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Learning about artificial intelligence? You may find this interesting.
https://arstechnica.com/ai/2025/03/you-can-now-download-the-source-...
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Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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A recent paper from Anthropic examines how large language models internally represent concepts related to emotions and how these representations influence behavior. The work is part of the company’s interpretability research and focuses on analyzing internal activations in Claude Sonnet 4.5 to understand the mechanisms behind model responses better.
By Robert Krzaczyński
Randy Shoup discusses the "Velocity Initiative," a transformation that doubled engineering productivity and modernized eBay’s DORA metrics. He shares the technical playbook used to scale 4,500 services while explaining why even elite engineering execution can’t save a company hampered by waterfall planning, risk aversion, and a "pathological" culture of fear.
By Randy Shoup
Docker Extensions boost developer speed but create a "visibility gap" by isolating telemetry. To meet enterprise needs, extensions must act as bridges to centralized platforms. This article details how to use OpenTelemetry, policy-as-code, and encryption to build secure pipelines. Learn to balance developer productivity with the governance required for scalable, compliant observability.
By Pragya Keshap
Airbnb's observability engineering team has published details of a large-scale migration away from StatsD and a proprietary Veneur-based aggregation pipeline toward a modern, open-source metrics stack built on OpenTelemetry Protocol (OTLP), the OpenTelemetry Collector, and VictoriaMetrics' vmagent. The resulting system now ingests over 100 million samples per second in production.
By Claudio Masolo
With the release of Gemma 4, Google aims to enable local, agentic AI for Android development through a family of models designed to support the entire software lifecycle, from coding to production.
By Sergio De Simone
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