Codetown ::: a software developer's community
The ability to Interpret image data using software is advancing fast! The two images above are captioned with program generated text. Here's an article that describes concepts and an approach to generate a caption for an image. The code is written in Python and uses TensorFlow. …
ContinueAdded by Michael Levin on May 25, 2017 at 8:57am — No Comments
This is what I'm reading right now. Here you go! Matt has given us good presentations that are quick and to the point. Super cool! If you decide to pay $19.95 for the printed book, it'll cover about 3 craft pints. The health monitor app Matt made will record one less point. You'll see! Enjoy, and be sure to let Matt know how much you appreciate this free mini…
Added by Michael Levin on May 18, 2017 at 2:30pm — No Comments
First of all, relax, I'm not announcing an exclusive executive swapmeet. The market for used cell phones has ramped up to a whopping $11 billion as of 2016[1]. That's a big number by itself, especially since the market scarcely existed just ten years ago. By comparison, everything sold in every category by everyone worldwide on Ebay, new or used, was $84 billion total in 2016[2].
Unless you are actually a senior exec and can offer your device, refurbished, to other…
ContinueAdded by Ismail Jones on May 15, 2017 at 8:36pm — No Comments
Mobile devices prove to be a setback for cross-platform software development, but I hope it will be a minor one. At present, Android totally dominates the mobile market both in terms of hardware and software volume. As well, mobile devices are overtaking desktops for overall usage as we speak. But Linux, as open-source-friendly as it is appears to be getting the rub from Google, so where are we?
As Google continues to grumble about not controlling the world, they're leaking…
ContinueAdded by Ismail Jones on May 14, 2017 at 9:24am — No 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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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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