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PrismML has released Ternary Bonsai 2 27B, a ternary-weight version of Qwen3.8 27B. The language model occupies 5.93 GB, against 53.80 GB in FP16. PrismML reports that it keeps 98.2% of the parent model’s average across 20 benchmarks. The model accepts text and images and supports a 262K-token context. PrismML demos it driving Cline coding […]
Platform teams running AI on Kubernetes rarely run one thing. They run a queueing system, a distributed runtime, GPU node health checks, dashboards, and a layer of submission scripts holding all of it together. The Azure Kubernetes Service engineering team open-sourced TauGrid, which collapses that assembly job into a single Helm install. Is it deployable?
Microsoft Open-Sources TauGrid: A Kubernetes-Native Stack for GPU AI Workloads Read More »
In this tutorial, we work through the cuDNN Frontend‘s graph API from below the framework: we describe a computation as a graph of operations, let cuDNN pick an engine to run it, and then take control of that choice ourselves. Every kernel we build here is expressed the same way: we declare tensors by their
Inside NVIDIA’s cuDNN Graph API: Fusion, Autotuning, and Plan Reuse with cuDNN Frontend Read More »
Backpropagation is a global algorithm: a forward pass, then a backward pass, then a weight update, each locked behind the previous one. Brains have no known mechanism for that kind of network-wide phase locking, which is why local-learning alternatives such as predictive coding (PC) keep drawing research interest. Sakana AI researchers propose Augmented Lagrangian Predictive
Robot developers do not have one compute problem. They have 3. A policy is trained on GB200 or H100 clusters, tested in Isaac Sim on RTX GPUs, then validated on a Jetson mounted inside a real robot. Each tier has its own cluster, its own scheduler, and its own glue scripts. NVIDIA OSMO is NVIDIA’s
An agent, in its simplest form, is an LLM calling tools in a loop. That loop works for short jobs. Give it a task that runs for an hour and 200 tool calls, and it breaks in 2 predictable ways. The AWS Samples design guide for autonomous cloud coding agents names them directly: shallow agents
In this tutorial, we implement NVIDIA cuML as a GPU-accelerated machine learning framework and build a practical workflow that demonstrates how RAPIDS can accelerate familiar data science and machine learning tasks. We begin by configuring the GPU environment and examining cuml.accel, which lets us accelerate existing scikit-learn workloads with minimal code changes, before moving to
The Fly Language Model (FLM) is a public chatbot that couples the complete retained MaleCNS v1.0 fruit fly connectome to a frozen LiquidAI LFM2.5-1.2B-Instruct backbone. The developer who created the FLM calls it the world’s first Fly Language Model, built on an architecture called GPF (Generative Pre-trained Fly). It does not use the GPF label,
Anthropic has published a new plugin evals workflow for Claude Code. The claude plugin eval command runs a plugin against realistic prompts, grades what Claude produced, and compares the result with a run where the plugin is not loaded. It answers 3 questions plugin developers could not previously measure: does the skill trigger, does it
Sakana AI has released Fugu Max and Fugu Ultra v2, 2 new models in its Sakana Fugu family. Fugu is not a single foundation model. It is a learned orchestrator that routes work across a pool of other models behind 1 API. The new release tunes that architecture for 2 missions. Fugu Max targets the
