Hey everyone, welcome back to the Elon Musk Podcast.
I'm thrilled to share some exciting news with you over the
next two weeks. We're evolving.
We'll be broadening our focus to cover all the tech Titans
shaping our world. And with that, our show will
become Stage 0. You'll still get the latest
insights on Elon Musk plus so much more.
So stay tuned for our official relaunch at Stage 0 coming soon.
I'd like to thank the sponsor of this show, Phish dot Audio, a
great service. So if you're a podcaster, a
voice over artist, or a content creator like myself and you're
looking for hyper realistic AI generated voices, you need to
check out Phish Audio. Ranked among the top 2 most
realistic voice generators in 13 languages, Phish Audio lets you
create high quality voice overs with just a few clicks.
Now I'm going to be honest with you, sometimes I make mistakes
during the show and I need to replace some words because I
misspoke or something was in the background, there was some noise
or something. I just can't get rid of it.
So sometimes I use AI generated me in order to fill in those
gaps. And I tried Phish Audio for this
and it worked so good, so much better than the others that I've
tried. And it's open source friendly.
It's super fast, it's even faster than 11 labs if you're
familiar with that. And best of all, it's
affordable. It has the lowest prices on the
market. So whether you need multilingual
voice cloning, real time speech to speech conversion, or
professional quality narration, Fish Audio has you completely
covered with whatever you need done.
Try it today for free at Fish dot Audio and see why it's the
absolute best AI vice tool out there today.
Go check them out at Fish dot Audio.
That's Fish dot Audio fish dot audio.
Head to Fish dot Audio and start creating with AI powered voices
right now. Welcome to this week's AI
update. So how many times can artificial
intelligence reinvent itself in a single week?
And what happens when it starts to reshape the very definition
of creativity, design, and human likeness?
This week in AI has introduced more than just flashy demos or
iterative upgrades. It has opened a new chapter in
how we visualize the future of interaction, media and autonomy.
From image generation that understands multiple references
to hyper realistic avatars that lip sync in multiple languages,
to humanoid robots executing front flips and punches, all
within a few days, the question is no longer what AI can do, but
what it will leave for us to do. Bytedance, Google, Meta,
Alibaba, Vivago AI and a constellation of open source
contributors have each launched new products, updates or
jaw-dropping showcases, many of which feel like they came from
different futures. This isn't about incremental
progress, it's about a cascade of systems each pushing
boundaries once thought unscalable.
But what's buried beneath the spectacle is the unsettling
realization. How fast are we letting machines
to what once required human hands, eyes, and voices, or
evened our own emotions? So let's start with Bytedance's
latest creation, Uno. This new AI model redefines what
it means to generate an image. Uno responds to text prompts,
but it also fuses multiple image references into a single
coherent output, something that previous models often struggle
with. Most impressively, it retains
character fidelity and object accuracy, regardless of how
surreal or stylistically diverse the prompt might be.
Now, say you upload a logo and a photo of AT shirt.
Uno doesn't just overlay it, it visualizes the logo printed on
the shirt with convincing fabric, shadows and appropriate
scale for the logo. Or consider uploading a doll and
a plush toy. Uno will place them together in
a new realistic scene. It even let's users generate A
stylized portrait of a person using a single input photo.
Anime, Pixar, or even video game style.
Uno handles all of that stuff while maintaining identity
trades. Now for creators, Uno is a
silent assassin. If you're running a fashion
brand, Uno is basically your model and your whole photo shoot
team. Upload 2 clothing items and
prompt the model to generate a person wearing them.
Set in a cityscape or flower field of sunset.
You can even try different models, body types, or urban
settings. And for influencers, Uno becomes
a face swapping studio. Give it one video of yourself
and it'll generate your likeness in any scene, doing anything,
wearing anything. This kind of tool doesn't just
help with photorealistic image creation, it enables entirely
new workflows for people who don't have a studio full of
people. Now, what used to require hours
and possibly days in Photoshop and multiple production rounds
is now available with just a few clicks and a smart prompt.
Now, Uno's value isn't just in flexibility, it's in fidelity.
In benchmark comparisons with tools like Omni IP Adapter and
OEM control, Uno consistently produce more accurate
generations. For instance, when fed a
reference image of a uniquely designed clock, Uno was the only
tool able to correctly recreate it on green grass surrounded by
sunflowers with even the yellow 3 intact.
The same held true for altering the color of toys or preserving
intricate shapes. Accuracy at the level means less
trial and error and more trust in AI generated visuals.
That's a quiet revolution for designers, developers and
content creators who work under very tight deadlines.
Now Byte Dance has made Uno freely available through a
Hugging Face demo with an optional GitHub repository for
local installs. You'll need a machine with at
least 16 gigs of RAM and some familiarity with launching
Python scripts. Quantized model variants are
also available for those with limited GPU resources and this
dual offering browser based ease and local control makes Uno
accessible without compromising its power.
Gives professionals and hobbyists alike the ability to
integrate next Gen. visual tooling into their own
workflows. Meanwhile, a whole different
team has pushed video generation to the next level.
Their latest tool, called One Minute Video Generation with
Test Time Training, allows AI to produce full length, minute long
videos that maintain consistent characters, environments, and
art styles. Instead of relying on a single
long prompt, you just breakdown a video into storyboard style
scenes. Each scene contains a short
description, like Jerry the brown mouse holds cheese or Tom
the cat snatches the cheese and the model stitches these
together to form a coherent, evolving story.
Yes, the generated videos have rough edges, the lip sync is
glitchy, backgrounds jitter, and text in scenes is often
illegible. But the consistency of
character, motion and design throughout a full minute is a
major leap forward. Prior tools could barely sustain
coherence over 3 to 5 seconds. This was made possible by
layering test time training modules over Cog Video's base
model. These modules act like memory
units, absorbing and maintaining the visual state across scene
transitions. It points to a near future where
AI can generate a 10 minute short film with nothing but a
script and a few references. Now then there's Hollow Point,
another new AI system focused on 3D modeling.
The tool doesn't just segment object, it reconstructs what's
hidden from view. If you upload a ring, the model
identifies the band in the settings, then completes the
invisible side of each. That completion isn't guesswork.
It uses a two stage system. First it segments visible parts.
Next, it sends each piece through a 3D diffusion model to
fill in occluded areas. The end result is a fully
editable mesh with complete logical subparts.
For 3D artists, this means they can now expand or customize
individual parts of a model, resize the diamond, change a rim
texture, or separate a chair's legs from its seat, all without
needing to manually remodel or make speculative guesses.
This kind of automation saves hours of work in production
design, animation, and game development.
Like many other tools this week, Hollow Part is available on
Hugging Face for interactive testing and through GitHub for
full installation. Open source models just got
better than commercial ones. One major development this week
came from a lesser known but quickly rising company called
Vivigo AI. It launched Hydram, a new open
source image generation model that has overtaken the
competition, and that's at least in benchmark ratings.
Unlike other high performing systems that remain closed or
partially commercialized, High Dream is fully uncensored and
openly available. According to Artificial Analysis
Independent Model Ranking Organization, High Dream now
holds the 3rd place position among all text to image models.
It is the highest ranked open source model on the list,
surpassing not only stable to Fusion, but also Flux 1D.
Flux Pro, which ranks slightly higher, remains closed source,
making Hydream the best available option for developers
and researchers working without licensing restrictions.
Early tests show that Hydream is more than a benchmark leader,
and it performs well under practical creative conditions.
Text prompts that previously produced vague or distorted
visuals now return precise, detailed, and highly stylized
results. This has opened up new use cases
for illustrators, concept designers, and product marketers
who want control over the visual fidelity of AI generated art.
Importantly, I Dream allows full creative expression without the
usual guardrails or sensors. This is a rare stance in the AI
space, where most companies apply aggressive filtering or
content restrictions. That raises ethical questions
for many users, particularly in animation satire and adult
design solves a problem they've long encountered with other
models. Now Omni SVG is also rising it's
text to vector generation. Another is stand out Omni SVG,
an AI tool designed to generate scalable vector graphics, or
SVGS, from text prompts or images.
Unlike pixel based images, SVGS are resolution independent means
that designers can scale these visuals from handheld to
billboard sizes without losing fidelity, and developers can
drop them into apps without worrying about file size or
weight on the SVG stands out for its ability to produce complex,
detailed vector illustrations that actually match user
prompts. Previous models SVG generation
often failed to capture layout or character details, but this
one completely nails it. Examples include cartoon
characters with mushroom hats, stylized buttons with web UI
concepts, and even photo based SVG conversations.
The retain line fidelity, so vectors still matter.
This matters because the web still runs on vectors.
Icons, logos, app UI elements, and infographics all rely on
SVGS. And for developers who need
sharp design across multiple screen sizes, or for companies
localizing assets into dozens of languages, tools like Omni SVG
reduce the time between idea and development.
And what's more, the model also accept raster images and
converts them into precise SVG renderings.
This brings it into direct competition with some commercial
vectorization tools and according to testing it
outperforms most of them in detail.
Preservation and line geometry code and data sets for Omni SVG
are expected to be released soon.
Meanwhile, Alibaba has debuted a new version of the talking head
generator dubbed Omni Talker. The tool takes a video of a
person talking just a few seconds and allows users to
change what that person says using a custom transcript.
And the results is a realistic looking video where the person
says anything you want them to say.
The output is not only visually smooth, but supports different
languages, maintains mouth movements In Sync with the
audio, and preserves facial expressions.
This means you can take an input of Jackie Chan speaking in
Mandarin and generate a video of him delivering a speech in
English, accent intact, expressions unbroken.
Of course, it's not perfect. The output can become uncanny if
the person moves their head rapidly or if there are long
monologues without breaks. Some cases, the AI renders the
face smoothly or loses subtle emotional transitions if the lip
sync and frame continuity far surpass most tools currently
available. And the more fascinating part is
emotional modulation. If the reference video shows a
sad expression, the generated face will appear somber even if
the transcript is upbeat. A happy reference video injects
cheerful expressions into whatever script is applied.
This emotional anchoring makes the system feel less robotic and
more like a tool for actors or presenters who want to alter
delivery without rerecording. Now most avatar generators top
out at about 10 to 15 seconds. Omni Talker handles multi minute
videos, maintaining voice sync and facial movements throughout.
In one test, a 2 minute political speech was generated
using just a headshot and a transcript, no voice acting
needed. You can even interact with the
avatars live in real time, giving them queries and getting
real time spoken answers. This makes the system useful for
educators, sales, customer service or political messaging.
Any scenario where one person must deliver dynamic scripts at
scale without reshooting or editing the video, removes AI
from behind the scenes to center stage.
And another related tool launched this week, though not
from Alibaba, can take a static photo and animate the face using
either an audio clip or a full reference video of facial
movement feeded a Steve Jobs speech and a photo of Einstein.
It'll make Einstein deliver Jobs words, lip syncing each syllable
with Uri accuracy. And what's remarkable here isn't
just the lip sync, it's the ability to mimic non verbal
cues, blinking, nodding, pausing or even glancing away.
The AI tracks motion and emotional shifts, mapping them
to any face, real or fictional. Whether it's Anne Hathaway or a
digital clone, the face mimics both speech and sentiment, and
compared to rivals like X portrait or live portrait, this
tool performs better on both fidelity and emotional nuance.
The head doesn't stay locked, the eyes shift naturally, and
when combined with expressive audio, it creates A convincing
illustration of live speech. The GitHub repository is listed,
but the code hasn't been released yet.
It's dual mode functionality, supporting both speech only
input and full motion transfer, means that users can choose
between simple lip sync generation or full body
animation. The results are strong enough to
enter entertainment production, especially for animated
interviewers, explainer videos or social content.
Now, robots. Aside of software, the most
viral moments this week came from humanoid robots.
Unitri's robot has performed flips and complex dances before,
but Engine AI's robot raises eyebrows with boxing humans
reacting to punches and landing counter blows.
The demo, though, was captured during a live stream with a well
known streamer visiting the company's facility in China.
Critics have long claimed these humanoid demos were faked CGI
stitched into real environments, but the live stream confirmed
otherwise. The robot fell, got back up,
aimed some punches and adjusted its stance all autonomously with
AI. Not pre recorded, not
choreographed. Unlike dancing routines or
rehearsed acrobatics, boxing requires real time adaptation.
The robot had to interpret opponent movements, adjust its
balance, and select appropriate actions, all within
milliseconds. Like human.
It's about machines competing with humans.
Physically a human versus a robot.
We've seen this movie before, and the humans don't fare too
well in it. Now what sets this apart is the
autonomy system wasn't remote controlled.
It executed decisions based on internal algorithms tracking
visual input and calculating body position.
If it fell, it knew how to stand up.
If it gets too close, it backed off.
For the first time, the idea of reacting humanoid robotics feels
actually real. Then there's Kawasaki.
They introduced a concept that sounds absurd until you watch
it, an AI powered mechanical horse.
Unlike traditional scooters or two Wheelers, this machine walks
on 4 robotic legs. Its body mimics the movement of
an actual horse and it's designed to be powered by
hydrogen, releasing only water vapor.
At this stage the prototype is non functional.
The riding demo is CGI, and the model shown at Osaka's Expo is a
static mock up. But the idea is absolutely
serious. Kawasaki envisions a transport
method that's clean, adaptive, and capable of navigating uneven
terrain, but early feedback has been skeptical.
Most people agree that wheels still outperform legs when it
comes to energy efficiency and also stability.
Now, all of these tools and models and demos are very
flashy. They're tangible shifts in how
humans can work, communicate, and create.
If you're a designer, AI will now generate not only your
visuals, but your style. If you're a performer, AI will
now speak with your face and your voice.
If you're a robotics engineer, the next leap may come not from
code, but from carbon fiber and real time planning algorithms.
The acceleration isn't evenly distributed, but the
opportunities and risks are everywhere.
These tools aren't just for labs or corporations anymore.
They're for us. They're available on GitHub.
Hugging Face or even browser based apps anyone can build with
them. Hey, thank you so much for
listening today. I really do appreciate your
support. If you could take a second and
hit this subscribe or the follow button on whatever podcast
platform that you're listening on right now, I greatly
appreciate it. It helps out the show
tremendously and you'll never miss an episode.
And each episode is about 10 minutes or less to get you
caught up quickly. And please, if you want to
support the show even more, go to Atreoncom Stage Zero.
And please take care of yourselves and each other, and
I'll see you tomorrow.