Nano Banana 2: Combining Pro capabilities with lightning-fast speed
Our latest image generation model offers advanced world knowledge, production ready specs, subject consistency and more, all at Flash speed.
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Q&A: How AI came to model the “messy” human mind
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
Profiling TorchNeuron (Part 1): System-level profiling on AWS Trainium.
A Blog post by Amazon on Hugging Face
Solving a 31-year-old grand challenge in mathematics – the KLS conjecture
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
Granite Speech 5.0: Transcribe, Translate, and Attribute more Accurately and Faster
A Blog post by IBM Granite on Hugging Face
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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.
Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysis
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Autonomous Agents in Software Development: A Vision Paper
The vision is to leverage the capabilities of multiple GPT agents to contribute to SE tasks and to propose an initial road map for future work, arguing that multiple G PT agents can perform creative and demanding tasks far beyond coding and debugging.