Codetown ::: a software developer's community
Thinking about Cloud Computing raises some concerns. Security is one concern that looms in many minds. What are some issues and how can we get our minds around the pitfalls before they happen?
"Lots of vendors have run into trouble with their cloud services, but the challenges faced by Apple last week should give some IT shops pause as they evaluate cloud computing.
People would be reaming Microsoft a new one but because it's Apple ... they get a passGordon Haff, cloud strategist, Red Hat
Apple's iCloud is a synchronization service that lets users keep data stored on their iPhone, iPad, iPod Touch and Mac products in synch. As 20 million or so end users launched the service for the first time, it didn't work as expected, and the backlash has been significant.
Siri, a cloud-based voice activation service unveiled with the iPhone 4S, has run into problems as well, according to Apple support discussion boards. It is supposed to let users control maps, call up recipes, arrange meetings and send messages, all via their voice. Artificial intelligence researchers have been working on this technology for decades. So it's not surprising that Apple hasn't got it right first time." (from "Why trust Apple in the cloud?", at TechTarget)
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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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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
Researchers at MIT's CSAIL published a design for Recursive Language Models (RLM), a technique for improving LLM performance on long-context tasks. RLMs use a programming environment to recursively decompose and process inputs, and can handle prompts up to 100x longer than base LLMs.
By Anthony Alford
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