OpenAI has unveiled its new O3 and O4 models, marking a significant breakthrough in the field of artificial intelligence. These models combine text and image processing capabilities, allowing for more accurate reasoning and more natural responses. The ability to understand visual content and use it in reasoning represents a substantial improvement over previous versions.
According to OpenAI, both O3 and O4-mini are designed to make thoughtful decisions, reasoning about when and how to use tools to produce detailed and considered answers, usually in less than a minute. This autonomous reasoning ability is a key step towards a more adaptive and efficient AI.
🔍 The O3 model stands out as the most advanced, optimized for areas such as programming, mathematics, visual perception, and science. It makes 20% fewer errors than its predecessor O1, resulting in greater speed and reliability. Ideal for tasks that require deep analysis, complex problem solving, and multimodal capabilities.
⚙️ O4-mini, on the other hand, is optimized for quick reasoning tasks, such as solving mathematical problems or interpreting simple images. Although it’s less powerful than O3, it offers higher usage limits, ideal for businesses or developers with high query volume and need for efficiency.
💬 Both models improve the user experience with more natural, conversational, and context-sensitive responses. In addition, they allow you to manipulate images in real time: rotate, enlarge 🔍, edit and analyze them to generate more accurate answers. This opens up new possibilities in areas such as visual data analysis and interactive content creation.
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Category: English
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OpenAI O3 and O4: A leap towards autonomous and multimodal AI
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Google launches Agent2Agent
The protocol that connects AI agents.
Google introduced Agent2Agent (A2A), an open protocol designed for artificial intelligence (AI) agents to exchange information and coordinate actions, even if they were developed by different companies or technologies.
Unlike traditional automation systems, these agents are able to dynamically adapt and make decisions autonomously. With A2A, they operate under a client-remote model, using agent cards in JSON format that describe their capabilities, making it easy to find and collaborate with the ideal agent. Communication is real-time and can include anything from data and responses to interfaces such as forms or videos.
This protocol was developed in collaboration with more than 50 technology partners, including Atlassian, Salesforce, SAP, and ServiceNow, with the goal of automating complex workflows and fostering new levels of efficiency and innovation.
For example, in a recruitment process, one agent might identify qualified candidates, while another would arrange interviews and a third party would conduct reference checks, all in a transparent and automated manner.
According to Google:
“This collaborative effort reflects a shared vision of a future where AI agents, regardless of their underlying technologies, will be able to collaborate seamlessly to automate complex business workflows and achieve unprecedented levels of efficiency and innovation. We believe this universal interoperability is essential to fully realize the potential of collaborative AI agents.”
Currently, A2A is available in Early Access, and is scheduled for official release in late 2025.
🌐 A key step towards a future where AIs work together, regardless of their origin.
#ArtificialIntelligence #GoogleA2A #IntelligentAgents #Automation #Innovation
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MCP on GitHub
A New Way to Integrate AI into Development
The Model Context Protocol (MCP) server on GitHub is an innovative tool that allows developers to improve their workflow by integrating artificial intelligence. This standardized protocol makes it easy to automate tasks, efficiently manage repositories, and incorporate advanced features directly into the development environment.
MCP is designed as an open-source project, allowing the community to actively collaborate. Developers can identify gaps in existing tools, contribute new functionality, and optimize API usage through pull requests.
Among its main advantages are:
✅ Increased relevance and context in AI tool responses.
✅ Intelligent automation of repetitive processes.
✅ Seamless integration with GitHub and other environments through the use of personal access tokens.
✅ Scalability and efficiency in troubleshooting during software development.
In addition, MCP can be easily installed in Visual Studio Code, making it an accessible and powerful option for teams looking to evolve their development practices with the support of AI.
#IA #GitHub #MCP #SoftwareDevelopment #Automation #OpenSource #DevTools
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🧠💻 Git is 20 years old!
Two decades since Linus Torvalds created this tool that forever changed the way we develop software.
Thanks to Git, we version, collaborate, step back, test fearlessly, and build as a team, no matter where we are.
It’s not just technology: it’s trust, control, and community.
🎉 Happy anniversary, Git! For many more commits, branches and merges 💪
#Git20Years #VersionControl #DevLife #OpenSource #ThankYouGit -
🔬 Science and Technology Day
🔬 April 10 – Science and Technology Day
“Science is not expensive, ignorance is expensive.” — Bernardo Houssay
We celebrate the knowledge, innovation and legacy of Bernardo Houssay, a pioneer of science in Latin America.
At Hedy Software we are committed to education and technology as engines of transformation. 💡🚀
#ScienceAndTechnologyDay #BernardoHoussay #HedySoftware #InnovationIsCreation