📰 NVIDIA - Synthetic Data Generation for Financial AI Research with NVIDIA NeMo
Fine-tuning LLMs for financial natural language processing (NLP) is constrained by limited, imbalanced data. Real-world financial news overrepresents earnings…
https://developer.nvidia.com/blog/synthetic-data-generation-for-financial-ai-research-with-nvidia-nemo/
Fine-tuning LLMs for financial natural language processing (NLP) is constrained by limited, imbalanced data. Real-world financial news overrepresents earnings…
https://developer.nvidia.com/blog/synthetic-data-generation-for-financial-ai-research-with-nvidia-nemo/
NVIDIA Technical Blog
Synthetic Data Generation for Financial AI Research with NVIDIA NeMo
Fine-tuning LLMs for financial natural language processing (NLP) is constrained by limited, imbalanced data. Real-world financial news overrepresents earnings and stock movements…
🆕 [HF Models] inclusionAI - SingGuard-0.8b-GGUF
https://huggingface.co/inclusionAI/SingGuard-0.8b-GGUF
🔓 [HF Models] inclusionAI - SingGuard-2b
https://huggingface.co/inclusionAI/SingGuard-2b
🔓 [HF Models] inclusionAI - SingGuard-8b
https://huggingface.co/inclusionAI/SingGuard-8b
🔓 [HF Models] inclusionAI - SingGuard-4b
https://huggingface.co/inclusionAI/SingGuard-4b
🆕 [HF Models] inclusionAI - SingGuard-8b-GGUF
https://huggingface.co/inclusionAI/SingGuard-8b-GGUF
🆕 [HF Models] inclusionAI - SingGuard-4b-GGUF
https://huggingface.co/inclusionAI/SingGuard-4b-GGUF
🆕 [HF Models] inclusionAI - SingGuard-2b-GGUF
https://huggingface.co/inclusionAI/SingGuard-2b-GGUF
🆕 [HF Models] inclusionAI - SingGuard-0.8b
https://huggingface.co/inclusionAI/SingGuard-0.8b
https://huggingface.co/inclusionAI/SingGuard-0.8b-GGUF
🔓 [HF Models] inclusionAI - SingGuard-2b
https://huggingface.co/inclusionAI/SingGuard-2b
🔓 [HF Models] inclusionAI - SingGuard-8b
https://huggingface.co/inclusionAI/SingGuard-8b
🔓 [HF Models] inclusionAI - SingGuard-4b
https://huggingface.co/inclusionAI/SingGuard-4b
🆕 [HF Models] inclusionAI - SingGuard-8b-GGUF
https://huggingface.co/inclusionAI/SingGuard-8b-GGUF
🆕 [HF Models] inclusionAI - SingGuard-4b-GGUF
https://huggingface.co/inclusionAI/SingGuard-4b-GGUF
🆕 [HF Models] inclusionAI - SingGuard-2b-GGUF
https://huggingface.co/inclusionAI/SingGuard-2b-GGUF
🆕 [HF Models] inclusionAI - SingGuard-0.8b
https://huggingface.co/inclusionAI/SingGuard-0.8b
huggingface.co
inclusionAI/SingGuard-0.8b-GGUF · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
📰 HuggingFace - Profiling in PyTorch (Part 3): Attention is all you profile
https://huggingface.co/blog/torch-attention-profile
https://huggingface.co/blog/torch-attention-profile
huggingface.co
Profiling in PyTorch (Part 3): Attention is all you profile
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
📰 OpenAI - How Deutsche Telekom is rewiring telecommunications with AI
https://openai.com/index/deutsche-telekom
https://openai.com/index/deutsche-telekom
OpenAI
How Deutsche Telekom is rewiring telecommunications with AI
How Deutsche Telekom is becoming an AI-native telco with OpenAI-transforming customer service, employee workflows, network operations, and the future of voice.
📰 PyTorch - Towards Free Normalization: Fusing Normalization into GEMM and Attention Kernels
Code available at: https://github.com/facebookresearch/ads_model_kernel_library/tree/main/multi_cta_norm_fusion and https://github.com/facebookresearch/ads_model_kernel_library/tree/main/gdpa_megakernel TL;DR In this blog post, we present various novel kernel fusion techniques for common normalization ops like LayerNorm and RMSNorm, which provide significant speedup...
https://pytorch.org/blog/towards-free-normalization-fusing-normalization-into-gemm-and-attention-kernels/
Code available at: https://github.com/facebookresearch/ads_model_kernel_library/tree/main/multi_cta_norm_fusion and https://github.com/facebookresearch/ads_model_kernel_library/tree/main/gdpa_megakernel TL;DR In this blog post, we present various novel kernel fusion techniques for common normalization ops like LayerNorm and RMSNorm, which provide significant speedup...
https://pytorch.org/blog/towards-free-normalization-fusing-normalization-into-gemm-and-attention-kernels/
GitHub
ads_model_kernel_library/multi_cta_norm_fusion at main · facebookresearch/ads_model_kernel_library
High-performance GPU kernels for Ads and Recsys model training, independently implemented and optimized for real-world workloads and model-specific input characteristics. - facebookresearch/ads_mod...
❤1
📰 Google AI Blog - LiteRT.js, Google's high performance Web AI Inference
We're excited to introduce LiteRT.js, the newest member of the LiteRT family! LiteRT.js is our powerful solution for running machine learning models directly in the browser, extending Google's cross-platform edge AI runtime to the web. Built for JavaScript developers, LiteRT.js delivers state-of-the-art ML model inference performance on WebGPU and upcoming WebNN, with a fallback to WebAssembly for CPU. This post provides a quick tour of LiteRT.js and gives web developers everything they need to get started.
https://developers.googleblog.com/en/litertjs-googles-high-performance-web-ai-inference/
We're excited to introduce LiteRT.js, the newest member of the LiteRT family! LiteRT.js is our powerful solution for running machine learning models directly in the browser, extending Google's cross-platform edge AI runtime to the web. Built for JavaScript developers, LiteRT.js delivers state-of-the-art ML model inference performance on WebGPU and upcoming WebNN, with a fallback to WebAssembly for CPU. This post provides a quick tour of LiteRT.js and gives web developers everything they need to get started.
https://developers.googleblog.com/en/litertjs-googles-high-performance-web-ai-inference/
Googleblog
Google for Developers Blog - News about Web, Mobile, AI and Cloud
Meet LiteRT.js: Google’s edge AI runtime for the web. Run ML models directly in the browser with high-performance WebGPU, WebNN, and WebAssembly.
📰 LMSys - Bringing DeepSeek-V4 Flash RL Training to AMD Instinct MI355X GPUs with Miles
https://lmsys.org/blog/2026-07-10-rocm-miles-dsv4
https://lmsys.org/blog/2026-07-10-rocm-miles-dsv4
www.lmsys.org
Bringing DeepSeek-V4 Flash RL Training to AMD Instinct MI355X GPUs with Miles
DeepSeek-V4 RL is now supported in Miles on AMD Instinct™ MI355X GPUs with ROCm™! RL requires SGLang rollout and Megatron training to implement the same policy closely enough that token probabilities ...
📰 Claude Blog - Working at the frontier: How Cognition trusts Claude Fable 5 to work through the night
https://claude.com/blog/working-at-the-frontier-how-cognition-trusts-claude-fable-5-to-work-through-the-night
https://claude.com/blog/working-at-the-frontier-how-cognition-trusts-claude-fable-5-to-work-through-the-night
Claude
Working at the frontier: How Cognition trusts Claude Fable 5 to work through the night | Claude by Anthropic
Cognition tested Claude Fable 5 in Devin, its AI software engineer. It's the first model its team trusts to run unattended for eight hours and deliver production-ready code.
📰 NVIDIA - Reducing High-Bandwidth Memory Bottlenecks in JAX-Based LLM Training with Host Offloading
Large language model (LLM) training workloads increasingly run into GPU memory limits before compute is fully used. Model weights, gradients, optimizer states…
https://developer.nvidia.com/blog/reducing-high-bandwidth-memory-bottlenecks-in-jax-based-llm-training-with-host-offloading/
📰 NVIDIA - AI Model Co-Design: Hardware-Friendly LLM Design
AI performance comes down to three dimensions: Deployments must balance all three: High accuracy is wasted if responses are slow, and raw throughput means…
https://developer.nvidia.com/blog/ai-model-co-design-hardware-friendly-llm-design/
📰 NVIDIA - Accelerating End-to-End Co-Folding Performance with NVIDIA BioNeMo Agent Toolkit
Biomolecular structure prediction and co-folding with models like OpenFold3 are now mainstream, large-scale workloads powering drug discovery and protein design.
https://developer.nvidia.com/blog/accelerating-end-to-end-co-folding-performance-with-nvidia-bionemo-agent-toolkit/
Large language model (LLM) training workloads increasingly run into GPU memory limits before compute is fully used. Model weights, gradients, optimizer states…
https://developer.nvidia.com/blog/reducing-high-bandwidth-memory-bottlenecks-in-jax-based-llm-training-with-host-offloading/
📰 NVIDIA - AI Model Co-Design: Hardware-Friendly LLM Design
AI performance comes down to three dimensions: Deployments must balance all three: High accuracy is wasted if responses are slow, and raw throughput means…
https://developer.nvidia.com/blog/ai-model-co-design-hardware-friendly-llm-design/
📰 NVIDIA - Accelerating End-to-End Co-Folding Performance with NVIDIA BioNeMo Agent Toolkit
Biomolecular structure prediction and co-folding with models like OpenFold3 are now mainstream, large-scale workloads powering drug discovery and protein design.
https://developer.nvidia.com/blog/accelerating-end-to-end-co-folding-performance-with-nvidia-bionemo-agent-toolkit/
NVIDIA Technical Blog
Reducing High-Bandwidth Memory Bottlenecks in JAX-Based LLM Training with Host Offloading
Large language model (LLM) training workloads increasingly run into GPU memory limits before compute is fully used. Model weights, gradients, optimizer states, communication buffers…
🔄 [GitHub Releases] sgl-project/sglang - v0.5.15
https://github.com/sgl-project/sglang/releases/tag/v0.5.15
https://github.com/sgl-project/sglang/releases/tag/v0.5.15
GitHub
Release v0.5.15 · sgl-project/sglang
Highlights
GLM-5.2 NVFP4, tuned for production: We took time this cycle to tune GLM-5.2 NVFP4 on Blackwell for optimized production serving. It now runs at 500+ tok/s/user on 8x B300, 450 on 4x GB3...
GLM-5.2 NVFP4, tuned for production: We took time this cycle to tune GLM-5.2 NVFP4 on Blackwell for optimized production serving. It now runs at 500+ tok/s/user on 8x B300, 450 on 4x GB3...
🆕 [HF Models] inclusionAI - SingGuard-NSFA-9B
https://huggingface.co/inclusionAI/SingGuard-NSFA-9B
🆕 [HF Models] inclusionAI - SingGuard-NSFA-4B
https://huggingface.co/inclusionAI/SingGuard-NSFA-4B
🆕 [HF Models] inclusionAI - SingGuard-NSFA-2B
https://huggingface.co/inclusionAI/SingGuard-NSFA-2B
🆕 [HF Models] inclusionAI - SingGuard-NSFA-0.8B
https://huggingface.co/inclusionAI/SingGuard-NSFA-0.8B
https://huggingface.co/inclusionAI/SingGuard-NSFA-9B
🆕 [HF Models] inclusionAI - SingGuard-NSFA-4B
https://huggingface.co/inclusionAI/SingGuard-NSFA-4B
🆕 [HF Models] inclusionAI - SingGuard-NSFA-2B
https://huggingface.co/inclusionAI/SingGuard-NSFA-2B
🆕 [HF Models] inclusionAI - SingGuard-NSFA-0.8B
https://huggingface.co/inclusionAI/SingGuard-NSFA-0.8B
huggingface.co
inclusionAI/SingGuard-NSFA-9B · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
🔄 [GitHub Releases] vllm-project/vllm - v0.25.0
https://github.com/vllm-project/vllm/releases/tag/v0.25.0
https://github.com/vllm-project/vllm/releases/tag/v0.25.0
GitHub
Release v0.25.0 · vllm-project/vllm
vLLM v0.25.0 Release Notes
Highlights
This release features 558 commits from 232 contributors (64 new)!
Model Runner V2 is now the default for all dense models (#44443). Building on quantized-mode...
Highlights
This release features 558 commits from 232 contributors (64 new)!
Model Runner V2 is now the default for all dense models (#44443). Building on quantized-mode...
🗓️ Weekly GitHub Activity
🦙 llama.cpp
└ Release: b9873 → b9966
└ 93 commits
- Added initial support for the ET backend targeting ET-Soc-1 hardware #24179
- Introduced Q2_0 quantization format with CPU backend support for Ternary Bonsai models #24448
- Added multimodal support for DeepSeek-OCR v1 multi-tile dynamic resolution #24717
- Refactored llama-cli into an HTTP-based implementation interacting with the server #24948
- Fused MMVQ post-scale for NVFP4 on CUDA to accelerate FP8 and NVFP4 models #24481
- Optimized OpenCL Flash Attention decoding performance #25366
- Fixed a decode bottleneck in tensor-split mode by compiling regex patterns statically #24710
- Enabled unsafe math optimizations for AMD/HIP builds to match CUDA performance #24668
- Fixed a security vulnerability involving out-of-bounds reads in the UGM tokenizer #18750
- Fixed a crash occurring when using tensor parallelism with CPU-offloaded MoE experts #25028
🔗 All changes | Latest release
🎨 stable-diffusion.cpp
└ Release: master-749-b11c95a → master-775-b5d8120
└ 26 commits
- Added support for Krea2OstrisEdit #1775 and lingbot video #1770
- Support hot-reloading ControlNet to swap models without rebuilding the context #1768
- Added DPM++ 2M SDE and DPM++ 2M SDE Brownian tree samplers #1742 and #1743
- Support loading safetensors index files #1769
- Use denoise strength as the starting noise level #1738
- Moved circular padding from context to per-generation parameters #1748
- Improve generation speed by driving layer splitting from graph-cut segments #1762
- Fixed SDXL ControlNet integration issues regarding diffusers naming and graph size #1752
- Fixed UNet block paths splitting across layers #1741
🔗 All changes | Latest release
🤗 Fresh models trending on HuggingFace:
bottlecapai/ThinkingCap-Qwen3.6-27B ♡235
conradlocke/krea2-identity-edit ♡185
Alissonerdx/LTX-Best-Face-ID ♡99
SupraLabs/Supra-Router-51M ♡98
Patil/Krea-2-depth-controlnet ♡91
robbyant/lingbot-video-moe-30b-a3b ♡84
migtissera/Tess-4-27B ♡84
mgwr/M87 ♡68
ostris/krea2_turbo_style_reference ♡62
ai-sage/GigaChat3.5-432B-A28B ♡60
robbyant/lingbot-world-v2-14b-causal-fast ♡60
empero-ai/Qwythos-9B-v2 ♡43
wikeeyang/Krea2-Turbo-HD-V1 ♡28
MirilAI/Miril-Drone-2B-1 ♡27
robbyant/lingbot-vla-v2-6b ♡27
robbyant/lingbot-video-dense-1.3b ♡23
Ateron/Gemma-4-Novelist-Eclipse-31B ♡23
rzgar/Bernini-R-S2V ♡21
SOLRICKS/ltx-2.3-product-ad-style ♡21
ostris/Krea2OstrisEdit ♡20
ai-sage/GigaChat3.5-432B-A28B-base ♡18
robbyant/lingbot-vision-vit-large ♡18
epfl-neuroai/NEvo ♡18
OrionLLM/GRM-2.6-Plus-0628 ♡17
FrontiersMind/Lumma-0.6B-Base ♡13
sais-org/Polaris_Pro ♡13
🦙 llama.cpp
└ Release: b9873 → b9966
└ 93 commits
- Added initial support for the ET backend targeting ET-Soc-1 hardware #24179
- Introduced Q2_0 quantization format with CPU backend support for Ternary Bonsai models #24448
- Added multimodal support for DeepSeek-OCR v1 multi-tile dynamic resolution #24717
- Refactored llama-cli into an HTTP-based implementation interacting with the server #24948
- Fused MMVQ post-scale for NVFP4 on CUDA to accelerate FP8 and NVFP4 models #24481
- Optimized OpenCL Flash Attention decoding performance #25366
- Fixed a decode bottleneck in tensor-split mode by compiling regex patterns statically #24710
- Enabled unsafe math optimizations for AMD/HIP builds to match CUDA performance #24668
- Fixed a security vulnerability involving out-of-bounds reads in the UGM tokenizer #18750
- Fixed a crash occurring when using tensor parallelism with CPU-offloaded MoE experts #25028
🔗 All changes | Latest release
🎨 stable-diffusion.cpp
└ Release: master-749-b11c95a → master-775-b5d8120
└ 26 commits
- Added support for Krea2OstrisEdit #1775 and lingbot video #1770
- Support hot-reloading ControlNet to swap models without rebuilding the context #1768
- Added DPM++ 2M SDE and DPM++ 2M SDE Brownian tree samplers #1742 and #1743
- Support loading safetensors index files #1769
- Use denoise strength as the starting noise level #1738
- Moved circular padding from context to per-generation parameters #1748
- Improve generation speed by driving layer splitting from graph-cut segments #1762
- Fixed SDXL ControlNet integration issues regarding diffusers naming and graph size #1752
- Fixed UNet block paths splitting across layers #1741
🔗 All changes | Latest release
🤗 Fresh models trending on HuggingFace:
bottlecapai/ThinkingCap-Qwen3.6-27B ♡235
conradlocke/krea2-identity-edit ♡185
Alissonerdx/LTX-Best-Face-ID ♡99
SupraLabs/Supra-Router-51M ♡98
Patil/Krea-2-depth-controlnet ♡91
robbyant/lingbot-video-moe-30b-a3b ♡84
migtissera/Tess-4-27B ♡84
mgwr/M87 ♡68
ostris/krea2_turbo_style_reference ♡62
ai-sage/GigaChat3.5-432B-A28B ♡60
robbyant/lingbot-world-v2-14b-causal-fast ♡60
empero-ai/Qwythos-9B-v2 ♡43
wikeeyang/Krea2-Turbo-HD-V1 ♡28
MirilAI/Miril-Drone-2B-1 ♡27
robbyant/lingbot-vla-v2-6b ♡27
robbyant/lingbot-video-dense-1.3b ♡23
Ateron/Gemma-4-Novelist-Eclipse-31B ♡23
rzgar/Bernini-R-S2V ♡21
SOLRICKS/ltx-2.3-product-ad-style ♡21
ostris/Krea2OstrisEdit ♡20
ai-sage/GigaChat3.5-432B-A28B-base ♡18
robbyant/lingbot-vision-vit-large ♡18
epfl-neuroai/NEvo ♡18
OrionLLM/GRM-2.6-Plus-0628 ♡17
FrontiersMind/Lumma-0.6B-Base ♡13
sais-org/Polaris_Pro ♡13
GitHub
Initial ET backend by marty1885 · Pull Request #24179 · ggml-org/llama.cpp
Overview
This PR is developed by AINekko and by members of AIFoundry (AINekko's OSS community) and adds the ET backend that supports the ET-SOC-1 processor. ET-SOC-1 was originally created ...
This PR is developed by AINekko and by members of AIFoundry (AINekko's OSS community) and adds the ET backend that supports the ET-SOC-1 processor. ET-SOC-1 was originally created ...