Top AI breakthroughs you need to know
Abigail Hing Wen discusses some of the most exciting recent breakthroughs in AI and robotics.
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AI and systems at RISELab
Ion Stoica outlines a few projects at the intersection of AI and systems that UC Berkeley's RISELab is developing.
The future of machine learning is tiny
Pete Warden digs into why embedded machine learning is so important, how to implement it on existing chips, and some of the new use cases it will unlock.
The future of hiring and the talent market with AI
Maria Zheng examines AI and its impact on people’s jobs, quality of work, and overall business outcomes.
Four short links: 8 July 2019
Algorithmic Governance, DevOps Assessment, Retro Language, and Open Source Satellite
Four short links: 5 July 2019
Online Not All Bad, Emotional Space, Ted Chiang, Thread Summaries
Four short links: 4 July 2019
Debugging AI, Serverless Foundations, YouTube Bans, and Pathological UI
Four short links: 3 July 2019
Models, More Models, robots.txt, and Event Sourcing
Four short links: 2 July 2019
Lock Convoys, AI Hardware, Lambda Observability, and AI for Science
RISELab’s AutoPandas hints at automation tech that will change the nature of software development
Neural-backed generators are a promising step toward practical program synthesis.
Four short links: 1 July 2019
General-Purpose Probabilistic Programming, Microsoft's Linux, Decolonizing Data, Testing Statistical Software
Four short links: 28 June 2019
Heartbeat Identity, Seam Carving, Q&A Facilitation, and Secure Data in Distributed Systems
How to become a truly data-driven organization
From basic BI to using AI to automate and augment human endeavors, data-driven systems are increasingly powerful and pervasive in the enterprise.
Demystifying the dark web
You’ve probably heard the term “dark web,” but what does it actually mean?
Iterative competition is a catalyst for better problem solving
Kaggle is more than a machine learning competition platform; it’s a facilitator for efficient problem solving and a community for sharing and learning.
Four steps for tackling technical debt
Technical debt is often misunderstood, but it can impact almost every aspect of a tech stack.
Use technology to do what you do better
Innovation has the power to change industries, but new technology doesn’t always mean you need a new business model.
One simple chart: Who is interested in Spark NLP?
As we close in on its two-year anniversary, Spark NLP is proving itself a viable option for enterprise use.