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News
Google AI Releases TimesFM-3: A 330M Parameter Zero-Shot Foundation Model For Multivariate Time Series Forecasting
1+ week, 5+ day ago (332+ words) MarkTechPost Google Research has released TimesFM-3, a 330 million parameter time series foundation model that forecasts multiple related series in a single forward pass. Every TimesFM checkpoint through 2.5 was univariate: one series, its own history, nothing else. TimesFM-3 is pretrained natively…...
Tencent Open-Sources AngelSpec: A Unified Training Framework for MTP and Block-Parallel Speculative Decoding on Hy3 Models
1+ mon, 2+ week ago (445+ words) Most speculative-decoding work searches for one drafter that scores well on an averaged benchmark mixture. Real serving traffic does not look like that mixture. AngelSpec treats workload heterogeneity as a first-class design constraint, and specializes structure, training data, and verification…...
Deploying a 1-Bit Bonsai-27B Model with PrismML llama.cpp and OpenAI-Compatible Local Inference Workflows
1+ mon, 2+ week ago (245+ words) We clone the PrismML fork of llama.cpp, which provides the specialized kernels required for the model’s Q1_0_g128 quantization format. We configure a CUDA-enabled release build with CMake and compile the command-line, server, and benchmarking executables. We also reuse previously generated…...
Meet Gigatoken: A Rust BPE Tokenizer that Encodes Text at 24.53 GB/s, up to 989x Faster than HuggingFace Tokenizers
1+ mon, 3+ week ago (426+ words) Tokenization is the one part of the language modeling stack that almost nobody profiles. Gigatoken, released by Marcel Rød (a PhD student from Stanford) under an MIT license, argues that this was a mistake. The library encodes text at gigabytes…...
Fine-Tuning Qwen3 with LoRA Using NVIDIA NeMo AutoModel: A Complete Single-GPU Google Colab Workflow Tutorial
1+ mon, 3+ week ago (288+ words) We import the core Python libraries required for file handling, process execution, path management, and formatted output. We define the repository, working, and checkpoint directories used throughout the workflow. We also create a reusable shell-command function that streams command output…...
NVIDIA AI Releases Nemotron 3 Embed: An Open Embedding Collection Whose 8B Checkpoint Ranks #1 on RTEB
1+ mon, 3+ week ago (539+ words) Embedding models decide which passages an agent ever sees. NVIDIA released Nemotron 3 Embed model to work on that layer. It targets production-scale RAG, agentic retrieval, code retrieval, and agent memory. All three are transformer encoders trained with bidirectional attention masking....
Moonshot AI Releases Kimi K3: A 2.8 Trillion Parameter Open MoE Model With Kimi Delta Attention and 1M Context
1+ mon, 3+ week ago (492+ words) Moonshot AI just released Kimi K3. It is a 2.8-trillion-parameter model with native vision and a 1-million-token context window. Moonshot calls it the world’s first open 3T-class model. Kimi K3 is a sparse Mixture-of-Experts (MoE) model built on two architectural updates. Those…...
Thinking Machines Lab Releases Inkling: A 975B-Parameter Open-Weights Multimodal MoE With 41B Active Parameters And Controllable Thinking Effort
1+ mon, 4+ week ago (523+ words) Thinking Machines Lab just released Inkling, their first model trained from scratch, weights are open, fine-tunable on Tinker. The lab pitches it as a base for customization. Inkling is a Mixture-of-Experts transformer with 975B total parameters and 41B active. It supports a…...
Google Releases LiteRT.js: A JavaScript Binding of LiteRT That Runs.tflite Models in Browsers via WebGPU
1+ mon, 4+ week ago (487+ words) Google's on-device inference runtime now targets the web. The same.tflite artifact used on Android and iOS runs locally through WebAssembly, WebGPU, and experimental WebNN. Google released LiteRT.js, a JavaScript binding of LiteRT. LiteRT is Google’s on-device inference library,…...
DeepSeek Releases DSpark, a Speculative Decoding Framework That Accelerates DeepSeek-V4 Per-User Generation 60–85% Over MTP-1
2+ mon, 2+ week ago (964+ words) DeepSeek released DSpark, a speculative decoding framework, with open-source checkpoints and training code. It is a serving optimization, not a new model. The checkpoints DeepSeek-V4-Pro-DSpark and DeepSeek-V4-Flash-DSpark reuse the existing V4 weights, with a draft module attached. The DeepSeek…...