AWS Big Data
MARCH 25, 2024
Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.
DataKitchen
JANUARY 3, 2022
Business analytic teams have ongoing deliverables – a dashboard, a PowerPoint, or a model that they refresh and renew. There’s a recent trend toward people creating data lake or data warehouse patterns and calling it data enablement or a data hub. Business Analytic Challenges.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Sisense
OCTOBER 6, 2020
These techniques allow you to: See trends and relationships among factors so you can identify operational areas that can be optimized Compare your data against hypotheses and assumptions to show how decisions might affect your organization Anticipate risk and uncertainty via mathematically modeling.
DataKitchen
NOVEMBER 29, 2021
In 2022, data organizations will institute robust automated processes around their AI systems to make them more accountable to stakeholders. Model developers will test for AI bias as part of their pre-deployment testing. Continuous testing, monitoring and observability will prevent biased models from deploying or continuing to operate.
AWS Big Data
NOVEMBER 29, 2023
These announcements drive forward the AWS Zero-ETL vision to unify all your data, enabling you to better maximize the value of your data with comprehensive analytics and ML capabilities, and innovate faster with secure data collaboration within and across organizations.
AWS Big Data
MARCH 27, 2024
This means you can seamlessly combine information such as clinical data stored in HealthLake with data stored in operational databases such as a patient relationship management system, together with data produced from wearable devices in near real-time. To get started with this feature, see Querying the AWS Glue Data Catalog.
IBM Big Data Hub
MAY 9, 2023
The answer is that generative AI leverages recent advances in foundation models. Unlike traditional ML, where each new use case requires a new model to be designed and built using specific data, foundation models are trained on large amounts of unlabeled data, which can then be adapted to new scenarios and business applications.
Expert insights. Personalized for you.
89 
Let's personalize your content