compliance Machine Learning Software Engineering 
Tom Tunguz
NOVEMBER 8, 2023
Most sophisticated data teams run like software engineering teams with product requirement documents, ticketing systems, & sprints. Data Products : The combination of large language models and data teams becoming software teams has led to data products. Software startups are rising to meet the need.
Tom Tunguz
JANUARY 21, 2025
He says the IT department of the future will be like the HR department for AI agents We’ll be managing and ’training’ these agents to work with our data Transition: This change starts first within the engineering org Slide 9 Clearing: Historically, there’s been a divide between software engineering and AI/ML teams.
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OpenView Labs
SEPTEMBER 14, 2021
Machine learning is proving to be an especially powerful way to use data because it can spot patterns that are otherwise undetectable by humans and can use those patterns to make decisions (hopefully smarter ones). . Model-centric vs. data-centric machine learning.
Audacix
JUNE 9, 2023
Table Of Contents As a software engineering leader, you know application security is no longer an activity that you can palm off to someone else. With the increasing number of sensitive data security breaches, it's essential to have the right automated application security tools in place to protect your software.
Stax
MAY 30, 2024
For example, you can leverage Artificial Intelligence (AI), machine learning algorithms, and predictive analytics to improve decision-making, efficiency, and user experience for both service providers and customers. It’s a smart solution that helps software providers integrated payments, enabling sub-merchants to take payments easily.
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