Microsoft has released the OmniParser model on HuggingFace, a vision-based tool designed to parse UI screenshots into structured elements, enhancing intelligent GUI automation across platforms without relying on additional contextual data.
OpenRecall is an open-source software that aims to be a privacy-focused alternative to Microsoft's Recall feature. It captures the user's digital history, processes text and images using OCR, and allows users to find specific information by searching for relevant keywords. Currently, it stores data locally but does not encrypt it. It is available for Windows, macOS, and Linux.
This article provides a step-by-step guide on fine-tuning the Florence-2 model for object detection tasks, including loading the pre-trained model, fine-tuning with a custom dataset, and evaluating the model's performance.
A recent TechRadar poll found that Grammarly has emerged as a surprise hit among AI tools, with 584 monthly users. ChatGPT remains the most popular tool, while Microsoft Copilot and Google Gemini also showed strong results.
Microsoft has deployed GPT-4, a large language model, in an isolated, air-gapped Azure Government Top Secret cloud for use by the Department of Defense. Once accredited, Pentagon officials will be able to use the technology in a secure environment. The tool is expected to help DOD officials deal with vast amounts of data and simplify information sorting. Microsoft is a major investor in OpenAI, the maker of GPT-4 and the popular ChatGPT.
Stay informed about the latest artificial intelligence (AI) terminology with this comprehensive glossary. From algorithm and AI ethics to generative AI and overfitting, learn the essential AI terms that will help you sound smart over drinks or impress in a job interview.
Microsoft revealed a new AI tool called Infra Copilot, which uses its existing GitHub Copilot to create infrastructure code.
Infra Copilot is designed to understand the context of infrastructure tasks and generate appropriate code suggestions based on natural language prompts.
The tool can streamline the coding process, enabling professionals to focus on higher-level tasks.
It also provides standardized code snippets for consistency across different environments.
Infra Copilot is available now to programmers with a recent Visual Studio Code version and a GitHub Copilot license.
Microsoft has also launched GitHub Copilot Enterprise, using data from a company's own code repositories to generate code and answer questions, priced at $39 per month per user.
Infra Copilot is designed to understand the context of infrastructure tasks and generate appropriate code suggestions based on natural language prompts.
The tool can streamline the coding process, enabling professionals to focus on higher-level tasks.
It also provides standardized code snippets for consistency across different environments.
Infra Copilot is available now to programmers with a recent Visual Studio Code version and a GitHub Copilot license.
Microsoft has also launched GitHub Copilot Enterprise, using data from a company's own code repositories to generate code and answer questions, priced at $39 per month per user.
Discusses HID over I2C, an underappreciated HID standard used in laptops.
Explains that I2C-HID is used for touchpads, touchscreens, and sensor hubs.
Distinguishes I2C-HID from non-HID I2C devices and explains its benefits.
Describes the author's experience with using I2C-HID for a laptop touchpad project.
Explains that I2C-HID is used for touchpads, touchscreens, and sensor hubs.
Distinguishes I2C-HID from non-HID I2C devices and explains its benefits.
Describes the author's experience with using I2C-HID for a laptop touchpad project.
Inside Phi 2: Microsoft's Small Language Model explores the development of tailored AI models that minimize resource usage, with a focus on small language models (SLMs). The article discusses Microsoft Research's approach to building generative AI models, highlighting their "textbooks are all you need" strategy used in training their Phi series SLMs. Key aspects include curating high-quality training data, generating synthetic content, and fine-tuning the model with domain-specific information. This innovative approach has resulted in surprisingly good outcomes, with some benchmarked SLMs performing similarly or even better than larger LLMs like GPT.
