Theme: "Building an AI Ecosystem for a Brand New Generation of Computing" Section I:  Leadership Lightning Insights Series Section II: Keynote Address Section III: Executive Panel Discussions

Foundation models including LLMs and multi-modal models released by OpenAI (GPT), Anthropic (Claude), Google (Gemini), Meta (Llama), and others have shown very impressive capabilities across a range of tasks. Some key drivers of this performance — such as investments in GPUs/compute, model size, and pre-training data — are relatively well understood. This presentation will focus […]

This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT Despite all the interest and hype both from within and outside our community, robotics is a relatively new and highly specialized field. We embody substantial diversity in research direction and style, the focus and flavor of industrial […]

This talk overviews research at Caltech on designing hybrid or neurosymbolic AI systems that blend learning with symbolic structure, in order to achieve both the flexibility of the former and the formal interpretability and generalization power of the latter.  By having systems that are formally interpretable, one can employ a wide range of formal analysis […]

As Moore's Law slows down, packet switch capabilities are falling behind datacenter demands. Recent hardware advances have enabled the new switching technology of nanosecond-scale rapid circuit switches. Combined with novel network designs, these have the potential to fully replace packet switches. This talk presents the Oblivious Reconfigurable Network (ORN) design paradigm which is ideally suited […]

AI-powered applications are exciting because of their potential to support people in unprecedented ways but they are also particularly challenging to design right: How does one design a useful AI-enabled product if the underlying AI is occasionally wrong? How can we make these applications feel predictable even though the AI technology is complex and can […]

Language models (LMs) have become ubiquitous in both AI research and commercial product offerings. As their commercial importance has surged, the most powerful models have become closed off, gated behind proprietary interfaces, with important details of their training data, architectures, and development undisclosed. Given the significance of these details in scientifically studying these models, including […]

We present an information-theoretic approach for integration of multi-resolution data into multiscale simulations.  Fine-scale information can comprise observational data and/or simulation results related to both system states and system parameters. It is aggregated into its coarse-scale representation by setting a probabilistic equivalence between the two scales, with parameters that are determined via minimization of observables […]

System software like operating systems and hypervisors forms the critical backbone of our computing infrastructure. However, due to their size and complexity, these systems often contain vulnerabilities that can compromise security. Formal verification offers a solution by mathematically proving software correctness, but its adoption is hindered by the substantial effort required to create these proofs. […]