AWS Machine Learning Blog

JANUARY 31, 2024

Embeddings play a key role in natural language processing (NLP) and machine learning (ML). This technique is achieved through the use of ML algorithms that enable the understanding of the meaning and context of data (semantic relationships) and the learning of complex relationships and patterns within the data (syntactic relationships).

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AWS Machine Learning Blog

JUNE 27, 2023

When machine learning (ML) models are deployed into production and employed to drive business decisions, the challenge often lies in the operation and management of multiple models. They swiftly began to work on AI/ML capabilities by building image recognition models using Amazon SageMaker.

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AWS Machine Learning Blog

APRIL 3, 2024

With Amazon Titan Multimodal Embeddings, you can generate embeddings for your content and store them in a vector database. We use Amazon OpenSearch Serverless as a vector database for storing embeddings generated by the Amazon Titan Multimodal Embeddings model. Rupinder Grewal is a Senior AI/ML Specialist Solutions Architect with AWS.

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ODSC - Open Data Science

APRIL 18, 2025

They dont possess a database of facts or access real-time information. Unless integrated with other systems, LLMs cant access recent data, current events, or proprietary databases. Week 3 of the ODSC East Bootcamp: From Hype to Hands-On with LLMs +RAG This isnt just another webinar that leaves you with buzzwords and more questions.

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Flipboard

DECEMBER 6, 2023

During the embeddings experiment, the dataset was converted into embeddings, stored in a vector database, and then matched with the embeddings of the question to extract context. The generated query is then run against the database to fetch the relevant context. Based on the initial tests, this method showed great results.

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AWS Machine Learning Blog

SEPTEMBER 24, 2024

AWS AI and machine learning (ML) services help address these concerns within the industry. AI/ML on AWS AI and ML have been a focus for Amazon for over 25 years, and many of the capabilities customers use with Amazon are driven by ML. Solutions Architect at AWS focusing on AI/ML and generative AI.

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AWS Machine Learning Blog

AUGUST 7, 2024

It works by first retrieving relevant responses from a database, then using those responses as context to feed the generative model to produce a final output. For example, retrieving responses from its database before generating a response could provide more relevant and coherent responses.

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ODSC - Open Data Science

OCTOBER 24, 2024

The Essential Tools for ML Evaluation and Responsible AI There are lots of checkmarks to hit when developing responsible AI, but thankfully, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation. Learn how Informa’s IIRIS team manages data from over 2.5 global trade shows.

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Data Science Dojo

APRIL 18, 2024

Hence, embeddings take on the role of a translator, making words comprehendible for ML models. Thus, these embeddings lead to the building of databases that transformers use to generate useful outputs in NLP applications. Here’s a video series providing a comprehensive exploration of embeddings and vector databases.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Knowledge Bases is completely serverless, so you don’t need to manage any infrastructure, and when using Knowledge Bases, you’re only charged for the models, vector databases and storage you use. In the Vector database section, select Quick create a new vector store , which manages the process of setting up a vector store. Choose Next.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

Internally, Amazon Bedrock uses embeddings stored in a vector database to augment user query context at runtime and enable a managed RAG architecture solution. The document embeddings are split into chunks and stored as indexes in a vector database. We use the Amazon letters to shareholders dataset to develop this solution.

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ODSC - Open Data Science

OCTOBER 19, 2023

Video of the Week: Accelerate Your AI/ML Initiatives and Deliver Business Value Quickly In this enlightening video, join Mahesh Krishnan and Peter Kilroy as they delve into the world of enterprise-level AI adoption.

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AWS Machine Learning Blog

OCTOBER 23, 2024

By automating document ingestion, chunking, and embedding, it eliminates the need to manually set up complex vector databases or custom retrieval systems, significantly reducing development complexity and time. She speaks at internal and external conferences such as AWS re:Invent, Women in Manufacturing West, YouTube webinars, and GHC 23.

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Iguazio

JULY 22, 2024

MongoDB for end-to-end AI data management MongoDB Atlas , an integrated suite of data services centered around a multi-cloud NoSQL database, enables developers to unify operational, analytical, and AI data services to streamline building AI-enriched applications. Additionally, compliance requirements and evolving regulations (e.g.

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ODSC - Open Data Science

MAY 22, 2025

Data-Driven Robotics: How Machine Learning is Enhancing Autonomous Navigation The better the data, the more accurate and responsive these systems become, which makes ML-powered navigation a cornerstone of modern robotics. AI Vector Search, including hybrid search and real-world demos that show its transformative power.

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AWS Machine Learning Blog

JULY 1, 2024

In this post, we demonstrate how you can build chatbots with QnAIntent that connects to a knowledge base in Amazon Bedrock (powered by Amazon OpenSearch Serverless as a vector database ) and build rich, self-service, conversational experiences for your customers. She helps key customer accounts on their data, generative AI and AI/ML journeys.

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AWS Machine Learning Blog

FEBRUARY 12, 2025

Machine learning (ML) engineers must make trade-offs and prioritize the most important factors for their specific use case and business requirements. The key is to choose a solution that can effectively host your database and compute infrastructure. Nitin Eusebius is a Sr.

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ODSC - Open Data Science

MARCH 6, 2025

ODSC Highlights Boston Meetup Explore the Future of Search: ML, Models & LiveDemo Thursday, March 6th, 6:008:00 PMET Join us for an electrifying meetup, brought to you in collaboration with ODSC and Elastic, where well journey beyond the limitations of traditional TF/IDF and plunge into the dynamic world of machine learning-powered search.

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AWS Machine Learning Blog

MARCH 1, 2024

Context is retrieved from the vector database based on the user query. She speaks at internal and external conferences such AWS re:Invent, Women in Manufacturing West, YouTube webinars, and GHC 23. She is passionate about women in technology and is a core member of Women in AI/ML at Amazon.

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ODSC - Open Data Science

MARCH 3, 2023

What are the Best Database Security Practices to Implement? Implementing these database security best practices can help keep your private data as secure as possible. Machine Learning Made Simple with Declarative Programming Tue, Mar 21, 2023 12:00 PM — 1:00 PM EDT Join this webinar and demo to learn about declarative ML systems, incl.

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AWS Machine Learning Blog

AUGUST 16, 2023

Thomson Reuters (TR), a global content and technology-driven company, has been using artificial intelligence (AI) and machine learning (ML) in its professional information products for decades. This post is cowritten by Shirsha Ray Chaudhuri, Harpreet Singh Baath, Rashmi B Pawar, and Palvika Bansal from Thomson Reuters.

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Pickl AI

NOVEMBER 4, 2024

Additionally, attending webinars and local meetups can significantly expand your knowledge and connections. Webinars often feature industry experts who share practical insights and experiences. Additionally, learn about data storage options like Hadoop and NoSQL databases to handle large datasets.

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ODSC - Open Data Science

MAY 11, 2023

Databases for the Era of Artificial Intelligence Everyone is talking about ChatGPT. But without a vector database, generative AI will not achieve the goal of truly human-like intelligence. Architecting the Edge for AI and ML Here, we examine trends driving the intersection of edge ML and the increased need for running ML anywhere.

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Iguazio

MAY 29, 2024

In the application pipeline, teams can swap: Logging inputs + responses to various data sources (database, stream, file, etc.) Classical ML models and LLMs If using QLORA to fine-tune, teams can swap out domain specific fine tuned adapters while using the same base model (e.g. For more info, check out this MLOps Community webinar.

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Precisely

NOVEMBER 13, 2023

To learn more about the real-world value of automation, digital transformation, and data quality and integrity, we were joined for a PEX Network webinar by representatives from The Coca-Cola Company and Nike: Jon Atienza, Manager, Intelligent Automation at The Coca-Cola Company Andrae Kirkland, Lead Tech Program Manager at Nike Andrew Hayden, Sr.

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ODSC - Open Data Science

FEBRUARY 22, 2024

Inference Benchmarking of Prominent Open-Source LLMs Tue, Feb 27, 2024 12:00 PM — 1:00 PM EST In the upcoming webinar, we delve into the inference benchmarking of prominent open-source Large Language Models such as the 13B and 70B Llama-2. We’ll also touch upon details of their book and what went into writing it.

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ODSC - Open Data Science

SEPTEMBER 26, 2024

Your hackathon journey begins with NVIDIA’s exclusive webinar on October 10th, where Kaggle Master Chris Deotte and NVIDIA experts will answer all your questions about the upcoming virtual and in-person hackathons. Where do explainable AI models come into play?

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Iguazio

FEBRUARY 20, 2024

To learn more, watch the webinar “Implementing Gen AI for Financial Services” with Larry Lerner, Partner & Global Lead - Banking and Securities Analytics, McKinsey & Company, and Yaron Haviv, Co-founder and CTO, Iguazio (acquired by McKinsey), which this blog post is based on. View the entire webinar here. Read more here.

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Pickl AI

NOVEMBER 28, 2024

Introduction Machine Learning ( ML ) is revolutionising industries, from healthcare and finance to retail and manufacturing. As businesses increasingly rely on ML to gain insights and improve decision-making, the demand for skilled professionals surges. This growth signifies Python’s increasing role in ML and related fields.

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Snorkel AI

OCTOBER 12, 2023

Discover the strategies used to drive data-driven decisions within the complex governmental landscape and gain valuable perspectives on the future of AI/ML, the ethical considerations in data science, and the transformative potential of leveraging data to better society. Current specialized ML libraries (e.g.,

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Iguazio

JULY 25, 2023

This article is based on our recent webinar “MLOps for Generative AI” with guests Nayur Khan, partner at QuantumBlack, AI by McKinsey, Mara Pometti, associate design director, McKinsey & Company, and Yaron Haviv, CTO and co-founder of Iguazio. You can watch the webinar here. Sequences of messages are then queued for Lucila.

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ODSC - Open Data Science

SEPTEMBER 12, 2024

Machine Learning and Data Science: Academia vs. Industry In this article, we compiled a list of the top five problems that every ML specialist faces only on the job, highlighting the gap between university curriculum and real-world practice. Million by Dutch Watchdog for Illegal Facial Recognition Database Clearview AI, a U.S.-based

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IBM Journey to AI blog

AUGUST 3, 2023

Using techniques that include artificial intelligence (AI) , machine learning (ML) , natural language processing (NLP) and network analytics, it generates a master inventory of sensitive data down to the PII or data-element level.

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ODSC - Open Data Science

DECEMBER 5, 2024

Announcing the AI Builders Summit: LLMs, AI Agents, & RAG A Virtual Month-Long Training Summit Jan 15 — Feb 8 The AI Builders Summit is a month-long virtual training event designed to equip data scientists, ML and AI engineers, and innovators with the latest advancements in LLMs, AI agents, and RAG. Register now!

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Precisely

SEPTEMBER 30, 2024

When a user enters bogus credentials on your website to access a download or webinar replay, for example, that anomaly should be detected before it enters your operational systems. Waiting until later risks sending a bogus “lead” to inside sales for follow up.

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Snorkel AI

JULY 5, 2023

Abhishek Ratna, in AI ML marketing, and TensorFlow developer engineer Robert Crowe, both from Google, spoke as part of a panel entitled “Practical Paths to Data-Centricity in Applied AI” at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Robert, I will leave the introduction part to you. Is more data always better?

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ODSC - Open Data Science

SEPTEMBER 19, 2024

Upcoming Webinars, Meetups, and Ai+ Live Training Sessions Ai+ Live Training: Operationalizing AI/ML Applications on OpenShift September 25th This workshop will delve into the “FlyingThings” project, a sophisticated computer vision demo developed to demonstrate the integration of AI/ML workflows within OpenShift.

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