OpenSource

China’s open-source AI champion

Welcome, AI enthusiasts.While tech giants proceed to pour billions into AI development, a Chinese startup just proved you possibly can construct an open-source powerhouse on a tiny budget.DeepSeek’s V3 model competes with the highest...

MIT researchers introduce Boltz-1, a completely open-source model for predicting biomolecular structures

MIT scientists have released a strong, open-source AI model, called Boltz-1, that might...

How Did Open Food Facts Fix OCR-Extracted Ingredients Using Open-Source LLMs?

Open Food Facts has tried to unravel this issue for years using Regular Expressions and existing solutions corresponding to Elasticsearch’s corrector, without success. Until recently.Because of the most recent advancements in artificial intelligence, we...

SAP’s Vision for AI-Powered Business: The Role of Joule and Open-Source Models

Artificial Intelligence (AI) is transforming how businesses manage data, make decisions, and streamline every day tasks. SAP, a worldwide leader in enterprise software, is leading this transformation. SAP has a daring vision for the...

Open-source AI takes the lead

Welcome, AI enthusiasts.Nvidia is already crushing the chipmaking game, but its models are also casually topping the LLM benchmarks and outperforming the giants. Did the corporate’s latest Nemotron release just give the open-source AI...

AI Video Goes Open-Source

Good morning. It’s Wednesday, October sixteenth.Did you understand: Concepts of the self-operating machine date back to the sixteenth century? Open-Source AI Video Generation Adobe Firefly Video Full-body...

Meta’s Llama 3.2: Redefining Open-Source Generative AI with On-Device and Multimodal Capabilities

Meta's recent launch of Llama 3.2, the newest iteration in its Llama series of huge language models, is a big development within the evolution of open-source generative AI ecosystem. This upgrade extends Llama’s capabilities...

A tiny recent open-source AI model performs in addition to powerful big ones

Ai2 achieved this by getting human annotators to explain the pictures within the model’s training data set in excruciating detail over multiple pages of text. They asked the annotators to discuss what they...

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