O'Reilly on Data
DECEMBER 10, 2019
Roughly a year ago, we wrote “ What machine learning means for software development.” In that article, we talked about Andrej Karpathy’s concept of Software 2.0. Karpathy argues that we’re at the beginning of a profound change in the way software is developed. Are we seeing the first steps toward the adoption of Software 2.0?
Analytics Vidhya
SEPTEMBER 14, 2023
Introduction In today’s tech-driven world, two professions have been making significant strides: Data Science and Software Engineering. While both play pivotal technological roles, they have distinct focuses, goals, and skill sets. appeared first on Analytics Vidhya.
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O'Reilly on Data
APRIL 8, 2025
But the distinction between senior and junior software developers is built into our jobs and job titles. As they move into the workforce, they need to deepen their knowledge and become part of a team writing a software system for a paying customer. It almost sounds pejorative, doesnt it?
datapine
MARCH 6, 2023
For this, you can use HR analytics software. Also, a great way to collect employee engagement data is using Gallup’s Q12 survey , which consists of 12 carefully crafted questions that gauge the most crucial aspects of employee engagement. But before you can improve something, you need to know where you stand.
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A healthy data-driven culture minimizes knowledge debt while maximizing analytics productivity. Agile Data Governance is the process of creating and improving data assets by iteratively capturing knowledge as data producers and consumers work together so that everyone can benefit.
O'Reilly on Data
JANUARY 21, 2025
This approach delivers substantial benefits: consistent execution, lower costs, better security, and systems that can be maintained like traditional software. 90% accuracy for software will often be a deal-breaker, but the promise of agents rests on the ability to chain them together: even five in a row will fail over 40% of the time!
O'Reilly on Data
MARCH 25, 2025
Weve seen this across dozens of companies, and the teams that break out of this trap all adopt some version of Evaluation-Driven Development (EDD), where testing, monitoring, and evaluation drive every decision from the start. Traditional versus GenAI software: Excitement builds steadilyor crashes after the demo. The way out?
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