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Unlock the potential of AI and multi-modal technologies to deliver intelligent, data-driven solutions that elevate your business.
OpenAI's language models, such as GPT-3 and GPT-4, are advanced deep learning models designed for natural language processing tasks. These models leverage large-scale datasets and transformer architecture to understand and generate human-like text, enabling applications in chatbots, content creation, summarization, and more.
Hugging Face provides an open-source platform that hosts a wide range of pre-trained models for natural language processing (NLP), enabling efficient development and deployment of large language models (LLMs) for tasks like text generation, sentiment analysis, and language translation. Its Transformers library offers easy-to-use tools to fine-tune and integrate state-of-the-art models into various applications.
LangChain is a framework designed to simplify the development of applications using large language models (LLMs). It provides tools for chaining together LLMs, managing complex workflows, and integrating external data sources, making it ideal for building robust, production-ready AI applications.
Ollama is an open-source framework designed to simplify the deployment of large language models (LLMs) in production environments. It provides easy-to-use APIs and infrastructure for integrating LLMs into applications, offering enhanced scalability and performance.
Claude is a cutting-edge language model developed by Anthropic, designed for use in large language model (LLM) applications. It focuses on ensuring safety, interpretability, and alignment with human intent, making it ideal for both conversational AI and complex tasks involving natural language understanding.
Milvus is an open-source vector database designed to handle large-scale, high-dimensional data, making it ideal for storing and searching embeddings in Large Language Models (LLMs). It provides fast and efficient similarity search, enabling real-time AI applications that require high-performance retrieval and analysis of text, images, and other unstructured data.
TensorFlow is an open-source machine learning framework developed by Google, designed to facilitate the development and deployment of AI models. It supports a wide range of tasks, including deep learning, neural networks, and statistical modeling, enabling efficient training and inference on various hardware platforms.
TensorFlow is an open-source machine learning framework widely used in computer vision for tasks such as image classification, object detection, and facial recognition. Its powerful neural network capabilities allow for efficient processing of visual data, making it a go-to tool for developing and deploying computer vision models.
MLOps (Machine Learning Operations) is a set of practices that unifies machine learning system development and operations, ensuring seamless deployment, monitoring, and governance of ML models in production. It aims to improve collaboration between data scientists and operations teams, optimizing the lifecycle of ML models from development to deployment and maintenance.
Streamlit is an open-source framework that allows developers to quickly create and deploy interactive web applications for machine learning and data science. It simplifies the process of building data-driven apps with minimal coding, making it ideal for visualizing AI/ML models and results in real-time.
Apache Airflow is an open-source platform used to programmatically author, schedule, and monitor workflows. In AI/ML technology, it is commonly utilized to automate data pipelines, manage model training workflows, and orchestrate tasks such as data preprocessing, model deployment, and model evaluation.
spaCy is an open-source Python library used for advanced Natural Language Processing (NLP). It provides fast and efficient tools for tasks such as tokenization, named entity recognition, part-of-speech tagging, and dependency parsing, making it ideal for building AI/ML models that require language understanding.
You might be based out of LA with dearth of solid engineering talent or in SF where attracting and retaining top IT talent requires you to sell an arm and a leg. We get you the top talent from India that get things done fast and within your budget.
95% of engineers interviewed by our clients get accepted. We do the heavy-lifting of scanning and ruling out the wrong candidates, so you don’t have to.
Guaranteed four hour overlap to ensure easier collaboration and communication. We adjust so you don't have to.
Hire fast from our pool of carefully-vetted engineers as you grow or downsize as you like. We can setup teams within a week's notice.
Thanks to the challenging projects our clients trust us with, it keeps the morale of our engineers high and our attrition rates low.
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Our cost-efficient robust business model leverages top talent worldwide to get things done quickly and within your budget. Join us in this transformation journey of creating intuitive & user-friendly mobile apps!
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