the cpu and the gpu
and the pixel 6 wins on the
npu
the geekbench machine learning benchmark
by the way uses tensorflow lite and
there's also the ai benchmark 4 that's
specialized for machine learning it runs
a huge number of different neural
networks on the devices and there once
again pixel 6 far outperforms galaxy s21
in fact it leads every other smartphone
on the current ai benchmark for
leaderboard again i think the takeaway
here in terms of benchmarks is that
pixel 6 does well on machine learning
tasks and snapdragon does well on cpu
gpu-centric tasks but they're both again
incredible machines
i think the important thing here is
what does this heterogeneous computing
enable in terms of software features
and the pixel 6 provides a huge number
of seamlessly integrated machine
learning algorithms increasing the
vibrancy of the color with the hdr plus
for the images and hdr net for the video
improving the accuracy and the
efficiency of the face detection again
both for images and video
and then there's just a huge number of
cool features like face on blur
motion mode that adds blur to moving
objects there's the magic eraser that's
actually shown here on screen where you
can select certain parts of the object
they can be removed and then
intelligently filled based on what the
background is
and for images there's real tone that's
looking at skin color making sure this
shows up looking great on photos
honestly the video is where the fun is
like i said hdr net that's an incredible
use of neural networks i actually
personally think super resolution
algorithms are one of the coolest
applications of computer vision in terms
of its uh maybe simplicity and
usefulness and impact and there's a huge
number of applications outside of visual
domain so speech automatic speech
recognition
you're talking about
deployment of state-of-the-art asr
algorithms that pay attention to context
pauses is able to do
noise removal
and on the language side there's neural
machine translation
obviously google is taking natural
language nlp really seriously in both
the textual domain in speech that's
audio and again back to images and video
this is incredible leveraging to do
heterogeneous computing on ai hardware
to enable all kinds of cool
computational photography features
okay let's look at some takeaways my two
favorite ai chips for android now are
the google tensor and the snapdragon 888
time will tell which wins for which
applications but for now competition in
the space is great for everyone
if you want me to talk about other ai
systems or about running machine
learning code on this and on other
phones let me know
i'll close with a quote from eliezer
ytkowski
by far the greatest danger of ai is that
people conclude too early that they
understand it
thanks for watching and hope to see you
next time
you