Sky Computing
Towards Utility Computing for the Cloud
News
March 4, 2026
OpenThoughts-Agent, Continual Learning Benchmark, and MAP announced as Slingshots // TWO projects with Laude Institute
These 14 projects from Stanford, Berkeley, MIT, CMU, UIUC, and Michigan are tackling production deployment, energy constraints, and continual learning. Several are building on infrastructure from Slingshots // ONE. Together, they show what happens when the right researchers get the right resources at the right time: research that ships, gets adopted, and moves the field forward.
November 18, 2025
vLLM is the top open source project on GitHub for 2025
2025’s top projects split between AI infrastructure (vllm, ollama, huggingface/transformers) and enduring ecosystems (vscode, godot, home-assistant).
October 21, 2025
EECS students drive AI innovation as Amazon PhD Fellows
Today, Amazon announced its new AI PhD Fellowship program, offering two years of funding to over 100 PhD students across nine universities. Ten of these inaugural fellowships have been awarded to graduate students from UC Berkeley EECS’ Sky Computing Lab, supporting cutting-edge research in core AI disciplines like machine learning, computer vision, and natural-language processing, ultimately driving innovations essential for the next evolution of practical AI.
October 21, 2025
Amazon launches $68 million AI PhD Fellowship program
“We are thrilled to partner with Amazon to advance open research in AI,” said Joseph E. Gonzalez, a professor of electrical engineering and computer science at UC Berkeley and co-director of the university’s Sky Computing Lab. “Through this fellowship, Amazon and UC Berkeley are investing in the next generation of researchers, and I am excited to see how our PhD students will shape the future of artificial intelligence.”
October 20, 2025
Barbarians at The Gate: How AI is Upending Systems Research
AI is no longer just tuning systems as a “black box.” It’s now rewriting their core algorithms by treating the system as a “white box” and discovering solutions that can outperform human experts in a few hours. This new approach, which we term AI-Driven Research for Systems (ADRS), can automate some of the most tedious parts of research.
Events
March 6, 2026
Sky Seminar: Stas Kelvich (Databricks) – Lakebase: Agent-Native OLTP
Over 80% of OLTP workloads on Databricks are now provisioned and managed by AI agents, giving rise to a new class of agentic database workloads. This emerging class of workloads presents new challenges and priorities for database system design. In this talk, we characterize these real-world agentic …
March 4, 2026
Dissertation Talk: Scaling Environments and Verifiers for Software Engineering Agents – Manish Shetty
Modern language models, trained primarily on static code corpora, are increasingly capable at writing code, yet struggle with real-world software engineering over long horizons. Software, however, is one of the few domains where AI systems can interact with reality cheaply: environments instantiate …
February 20, 2026
Sky Seminar: Mohsen Lesani (UCSC) – Generation of Verified Distributed Systems
Distributed systems are the backbone of modern computing. Yet, building distributed systems with reliability and security guarantees has proven to be complicated, and remains elusive. This complication is not only faced by experts that design and implement distributed systems but is also exposed to …
February 13, 2026
Sky Seminar: Melih Elibol & Stephen Jones (Nvidia) – From CUDA to Rust: Scaling GPU Performance with Tile-Based Programming
As GPU architectures boost performance with specialized hardware like Tensor Cores, tile-based programming has emerged as a vital strategy to simplify development by shifting the focus from scalar processing with individual threads to collective operations on high-level data “tiles.” This seminar is…
Publications
January 2026
UCCL-EP: Portable Expert-Parallel Communication.
January 2026
Supporting Our AI Overlords: Redesigning Data Systems to be Agent-First.
January 2026
Text2SQL is Not Enough: Unifying AI and Databases with TAG.
December 2025
RedunCut: Measurement-Driven Sampling and Accuracy Performance Modeling for Low-Cost Live Video Analytics.
December 2025
Let the Barbarians In: How AI Can Accelerate Systems Performance Research.
December 2025
TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times.
December 2025
FrontierCS: Evolving Challenges for Evolving Intelligence.
December 2025
SonicMoE: Accelerating MoE with IO and Tile-aware Optimizations.
December 2025
MiniScope: A Least Privilege Framework for Authorizing Tool Calling Agents.
December 2025
Radial Attention: O(n log n) Sparse Attention with Energy Decay for Long Video Generation.
December 2025
Measuring Agents in Production.
December 2025
Accelerating Large-Scale Reasoning Model Inference with Sparse Self-Speculative Decoding.
Recent Projects
Sky Computing Story
Berkeley’s computer science division has an ongoing tradition of 5-year collaborative research labs. Recent labs included the AMPLab (ended in 2016) and the RISELab. These labs have had significant impact in both academia and industry. Past labs publish their research at top conferences in systems, databases, and machine learning. On the industrial side, AMPLab and RISELab fostered several successful startups (Databricks, Opaque, Ponder, Anyscale, to name a few). We are excited to announce the Berkeley Sky Computing Lab where we will strike to make cloud computing a true commodity.
Context
The Sky Computing Lab represents the next chapter of data-intensive systems research at Berkeley. Recent years have seen the explosion of cloud computing. Applications are moving their data and computation to the cloud; on-premise services are dying. In doing so, companies have to make difficult choices between the myriad of cloud providers, each with different services or hardware. Lock-in, whether through artificial migration costs, legal constraints or engineering baggage is real. In the Sky Computing Lab, we will leverage distributed systems, programming languages, security, and machine learning to decouple the services that a company wants to implement from the choice of a specific cloud. Much like the Internet today, cloud computing should be an undifferentiated commodity. Applications should run seamlessly on any or multiple clouds.
Mission
Our mission in the Sky Computing Lab is to transform the cloud into an undifferentiated commodity and ease application burden. As in previous labs, we’re all in — working on everything from basic research to software development, all in the Berkeley tradition of open publication and open source software. Our founding team consists of experts in distributed systems, machine learning, security and programming languages. We’ll use this space to lay out our ideas and progress as we go.
Commitment to Diversity
Sky Computing is guided by Berkeley’s Principles of Community and is committed to providing a safe and caring research environment for every member of our community. We believe that a diverse student body, faculty, and staff are essential to the open exchange of ideas that Sky Computing Lab is founded on.
Our head is in the cloud. We are heading for the SKY.
Sponsors
