Search Results for "context"

...It integrates deep system-level capabilities with a wide range of tools, allowing the AI to perform real tasks such as file management, automation, and system control directly on the device. A standout aspect of the project is its built-in Ubuntu 24 environment, which enables users to run Linux commands, scripts, and development tools in a mobile context. Operit supports both local and remote AI models, including offline execution through frameworks like llama.cpp and MNN, helping preserve user privacy while maintaining flexibility. Operit also includes an intelligent memory system that stores, organizes, and retrieves user interactions to provide more personalized and context-aware responses. ...

...Unlike dense models that activate all their parameters for every token, Step 3.5 Flash uses a sparse Mixture-of-Experts (MoE) architecture that selectively engages only about 11 billion of its roughly 196 billion total parameters per token, delivering high-quality reasoning and interaction at far lower compute cost and latency than traditional large models. Its design targets deep reasoning, long-context handling, coding, and real-time responsiveness, making it suitable for building autonomous agents, advanced assistants, and long-chain cognitive workflows without sacrificing performance.

...RWKV is a novel large language model architecture, with the largest model in the family having 14B parameters. In contrast to Transformer with O(n^2) attention, RWKV requires only state from the previous step to calculate logits. This makes RWKV very CPU-friendly on large context lengths.

...Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. These bindings can be significantly faster than full Python implementations; in particular for the multiresolution hash encoding.

...Our frontend contains Text Normalization and Grapheme-to-Phoneme (G2P, including Polyphone and Tone Sandhi). Moreover, we use self-defined linguistic rules to adapt Chinese context.

...There are many use cases where the lower accuracy is acceptable in return of lower consumption of computing resources. Learning Automata (LA) are adaptive mechanisms requiring feedback from the executing environment to converge to certain states. In the context of network routing, LA residing at intermediate nodes along a path, exploit feedback from the destination node for reducing, e.g., path's length. According to topology’s resources like the node and edge numbers, the proper number of iterations must be used. More iterations lead to paths with higher probability of being optimal but more computing resources are consumed. ...

ARCOS (Asynchronous Reasoning with COntexts and Streams) is a software system which implements the concept of Asynchronous Multi-Context Systems, which where recently proposed as another generalisation of Multi-Context Systems and Reactive Multi-Context Systems.

A prototype solver for computing partial equilibria of Distributed Nonmonotonic Multi-Context Systems (MCS).

Easy-to-use platform-independent plugin API for the extraction of low-level features from audio data in PCM format, as required in the context of music information retrieval software.

Context-aware experience sampling/ecological momentary assessment software that uses sensors on PDA devices with artificial intelligence algorithms to enable researchers to study people and how they behave in real environments.

The VISL Phrase Structure Grammar Compiler is an implementation of a parser generator for ambiguous context-free grammars, ambiguous input, and ambiguous output.

When translating becomes a game ! Text to translate can be graphically selected. Several dictionnaries can be sorted according to the context. A large choice of matching strategies is available. The OCR engine is tunable.