Sky Computing
Towards Utility Computing for the Cloud
News
February 4, 2025
NBC News: Ion Stoica on DeepSeek
January 29, 2025
How Chinese A.I. Start-Up DeepSeek Is Competing With Silicon Valley Giants
The company built a cheaper, competitive chatbot with fewer high-end computer chips than U.S. behemoths like Google and OpenAI, showing the limits of chip export control.
January 14, 2025
Researchers open source Sky-T1, a ‘reasoning’ AI model that can be trained for less than $450
So-called reasoning AI models are becoming easier — and cheaper — to develop.
December 12, 2024
The UC Berkeley Project That Is the AI Industry’s Obsession
Ranking AI is tricky, so two students developed a way to make the best bots battle
December 9, 2024
UC Berkeley announces Intel OneAPI Center of Excellence for AI
The center will serve as a hub for cutting-edge applied research in generative AI (GenAI), drawing on the collective knowledge and resources of Intel and the UC Berkeley research community, including the Sky Computing Lab, BAIR, and other affiliated labs.
Events
February 7, 2025
Sky Seminar: Ada Gavrilovska (Georgia Tech) – Computing in the Sky: Enabling LEO Compute Clouds with Krios
The rapid expansion of Low Earth Orbit (LEO) satellites in recent years has led to a surge in diverse use cases, creating a vision for a new “LEO compute cloud.” In this emerging landscape, satellite providers could offer their infrastructure as a platform for hosting various tenants. However, t…
December 6, 2024
Dissertation Talk: Towards Robust and Scalable Evaluation of Large Language Models – Wei-Lin Chiang
The rapid advancement of Large Language Models (LLMs), driven by scaling laws and substantial investments, has unlocked remarkable capabilities. Yet, effectively evaluating these generalist AI systems presents significant challenges, including their broad functionality, concerns over benchmark conta…
December 6, 2024
Dissertation Talk: An Extensible Architecture for Distributed Heterogeneous Processing – Frank Sifei Luan
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November 22, 2024
Sky Seminar: Anyscale – AI Infrastructure at Anyscale
Anyscale was founded in 2019 to commercialize Ray and to simplify distributed machine learning for organizations across the world. In this talk, we’ll cover the story behind Anyscale and deep dive into Ray Data and Ray Compiled Graphs, two key frameworks we’ve developed to solve emerging AI infr…
Publications
December 2024
Revisiting Cache Freshness for Emerging Real-Time Applications.
December 2024
FogROS2-FT: Fault Tolerant Cloud Robotics.
December 2024
A Statistical Framework for Ranking LLM-Based Chatbots.
December 2024
Syzygy: Dual Code-Test C to (safe) Rust Translation using LLMs and Dynamic Analysis.
December 2024
HashAttention: Semantic Sparsity for Faster Inference.
December 2024
Specifications: The missing link to making the development of LLM systems an engineering discipline.
December 2024
VibeCheck: Discover and Quantify Qualitative Differences in Large Language Models.
December 2024
VisionArena: 230K Real World User-VLM Conversations with Preference Labels.
December 2024
GameArena: Evaluating LLM Reasoning through Live Computer Games.
December 2024
FogROS2-FT: Fault Tolerant Cloud Robotics.
November 2024
BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching.
November 2024
CARFF: Conditional Auto-Encoded Radiance Field for 3D Scene Forecasting.

Ion Stoica – Featured Projects
SkyPilot
To comply with the increasing number of government regulations about data placement and processing, and to protect themselves against major cloud outages, many users want the ability to easily migrate their workloads between clouds. We propose doing so not by imposing uniform and comprehensive standards, but by creating a fine-grained two-sided market via intercloud brokers. SkyPilot is an intercloud broker that treats the cloud ecosystem not just as a collection of individual and largely incompatible clouds but as a more integrated Sky of Computing. SkyPilot enables users to run Machine Learning and Data Science batch jobs seamlessly on any cloud, reduce cloud costs substantially, tap into best-in-class hardware on different clouds, and enjoy higher resource availability.
Skyplane
Cloud applications are increasingly distributing data across multiple regions and cloud providers in response to privacy regulations, to take advantage of specialized hardware, and to prevent vendor lock-in. Unfortunately, wide-area bulk data transfers are often slow and expensive due to egress fees. This work aims to reduce both the latency and the cost of inter-cloud bulk transfer by using a variety of techniques, including overlay routing, multiple instances, multiple TCP connections, and taking advantage of different network tiers. Together, these techniques allow Skyplane to significantly improve object transfer throughput and lower the costs.

Natacha Crooks – Featured Project
Basil
Basil explores the design of SQL databases with high integrity and decentralized trust. How can traditional functionality like ACID transactions and SQL queries be efficiently implemented when trust is decentralized among n distinct parties, of which a subject can misbehave.

Joseph Gonzalez – Featured Project
Gorilla
The Gorilla project is designed to connect large language models (LLMs) with a wide range of services and applications exposed through APIs. Imagine if ChatGPT could interact with thousands of services, ranging from Instagram and Doordash to tools like Google Calendar and Stripe, to help you accomplish tasks. This may be how we interact with computers and even the web in the future. Gorilla is an LLM that we train using a concept we call retriever-aware training (RAT), which picks the right API to perform a task that a user can specify in natural language. Gorilla also introduces an Abstract Syntax Tree (AST) based sub-tree matching algorithm, which for the first time allows us to measure hallucination of LLMs!

Raluca Ada Popa – Featured Project
MC2
MC2 is a platform for running secure analytics and machine learning on encrypted data. With MC2, organizations can safely upload their confidential data to the cloud in encrypted form and securely compute analytics and machine learning without exposing the unencrypted data to the cloud provider. MC2 also enables secure collaboration among multiple organizations, where the data owners can use the platform to jointly analyze their collective data without revealing their individual data to each other.

Koushik Sen – Featured Project
FuzzFactory
FuzzFactory is domain-specific fuzz testing tool that generalizes coverage-guided fuzzing to domain-specific testing goals. FuzzFactory allows users to guide the fuzzer’s search process without having to modify the core search algorithm.
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.
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