⚠️ BREAKING: A powerful new AI model from China has just been revealed — and it's outperforming GPT-4.5 on every level! 🇨🇳🧠💥
In this video, we explore:
🤖 What this Chinese AI can do that GPT-4.5 can’t
🧪 Benchmarks and real-world comparisons
🌍 What this means for the global AI race
🥵 How OpenAI, Google, and others might respond
The AI WARS are officially heating up 🔥—is the future of AI shifting eastward?
📌 Like & Subscribe for the latest updates in AI and tech innovation!
#AIWars
#GPT45
#ChineseAI
#AIRevolution
#AIvsAI
#FutureOfAI
#ArtificialIntelligence
#OpenAI
#TechNews
#AIModel
#GPT4
#ChinaTech
#AIBreakthrough
#GlobalAI
#AIUpdate
#NextGenAI
#MachineLearning
#AIComparison
#AIShowdown
#EmergingTech
In this video, we explore:
🤖 What this Chinese AI can do that GPT-4.5 can’t
🧪 Benchmarks and real-world comparisons
🌍 What this means for the global AI race
🥵 How OpenAI, Google, and others might respond
The AI WARS are officially heating up 🔥—is the future of AI shifting eastward?
📌 Like & Subscribe for the latest updates in AI and tech innovation!
#AIWars
#GPT45
#ChineseAI
#AIRevolution
#AIvsAI
#FutureOfAI
#ArtificialIntelligence
#OpenAI
#TechNews
#AIModel
#GPT4
#ChinaTech
#AIBreakthrough
#GlobalAI
#AIUpdate
#NextGenAI
#MachineLearning
#AIComparison
#AIShowdown
#EmergingTech
Category
🤖
TechTranscript
00:00So, Baidu just made a bold move in the AI arms race.
00:06And it's not just another model drop.
00:08It's a strategic shift aimed at shaking the foundations of China's AI market.
00:13On April 25th, Baidu officially introduced two upgraded models,
00:17Ernie 4.5 Turbo and Ernie X1 Turbo.
00:21Let me tell you, these models are turning heads not just because of their performance,
00:26but also because of their pricing.
00:28Now, for those of you who've been following Baidu's AI journey,
00:31you'll know this isn't some sudden pivot.
00:34Their Ernie series dates back to 2019,
00:37when the first model outperformed even Google and Microsoft on the Glue benchmark.
00:42That version used a clever strategy,
00:45masking strings of characters rather than individual words,
00:48which made it a powerhouse in Chinese language understanding
00:51while still holding its own in English.
00:53Fast forward to today, and Baidu's AI infrastructure
00:56is handling over 1.5 billion API calls daily.
01:00That's a 7.5 times increase in usage,
01:03which says a lot about how deeply these models are embedded across industries now.
01:08So, what's new with Ernie 4.5 Turbo and X1 Turbo?
01:12First off, they're fast, smart, and ridiculously cheap,
01:15especially compared to the competition.
01:17Ernie 4.5 Turbo comes in at only 11 cents per 1 million input tokens
01:22and 44 cents for output.
01:24That's roughly 40% of the price of DeepSeq V3,
01:28which was considered a solid contender until now.
01:31Meanwhile, the X1 Turbo model is priced just a bit higher,
01:3514 cents for inputs and 55 cents for outputs,
01:38but it still undercuts DeepSeq R1 by around 25%.
01:43But price isn't the only headline here.
01:45Performance-wise, Baidu's new Turbo models are firing on all cylinders.
01:50Ernie 4.5 Turbo scored an average of 77.68 on benchmark tests for multimodal tasks.
01:57To put that in perspective, GPT-4.0, the much-hyped multimodal release from OpenAI, scored 72.76.
02:06So, yeah, Baidu's model actually outperformed GPT-4.0 in that category.
02:12These models are built for serious work,
02:14multimodal understanding, logical reasoning, creative writing, and even image analysis.
02:19They integrate seamlessly with tools and APIs through Baidu's key and fan platform,
02:24making them a solid choice for developers, enterprises, and researchers.
02:28X1 Turbo, in particular, is all about deep reasoning.
02:32It's essentially an upgraded brain sitting on top of 4.5 Turbo,
02:36enhancing chain-of-thought capabilities and tool calling.
02:40And if you're wondering how this all fits into the bigger picture,
02:43this is Baidu aligning itself tightly with China's national AI strategy.
02:49Beijing has been pushing hard to make China the global AI leader by 2030,
02:55and Baidu's a centerpiece in that plan.
02:57They're not just any tech company.
02:59They were chosen to lead the National Engineering Lab of Deep Learning.
03:03That kind of institutional backing doesn't just come with money.
03:06It also comes with data access, research talent, and long-term policy support.
03:11Private investment in generative AI in China exploded from $650 million in 2023
03:18to over $3.1 billion in 2024.
03:21And Baidu is right at the center of that storm.
03:24With over 4,300 AI companies now active across China
03:28and an AI market valued above $70 billion, there's serious momentum.
03:33And with tech giants like Alibaba and Tencent racing to launch their own advanced models,
03:39like Tencent's Hanyan T1, the competition is fierce.
03:43Everyone's scrambling for market share, and
03:46Baidu is playing both the long and short game.
03:49Drive down prices to increase adoption today,
03:52while investing in next-gen models to dominate tomorrow.
03:56During Baidu's Create 2025 Developer Conference,
03:59Robin Li, Baidu's founder, doubled down on the importance of choosing the right base model
04:04and fine-tuning it for real-world applications.
04:07According to him,
04:09multimodal models are the future.
04:11Pure text models are already on their way out.
04:14This is why both Turbo models now support text, image, and logic-based inputs,
04:18and they've been tuned for diverse scenarios,
04:21from education to finance to healthcare.
04:24But it doesn't stop there.
04:26Baidu also showed off something that honestly feels straight out of a sci-fi movie,
04:31a hyper-realistic digital anchor system powered by their Wenshin models.
04:35It's called Huope Hue Boxing, and it lets you clone yourself,
04:39or anyone else, for live broadcasting.
04:42You just record a two-minute video, and boom!
04:45An AI-powered version of you, complete with facial expressions, emotions, and gestures,
04:49is ready to go live.
04:51And it doesn't just sit there.
04:53It thinks.
04:54It reacts in real-time, changes tone, shows visuals, even switches roles during a broadcast.
05:00One person can now run an entire marketing team with the help of one AI anchor.
05:06So, whether you're selling beauty products on a livestream, hosting an educational channel,
05:10or launching a game promo, Baidu's digital anchor tech is designed to maximize conversion and user retention.
05:17And again, it's all powered by the same deep, multimodal architecture that's driving their core language models.
05:24Now, if we zoom out just a bit, this is also Baidu's answer to rising geopolitical pressures.
05:30With the U.S. cracking down on exports to Chinese tech firms, Baidu's message at this event was clear.
05:36They're not slowing down, they're self-reliant, they're optimized for cost,
05:40and they're setting the pace both in China and increasingly on the global stage.
05:45But while Baidu's been grabbing attention with its rapid model releases and digital clones in Asia,
05:50over in the U.S., NVIDIA just made a huge leap, but in a completely different direction.
05:56Instead of chasing the general-purpose AI crowd, NVIDIA went deep into a problem that's been frustrating researchers for years.
06:04Mathematical reasoning.
06:06Large language models might be great at chatting, generating stories, and even passing coding interviews,
06:11but when it comes to solving complex math problems, especially multi-step ones, they usually start to fall apart.
06:18NVIDIA took that challenge head-on with its new OpenMath Nemetron series.
06:24They've introduced two models, OpenMath Nemetron 32B and a smaller, more efficient version called the 14B Kaggle model.
06:34Both are built on top of the QUIN 2.5 architecture and fine-tuned using a dataset called OpenMath Reasoning,
06:40which is packed with difficult problems pulled from actual math competitions like the AIME,
06:46the Harvard Math Math Mathematics Tournament, and the HLE Math Series.
06:50These aren't basic equations, they're the kind of problems that require multiple logical steps and a solid grasp of advanced concepts,
06:57the stuff that usually trips up even the most capable LOMs.
07:01Now, the 32B model is a beast.
07:04It has 32.8 billion parameters and was specifically optimized for NVIDIA's own hardware using BF16 tensor operations
07:13to maximize performance while keeping memory usage efficient.
07:17In its tool-integrated reasoning mode, basically where it can use external tools during the reasoning process,
07:24it scored a pass at one accuracy of 78.4% on AIME24.
07:31Even more impressive, when using majority voting techniques, it hit 93.3% accuracy.
07:38That's industry-leading performance beating out everything else in this space so far.
07:42But not everyone has access to data centers stacked with high-end GPUs, right?
07:47That's where the 1.4b Kaggle model comes in.
07:51It's lighter, 14.8 billion parameters, but it's optimized to punch well above its weight.
07:57It was designed specifically for competitive performance and it actually won the AIMO2 Kaggle competition,
08:03which focused on solving advanced math challenges.
08:06In chain-of-thought mode, where the model shows its work step-by-step,
08:10it scored 73.7% on AIME24.
08:14Under GenSelect mode, which generates multiple answers and picks the most consistent one,
08:19it pushed that up to 86.7%.
08:22That's serious performance from a relatively compact model.
08:26What's great about both versions is that they come with full transparency.
08:30NVIDIA's made the entire training pipeline open-source through their NEMO Skills framework.
08:35You can access everything from data generation and training steps to benchmark testing and inference configurations.
08:41Whether you're a developer building a next-gen math tutor or someone integrating formal reasoning into a scientific workflow,
08:47you get all the tools you need to build on top of what NVIDIA's already done.
08:51And from an infrastructure standpoint, it's all been optimized to run across NVIDIA's hardware ecosystem,
08:57from Ampere to the newer Hopper GPUs.
09:00You also get support for Triton Inference Server, CUDA libraries and TensorRT optimizations,
09:06which means you can deploy these models in real-time systems or batch jobs without major latency trade-offs.
09:12What's especially clever is the flexibility in how you use them.
09:17There's chain-of-thought mode if you want transparency and step-by-step reasoning,
09:21tool-integrated reasoning when external problem-solving is needed,
09:24and GenSelect if you want maximum answer precision.
09:27This adaptability makes the models useful not just in academic environments,
09:31but also in performance, explainability, and accuracy all matter.
09:35So while NVIDIA is solving math like a pro, Baidu's over here cloning humans for livestreams.
09:41But if you found out your favorite streamer wasn't real, just a digital copy, would you keep watching?
09:46Should we be amazed or genuinely concerned?
09:49Drop your thoughts in the comments, thanks for watching, and I'll catch you in the next one.
10:05Hi.