Africa’s digital decade: AI upskilling and expanding speech technology
As Sub-Saharan Africa looks to its ‘digital decade’, President of Google EMEA Matt Brittin discusses the big opportunities and some new announcements from Google.
How Planview built a scalable AI Assistant for portfolio and project management using Amazon Bedrock
This post is co-written with Lee Rehwinkel from Planview. Businesses today face numerous challenges in managing intricate projects and programs, deriving valuable insights from massive data volumes, and making timely decisions. These hurdles frequently lead to productivity bottlenecks for program managers and executives, hindering their ability to drive organizational success efficiently. Planview, a leading provider …
Super charge your LLMs with RAG at scale using AWS Glue for Apache Spark
Large language models (LLMs) are very large deep-learning models that are pre-trained on vast amounts of data. LLMs are incredibly flexible. One model can perform completely different tasks such as answering questions, summarizing documents, translating languages, and completing sentences. LLMs have the potential to revolutionize content creation and the way people use search engines and …
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From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 1
The AWS Generative AI Innovation Center (GenAIIC) is a team of AWS science and strategy experts who have deep knowledge of generative AI. They help AWS customers jumpstart their generative AI journey by building proofs of concept that use generative AI to bring business value. Since the inception of AWS GenAIIC in May 2023, we …
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Enhance your Amazon Redshift cloud data warehouse with easier, simpler, and faster machine learning using Amazon SageMaker Canvas
Machine learning (ML) helps organizations to increase revenue, drive business growth, and reduce costs by optimizing core business functions such as supply and demand forecasting, customer churn prediction, credit risk scoring, pricing, predicting late shipments, and many others. Conventional ML development cycles take weeks to many months and requires sparse data science understanding and ML …
Create a generative AI-based application builder assistant using Amazon Bedrock Agents
In this post, we set up an agent using Amazon Bedrock Agents to act as a software application builder assistant. Agentic workflows are a fresh new perspective in building dynamic and complex business use- case based workflows with the help of large language models (LLM) as their reasoning engine or brain. These agentic workflows decompose …
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Transitioning from Amazon Rekognition people pathing: Exploring other alternatives
Amazon Rekognition people pathing is a machine learning (ML)–based capability of Amazon Rekognition Video that users can use to understand where, when, and how each person is moving in a video. This capability can be used for multiple use cases, such as for understanding: Retail analytics – Customer flow in the store and identifying high-traffic …
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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock
This post is cowritten with Greg Benson, Aaron Kesler and David Dellsperger from SnapLogic. The landscape of enterprise application development is undergoing a seismic shift with the advent of generative AI. SnapLogic, a leader in generative integration and automation, has introduced the industry’s first low-code generative AI development platform, Agent Creator, designed to democratize AI …
Next-generation learning experience using Amazon Bedrock and Anthropic’s Claude: Innovation from Classworks
This post is co-written with Jerry Henley, Hans Buchheim and Roy Gunter from Classworks. Classworks is an online teacher and student platform that includes academic screening, progress monitoring, and specially designed instruction for reading and math for grades K–12. Classworks’s unique ability to ingest student assessment data from various sources, analyze it, and automatically deliver …
Fine-tune a BGE embedding model using synthetic data from Amazon Bedrock
Have you ever faced the challenge of obtaining high-quality data for fine-tuning your machine learning (ML) models? Generating synthetic data can provide a robust solution, especially when real-world data is scarce or sensitive. For instance, when developing a medical search engine, obtaining a large dataset of real user queries and relevant documents is often infeasible …
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