Search Results for "self driving"
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Showing 10 open source projects for "self driving"
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Open Interface
Control Any Computer Using LLMs
...By sending user requests to an LLM backend, it determines the necessary steps and executes them by simulating keyboard and mouse inputs. The system can adjust its actions based on real-time feedback, providing a self-driving computer experience. -
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CatBoost
High-performance library for gradient boosting on decision trees
...It has best in class prediction speed, supports both numerical and categorical features, has a fast and scalable GPU version, and readily comes with visualization tools. CatBoost was developed by Yandex and is used in various areas including search, self-driving cars, personal assistance, weather prediction and more. -
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Inkeep
Create AI Agents in a No-Code Visual Builder or TypeScript SDK
Inkeep is an open-source framework for building and deploying AI agent workflows and interactive assistants that operate autonomously across applications, enterprise environments, and customer engagement use cases. It lets developers and non-technical users create, manage, and orchestrate multi-agent systems using both a no-code visual builder and a full TypeScript SDK, giving two ways to define agent behaviors that stay in sync with each other. Agents built with this framework can act as... -
4
Adaptive Intelligence
Adaptive Intelligence also known as "Artificial General Intelligence"
Adaptive Intelligence is the implementation of neural science, forensic psychology , behavioral science with machine-learning and artificial intelligence to provide advanced automated software platforms with the ability to adjust and thrive in dynamic environments by combining cognitive flexibility, emotional regulation, resilience, and practical problem-solving skills. -
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5
Thinknowlogy
The world's only naturally intelligent knowledge technology
...Natural language and spatial information are sources of natural intelligence: - Natural language is providing concrete logic for organizing knowledge objects, - Spatial information provides concrete logic for organizing spatial objects (utilized in, e.g., self-driving cars). In this way, our brains know how to organize their knowledge and spatial information. I focus on natural language because this source of natural intelligence is hardly understood by scientists. Hence, the inability of Large Language Models to organize changes in their knowledge independently. -
6
BEVFormer
Implementation of BEVFormer, a camera-only framework
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries. ... -
7
neurojs
A JavaScript deep learning and reinforcement learning library
...Several interactive demonstrations included with the project illustrate how neural networks can be used to train agents in simulated tasks, including a browser-based self-driving car example. These demos allow users to visualize how reinforcement learning agents improve their behavior over time as they receive rewards and update their neural networks. -
8
BNFGen
Generates random text based on context-free grammars defined in BNF
...Project goals are to make it easy to write and share grammar and give the user total control of and insight into the generation process. BNFGen provides a "DSL" for grammar definitions. It's a familiar BNF-like syntax with a few additions. One problem with using straight BNF for driving language generators is that you have no control over the process. BNFGen adds two features to fix that. The canonical way to express repetition in BNF is to use a self-referential recursive rule. In classic BNF, that can easily lead to the process terminating to early, since there's a 50% chance that it will take the non-recursive alternative. -
9
road-scene-understanding
A dataset for road scene understanding.
Autonomous driving is gaining increasing attention in the computer vision research community, as vision based scene understanding is key to self-driving cars. In this web page, we make image datasets public for the purpose of furthering research in scene understanding. -
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10
Urban Challege
Hardware and software for self-driving vehicles
The DARPA Urban Challenge race for robot vehicles took place on Nov 3, 2007. We pose a new urban challenge: build a safe, convenient, energy efficient people mover. This site provides the hardware and software for a prototype system.
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