Unity AI
AI Antibiotic
Minecraft AI
MIT: Math AI
Picture-to-3D
Google Starline
Nvidia Game AI
Google Flood AI
ChatGPT in Court
TIME: Humanity End
Neuralink FDA Approval
42% US Not Used ChatGPT
Japan No Copyright OK for AI
Here what you need to know:
1. Unity AI
Unity, the game engine behind 80%+ of mobile games, released the beta for its AI engine.
It will enable the next generation of mobile developers to go live with small teams.
In the future, a solopreneur game dev will make a billion dollars - thanks to AI.
Unity CEO John Riccitello knows a thing or two about games.
He has driven the mobile transformation in games the last 17 years.
He said generative AI in games a 10x transformation that will drive exponential growth.
2. AI Antibiotic
Scientists published a paper using AI to discover a new antibiotic.
It came out last week in the prestigious Nature Chemical Biology.
They used deep learning AI methods to prune through many options and find an ideal candidate.
And the crazy part - it just keeps getting better over time 🤯
It writes CODE to play Minecraft.
It's an advanced application of autonomous agents (started before AutoGPT but supported by its reception).
It just keeps improving itself.
And it's totally open-sourced.
4. Picture to 3D
Instorier released a next-level picture to 3d tool.
This is one of the most details and manipulable photo enhancing tools out there.
What a demo.
Instorier is a storytelling tool from photos.
This AI enhancement represents another big leap and shows how the convergence of 3D, Graphics & AI is leading to mind-blowing results.
When focused products add AI, magic happens.
5. MIT: Math AI
MIT researchers released a paper using AI to solve complex math problems much faster than they could have otherwise.
The AI auto-discovers conservation laws from differential equations.
An MIT researcher spent 12 months to solve 12 quantities.
The AI found 14 in less than a minute.
As AI helps us speed up our understanding of basic science - math - the applied stuff will speed up as well. More exponential progress is on the horizon.
6. Google Starline
Google has released a prototype of its 3D telepresence product.
The new version uses breakthroughs in AI to render a 3D version of you to make people feel 'present' next to you.
With just 2 unobtrusive cameras.
Thanks to AI, it's progressed very far from the giant booth you needed to use a while ago.
This technology is going to enable people to feel more connected than ever to their loved one's.
And one day, it will land up in Google Meet - to give Google a Zoom differentiator.
7. Nvidia Game AI
Nvidia showcased how AI can power (non-player character) NPC characters life.
It uses Audio-to-speech, AI-powered conversation (think ChatGPT with a voice), and advanced Nvidia graphics tech to create 'next gen' NPCs.
8. Google Flood AI
In its ongoing attempt to "add AI to everything," Google released an AI to forecast flood dangers near your home.
It uses AI to read weather patterns 7 days in advance and predict how deep the waters will get.
And it works GLOBALLY to help those in need.
Best of all - it's completely FREE.
Google Flood Hub is designed to help people who live near rivers and are aware of flooding threats. It gives them access to real-time data to stay safe.
In places like Africa and India where resources are low, even government agencies use it.
9. ChatGPT in Court
A lawyer used ChatGPT in court and didn't check the cases it cited.
This is the most important part of the homepage. Too many people waste the space:
A. Convey the category of software your product is in, and how your solution differs
B. Add in wow logos from industries in your ICP (ideal customer profile)
2. Three Key Value Props
Remember the rule of threes.
Deliver on your hook above the fold and make your differentiators crystal clear.
Don't just tell, either. Show. Let people experience the product. Attio's videos move when you scroll.
For a company founded in '93, Nvidia's ascent to $2.7T market cap has been FAST. But what really is Nvidia's moat?
Let's break it down.
PART 1 — SOFTWARE
The story starts all the way back in the early 2000s. That's when Jensen Huang, Nvidia CEO, and his team were out meeting researchers using their products.
Most researchers were hacking graphics packages to run complex parallel compute tasks. It was not ideal. To say the least.
So, when the Nvidia team met Ian Buck, who had the vision of running general purpose programming languages on GPUs, they funded his Ph.D. After graduation, Ian came to Nvidia to commercialize the tech.
Two years later, in 2006, Nvidia released CUDA.
C ompute
U nified
D evice
A rchitecture
CUDA made all those parallelization hacks the researchers were doing available to everyone. Over time, CUDA became the default choice for researchers.
CUDA allowed accessible customization of the low-level hardware. So developers loved it.
Nowadays, when startups like MosaicML evaluate the available technology vs CUDA, they inevitably choose CUDA.
The ecosystem around CUDA has grown so robust that its lead is virtually unbeatable. This software layer is at the core of Nvidia's moat.
PART 2 — HARDWARE
The other side of Nvidia's moat is hardware. But it's not graphics cards for crypto and gaming. The hardware that matters is AI supercomputers.
The story of these supercomputers begins in the late 2000s. As Nvidia was developing CUDA, Jensen asked the team to build a supercomputer to help him build better chips.
The result was a massive supercomputer that weighed 100 pounds and strung together many GPUs with world-class networking for ultra-fast computing.
In the early 2010s, Jensen gave a talk at a conference about this AI supercomputer. Elon Musk got wind of it and said, "I want one."
So, in 2016, Jensen actually donated one to Elon Musk's relatively unknown nonprofit, OpenAI. He hand delivered it, and there's photographic proof.
OpenAI quickly learned the supercomputer worked really well. Especially for training large neural networks. That 2016 Pascal architecture delivered an impressive 19 TFLOPS of FP16 operations.
That's 19 trillion floating point operations per second. It's a massive amount. But that was just the beginning.
Since then, Jensen and the Nvidia team have been lapping the industry in delivering more TFLOPS, growing them at an exponential rate.
The latest Blackwell architecture delivers a massive 5000 TFLOPS. That's >260x AI computer in 8 years. And sells for more than $75K. But buyers like Meta, OpenAI, Google, and Amazon just can't get enough, as their internal ASICs are nowhere near Nvidia's level.
As a result, Nvidia's profits and market cap continue to soar, cementing its position as a leader in the AI hardware and software space.
Jensen is one of the most impressive entrepreneurs alive.
He spotted the AI revolution before any other semiconductor CEO and bet the company on it.
That's a rare trait.
And he has a rare management style as well.
He has over 60 direct reports, and doesn't have 1:1s with any of them.
He believes in sharing feedback in public, so everyone can learn from it. And he also does it to remove layers.