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AI adoption in the enterprise 2020

O'Reilly on Data

More than half of respondent organizations identify as “mature” adopters of AI technologies: that is, they’re using AI for analysis or in production. Supervised learning is the most popular ML technique among mature AI adopters, while deep learning is the most popular technique among organizations that are still evaluating AI.

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Deep Learning is Critical for Modern Small Business Accounting

Smart Data Collective

Deep learning technology is changing the future of small businesses around the world. A growing number of small businesses are using deep learning technology to address some of their most pressing challenges. New advances in deep learning are integrated into various accounting algorithms.

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The quest for high-quality data

O'Reilly on Data

A recent O’Reilly survey found that those with mature AI practices (as measured by how long they’ve had models in production) cited “Lack of data or data quality issues” as the main bottleneck holding back further adoption of AI technologies. Data integration and cleaning. Data unification and integration.

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The DataOps Vendor Landscape, 2021

DataKitchen

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix. Data breaks.

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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

From automating tedious tasks to unlocking insights from unstructured data, the potential seems limitless. Think about it: LLMs like GPT-3 are incredibly complex deep learning models trained on massive datasets. Typically, the initial excitement about the latest and greatest technology can blind us to practical considerations.

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Introducing the technology behind watsonx.ai, IBM’s AI and data platform for enterprise

IBM Big Data Hub

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. But these powerful technologies also introduce new risks and challenges for enterprises. Data: the foundation of your foundation model Data quality matters.

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What are model governance and model operations?

O'Reilly on Data

With the shift toward the implementation of machine learning, it’s natural to expect improvement in tools targeted at helping companies with ML. Related content : “Modern Deep Learning: Tools and Techniques” - a new tutorial at the Artificial Intelligence conference in San Jose.

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