Codetown
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Groovy and Grails Discussions (3)
| Discussions | Replies | Latest Activity |
|---|---|---|
EasyBThis just in from Luis Espinal of MJUG: http://www.easyb.org/ The EasyB syntax for writing stories and specifications is a lot more succ… Started by Michael Levin |
0 | Jul 27, 2011 |
Groovy and Grails biggest problem...From what I've seen of Groovy and Grails, its biggest hurdle is adoption. Why else would anyone resist using a language that improves on Ja… Started by Michael Levin |
5 |
Jan 3, 2010 Reply by John Thompson |
SpringSource + G2OneThere were quit some news generated from SpringSource acquired the G2One company recently. However some didn't like Spring's recent changes… Started by Zemian Deng |
0 | Nov 14, 2008 |
Happy 10th year, JCertif!
Notes
Welcome to Codetown!
Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.
Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.
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InfoQ Reading List
Presentation: The Time is Now: Delight Your Developers with User-Centric Platforms & Practices
Ana Petkovska discusses creating platform teams, establishing the team API, engagement of early adopters, easing adoption and providing a high quality product.
By Ana PetkovskaDeepSeek Open-Sources DeepSeek-V3, a 671B Parameter Mixture of Experts LLM
DeepSeek open-sourced DeepSeek-V3, a Mixture-of-Experts (MoE) LLM containing 671B parameters. It was pre-trained on 14.8T tokens using 2.788M GPU hours and outperforms other open-source models on a range of LLM benchmarks, including MMLU, MMLU-Pro, and GPQA.
By Anthony AlfordArticle: A Framework for Building Micro Metrics for LLM System Evaluation
LLM accuracy is a challenging topic to address and is much more multi-dimensional than a simple accuracy score. Denys Linkov introduces a framework for creating micro metrics to evaluate LLM systems, focusing on goal-aligned metrics that improve performance and reliability. By adopting an iterative "crawl, walk, run" methodology, teams can incrementally develop observability.
By Denys LinkovGoogle Releases Experimental AI Reasoning Model
Google has introduced Gemini 2.0 Flash Thinking Experimental, an AI reasoning model available in its AI Studio platform.
By Daniel DominguezGoogle Vertex AI Provides RAG Engine for Large Language Model Grounding
Vertex AI RAG Engine is a managed orchestration service aimed to make it easier to connect large language models (LLMs) to external data sources to be more up-to-date, generate more relevant responses, and hallucinate less.
By Sergio De Simone
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