Contextual Retrieval - Enhancing RAG Performance
Traditional RAG systems cannot maintain context in retrieved information. Contextual Retrieval addresses this by enriching data with context| TensorOps
Traditional RAG systems cannot maintain context in retrieved information. Contextual Retrieval addresses this by enriching data with context| TensorOps
Compare context caching in LLMs—OpenAI, Anthropic, Google Gemini. Discover the best option for your project's cost, ease, and features.| TensorOps
The LLM Deployment Assessment is a professional service that combines expert consulting with an open-source framework to enhance the visibility and optimization process of your LLM deployment| TensorOps
When it comes to data science and machine learning, notebooks (based on Jupyter) are often the main tool for research and exploration as they allow interactive work with data, in-line visualization, and co-coding. Data scientists may want to move away from notebooks running locally to a cloud service, especially when they need flexible and more robust infrastructure to host the notebooks and when they want to collaborate with others. Google Cloud offers two excellent options: Vertex AI Workbench| TensorOps
Generative AI has been at the forefront of the automation revolution, particularly since the emergence of ChatGPT. The emergence of applications such as chatbots, video makers, and co-pilots has helped companies automate processes across numerous industries, including software supply chains, marketing, and information security. However, the full potential of GenAI is yet to be unlocked. A significant reason for this is the cost implications. The cost of incorporating Large Language Models (LLMs)| TensorOps
On a sad February day, I attended the professional event known as the “RAG Funeral,” which, contrary to its name, was a lively and enlightening gathering of AI and technology aficionados. The meeting centered around discussions proclaiming the "death" of Retrieval-Augmented Generation (RAG), and I had the pleasure of meeting a variety of semi-professionals, each bringing their unique experiences and insights to the table. Below, I delve into the distinctive characters I encountered, each ...| TensorOps
In today’s AI landscape, companies like Microsoft and Google offer sophisticated Retriever-Augmented Generation (RAG) solutions through platforms like Azure and GCP, simplifying the creation of AI applications with managed services. These services, such as Azure's AI search, boast powerful capabilities and manage vast quantities of documents with ease. However, such managed services can be costly, may lack customisation, and impose limitations like rate limits and model access. What if you ...| TensorOps
MDClone: Setting New Standards for clinical analysis with ADAMMDClone is a successful startup that provides the ADAMS Platform, an advanced analytics platform designed specifically for medical and clinical personnel. This platform has already brought advanced data analytics capabilities to clinical users, offering a HIPAA-compliant environment for data investigation without compromising patient privacy.ADAMS Highlights: • HIPAA-compliant environment • Revolutionizing clinical data handlin...| TensorOps
What stands behind the cost of LLMs? Do you need to pay for training an LLM and how much does it cost to host one on AWS? Read about it here| TensorOps
Discover LLM-FinOps: The art of balancing cost, performance, and scalability in AI, where strategic cost monitoring meets innovative perform| TensorOps
Explaining Mixture of Experts LLM (MoE): GPT4 is just 8 smaller Expert models; Mixtral is just 8 Mistral models. See the advantages and disadvantages of MoE. Find out how to calculate their number of parameters.| TensorOps
LISBON, PORTUGAL - A significant shift in Portugal's work culture is underway as several companies opt to end their "remote working" policies. Leading the charge, luxury fashion platform Farfetch has announced that it will require its employees to work from the office at least two days a week.The Shift from Full-time Remote WorkWhile the COVID-19 pandemic catalyzed the trend toward remote working, many companies in Portugal are now reconsidering its sustainability and long-term benefits. Farfetc| TensorOps
Co-written with Gad BenramThe sophistication of large language models, like Google's PaLM-2, has redefined the landscape of natural language processing (NLP). These models' ability to generate human-like text has opened up a vast array of applications, including virtual assistants, content generation, and more. To truly leverage these models' potential, an efficient approach is needed: Prompt Engineering. This blog post aims to elucidate key design patterns in prompt engineering, complete with r| TensorOps
LLMstudio, Prompt Flow, and Langsmith emerge as tools in the toolkit of the prompt engineer. We evaluate their capabilities and limitations| TensorOps
Quantization is a technique used to compact LLMs. What methods exist and how to quickly start using them?| TensorOps
