Auto Added by WPeMatico
Google has open sourced A2UI, an Agent to User Interface specification and set of libraries that lets agents describe rich native interfaces in a declarative JSON format while client applications render them with their own components. The project targets a clear problem, how to let remote agents present secure, interactive interfaces across trust boundaries without […]
Anthropic has released Bloom, an open source agentic framework that automates behavioral evaluations for frontier AI models. The system takes a researcher specified behavior and builds targeted evaluations that measure how often and how strongly that behavior appears in realistic scenarios. Why Bloom? Behavioral evaluations for safety and alignment are expensive to design and maintain.
NVIDIA has released the Nemotron 3 family of open models as part of a full stack for agentic AI, including model weights, datasets and reinforcement learning tools. The family has three sizes, Nano, Super and Ultra, and targets multi agent systems that need long context reasoning with tight control over inference cost. Nano has about
Google has released T5Gemma 2, a family of open encoder-decoder Transformer checkpoints built by adapting Gemma 3 pretrained weights into an encoder-decoder layout, then continuing pretraining with the UL2 objective. The release is pretrained only, intended for developers to post-train for specific tasks, and Google explicitly notes it is not releasing post-trained or IT checkpoints
Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance
Even networks long considered “untrainable” can learn effectively with a bit of a helping hand. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a brief period of alignment between neural networks, a method they call guidance, can dramatically improve the performance of architectures previously thought unsuitable for modern tasks.Their findings
Guided learning lets “untrainable” neural networks realize their potential Read More »
Most languages use word position and sentence structure to extract meaning. For example, “The cat sat on the box,” is not the same as “The box was on the cat.” Over a long text, like a financial document or a novel, the syntax of these words likely evolves. Similarly, a person might be tracking variables in
A new way to increase the capabilities of large language models Read More »
For most of photography’s roughly 200-year history, altering a photo convincingly required either a darkroom, some Photoshop expertise, or, at minimum, a steady hand with scissors and glue. On Tuesday, OpenAI released a tool that reduces the process to typing a sentence. It’s not the first company to do so. While OpenAI had a conversational
OpenAI’s new ChatGPT image generator makes faking photos easy Read More »
In my first article on hyperparameter autotuning, I used a cake analogy to show how to use hyperparameter autotuning with Optuna and the sasviya.ml package in Python to improve detecting Higgs bosons in a particle accelerator. SAS Viya Workbench now supports hyperparameter autotuning in SAS code with a variety of […] The post The afterparty:
The afterparty: Hyperparameter autotuning revisited Read More »
Why did humans evolve the eyes we have today?While scientists can’t go back in time to study the environmental pressures that shaped the evolution of the diverse vision systems that exist in nature, a new computational framework developed by MIT researchers allows them to explore this evolution in artificial intelligence agents.The framework they developed, in
A “scientific sandbox” lets researchers explore the evolution of vision systems Read More »
