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Iterate open-sources their LLM, AppCoder has open-sourced their LLM, AppCoder, on Github. AppCoder is designed to improve the technology that powers their top projects, like their integrated Generative AI to scale at enterprise level.

A Large Language Model (LLM) is a type of artificial intelligence program designed to understand, generate, and interact with human language at a large scale. These models are trained on vast amounts of text data, allowing them to grasp the nuances, context, and complexities of language. LLMs can perform a wide range of tasks, such as translating languages, answering questions, generating text based on prompts, and more. They work by analyzing the patterns and structures in the data they’ve been trained on, enabling them to generate responses that mimic human-like understanding and articulation.

To open-source something means to release its source code publicly, allowing anyone to view, modify, and distribute it. This practice is a cornerstone of collaborative software development, fostering innovation and improvement by leveraging the collective expertise of developers worldwide. Open-source projects encourage a community-driven approach, where developers contribute to the project’s growth and evolution, often leading to more secure, efficient, and adaptable software. Open-sourcing a project not only promotes transparency and accessibility but also facilitates learning and experimentation within the developer community.

Iterate’s goal when designing AppCoder was to generate working and updated code for generative AI projects that they build alongside their enterprise clients. This technology is now available on Github, a code hosting platform for version control and collaboration which lets users work together on projects from anywhere.

“We are excited to announce that our AppCoder technology is now available for continued collaboration on GitHub. After months of fine-tuning CodeLlama -7B, 34B and Wizard Coder -15B, 34B, we combined this fine-tuning with our dataset training on LangChain, YOLO V8, VertexAI and other libraries to build a sophisticated program on top of WizardCoder-15B. AppCoder has continued to hit ICE benchmarks on usefulness and functionality, making this program a perfect addition to GitHub,” explains Brian Sathianathan, CTO, CDO and Co-Founder of

In addition to open-sourcing AppCoder, Iterate recently open-sourced their Threat Awareness technology to curb gun violence, making it free for schools and other organizations to implement. Iterate’s desire to open-source their technology demonstrates an active desire to continually expand the collaborative environment of AI engineering.

“Creativity and ingenuity are key to continued AI innovation. By open-sourcing our technology, we hope to participate and stand as leaders in the ongoing and evolving culture of collaboration that those in the AI sector thrive on in 2024 and beyond,” Sathianathan says. is at the forefront of empowering businesses with state-of-the-art AI tools and technologies. Its platform is cloud-agnostic, and it can run AI on the edge and in secure private environments. With four patents granted and nearly a dozen more pending, Iterate’s platform offers corporate innovators a low-risk, systematic way to scale in-house, near-term digital innovation initiatives.’s decision to open-source AppCoder on GitHub marks a significant milestone in the democratization of advanced AI technologies. By making this sophisticated Large Language Model available to the public, not only enhances the technology that powers their top projects but also invites the global developer community to contribute to its evolution. This move aligns with the core principles of open-source culture, fostering innovation, collaboration, and transparency. AppCoder, designed to generate efficient code for enterprise-level generative AI projects, stands as a testament to’s commitment to advancing AI technology in a way that is accessible and beneficial for a wide range of users. Through initiatives like open-sourcing AppCoder and their Threat Awareness technology, demonstrates a forward-thinking approach to AI development, emphasizing community involvement, continuous improvement, and the potential for AI to address critical challenges. Their actions not only contribute to the growth of AI technologies but also reflect a broader vision of building a collaborative and innovative future in the tech industry.

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