OpenAI reveals its first AI processor: Jalapeño
OpenAI has just revealed a new 'intelligence processor' chip for AI servers made in partnership with Broadcom. The chip, called Jalapeño, is designed to power current and future large language models,
Knowledge catalogue
OpenAI has just revealed a new 'intelligence processor' chip for AI servers made in partnership with Broadcom. The chip, called Jalapeño, is designed to power current and future large language models,
arXiv:2606.24796v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has garnered significant attention in Simultaneous Localization and Mapping (SLAM) due to its advances in capturing fine-gr
arXiv:2603.08287v2 Announce Type: replace-cross Abstract: We analyze the Bayesian regret of the Gaussian process posterior sampling reinforcement learning (GP-PSRL) algorithm. Posterior sampling is a
arXiv:2410.14843v4 Announce Type: replace-cross Abstract: Vanilla variational inference finds an optimal approximation to the Bayesian posterior distribution, but even the exact Bayesian posterior is
arXiv:2606.17102v2 Announce Type: replace-cross Abstract: Quantum computing promises transformative advances across science and industry, yet the physical hardware that enables these computations rema
arXiv:2606.24496v1 Announce Type: cross Abstract: The use of agentic systems to perform offensive security operations has moved from a theoretical possibility to a commoditized capability. However, wh
arXiv:2508.17728v2 Announce Type: replace Abstract: Cervical cancer remains a significant global health concern and a leading cause of cancer-related deaths among women. Early detection through Pap sm
arXiv:2606.23743v1 Announce Type: cross Abstract: Modern video diffusion models achieve higher generation quality through scaling, but this also increases inference cost. Although many acceleration me
arXiv:2606.17165v3 Announce Type: replace-cross Abstract: Organizations and researchers show increasing interest in using large language models (LLMs) in place of human participants in A/B tests, in t
arXiv:2502.01015v5 Announce Type: replace Abstract: Task arithmetic, representing downstream tasks through linear operations on task vectors, has emerged as a simple yet powerful paradigm for transfer
Gary Marcus argues that generative AI, while significant, represents only a narrow subset of the broader computing field and should not overshadow the diverse and impactful work occurring across other
arXiv:2606.24279v1 Announce Type: new Abstract: In Description Logics (DLs), reasoning under Rational Closure (RC) is a well-known and widely accepted non-monotonic formalism to handle defeasible know
arXiv:2606.24282v1 Announce Type: new Abstract: High frame-rate RGB-D videos are crucial for a variety of downstream tasks, including motion analysis, dynamic scene understanding, and 3D reconstructio
arXiv:2606.24462v1 Announce Type: new Abstract: This paper presents a scalable framework for multi-robot task allocation in complex environments where estimating task execution costs is computationall
very proud to host this session opening night! if you work in tech but have never heard of Touchy Feely, you are exactly the kind of person that needs to see this. You have no idea the shocking number
Written by: Chester Sng, Pete Boonyakarn, Logeswaran Nadarajan Introduction In early 2026, Mandiant identified a threat actor targeting SD-WAN infrastructure at a service provider. After gaining initi
arXiv:2601.16192v2 Announce Type: replace Abstract: Lifting perspective images and videos to 360{eg} panoramas enables immersive 3D world generation. Existing approaches often rely on explicit geometr
arXiv:2511.15098v2 Announce Type: replace Abstract: Discrete diffusion-based multimodal large language models (dMLLMs) have emerged as a promising alternative to autoregressive MLLMs thanks to their a
arXiv:2606.20955v1 Announce Type: new Abstract: Dynamic average estimation is a critical problem in multi-agent systems, enabling agents to collaboratively estimate time-varying signals using only loc
arXiv:2603.21911v2 Announce Type: replace Abstract: Synthetic hyperspectral image (HSI) generation is essential for large-scale simulation, algorithm development, and mission design, yet traditional r
arXiv:2606.21350v1 Announce Type: new Abstract: This paper introduces an interpretation of Temporal Behavior Trees (TBTs) as Reward-Petri-Nets (RPNs) for reinforcement learning (RL). Designing reward
arXiv:2606.21528v1 Announce Type: cross Abstract: We study first-order methods for solving monotone variational inequalities arising in min-max optimization. Classical approaches such as the extragrad
arXiv:2606.22112v1 Announce Type: new Abstract: The performance of advanced materials for extreme environments is underpinned by their microstructure, including the size and distribution of reinforcin
arXiv:2606.22091v1 Announce Type: new Abstract: Per-scene 3D Gaussian Splatting (3DGS) enables high-fidelity rendering, but practical robotic and AR scene capture pipelines often depend on external ge
arXiv:2606.23359v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide an effective way to solve partial differential equations (PDEs) by embedding physical principles into t
arXiv:2606.20738v1 Announce Type: new Abstract: This article presents a complementary approach for integrating multimodal medical data in cancer classification, based on state space models represented
arXiv:2606.21209v1 Announce Type: cross Abstract: We present an iterative algorithm to compute an arc-length parameterized spline interpolating a set of points. This differs from other methods where t
arXiv:2606.21701v1 Announce Type: cross Abstract: Long-term records of the Martian atmosphere based on general circulation models and reanalysis of atmospheric state variables are important to underst
arXiv:2606.23251v1 Announce Type: cross Abstract: High-fidelity simulations of free-surface flows using Lagrangian methods such as the Particle Finite Element Method (PFEM) are computationally demandi
arXiv:2504.03615v2 Announce Type: replace Abstract: Rapid advances in generative AI have enabled the creation of highly realistic synthetic images, which, while beneficial in many domains, also pose s
arXiv:2606.20668v1 Announce Type: cross Abstract: LLM supervision systems, namely input/output moderation filters and jailbreak detectors, are the primary safeguard against misuse in deployed AI appli
arXiv:2606.22138v1 Announce Type: cross Abstract: We present BioMatrix, the first multimodal foundation model that natively integrates sequences, structures, and natural language for both molecules an
This is a live broadcast or masterclass hosted by Replit on the X platform (formerly Twitter) that provides foundational guidance for beginners learning to build projects using the Replit IDE and deve
arXiv:2505.01652v2 Announce Type: replace Abstract: Fair machine learning seeks to identify and mitigate biases in predictions against unfavorable populations characterized by demographic attributes,
The growing use of AI agents throughout the enterprise is forcing a thorough reevaluation of the data layer. This shift is driven by the need for millisecond responses that enable agents to make decis
arXiv:2606.22837v1 Announce Type: new Abstract: Sensors are critical components of modern intelligent devices. The proliferation of the Internet of Things (IoT) and wearable mobile devices has enabled
arXiv:2606.23517v1 Announce Type: new Abstract: Higher-order structures are powerful relational modeling tools, yet existing spectral operators decompose the topology into separate ranks, leaving prac
arXiv:2606.21562v1 Announce Type: new Abstract: Transformers are AI's workhorse with strong performance in modeling sequential data, but their computational cost becomes prohibitive when processing lo
arXiv:2606.23521v1 Announce Type: cross Abstract: Long-running LLM agents keep valuable state resident on GPUs: KV caches, request schedulers, communication state, and sometimes online adapters. Losin
arXiv:2507.15741v2 Announce Type: replace-cross Abstract: This paper introduces a framework for uncertainty quantification in regression models defined on metric spaces. Using a proposed notion of hom
arXiv:2606.22757v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) is a problem that requires computing collision-free paths for a set of agents from their start locations to designated g
arXiv:2606.22439v1 Announce Type: new Abstract: Commercial greenhouse cucumber production is graded by fruit length, which drives harvest scheduling, labour allocation, and logistics. Manual measureme
arXiv:2010.14694v4 Announce Type: replace-cross Abstract: This paper integrates deep neural networks (DNNs) into structural models to increase flexibility and capture rich heterogeneity while preservi
This Vercel changelog entry describes integration between Claude Design and Vercel that enables direct deployment of designs to the Vercel platform. The feature likely streamlines the workflow for dev
arXiv:2510.10854v3 Announce Type: replace Abstract: Diffusion models have demonstrated remarkable performance in generating high-dimensional samples across domains such as vision, language, and the sc
arXiv:2606.20663v1 Announce Type: cross Abstract: Large Language Models have the potential to expand and improve the access to clinical information by enabling new ways of interacting with medical kno
arXiv:2606.21427v1 Announce Type: new Abstract: Tensor factorization (TF) has been widely adopted for high-dimensional sparse data completion tasks. Despite significant progress, neural TF methods oft
arXiv:2606.21153v1 Announce Type: cross Abstract: Decentralized bilevel optimization (DBO) provides a powerful framework for multi-agent systems to solve local bilevel tasks in a decentralized fashion
arXiv:2606.22167v1 Announce Type: new Abstract: Graph Neural Networks are great for link prediction in various network-like structures; however, the question of their speed/quality tradeoff has been b
arXiv:2602.03729v2 Announce Type: replace Abstract: Sampling from unnormalized probability densities is a central challenge in computational science. Boltzmann generators are generative models that en
arXiv:2606.20592v1 Announce Type: cross Abstract: Embodied artificial intelligence (AI) is emerging as a key driver of the sixth-generation (6G) wireless networks by enabling agents that continuously
arXiv:2508.14600v4 Announce Type: replace Abstract: Non-Intrusive Load Monitoring (NILM) offers a cost-effective method to obtain fine-grained appliance-level energy consumption in smart homes and bui
arXiv:2606.21378v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have demonstrated significant potential in supporting engineering design tasks, including computer-aided
Harrison Chase suggests that evaluations (evals) are becoming as critical to AI/LLM development as Product Requirements Documents (PRDs) traditionally were, implying a shift in how teams validate and
arXiv:2606.20177v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in various Remote Sensing (RS) tasks. However, their ability to compre
This article explores the Cross-Origin Storage API and its implementation within Transformers.js, a JavaScript library for machine learning models. It likely discusses how this API enables secure cros
arXiv:2606.23370v1 Announce Type: cross Abstract: Device-side Large Language Models (LLMs) have grown explosively, offering stronger privacy and higher availability than their cloud-side counterparts.
Genesis Workbench is a collaborative framework developed by Databricks and NVIDIA designed to accelerate AI adoption in the life sciences industry by providing integrated tools and best practices. The
arXiv:2512.20399v3 Announce Type: replace Abstract: We present GeoTransolver, a multiscale geometry-aware physics attention transformer for Computer Aided Engineering (CAE). GeoTransolver extends the
arXiv:2606.22922v1 Announce Type: new Abstract: Applying machine learning techniques to solving long-standing mathematical conjectures can be particularly challenging due to their extreme reward spars