Introduction to Embedchain – A Data Platform Tailored for LLMs
Analytics Vidhya
NOVEMBER 5, 2023
Introduction The introduction to tools like LangChain, and LangFlow, has made things easier when building applications with Large Language Models.
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Open source large language models: Benefits, risks and types
IBM Journey to AI blog
SEPTEMBER 27, 2023
Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles and books, to generate text, translate between languages and write many types of content. The license may restrict how the LLM can be used.
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Introducing Snorkel’s Foundation Model Data Platform
Snorkel AI
JUNE 12, 2023
In 2007, Google researchers published a paper on a class of statistical language models they dubbed “large language models”, which they reported as achieving a new state of the art in performance. They used a very standard model and a decoding algorithm so simple they named it “Stupid Backoff” 1.
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Introducing Snorkel’s Foundation Model Data Platform
Snorkel AI
JUNE 12, 2023
In 2007, Google researchers published a paper on a class of statistical language models they dubbed “large language models”, which they reported as achieving a new state of the art in performance. They used a very standard model and a decoding algorithm so simple they named it “Stupid Backoff” 1.
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IBM TechXchange underscores the importance of AI skilling and partner innovation
IBM Journey to AI blog
SEPTEMBER 21, 2023
Generative AI and large language models are poised to impact how we all access and use information. is the first enterprise-grade LLM offering that brings trustworthy, scalable, and transparent AI that can be delivered on timelines and maintained at costs that align with industry leading return on investment (ROI).”
Using John Snow Labs’ Medical Large Language Models on Azure Fabric
John Snow Labs
FEBRUARY 12, 2025
John Snow Labs’ Medical Language Models library is an excellent choice for leveraging the power of large language models (LLM) and natural language processing (NLP) in Azure Fabric due to its seamless integration, scalability, and state-of-the-art accuracy on medical tasks.
How to prevent prompt injection attacks
IBM Journey to AI blog
APRIL 24, 2024
Large language models (LLMs) may be the biggest technological breakthrough of the decade. Prompt injections are a type of attack where hackers disguise malicious content as benign user input and feed it to an LLM application. Hackers do not need to feed prompts directly to LLMs for these attacks to work.
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IBM watsonx Assistant transforms content into conversational answers with generative AI
IBM Journey to AI blog
AUGUST 31, 2023
IBM watsonx Assistant connects to watsonx, IBM’s enterprise-ready AI and data platform for training, deploying and managing foundation models, to enable business users to automate accurate, conversational question-answering with customized watsonx large language models.
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How two software companies are using IBM watsonx for their enterprise generative AI solutions
IBM Journey to AI blog
AUGUST 7, 2024
In the year since we unveiled IBM’s enterprise generative AI (gen AI) and data platform, we’ve collaborated with numerous software companies to embed IBM watsonx™ into their apps, offerings and solutions. IBM’s established expertise and industry trust make it an ideal integration partner.”
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LLM integration takes Cloudera data lakehouse from Big Data to Big AI
JUNE 6, 2023
Cloudera got its start in the Big Data era and is now moving quickly into the era of Big AI with large language models (LLMs). Today, Cloudera announced its strategy and tools for helping enterprises integrate the power of LLMs and generative AI into the company’s Cloudera Data Platform (CDP). …
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The recipe for RAG: How cloud services enable generative AI outcomes across industries
IBM Journey to AI blog
JUNE 19, 2024
Thankfully, retrieval-augmented generation (RAG) has emerged as a promising solution to ground large language models (LLMs) on the most accurate, up-to-date information. IBM unveiled its new AI and data platform, watsonx™, which offers RAG, back in May 2023.
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Generate compliant content with Amazon Bedrock and ConstitutionalChain
AWS Machine Learning Blog
APRIL 1, 2025
Understanding Constitutional AI Constitutional AI is designed to align large language models (LLMs) with human values and ethical considerations. It works by integrating a set of predefined rules, principles, and constraints into the LLMs core architecture and training process. with st.spinner(f"Generating."): .
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Generative AI that’s tailored for your business needs with watsonx.ai
IBM Journey to AI blog
SEPTEMBER 28, 2023
An AI and data platform, such as watsonx, can help empower businesses to leverage foundation models and accelerate the pace of generative AI adoption across their organization. The latest open-source LLM model we added this month includes Meta’s 70 billion parameter model Llama 2-chat inside the watsonx.ai
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Manage access controls in generative AI-powered search applications using Amazon OpenSearch Service and Amazon Cognito
NOVEMBER 19, 2024
Pre-filtered documents that relate to the user query are included in the prompt of the large language model (LLM) that summarizes the answer. Then, Lambda replies back to the web interface with the LLM completion (reply). He helps customers and partners build big data platform and generative AI applications.
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How the Masters uses watsonx to manage its AI lifecycle
IBM Journey to AI blog
APRIL 9, 2024
This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.”
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Databricks + Snorkel Flow: integrated, streamlined AI development
Snorkel AI
JANUARY 8, 2025
In todays fast-paced AI landscape, seamless integration between data platforms and AI development tools is critical. At Snorkel, weve partnered with Databricks to create a powerful synergy between their data lakehouse and our Snorkel Flow AI data development platform.
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Amazon Bedrock announces general availability of multi-agent collaboration
AWS Machine Learning Blog
MARCH 10, 2025
Recommendation agent Analyzes the aggregated data to provide tailored recommendations for precise input applications, product placement, and strategies for pest and disease control. This experience was instrumental in her professional growth.
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The Sequence Radar #516: NVIDIA’s AI Hardware and Software Synergies are Getting Scary Good
TheSequence
MARCH 23, 2025
. 🔎 AI Research Synthetic Data and Differential Privacy In the paper "Private prediction for large-scale synthetic text generation " researchers from Google present an approach for generating differentially private synthetic text using large language models via private prediction. Mistral Small 3.1
AI, Go Fetch! New NVIDIA NeMo Retriever Microservices Boost LLM Accuracy and Throughput
NVIDIA
JULY 23, 2024
An embedding model transforms diverse data — such as text, images, charts and video — into numerical vectors, stored in a vector database, while capturing their meaning and nuance. Embedding models are fast and computationally less expensive than traditional large language models, or LLMs.
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Eric Landau, Co-Founder & CEO of Encord – Interview Series
Unite.AI
SEPTEMBER 10, 2024
In his spare time, Eric enjoys playing with ChatGPT and large language models and craft cocktail making. What inspired you to co-found Encord, and how did your experience in particle physics and quantitative finance shape your approach to solving the “data problem” in AI? He holds an S.M.
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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval
AWS Machine Learning Blog
MARCH 5, 2025
These assistants can be powered by various backend architectures including Retrieval Augmented Generation (RAG), agentic workflows, fine-tuned large language models (LLMs), or a combination of these techniques. To learn more about FMEval, see Evaluate large language models for quality and responsibility of LLMs.
How foundation models and data stores unlock the business potential of generative AI
IBM Journey to AI blog
AUGUST 1, 2023
For example, a foundation model might be used as the basis for a generative AI model that is then fine-tuned with additional manufacturing datasets to assist in the discovery of safer and faster ways to manufacturer a type of product. An open-source model, Google created BERT in 2018.
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Build generative AI–powered Salesforce applications with Amazon Bedrock
AWS Machine Learning Blog
JULY 29, 2024
In this post, we show how native integrations between Salesforce and Amazon Web Services (AWS) enable you to Bring Your Own Large Language Models (BYO LLMs) from your AWS account to power generative artificial intelligence (AI) applications in Salesforce. For this post, we use the Anthropic Claude 3 Sonnet model.
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AI and the future of unstructured data
IBM Journey to AI blog
OCTOBER 14, 2024
Just last month, Salesforce made a major acquisition to power its Agentforce platform—just one in a number of recent investments in unstructured data management providers. “Most data being generated every day is unstructured and presents the biggest new opportunity.”
Transforming customer service: How generative AI is changing the game
IBM Journey to AI blog
JULY 17, 2023
Currently chat bots are relying on rule-based systems or traditional machine learning algorithms (or models) to automate tasks and provide predefined responses to customer inquiries. is a studio to train, validate, tune and deploy machine learning (ML) and foundation models for Generative AI. Watsonx.ai
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Getting ready for artificial general intelligence with examples
IBM Journey to AI blog
APRIL 18, 2024
AI systems like LaMDA and GPT-3 excel at generating human-quality text, accomplishing specific tasks, translating languages as needed, and creating different kinds of creative content. Achieving these feats is accomplished through a combination of sophisticated algorithms, natural language processing (NLP) and computer science principles.
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Improving air quality with generative AI
AWS Machine Learning Blog
JUNE 18, 2024
This post presents a solution that uses a generative artificial intelligence (AI) to standardize air quality data from low-cost sensors in Africa, specifically addressing the air quality data integration problem of low-cost sensors. The solution only invokes the LLM for new device data file type (code has not yet been generated).
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John Snow Labs Closes 2024 with Record Revenue, Customer Base Growth, and Open-Source Adoption, Thanks to State-of-the-art Healthcare-Specific Large Language Models
John Snow Labs
JANUARY 14, 2025
This is the result of a concentrated effort to deeply integrate its technology across a range of cloud and data platforms, making it easier for customers to adopt and leverage its technology in a private, safe, and scalable way.
Delight your customers with great conversational experiences via QnABot, a generative AI chatbot
AWS Machine Learning Blog
AUGUST 15, 2024
QnABot on AWS provides access to multiple FMs through Amazon Bedrock, so you can create conversational interfaces based on your customers’ language needs (such as Spanish, English, or French), sophistication of questions, and accuracy of responses based on user intent.
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The Limits of Retrieval Augmentation, 8 AI Research Labs Worth Exploring, and Supercharging LLMs…
ODSC - Open Data Science
FEBRUARY 22, 2024
8 AI Research Labs Pushing the Boundaries of Artificial Intelligence These eight AI research labs are designing the future of the field of data science, ranging from developing new LLMs to using AI to improve quality of life. Here’s a bit more on why that’s the case. Register now for 40% off! Sign up for our new newsletter here!
Yann LeCun's Vision Starts Materializing
TheSequence
JUNE 18, 2023
We discuss Google Research’s paper about REALM, the original retrieval-augmented foundation model and the new version of the Ray platform that includes support for LLMs. Edge 302: We deep dive into MPT-7B, an open source LLM that supports 65k tokens.
Ground truth curation and metric interpretation best practices for evaluating generative AI question answering using FMEval
AWS Machine Learning Blog
SEPTEMBER 6, 2024
Generative artificial intelligence (AI) applications powered by large language models (LLMs) are rapidly gaining traction for question answering use cases. To learn more about FMEval, refer to Evaluate large language models for quality and responsibility.
Databricks + Snorkel Flow: integrated, streamlined AI development
Snorkel AI
JANUARY 8, 2025
In todays fast-paced AI landscape, seamless integration between data platforms and AI development tools is critical. At Snorkel, weve partnered with Databricks to create a powerful synergy between their data lakehouse and our Snorkel Flow AI data development platform.
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LLMOps: What It Is, Why It Matters, and How to Implement It
The MLOps Blog
MARCH 12, 2024
TL;DR LLMOps involves managing the entire lifecycle of Large Language Models (LLMs), including data and prompt management, model fine-tuning and evaluation, pipeline orchestration, and LLM deployment. What is Large Language Model Operations (LLMOps)?
AI Agents — A Practical Implementation
ODSC - Open Data Science
JANUARY 9, 2025
With the advent of Generative AI and Large Language Models (LLMs), we witnessed a paradigm shift in Application development, paving the way for a new wave of LLM-powered applications. We configure the agent asfollows: LLM: we can choose a language model such as GPT-4o, Llama-3, Mistral and manyothers.
The Future of Data-Centric AI Day 2: Snorkel Flow and Beyond
Snorkel AI
JUNE 9, 2023
Snorkel AI wrapped the second day of our The Future of Data-Centric AI virtual conference by showcasing how Snorkel’s data-centric platform has enabled customers to succeed, taking a deep look at Snorkel Flow’s capabilities, and announcing two new solutions. This approach, Zhang said, yields several advantages.
The Future of Data-Centric AI Day 2: Snorkel Flow and Beyond
Snorkel AI
JUNE 9, 2023
Snorkel AI wrapped the second day of our The Future of Data-Centric AI virtual conference by showcasing how Snorkel’s data-centric platform has enabled customers to succeed, taking a deep look at Snorkel Flow’s capabilities, and announcing two new solutions. This approach, Zhang said, yields several advantages.
Getting Started with Multimodal Retrieval Augmented Generation
ODSC - Open Data Science
MARCH 8, 2024
Be sure to check out her talk, “ The AI Paradigm Shift: Under the Hood of a Large Language Models ,” there! An implementation with CLIP and GPT-4-vision In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across various natural language understanding and generation tasks.
Snorkel Flow Summer 2023: faster, easier and more secure
Snorkel AI
JULY 14, 2023
In addition to the latest release of Snorkel Flow, we recently introduced Foundation Model Data Platform that expands programmatic data development beyond labeling for predictive AI with two core solutions: Snorkel GenFlow for building generative AI applications and Snorkel Foundry for developing custom LLMs with proprietary data.
Snorkel Flow Summer 2023: faster, easier and more secure
Snorkel AI
JULY 14, 2023
In addition to the latest release of Snorkel Flow, we recently introduced Foundation Model Data Platform that expands programmatic data development beyond labeling for predictive AI with two core solutions: Snorkel GenFlow for building generative AI applications and Snorkel Foundry for developing custom LLMs with proprietary data.
Find Your AI Solutions at the ODSC West AI Expo
ODSC - Open Data Science
OCTOBER 20, 2023
Build and productionize LLM models with ease with Dagster Pedram Navid | Head of Data Engineering and Developer Relations | Elementl/Dagster Labs During this session, you’ll discuss the role of orchestration in LLM training and deployment and the importance of an asset-centric framework in data engineering.
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Gen AI Applications and Use Cases in Banking & Financial Services
TransOrg Analytics
APRIL 21, 2024
Different Types of Generative AI Models Generative AI represents cutting-edge innovations that are transforming industries worldwide. Understanding the different types of Generative AI models is essential for navigating the evolving landscape of modern AI.
Databricks Acquires MosaicML and Other Recent AI Acquisitions
ODSC - Open Data Science
JULY 20, 2023
This open-source startup that specializes in neural networks has made a name for itself building a platform that allows organizations to train large language models. MosaicML is one of the pioneers of the private LLM market, making it possible for companies to harness the power of specialized AI to suit specific needs.
Discover insights from Box with the Amazon Q Box connector
AWS Machine Learning Blog
AUGUST 8, 2024
Next, you need to index this data to make it available for a Retrieval Augmented Generation (RAG) approach where relevant passages are delivered with high accuracy to a large language model (LLM). Senthil Kamala Rathinam is a Solutions Architect at Amazon Web Services specializing in data and analytics.
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