Eric Xing

Researcher, educator, entrepreneur, and administrator in computer science, artificial intelligence, and healthcare.

[Mingkai Deng @mdeng34]

We agree that the world model should be a simulator that supports decision-making, not rendering beautiful images/videos.

Our difference is in how the world state should be represented.

Should the world be anchored in Gaussian splats and physics engines for program-as-simulator? Or in learned representations for model-as-simulator?

We believe the latter is a more scalable, bitter-lesson-pilled approach.

More in our position paper "Critiques of World Models" coauthored with Prof. @ericxing and @jinyuhou0

https://t.co/NqnxGtKNBL

[Institute of Foundation Models @IFM_MBZUAI]

1/4
Frontier LLMs are converging on adaptive reasoning.

But controlling how much to think is not the same as controlling what kind of thinking to do.

SR²AM introduces self-regulated simulative reasoning: an agent that simulates possible futures through a world model and learns when that simulation is worth the cost.

[CMU School of Computer Science @SCSatCMU]

Congrats to Parallel Data Lab researchers including SCS faculty member Eric Xing on receiving the Test of Time Award during the 2026 EuroSys Conference!

https://t.co/7f1PZ68aqu

[Mingkai Deng @mdeng34]

Frontier LLMs are converging on efficient, adaptive reasoning. Opus 4.7 lets the model decide how deeply to reason. GPT-5.5 achieves strong results with fewer reasoning tokens.

We study a related but more structural question: what 𝗸𝗶𝗻𝗱 𝗼𝗳 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 should we adapt?

Last year in SiRA (upper figure), we showed that simulative reasoning (System II), which uses a 𝘄𝗼𝗿𝗹𝗱 𝗺𝗼𝗱𝗲𝗹 to evaluate consequences of actions, yields up to 124% improvement over reactive baselines (System I), and that strong reasoning models (o1, o3-mini) fail as planners without this structure.

In our new paper SR²AM (lower figure), we add a learned 𝗰𝗼𝗻𝗳𝗶𝗴𝘂𝗿𝗮𝘁𝗼𝗿 (System III) that self-regulates when to simulate, how far ahead, and when to skip planning entirely.

Efficient reasoning is not just shorter reasoning: it is better allocation of simulation.

[Mingkai Deng @mdeng34]

This is a prototype using language-based world models. Stay tuned for our next steps on multimodal and physical world models.

The concept of a configurator, which decides when and how deeply to engage a reasoning process, is not specific to planning, but extensible to learning and adaptation going forward.

📄 SR²AM: https://t.co/LKeXZFN8Hh
📄 SiRA: https://t.co/5JzLSEu4nO
🌐 Project: https://t.co/1CUlEdFMxY
💻 Code: https://t.co/JSBoERYHaB

🤗 SR²AM-v0.1-8B: https://t.co/b1kkuvFL6k
🤗 SR²AM-v1.0-30B: https://t.co/PES00q6a4J

Joint work with @jinyuhou0, @larasnevess, @varad0309, @tw_killian, @waterluffy, @ericxing

[MBZUAI @mbzuai]

MBZUAI and the United Arab Emirates Government have signed a strategic collaboration agreement.

As the Strategic Knowledge Partner, MBZUAI will support the UAE's national initiative to deploy agentic AI across 50% of government services, training 80,000 federal employees and delivering executive programs for government leaders, reinforcing the UAE's commitment to becoming a global leader in AI-enabled governance and public sector innovation. The collaboration will advance AI readiness, literacy, and executive capability building across UAE federal government entities and ministries, and driving the responsible adoption of generative and agentic AI technologies.

In the presence of H.E. Mohammad Abdullah Al Gergawi, Minister of Cabinet Affairs, and H.E. Khaldoon Khalifa Al Mubarak, Secretary General of the Artificial Intelligence and Advanced Technology Council and Chairman of MBZUAI’s Board of Trustees, the MOU was signed by H.E. Ohood Khalfan Al Roumi, Minister of State for Government Development and the Future and Chairwoman of Federal Authority for Government Human Resources (FAHR), and Prof. Eric Xing, MBZUAI President and University Professor.

[Institute of Foundation Models @IFM_MBZUAI]

Zihan Liu, Technical Lead for the PAN world model at IFM’s Silicon Valley Lab, is joining us at @Stanford on May 21 to share how he and his team build interactive, long-horizon world simulations.

[Institute of Foundation Models @IFM_MBZUAI]

Hector Liu, Director of IFM’s Silicon Valley Lab, is joining us at @Stanford on May 21 to share how he and his team build and deploy IFM’s reasoning and world models.

[The Royal Family @RoyalFamily]

A very special delivery for David Attenborough, beloved by people (and animals) everywhere 💚

To honour Sir David’s 100th birthday, His Majesty The King is supported by a cast of stars from British nature to relay his handwritten message in time for the celebration at the Royal Albert Hall.

Watch David Attenborough’s 100 Years on Planet Earth on @BBCiPlayer.

https://t.co/yZojhLlUXp

[Eric Xing @ericxing]

Glad to see @mbzuai , a university 5 years old, is in this list of top contributors alongside world leading universities. Contributions to my colleagues.

[ℏεsam @Hesamation]

someone analyzed all 5000+ accepted papers at ICLR 2026, and it's a good signal who's pushing the research of AI:
> China has surpassed the US with 43.7% of the papers
> Europe's contribution is surprisingly small (5.3% including UK)

[Eric Xing @ericxing]

“A university that asks students what they want and gives it to them is not educating – it is catering.”

In my annual MBZUAI commencement address today, I emphasized two principles that shape our university: 1) The core business of university is creating knowledge and teaching knowledge, everything else is secondary; 2) Our university is a forge. Faculty and leaders are not pastoral counselors; they are forge masters. Their job is to make people capable, not comfortable. — Maybe obvious, but hard to say and hard to enact these days.

https://t.co/nq6YjFUP0T

[Aviv Bick @avivbick]

SSMs fail on recall tasks they have the capacity to solve. The two dominant approaches today, SSMs and sliding-window attention, both lack persistence: memory either decays over time or gets evicted.

We built Raven to fix this, surpassing all prior linear models even at 16× their training sequence length. 🧵🐦‍⬛

[MBZUAI @mbzuai]

Professor Xiaosong Ma, Chair of Computer Science has a message for the Class of 2026:
"The world will keep changing - the tools, the skills, the technology. But how you work, how you treat data, experiments, and people? That stays with you."

And to every graduate crossing the stage, a reminder: "It's your party. Don't be nervous."

#PioneeringWhatsNext #MBZUAI2026

[Special Competitive Studies Project @scsp_ai]

.@ericxing, Professor of Computer Science at @CarnegieMellon University, will share his expertise on the South Stage this Saturday, May 9 at the #AIExpoDC.

[Eric Xing @ericxing]

Strong line of continuous innovation! Proud of our team.

[Hao Zhang @haozhangml]

Such an honor to share that our 2016 paper GeePS just received the EuroSys Test-of-Time Award 🫡🚀🏆

It was actually my first system paper (and obviously my first MLSys paper, too) in phd -- and arguably the first paper to systematically tackle GPU memory swapping for deep learning, right after AlexNet moved DL onto GPUs.

It has been 10 years! The ideas are everywhere. A short thread on what we did and where it went 🧵

[Ihtesham Ali @ihtesham2005]

An MIT professor taught the same math course for 62 years, and the day he retired, students from every country on earth showed up online to watch him give his final lecture.

I opened the playlist at 2am and ended up watching three of them back to back.

His name is Gilbert Strang. The course is MIT 18.06 Linear Algebra.

Every machine learning engineer, every data scientist, every quant, every self-taught programmer who actually understands how AI works learned the math from this one man. Most of them never set foot on MIT's campus. They just opened a free playlist on YouTube and let him teach.

Here's the story almost nobody tells you.

Strang joined the MIT math faculty in 1962. He retired in 2023. That is 61 years of standing at the same chalkboard teaching the same subject to 18-year-olds.

The interesting part is what he did when MIT launched OpenCourseWare in 2002. Most professors were skeptical. They worried that putting their lectures online would make their classrooms irrelevant. Strang did not hesitate. He said his life's mission was to open mathematics to students everywhere. He filmed every lecture and gave it away.

The decision quietly changed how the world learns math.

For decades linear algebra was taught the wrong way. Professors started with abstract vector spaces and proofs about field axioms. Students drowned in the abstraction. Most never recovered. They walked out believing they were bad at math when they had simply been taught in an order that nobody's brain is built to absorb.

Strang inverted the entire curriculum.

He started with matrix multiplication. Something you can write down on paper. Something you can compute by hand. Something you can see. Then he showed his students that everything else in linear algebra eigenvectors, singular value decomposition, orthogonality, the four fundamental subspaces was just a different lens for understanding what the matrix was actually doing under the hood.

His rule was strict. If a student could not explain a concept using a concrete 3 by 3 example, that student did not actually understand the concept yet. The abstraction was supposed to come last, not first. The intuition was the foundation. The proofs were just confirmation that the intuition was correct.

The second thing Strang changed was the classroom itself. He said please and thank you to his students. Every single lecture. He paused mid-derivation to ask "am I OK?" to check if anyone was lost. He never used the word "obviously" or "trivially" because he knew exactly what those words do to a student who is one step behind. He treated 19-year-olds learning math for the first time the way he treated his own colleagues. With patience. With respect. With the assumption that they belonged in the room.

For 62 years.

The result is something that has never happened in the history of education. A single math professor became the default teacher of his subject for the entire planet.

Universities in India, China, Brazil, Nigeria, every country with a computer science department, started telling their own students to just watch Strang's lectures. The University of Illinois revised its linear algebra course to do almost no in-person lecturing. The reason was honest. The professor said they could not compete with the videos.

His final lecture was in May 2023.

The auditorium was packed with students who had never met him before. He walked to the chalkboard, taught for an hour, and at the end the entire room stood and applauded. He looked confused for a moment, like he genuinely did not understand why they were cheering. Then he smiled and waved them off and walked out.

His written comment under the YouTube video of that final lecture was four sentences long. He said teaching had been a wonderful life. He said he was grateful to everyone who saw the importance of linear algebra. He said the movement of teaching it well would continue because it was right.

That was it. No book promotion. No farewell speech. No legacy management.

The man whose teaching is the foundation of modern AI just thanked the audience and went home.

20 million views. Zero ego. The entire engine of the AI revolution sits on top of math that millions of people learned for free from one quiet professor in Cambridge.

The course is still on MIT OpenCourseWare. Every lecture, every problem set, every exam, every solution. Free.

The most important math course of the 21st century is sitting one click away from you. Most people will never open it.

[Eric Xing @ericxing]

At ⁦@genbioai⁩, we use AI to build AI, so virtual cells can be made and harnessed automatically at scale. https://t.co/A58YNZwraO

[Institute of Foundation Models @IFM_MBZUAI]

Hacktech is almost here, and we’re bringing K2 Think V2 to @Caltech.

Hackers will get free access to our fully open‑source reasoning model all weekend for agents, tools, simulations, and whatever wild ideas you’re ready to test.

[MBZUAI @mbzuai]

"At some point, I believe disease can be simulated digitally," MBZUAI President and University Professor @ericxing tells @washingtonpost how world models could make drug discovery unimaginably faster.
Plus: How our research is pushing past LLMs, and why the UAE matters in the global AI race.
@genbioai

Read the full article. ⬇️
https://t.co/PSCnJtMXkO