Google DeepMind's New AI Just Did in Minutes What Took Scientists YEARS! ⚡🧠 | AI Revolution - video Dailymotion

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Google DeepMind’s latest AI breakthrough is rewriting the rules of science. In just minutes, this new AI accomplished what took human scientists years of research! 🤯  From cracking complex protein structures to solving unsolvable math problems, DeepMind is pushing the limits of what's possible with AI.  🌐 What is this new AI model capable of? 🧬 How is it changing science forever? ⚡ Could this be the start of a new era in discovery?  Watch this video to uncover how DeepMind's powerful technology is revolutionizing scientific progress — and what it means for the future of humanity.  👁️‍🗨️ Don’t forget to Like, Subscribe & Hit the Bell for more mind-blowing AI content!  🔍 Dive into the AI that’s changing the world — one breakthrough at a time. #GoogleDeepMind #DeepMindAI #ArtificialIntelligence #ScientificBreakthrough #AIRevolution #MachineLearning #AIDiscovery #TechNews #FutureTech #ScienceNews #AIvsHuman #EmergingTechnology #AIProgress #DeepLearning #Innovation #AIinScience #AI2025 #GoogleAI #SmartTech #AGI

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00:00What if AI could not only predict how proteins interact, but actually create new ones to fight

00:07diseases like C19 or cancer? In this video, we're exploring two groundbreaking AI models,

00:12Alpha, Proteo, and Orb, that are reshaping everything from drug discovery to material

00:17science. And before we get started, take a second to subscribe and stay ahead of the curve on all

00:22the latest AI trends and updates. Alright, you know how proteins are like the workhorses of

00:27our bodies, right? They do everything from helping our cells grow to keeping our immune systems

00:32running smoothly. And of course, they're at the core of pretty much every biological process.

00:37But here's the catch. These proteins don't just do their jobs in isolation. They interact with other

00:43proteins. Think of it like a key fitting into a lock. One protein binds to another. And that's how

00:50all these critical functions happen inside our cells. Now, thanks to things like AlphaFold, we

00:55already have a pretty solid understanding of how proteins interact. AlphaFold helps us predict what

01:00these interactions look like, which has been huge for science. But here's the kicker. While AlphaFold

01:05is awesome at figuring out how proteins connect, it doesn't create new proteins that could manipulate

01:11or influence these interactions. And that's where the real magic comes in, guys. Enter Alpha Proteo by

01:17Google DeepMind. This is the new AI system we're talking about today. It doesn't just predict

01:22interactions. It designs entirely new proteins that can bind to specific target molecules.

01:28And why is that important? Well, these designed proteins, also called binders, can speed up all

01:34sorts of research, from drug discovery to figuring out how diseases work, to making crops more resistant

01:40to pests. Now, let's break this down. When you want to create a protein that binds tightly to a target,

01:45like, say, a virus protein that causes C19, it's not easy. Traditional methods are super slow.

01:52You have to create binders in the lab, test them, optimize them, then test them again. It's like an

01:59endless cycle of trial and error, which, as you can guess, takes forever. But with Alpha Proteo,

02:04we're talking about a major shortcut. This AI system has been trained on a ton of protein data.

02:10We're talking about data from the protein data bank and more than 100 million predicted structures

02:15from AlphaFold. So yeah, it's learned a thing or two about how proteins interact.

02:19Now, if you give Alpha Proteo the structure of a target protein and tell it where you want the

02:25protein to bind, it can design a binder protein that fits that target almost perfectly. That's like

02:31handing it the blueprint for a lock and having it design the perfect key. And it works on all kinds

02:37of proteins. Cancer-related proteins, proteins from viruses like SARS-CoV-2, yes, the one involved in the

02:44lockdown era, the C-19, and even proteins tied to autoimmune diseases. So far, the results are

02:51pretty mind-blowing. In fact, Alpha Proteo generated binders for seven different target proteins. And

02:57here's the kicker. They tested these proteins in the lab and the AI-designed binders worked like a

03:01charm. I'm talking about three to three hundred times better binding strengths than the best existing

03:07methods. Insane, right? For example, let's take VGFA, which is a protein linked to cancer and diabetes

03:14complications. For the first time ever, an AI system, Alpha Proteo, designed a protein binder

03:21that successfully binds to VGFA. That alone is a huge milestone. And it's not just one-off successes.

03:28Let's take another protein, BHRF1, which is a viral protein. In the lab, 88% of Alpha Proteo's

03:35candidate binders actually bound to BHRF1 successfully. And get this, Alpha Proteo's

03:40binders on average are binding 10 times stronger than any of the current best designs.

03:46Now, one of the most hyped targets was the SARS-CoV-2 spike protein, the very same spike that

03:52helps the virus get into our cells. And yeah, Alpha Proteo nailed it. Not only did it design binders for

03:58this spike protein, but those binders were tested by some top research groups like the Francis Crick

04:04Institute, and they confirmed the binders were legit. These binders even managed to block the virus

04:09and some of its variants from infecting cells. So we're looking at something that could potentially

04:15help in virus prevention. Now, obviously, this tech isn't perfect yet. For example, Alpha Proteo couldn't

04:21design a successful binder for TNFA, which is a protein associated with autoimmune diseases like

04:28rheumatoid arthritis. But to be fair, TNFA is known to be a beast in terms of difficulty.

04:34The team picked it on purpose to test the limits of the system. So it's not all bad news. In fact,

04:39it's a sign that they're pushing the system to improve. And while strong binding is critical,

04:43it's just the first step in using these proteins for real-world applications, like drug design.

04:49There's still a ton of bioengineering work to do, but Alpha Proteo has already knocked out one of the

04:54toughest parts. Now, the team behind Alpha Proteo is working with scientists across the world to make

05:00this system even better. And they're thinking responsibly about biosecurity. That means making

05:06sure this powerful tech is used for good, like developing treatments and cleaning the environment

05:11rather than, you know, any shady stuff. And if you're wondering where this is going, well, they've

05:15already teamed up with groups like the Nuclear Threat Initiative to set up best practices. So the tech is

05:21evolving, but with caution, which is honestly a relief. Looking ahead, they're also exploring drug

05:27design applications with a company called Isomorphic Labs. And they're actively working

05:32on improving the algorithms to make the system even stronger and more versatile. And they're not

05:37just doing this in a vacuum. They're collaborating with experts in machine learning, biochemistry,

05:42and structural biology. So the future of protein design, yeah, it's looking pretty exciting.

05:47All right. Now there is another thing I'm seriously hyped about, and it's actually a massive

05:51breakthrough in AI and material science. We're talking about ORB, the latest and greatest AI

05:56model for simulating advanced materials. It's open source, it's blazing fast, and it's leaving big

06:02names like Google and Microsoft in the dust. If you're into AI, energy, or just cutting-edge tech,

06:08you're going to love this. So let me break it down for you. Imagine you're a scientist working on

06:13materials for, say, better batteries or solar panels, things that are crucial for the energy

06:17transition, right? Well, here's the thing. To design these super-efficient materials,

06:22you need to know exactly what's happening at the atomic level. We're talking about how atoms and

06:28molecules are interacting, what makes certain materials conduct energy better, or how you can

06:32tweak them to be more efficient. But, and this is the tricky part, actually seeing or simulating

06:38what's happening inside these materials is insanely hard. Traditional methods for simulating this stuff,

06:43they're slow, costly, and often involve simplifying things so much that you're not even getting an

06:50accurate picture. It's like trying to watch a 4K movie on dial-up internet. It's just not happening. And

06:56that's where AI comes in, giving us a new way to look at these materials with way more detail, without

07:02waiting forever. This brings us to ORB, the model we're talking about today. Built by a company called

07:08Orbital. ORB is designed to simulate materials at the atomic level faster and more accurately than

07:15anything else out there right now. And get this, it's based on a bigger AI model they've been working

07:20on internally called Linus. So basically, they've been fine-tuning this thing for a while now, and it's

07:25paying off in a huge way. Now, ORB isn't just faster than the competition, it's five times faster than the

07:31best alternatives for large-scale simulations. That's a huge leap forward. And we're not just talking about

07:36beating random models either. ORB is outperforming Google's and Microsoft's models when it comes to

07:42accuracy and speed. And here's where things get even more exciting. They've open-sourced it.

07:47Yup, it's free for non-commercial uses in startups. So anyone looking to develop new materials can jump

07:52in and use this tech. You can even go to their GitHub right now and check out the full technical

07:58breakdown. Now, let me pause here for a second to explain why this is so important. We're in the middle

08:04of a massive shift toward renewable energy, and materials are at the heart of that. Whether it's

08:09batteries for electric cars, solar panels for homes, or semiconductors for basically all of our tech,

08:14the materials we use need to get better, more efficient, longer lasting, you name it. And the

08:20faster we can simulate and design these materials, the faster we can make them a reality. ORB is a tool

08:26that's going to accelerate that process in a big way. Now, if you're wondering how ORB came to be,

08:32it all ties back to this foundation model I mentioned earlier, Linus. The team at Orbital

08:37has been training and refining Linus from the ground up. ORB is like Linus on steroids,

08:43specifically fine-tuned for advanced material simulations. They've got a whole blog explaining

08:48the key elements if you want to dive into the technical side, and they've got even more info

08:53coming soon. So yeah, this isn't some random new AI model. It's been a long time coming. And can we just

08:59take a second to appreciate the team behind this? This isn't some massive tech giant with endless

09:04resources. We're talking about a small, tight-knit group that's competing with the biggest names in

09:08AI, Google, Microsoft, and so on. It's proof that even in an era where it seems like only the giants

09:14can make big moves, a scrappy, motivated startup can still come out on top. So there you have it.

09:20ORB, the fastest and most accurate AI model for advanced material simulations, is out there.

09:25And it's free to use for non-commercial purposes. I can't wait to see where this goes.

09:30As always, drop your thoughts in the comments. Are you as excited about this as I am?

09:35Smash that like button, and don't forget to subscribe for more deep dives into AI and tech.

09:40Thanks for watching, and I'll see you in the next one.

Google DeepMind's New AI Just Did in Minutes What Took Scientists YEARS! ⚡🧠 | AI Revolution

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