Codetown ::: a software developer's community
CISE invites you to attend an information meeting and webinar to announce and answer questions concerning its recently released solicitation, Future Internet Architecture-Next Phase (FIA-NP: NSF 13-538) on Monday, February 11, 2013, 1:00 PM to 2:30 PM EDT. You must register at …
ContinueAdded by Michael Levin on February 9, 2013 at 7:53am — No Comments
It may not adhere to the strict Java format of OJUG but was quite useful in learning more of the growing tools available to the web based developer.
Jackie Gleason answered this and unlocked other mysteries when he explained what NODE.JS was about. Including a demo where he started a .js server, Jackie showed us how to set up an Express Project Layout worked starting with NPM and yielding to his own "Hello World" page. He continued by showing us how document styled db could be…
Added by Mike Bivins on February 1, 2013 at 11:13am — No Comments
Hey everyone,
Thanks again for making it out last night sorry I had to run so quick. The slides from the presentation are located here...
And here is the code example we used...
…
ContinueAdded by Jackie Gleason on February 1, 2013 at 9:30am — 5 Comments
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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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Kyra Mozley discusses the evolution of autonomous vehicle perception, moving beyond expensive manual labeling to an embedding-first architecture. She explains how to leverage foundation models like CLIP and SAM for auto-labeling, RAG-inspired search, and few-shot adapters. This talk provides engineering leaders a blueprint for building modular, scalable vision systems that thrive on edge cases.
By Kyra Mozley
In this series, we examine what happens after the proof of concept and how AI becomes part of the software delivery pipeline. As AI transitions from proof of concept to production, teams are discovering that the challenge extends beyond model performance to include architecture, process, and accountability. This transition is redefining what constitutes good software engineering.
By Arthur Casals
To prevent agents from obeying malicious instructions hidden in external data, all text entering an agent's context must be treated as untrusted, says Niv Rabin, principal software architect at AI-security firm CyberArk. His team developed an approach based on instruction detection and history-aware validation to protect against both malicious input data and context-history poisoning.
By Sergio De Simone
Introducing Claude Cowork: Anthropic's groundbreaking AI agent revolutionizing file management on macOS. With advanced automation capabilities, it enhances document processing, organizes files, and executes multi-step workflows. Users must be cautious of backup needs due to recent issues. Explore its potential for efficient office solutions while ensuring data integrity.
By Andrew Hoblitzell
Meta has revealed how it scales its Privacy-Aware Infrastructure (PAI) to support generative AI development while enforcing privacy across complex data flows. Using large-scale lineage tracking, PrivacyLib instrumentation, and runtime policy controls, the system enables consistent privacy enforcement for AI workloads like Meta AI glasses without introducing manual bottlenecks.
By Leela Kumili
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