Remove category large-language-models
article thumbnail

Practical Skills for The AI Product Manager

O'Reilly on Data

In his article “ Machine Learning for Product Managers ,” Neal Lathia distilled ML problem types into six categories: ranking, recommendation, classification, regression, clustering, and anomaly detection. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

article thumbnail

Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

Strategy 290
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

2021 Data/AI Salary Survey

O'Reilly on Data

There was a lot of uncertainty about stability, particularly at smaller companies: Would the company’s business model continue to be effective? Salaries by Programming Language. Discussing the connection between programming languages and salary is tricky because respondents were allowed to check multiple languages, and most did.

article thumbnail

Enriching metadata for accurate text-to-SQL generation for Amazon Athena

AWS Big Data

These data processing and analytical services support Structured Query Language (SQL) to interact with the data. Large language model (LLM)-based generative AI is a new technology trend for comprehending a large corpora of information and assisting with complex tasks. Can it also help write SQL queries?

Metadata 104
article thumbnail

Generative AI in the Enterprise

O'Reilly on Data

And everyone has opinions about how these language models and art generation programs are going to change the nature of work, usher in the singularity, or perhaps even doom the human race. 16% of respondents working with AI are using open source models. A few have even tried out Bard or Claude, or run LLaMA 1 on their laptop.

article thumbnail

Data Science Tools: Understanding the Multiverse

Domino Data Lab

These data science tools are used for doing such things as accessing, cleaning and transforming data, exploratory analysis, creating models, monitoring models and embedding them in external systems. Key categories of tools and a few examples include: Data Sources. Data Languages. Types of Data Science Tools.

article thumbnail

How Far We Can Go with GenAI as an Information Extraction Tool

Ontotext

Generative AI (GenAI) models, such as GPT-4, offer a promising solution, potentially reducing the dependency on labor-intensive annotation. Beyond knowledge graph building, NER supports use cases such as natural language querying (NLQ) , where accurate entity recognition improves search accuracy and user experience. sec Llama 87.4