local ai

arXiv:2607.12663v1 Announce Type: new Abstract: Accurate differentiation between gastric adenoma and carcinoma during endoscopy is critical for clinical decision-making. Yet, this task is highly chall

arXiv:2607.12429v1 Announce Type: new Abstract: Consistent cross-view understanding under extreme viewpoint changes is essential for spatial intelligence, as it enables models to recognize the same sc

General-purpose robots and autonomous machines are moving from research labs to real-world mass-market deployment, creating demand for compact, power-efficient AI supercomputers capable of running fou

Ollama announced its return to New York City on July 15 2026, celebrating a growing audience of individuals and businesses that value open AI models. The message highlights key benefits of Ollama’s pl

arXiv:2607.11896v1 Announce Type: cross Abstract: Forecasting particulate matter (PM10) requires both station-scale accuracy and continuous spatial fields, especially during severe dust storms. Chemic

arXiv:2607.12257v1 Announce Type: new Abstract: On-device research agents search a corpus, read sources, and write a cited brief on a personal laptop. Whether their citations are faithful, and at what

arXiv:2607.12911v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly used for dietary assessment from meal images, where retrieval-augmented grounding was shown to

arXiv:2607.13027v1 Announce Type: cross Abstract: Large Language Model (LLM) agents have moved beyond generating responses to executing multi-step tasks by calling tools, observing the results, and it

arXiv:2605.26095v2 Announce Type: replace Abstract: Automated pavement distress assessment requires more than image-level classification or coarse bounding box detection, demanding precise localizatio

arXiv:2508.19186v2 Announce Type: replace-cross Abstract: Reactive obstacle avoidance methods often cause agents to become trapped in local minima, because they can often only reason one step ahead (i

arXiv:2607.12206v1 Announce Type: new Abstract: We present RegHead, a framework for constructing semantic blendshape sets for animatable non-humanoid head avatars. With a fixed expression vocabulary,

Disclosure: I work at Pluralis Research, the lab that built this. Code is open, and I'm happy to answer questions. TL;DR: As far as we can tell, this is the first RL post-training run whose entire rol

arXiv:2607.12379v1 Announce Type: new Abstract: UV seam placement is a critical yet labor-intensive step in 3D content creation, requiring artists to balance chart shape, seam concealment, and alignme

arXiv:2607.12398v1 Announce Type: new Abstract: Freehand 3-D ultrasound (US) imaging has attracted increasing attention owing to its intuitive volumetric visualization, ease of use, and low cost. Howe

arXiv:2607.12171v1 Announce Type: cross Abstract: In rectified-flow-based generative models, the neural network can be trained to predict two different targets, such as the instantaneous velocity or t

https://techcrunch.com/2026/07/13/satya-nadella-has-issued-a-shocking-warning-to-companies-using-ai/ Venture capitalists have been warning for awhile that OpenAI and Anthropic are getting access to se

arXiv:2506.21324v3 Announce Type: replace-cross Abstract: Neuromorphic and quantum computing have recently emerged as promising paradigms for advancing artificial intelligence, each offering complemen

arXiv:2607.12863v1 Announce Type: cross Abstract: Transformer language models are increasingly used as software components, yet biased outputs remain difficult to localize and repair inside the model.

arXiv:2607.10467v2 Announce Type: replace-cross Abstract: Healthcare organizations often cannot freely centralize patient data because medical records are sensitive, regulated, and institutionally con

arXiv:2607.11939v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction in crowded environments remains challenging due to the multimodal uncertainty of human motion and the variable

arXiv:2607.12892v1 Announce Type: cross Abstract: Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect

arXiv:2607.12592v1 Announce Type: new Abstract: We present WanToFight, a generative game engine that simulates real-time, two-player The King of Fighters '97 (KOF~'97) gameplay from keyboard input. Pr

arXiv:2607.12501v1 Announce Type: new Abstract: The Forward-Forward (FF) algorithm trains each layer locally, so that a scalar goodness - the sum of squared activations - is high on real inputs and lo

You can use OpenCode Desktop with Ollama! Try it with the top open models! Introducing Tabs OpenCode Desktop is now built around tabs. Start a new session in a tab, or open an existing session from an

Very impressive release by the PrismML team. 1-bit quantization shrinks it from 54GB to just 3.8GB (-93%), while retaining 90% of its intelligence. - Collection on Hugging Face: https://huggingface.co

Bonsai 27B is a big step for local AI: 27B-class multimodal capability in a phone-class footprint. Congrats to @PrismML on the launch. Try Ternary Bonsai 27B on Together AI: https://www.together.ai/mo

Huge if true! We are talking about a 27B multimodal model that runs locally on a phone. That's wild! Bonsai 27B reaches up to 163 tok/s in 1-bit and 134 tok/s in Ternary on an NVIDIA GeForce RTX 5090.

Local AI is the future. Learning how to run Opensource models (Inference), how to evaluate them systematically (Evals), and how to customize them (Fine-tuning / RL / Post-training) are invaluable skil

**Official Ollama Extension for VS Code** The extension on the Visual Studio Marketplace provides a dedicated Ollama language‑model integration for Visual Studio Code, enabling developers to run and a

Today, we’re announcing Bonsai 27B: the first 27B-class model to run on a phone. Bonsai 27B is the new multimodal flagship of the Bonsai family. Based on Qwen3.6 27B, it brings a new capability tier t

For the last few months, the conversation around open models has centered on cost and performance optimization. But Satya highlights something more existential: open models aren't just an optimization

Ollama’s partner @jmorgan hosted a live session on Yahoo Finance on July 13, 2026 at 8:30 PM, where they discussed open‑model initiatives. The event was streamed in real time and attracted 16.3 K view

Parse any PDF into agent-ready context. Fully local, free desktop app. No model / internet connection required! Ever wanted to quickly turn a PDF into clean text to paste into your favorite AI agent,

.@satyanadella's Reverse Information Paradox is real. What @satyanadella's calling for already exists: open models. Over 9M+ developers have used @ollama to access open models and keep their competiti

We just shipped a full revamp of the RunAnywhere apps. iOS and Android, live now. One assistant, fully on-device, works offline: - new UI, opens straight into chat - device-aware model recommendations

A local coding agent, an in-app customer assistant, and an AI SRE triaging production logs may all use the same model class—but not the same harness, eval plan, or rollout risk. Mastra CEO Sam Bhagwat

arXiv:2512.21414v2 Announce Type: replace Abstract: Recent tool-use frameworks powered by vision-language models (VLMs) improve image understanding by grounding model predictions with specialized tool

arXiv:2607.08041v1 Announce Type: new Abstract: How diffusion models circumvent the curse of dimensionality to learn complex distributions over high dimensional spaces from a finite training set, inst

arXiv:2503.15414v3 Announce Type: replace-cross Abstract: Federated learning seeks to foster collaboration among distributed clients while preserving the privacy of their local data. Traditional feder

arXiv:2607.08252v1 Announce Type: new Abstract: Long-term persona agents must remain identifiable while adapting to new events, relationships, evidence, and social conditions. We identify self-locking

The search did not return the specific details of the b9947 release. Based on the repository and context available: B9947 is a release of llama.cpp, which enables LLM inference in C/C++ . The release

b9948 is a build release of llama.cpp, an open-source C/C++ project for efficient large language model inference. The project ships continuous build-tagged releases using a build numbering system rath

b9949 is a release build of llama.cpp, the open-source C/C++ inference engine for running large language models locally. llama.cpp releases are published frequently with build versions in the b-series

b9950 is a release of llama.cpp, a C/C++ tool for LLM inference . This build number represents one of the frequent incremental releases from the llama.cpp project, which follows a rapid development cy

Release b9956 is a build version of llama.cpp, an open-source project for LLM inference in C/C++ . The project releases frequently, with multiple releases published in a single day , and b9956 represe

Release b9967 of llama.cpp, an LLM inference project in C/C++, includes an update to the server component allowing it to accept null sampling parameters (PR #25538). This change enables more flexible