You can’t get more 2026 than that
The article discusses a notable AI hallucination, highlighting how large language models can confidently generate false or fabricated information, which underscores ongoing reliability issues with such technology.
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OpenAI's 2016 blog post introduces generative models, which learn the underlying probability distribution of training data to generate new samples. It contrasts these with discriminative models, explains key types like GANs and VAEs, and highlights their potential for unsupervised learning, creativity, and AI advancement.
INT21 has launched a self-improving PTX Kernel Factory that automates the creation of highly optimized CUDA GPU kernels. The system writes, tests, and benchmarks kernel candidates, iteratively refining them to match or exceed hand-tuned performance. Initial results show strong performance on GEMM and RNN operations, with plans to expand functionality.
The Artificial Intelligence Index Report 2026 provides a comprehensive analysis of AI developments, including trends in research, technical performance, responsible AI, policy, economy, and public opinion. The report tracks key metrics such as AI investment, patent filings, and model benchmarks, highlighting the accelerating pace of AI advancement and its societal implications.
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The Reuters Institute's Digital News Report 2026 examines global news consumption trends, highlighting shifts in platform usage, trust in media, and the growing role of AI in news production and distribution. Based on survey data from multiple countries, it tracks how audiences engage with news across digital and social platforms.