Artificial Intelligence
Category: Intermediate (200)
Generating value from enterprise data: Best practices for Text2SQL and generative AI
Generative AI has opened up a lot of potential in the field of AI. We are seeing numerous uses, including text generation, code generation, summarization, translation, chatbots, and more. One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing […]
Overcoming common contact center challenges with generative AI and Amazon SageMaker Canvas
Great customer experience provides a competitive edge and helps create brand differentiation. As per the Forrester report, The State Of Customer Obsession, 2022, being customer-first can make a sizable impact on an organization’s balance sheet, as organizations embracing this methodology are surpassing their peers in revenue growth. Despite contact centers being under constant pressure to […]
Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas
This is a guest post co-written with Babu Srinivasan from MongoDB. As industries evolve in today’s fast-paced business landscape, the inability to have real-time forecasts poses significant challenges for industries heavily reliant on accurate and timely insights. The absence of real-time forecasts in various industries presents pressing business challenges that can significantly impact decision-making and […]
Create summaries of recordings using generative AI with Amazon Bedrock and Amazon Transcribe
October 2024: The contents of this post are outdated. Please refer to Summarize call transcriptions securely with Amazon Transcribe and Amazon Bedrock Guardrails for latest solution and code artifacts. Meeting notes are a crucial part of collaboration, yet they often fall through the cracks. Between leading discussions, listening closely, and typing notes, it’s easy for […]
Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium
Large language models (or LLMs) have become a topic of daily conversations. Their quick adoption is evident by the amount of time required to reach a 100 million users, which has gone from “4.5yrs by facebook” to an all-time low of mere “2 months by ChatGPT.” A generative pre-trained transformer (GPT) uses causal autoregressive updates […]
Vodafone advances its machine learning skills with AWS DeepRacer and Accenture
Vodafone is transitioning from a telecommunications company (telco) to a technology company (TechCo) by 2025, with objectives of innovating faster, reducing costs, improving security, and simplifying operations. Thousands of engineers are being onboarded to contribute to this transition. By 2025, Vodafone plans to have 50% of its global workforce actively involved in software development, with […]
Boosting developer productivity: How Deloitte uses Amazon SageMaker Canvas for no-code/low-code machine learning
The ability to quickly build and deploy machine learning (ML) models is becoming increasingly important in today’s data-driven world. However, building ML models requires significant time, effort, and specialized expertise. From data collection and cleaning to feature engineering, model building, tuning, and deployment, ML projects often take months for developers to complete. And experienced data […]
New – Code Editor, based on Code-OSS VS Code Open Source now available in Amazon SageMaker Studio
Today, we are excited to announce support for Code Editor, a new integrated development environment (IDE) option in Amazon SageMaker Studio. Code Editor is based on Code-OSS, Visual Studio Code Open Source, and provides access to the familiar environment and tools of the popular IDE that machine learning (ML) developers know and love, fully integrated […]
Minimize real-time inference latency by using Amazon SageMaker routing strategies
Amazon SageMaker makes it straightforward to deploy machine learning (ML) models for real-time inference and offers a broad selection of ML instances spanning CPUs and accelerators such as AWS Inferentia. As a fully managed service, you can scale your model deployments, minimize inference costs, and manage your models more effectively in production with reduced operational […]
Build and evaluate machine learning models with advanced configurations using the SageMaker Canvas model leaderboard
Amazon SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate machine learning (ML) predictions for their business needs. Starting today, SageMaker Canvas supports advanced model build configurations such as selecting a training method (ensemble or hyperparameter optimization) and algorithms, customizing the training and validation data split ratio, and […]









