Artificial intelligence
fromMedium
15 hours agoMost Developers Are Using AI Wrong.
Using AI in coding can create an illusion of speed, leading to a lack of understanding and ownership of the code.
#llm-coding
#llm-coding
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#ai #claude-code #software-development #automation #open-source #developer-tools #ollama #python #ai-tools #openai
Online learning
fromwww.businessinsider.com
3 days agoInside the OpenAI project where freelancers train ChatGPT on everything from farming to commercial flying
Contractors are enhancing ChatGPT's capabilities in specialized fields through Project Stagecraft, employing thousands for data labeling and task creation.
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fromSubstack
3 weeks agoFriday Links #36: JavaScript, AI Tools, and Ecosystem Updates
The TypeScript team released an early preview of TypeScript 6. This release is mainly about internal changes preparing for the future Go-based compiler planned for TypeScript 7. Large monorepos could see dramatic speed improvements once the Go compiler lands.
JavaScript
Data science
fromInfoQ
3 weeks agoGoogle Researchers Propose Bayesian Teaching Method for Large Language Models
Google researchers developed a training method enabling large language models to approximate Bayesian reasoning by learning from optimal Bayesian system predictions, improving belief updates during multi-step interactions.
fromInfoWorld
4 weeks agoOpenAI developing GitHub rival as AI coding platform race intensifies
To dislodge that, OpenAI would need to deliver a platform that is meaningfully AI native rather than AI augmented. That means the repository itself becomes a living system that continuously understands the codebase, its intent, and its risks, rather than a passive store of files.
DevOps
Artificial intelligence
fromZDNET
3 weeks agoWhy AI is both a curse and a blessing to open-source software - according to developers
AI can benefit open source when properly applied for security analysis, but causes harm when generating low-quality automated bug reports that overwhelm maintainers with false positives.
#ai-code-generation
Software development
fromMedium
2 weeks agoPrecise AI Control: How XML Structured Prompting Revolutionizes Code Generation
XML Structured Prompting is a framework using XML templates with defined stages, constraints, and numbered requirements to generate predictable, production-ready code from AI systems.
Software development
fromMedium
2 weeks agoPrecise AI Control: How XML Structured Prompting Revolutionizes Code Generation
XML Structured Prompting is a framework using XML templates with defined stages, constraints, and numbered requirements to generate predictable, production-ready code from AI systems.
Software development
fromMedium
2 weeks agoInside Dify AI: How RAG, Agents, and LLMOps Work Together in Production
Dify AI provides a unified platform for deploying production language model systems with built-in solutions for data freshness, observability, versioning, and safe deployment across multiple cloud environments.
fromTechCrunch
1 month agoFor open-source programs, AI coding tools are a mixed blessing | TechCrunch
AI coding tools have caused as many problems as they have solved, according to industry experts. The easy-to-use and accessible nature of AI coding tools has enabled a flood of bad code that threatens to overwhelm projects. Building new features is easier than ever, but maintaining them is just as hard and threatens to further fragment software ecosystems. The result is a more complicated story than simple software abundance.
Software development
fromFast Company
1 month agoAre LTMs the next LLMs? This new type of AI can do what large-language models can't
A major difference between LLMs and LTMs is the type of data they're able to synthesize and use. LLMs use unstructured data-think text, social media posts, emails, etc. LTMs, on the other hand, can extract information or insights from structured data, which could be contained in tables, for instance. Since many enterprises rely on structured data, often contained in spreadsheets, to run their operations, LTMs could have an immediate use case for many organizations.
Artificial intelligence
Artificial intelligence
fromComputerworld
1 month agoResearchers propose a self-distillation fix for 'catastrophic forgetting' in LLMs
Continual learning is essential for foundation models; SDFT uses in-context learning to generate on-policy signals, avoiding explicit reward functions and reducing forgetting.
fromInfoQ
1 month agoOpenCode: an Open-source AI Coding Agent Competing with Claude Code and Copilot
Open-source AI coding tool OpenCode features a native terminal-based UI, multi-session support, and compatibility with over 75 models, including Claude, OpenAI, Gemini, and local models. In addition to its CLI tool, OpenCode is also available as a desktop app and and an IDE extension for VS Code, Cursor, and other tools. OpenCode allows developers to use their existing subscriptions to paid services such as ChatGPT Plus/Pro, GitHub Copilot. Additionally, it includes a set of free models that can be used locally through LM Studio.
Software development
fromInfoQ
2 months agoMeta Applies Mutation Testing with LLM to Improve Compliance Coverage
Meta has applied large language models to mutation testing to improve compliance coverage across its software systems. The approach integrates LLM-generated mutants and tests into Meta's Automated Compliance Hardening system (ACH), addressing scalability and accuracy limits of traditional mutation testing. The system is intended to keep products and services safe while meeting compliance obligations at scale, helping teams satisfy global regulatory requirements more efficiently.
Software development
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