Alibaba released RynnBrain, an open-source embodied AI model built to help robots perform real-world tasks like navigation and object handling.Alibaba released RynnBrain, an open-source embodied AI model built to help robots perform real-world tasks like navigation and object handling.

Alibaba open-sources RynnBrain to challenge Google, Nvidia robotics tech

2026/02/10 17:45
3 min di lettura
Per feedback o dubbi su questo contenuto, contattateci all'indirizzo crypto.news@mexc.com.

Alibaba has on Tuesday launched RynnBrain, a new embodied AI model that helps machines handle real-world tasks.

RynnBrain is open-source, and it’s already up on GitHub and Hugging Face, with the Chinese giant claiming it thing can help robots figure out how to grab stuff, understand where objects are, and plan what to do next.

Basically, Alibaba is turning robots into workers. RynnBrain was built by the company’s internal research group called DAMO Academy. It’s trained to recognize objects, understand how they move, and make decisions based on space and time.

That’s the kind of stuff robots need if they’re going to be useful outside labs. The company says the model performs better than Google’s Gemini Robotics‑ER 1.5 and Nvidia’s Cosmos‑Reason2 in benchmark tests.

Alibaba releases multiple versions and trains AI model on Qwen3-VL

The RynnBrain AI model is trained on Alibaba’s Qwen3‑VL, and comes in different sizes, starting with 2 billion parameters, and there’s also a version built using a mixture-of-experts design for better efficiency.

Developers can try out whichever version fits their project best. Alibaba made sure the model can be used for robotics in real settings like factories and kitchens. It’s built to predict where objects might go, avoid crashes, and plan what action to take.

This kind of AI is exactly what Beijing is focusing on right now. The Chinese government is putting money and attention into physical AI, especially robots that can work in manufacturing and hospitality. The goal is simple: beat the U. S. in the next round of tech battles.

Jeff Zhang, who is the Chief Technology Officer at Alibaba, also runs the DAMO Academy. He’s leading the team behind this release and the labs they’re building next.

Alibaba expands global labs and launches hiring for 100 researchers

Alibaba is building seven new labs around the world in Beijing, Hangzhou, San Mateo, Bellevue, Moscow, Tel Aviv, and Singapore.

Their work includes machine learning, fintech, network security, visual computing, quantum computing, and human-machine interaction.

Alibaba also plans to recruit 100 researchers from around the world who specialize in IoT, data intelligence, and natural language processing.

The DAMO Academy is also working with schools. One of their main partners is the University of California, Berkeley, where they’re teaming up with the RISE Lab on secure real-time computing. That means their work won’t stay inside corporate walls.

Jeff said:-

This is all part of Alibaba’s long-term plan. The company says it wants to serve 2 billion customers and create 100 million jobs in the next 20 years.

Right now, it already has a tech team of 25,000 engineers and scientists. But with the release of RynnBrain, they’re making it clear they’re not done building.

The smartest crypto minds already read our newsletter. Want in? Join them.

Disclaimer: gli articoli ripubblicati su questo sito provengono da piattaforme pubbliche e sono forniti esclusivamente a scopo informativo. Non riflettono necessariamente le opinioni di MEXC. Tutti i diritti rimangono agli autori originali. Se ritieni che un contenuto violi i diritti di terze parti, contatta crypto.news@mexc.com per la rimozione. MEXC non fornisce alcuna garanzia in merito all'accuratezza, completezza o tempestività del contenuto e non è responsabile per eventuali azioni intraprese sulla base delle informazioni fornite. Il contenuto non costituisce consulenza finanziaria, legale o professionale di altro tipo, né deve essere considerato una raccomandazione o un'approvazione da parte di MEXC.

$30,000 in PRL + 15,000 USDT

$30,000 in PRL + 15,000 USDT$30,000 in PRL + 15,000 USDT

Deposit & trade PRL to boost your rewards!