Vision Language Models (Better, faster, stronger)
More from the blog
GPT-Lab
· gpt-lab.eu
Sep 17, 2026
Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
New method enables AI for safety-critical situations
The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.
GPT-Lab
· gpt-lab.eu
Sep 10, 2026
Responsible AI Must Consider Its Afterlife
AI may appear weightless, but every model depends on physical infrastructure. To understand responsible AI, we need to look beyond algorithms and consider the entire lifecycle of the hardware behind them. The post Responsible AI Must Consider Its Afterlife appeared first on GPT-Lab.
IBM releases SOTA Granite Time Series PatchTST-FM-r2 model with commercial-friendly license
Related papers
“Failures” to be celebrated: an analysis of major pivots of software startups
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
AI-powered Code Review with LLMs: Early Results
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Are Happy Developers more Productive? The Correlation of Affective States of Software Developers and their self-assessed Productivity
An empirical study on the impact of affective states on software developers’ performance while programming and the value of applying psychometrics in Software Engineering studies is demonstrated and a call to valorize the human, individualized aspects of software developers is echoed.