LM-Kit.NET
LM-Kit.NET serves as a comprehensive toolkit tailored for the seamless incorporation of generative AI into .NET applications, fully compatible with Windows, Linux, and macOS systems. This versatile platform empowers your C# and VB.NET projects, facilitating the development and management of dynamic AI agents with ease.
Utilize efficient Small Language Models for on-device inference, which effectively lowers computational demands, minimizes latency, and enhances security by processing information locally. Discover the advantages of Retrieval-Augmented Generation (RAG) that improve both accuracy and relevance, while sophisticated AI agents streamline complex tasks and expedite the development process.
With native SDKs that guarantee smooth integration and optimal performance across various platforms, LM-Kit.NET also offers extensive support for custom AI agent creation and multi-agent orchestration. This toolkit simplifies the stages of prototyping, deployment, and scaling, enabling you to create intelligent, rapid, and secure solutions that are relied upon by industry professionals globally, fostering innovation and efficiency in every project.
Learn more
SciSure
SciSure is revolutionizing laboratories across the globe with innovative digital solutions designed for the future. Our Digital Lab Platform (DLP) integrates essential tools such as Electronic Lab Notebooks (ELN) and Laboratory Information Management Systems (LIMS), alongside cutting-edge technologies like artificial intelligence and machine learning. Engineered for effortless integration with your laboratory's existing hardware and software, this platform significantly boosts flexibility, security, and overall efficiency. By streamlining and optimizing your research and development processes within a secure and compliant framework, we enable researchers to focus more on driving innovation. Our dedicated team of experts is here to assist you throughout every phase of your digital lab transformation journey, ensuring a smooth transition.
Learn more
Biohub
Biohub is a user-friendly platform focused on enhancing the comprehension of protein biology. It provides access to the ESM model family, which features ESMC, ESMFold2, and ESM3, as well as interactive tools and resources specifically designed for developers engaged in protein science research. ESMC is recognized as a state-of-the-art protein language model, carefully trained on extensive evolutionary sequence data, enabling it to generate representations that clarify fundamental mechanisms related to protein structure and function. This model supports a variety of applications, including functional analysis, structural predictions, protein design, and exploring evolutionary relationships among diverse proteins. In addition, ESMFold2 excels in predicting high-resolution, all-atom 3D structures of biomolecular complexes from sequences, and it allows for the incorporation of multiple sequence alignments to enhance accuracy for challenging targets. Furthermore, ESM3 adopts a comprehensive methodology by concurrently modeling sequence, structure, and function, which facilitates the innovative design of new proteins through a synergistic approach. This remarkable combination of tools and models equips researchers with the means to push the boundaries of protein science, fostering groundbreaking discoveries that could transform the field. Overall, Biohub's offerings represent a significant leap forward in our ability to manipulate and understand protein interactions and functionalities.
Learn more
Evo 2
Evo 2 is an advanced genomic foundation model that excels in predicting and creating tasks associated with DNA, RNA, and proteins. Utilizing a sophisticated deep learning architecture, it models biological sequences with precision down to single-nucleotide accuracy, demonstrating remarkable scalability in both computational and memory resources as context length expands. The model has been trained on an impressive 40 billion parameters and can handle a context length of 1 megabase, analyzing an immense dataset of over 9 trillion nucleotides derived from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function predictions across a range of biological types, including DNA, RNA, and proteins, while also generating novel sequences that adhere to plausible genomic frameworks. Its robust capabilities have been highlighted in applications such as the design of efficient CRISPR systems and the identification of potentially disease-causing mutations in human genes. Additionally, Evo 2 is accessible to the public via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework, which significantly enhances its availability to researchers and developers. This integration not only broadens the model's reach but also represents a pivotal advancement in the fields of genomic modeling and analysis, paving the way for future innovations in biotechnology.
Learn more
