This article is divided into two parts; they are: • Fine-tuning a BERT Model for GLUE Tasks • Fine-tuning a BERT Model for SQuAD Tasks GLUE is a benchmark for evaluating natural language understanding (NLU) tasks.
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Ayn Rand described Thanksgiving as “a typically American holiday . . . its essential, secular meaning is a celebration of successful production. It is a producers’ holiday. The lavish meal is a symbol of the fact that abundant consumption is the result and reward of production.”
The playlists can factor in world knowledge, go back to your listening history from day one, and be refreshed daily or weekly.
Author(s): Manash Pratim Originally published on Towards AI. A tiny local language model now organizes my files in real time for free, offline, and with zero rules. My Downloads folder used to feel like a crime scene. iMAGE GENERATED USING AIThe article discusses the author’s experience with automating the organization of their Downloads folder using a local AI agent that analyzes new files and categorizes them appropriately without any predetermined rules. The system consists of a few components […]
At this point, Google and OpenAI are battling it out neck to neck in terms of AI models. Earlier today, we reported that Google is finalizing an affordable image generation model that offers somewhat similar image quality as the Nano Banana Pro model. Here, the image generation model in question is the Nano Banana 2 Flash, and it will reportedly be powered by Gemini 3 Flash. OpenAI is reportedly testing a new AI image model Now, OpenAI appears […]
For powering next-generation AI models in 2026, Bright Data’s Web Scraper API delivers on all fronts: dynamic site support, anti-bot automation, structured output, and global reach.
Trump signed an AI executive order targeting state laws and promising one national rulebook. Critics warn it could trigger court battles and prolong uncertainty for startups while Congress debates federal rules.
Learn how to become a more efficient programmer with local testing The post How to Increase Coding Iteration Speed appeared first on Towards Data Science.
In my previous paper posted here, I explained how I built a new class of non-standard deep neural networks, with various case studies based on synthetic data and open-source code, covering problems such as noise filtering, high-dimensional curve fitting, and predictive analytics. One of the models featured a promising universal function able to represent any type of smooth response, while leading to fast convergence. Here I explore weight sensitivity and distillation. The words weight and parameter are used […]