July 2016 Blog Posts (3)

Going Pro in Data Science

When you're learning data science, you usually practice with nice, clean, pre-packaged data sets and tidy case studies that lead you step-by-step from data collection to cool insights.

But when real life hits, many data scientists have to work with missing or sketchy information extracted from (multiple) sources in the organization. Data science that works is a messy, trial-and-error process of creating and testing hypotheses, gathering evidence, and drawing conclusions.

Going Pro in… Continue

Added by Michael Levin on July 31, 2016 at 2:17pm — No Comments

Call for proposals: The O'Reilly Design Conference

O'Reilly has just opened the call for proposals for their second Design Conference, coming to San Francisco March 19–22, 2017. Got something to share with the design community? Think it over and submit your idea by September 7, 2016.
http://www.oreilly.com/pub/cpc/24650

Added by Michael Levin on July 28, 2016 at 7:55pm — No Comments

Enter for a chance to win!

O'Reilly technology conferences help you change your business—and change the world—by bringing you face-to-face with the knowledge of innovators and practitioners. Discover the right conference for you below and enter to win a Platinum pass!

"The O'Reilly conferences are the gold standard for drawing together a critical mass of thought leaders." —Steve Gillmor, CRN

Link: http://www.oreilly.com/pub/cpc/24305

Added by Michael Levin on July 26, 2016 at 12:39pm — No Comments

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InfoQ Reading List

Anthropic Lead: HTML Increasingly Better Than Markdown at Keeping Humans Engaged in Agentic Loops

Thariq Shihipar, engineering lead for the Claude Code team, recently published a blog post (Using Claude Code: The Unreasonable Effectiveness of HTML) arguing that HTML, with its richer visualizations, color, and interactivity, improves the productivity of human-agent communication in many settings, especially when compared to default Markdown outputs.

By Bruno Couriol

Google OpenRL is an Experimental Self-hosted API for LLM Post-Training Fine-tuning

Google's GKE Labs has introduced OpenRL, an open-source project that provides a self-hosted API for post-training and fine-tuning Large Language Models (LLMs) on standard Kubernetes clusters.

By Sergio De Simone

AI Is Moving up the Software Lifecycle: From Code Review to PRD Governance

Technology companies are extending AI beyond code generation into earlier stages of the software lifecycle, including PRD validation, design inputs, and code review. Initiatives from Uber, DoorDash, and Cloudflare highlight a shift toward AI-driven governance layers that evaluate engineering artifacts before implementation while preserving human oversight across the development pipeline.

By Leela Kumili

Presentation: Rules for Understanding Language Models

Naomi Saphra discusses 5 rules governing language model behavior, breaking down why LLMs act like populations rather than individuals. She explains how tokenization creates strange semantic blind spots and highlights the mechanics of sycophancy, showing how models leverage subtle data associations to match user biases and demographics - even guessing political views based on favorite sports teams.

By Naomi Saphra

Article: Beyond CLEAN and MVP: Architecting an Offline-first Reactive Data Layer in Android

With the Reactive Data Layer Architecture (RDLA), you establish a clear boundary between public data APIs and private, framework-specific data-source implementations. Your presentation layer operates in a purely reactive manner, observing data changes rather than procedurally querying them. RDLA also simplifies testing by encouraging you to program to interfaces and use clean seeding patterns.

By Mervyn Anthony

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