Jax
PulseAugur coverage of Jax — every cluster mentioning Jax across labs, papers, and developer communities, ranked by signal.
- used by reinforcement learning 90%
- used by Fortran 90%
- used by graphics processing unit 70%
- used by NumPy 70%
- developed by reinforcement learning 70%
- used by NVIDIA H100 70%
- used by central processing unit 70%
- used by Orbax Distributed Checkpointing With Jax 70%
- used by robotics 70%
- instance of robotics 70%
- developed by Orbax Distributed Checkpointing With Jax 70%
- developed Fortran 70%
15 day(s) with sentiment data
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Google's TPU v6e-1 offers memory upgrade but at a higher cost
A technical analysis reveals that Google's new Cloud TPU v6e-1 (Trillium) offers a performance increase over the v5e-1, but its higher cost makes it less cost-effective for certain workloads. The v6e-1 provides double t…
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Google details DiffusionGemma text-to-image model in technical report
Google has released a technical report detailing DiffusionGemma, a new text-to-image model. The report outlines the model's architecture, which incorporates elements like U-Net and LoRA+, and discusses its performance u…
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New JAX framework simplifies tensor network kernel machine development
Researchers have developed "tnkm," an open-source Python library built with JAX for constructing and training Tensor Network Kernel Machines (TNKM). This framework aims to create nonlinear models that are both expressiv…
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New SoRoMoX framework enables faster, differentiable soft robot modeling
Researchers have developed SoRoMoX, a new Python/JAX framework designed for soft robot modeling. This framework is notable for its differentiability and parallel processing capabilities, enabling faster and more efficie…
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Self-host AI agent backend on single Google Cloud TPU v5e chip
A technical guide details how to self-host a lightweight AI agent backend on a single Google Cloud TPU v5e chip. The setup utilizes the Gemma 4-E2B model with the vLLM inference engine, achieving a throughput of 1,496 o…
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Fortran transpiler FGPT bridges legacy code to JAX and NumPy
Researchers have developed FGPT, a novel transpiler designed to convert legacy Fortran code into modern Python frameworks like JAX and NumPy. This tool aims to bridge the expertise gap for scientists who are unfamiliar …
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TimesFM 2.5 enhances time-series forecasting with new features
TimesFM 2.5, a time-series forecasting model, has been updated to include advanced features for end-to-end workflow development. The new version supports backtesting, covariate integration, anomaly detection, and scalab…
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OpenAI releases Codex Security CLI; Open Dreamer launches; Grok 4.5 gets India pricing
OpenAI has released Codex Security CLI, a local AI agent designed to automatically detect and fix vulnerabilities within code repositories. Separately, independent researchers have launched Open Dreamer, an open-source …
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PyTorch aims to become a reference language for deep learning
PyTorch is being positioned as a reference language for deep learning, moving beyond its role as a framework. This shift aims to provide a more unified and expressive programming experience, integrating features that en…
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Open Dreamer: JAX/Flax reproduction of Dreamer 4 world model pipeline released
Researchers from Reactor have released Open Dreamer, an open-source implementation of the Dreamer 4 world model pipeline. This project, built with JAX and Flax NNX, includes a causal video tokenizer, an action-condition…
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JAXBench launches to optimize AI kernels on Google TPUs
A new benchmark suite called JAXBench has been developed to specifically address the optimization of AI kernel performance on Google Cloud TPUs. This suite includes 50 JAX workloads derived from prominent AI models like…
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Google releases Gemma 2 open models, challenging larger proprietary systems
Google has launched Gemma 2, a new generation of its open-source AI models, featuring redesigned architectures and improved efficiency. The 27-billion parameter version offers performance comparable to models twice its …
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Google unveils Tunix to speed up agentic RL on TPUs
Google has introduced Tunix, a new JAX-native library designed to accelerate agentic reinforcement learning. Tunix aims to reduce idle time on Tensor Processing Units (TPUs) by implementing asynchronous rollouts and dec…
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New PIV method fuses algorithms for improved fluid dynamics control
Researchers have developed a novel method to refine Particle Image Velocimetry (PIV) measurements by fusing estimates from multiple heterogeneous algorithms. This consensus-based approach, utilizing the Alternating Dire…
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New paper details IKPLS speedups up to 6x on GPU
A new paper details significant speedups for Improved Kernel Partial Least Squares (IKPLS) algorithms, which are known for their efficiency in PLS calibration. The research introduces optimizations for computing X rotat…
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New 26M-parameter model handles tool-calling locally
A new model named Cactus Needle, with 26 million parameters, has been developed to handle tool-calling functions locally without relying on cloud-based frontier models. This small model, approximately 16.2MB when compre…
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Google optimizes Qwen 3.5-397B MoE on Ironwood TPUs for 4.7x speedup
Google has optimized the Qwen 3.5-397B Mixture-of-Experts (MoE) model to run on its Ironwood Tensor Processing Units (TPUs). This optimization, achieved using JAX and Pallas, resulted in a 4.7x speedup for prefill workl…
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NetForge RL: New Cyber Defense Simulation Environment Released
Researchers have introduced NetForge RL, a new multi-agent simulation environment designed for training reinforcement learning agents in cyber defense scenarios. This environment features procedurally generated networks…
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Fortran code gains automatic differentiation via LFortran and Enzyme
Researchers have developed a method to enable automatic differentiation for legacy Fortran code, allowing it to be integrated into modern machine learning frameworks like JAX and PyTorch. This approach uses LFortran to …
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Ph.D. thesis explores differentiable ray tracing for radio propagation modeling
A Ph.D. thesis has been published on Differentiable Ray Tracing for Radio Propagation Modeling, aiming to serve as an accessible textbook. The research integrates automatic differentiation with ray tracing to compute ex…