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Stable Diffusion Models are Secretly Good at Visual In-Context Learning Apple Machine Learning Research

​Large language models (LLM) in natural language processing (NLP) have demonstrated great potential for in-context learning (ICL) — the ability to leverage a few sets of example prompts to adapt to various tasks without having to explicitly update the model weights. ICL has recently been… Read More »Stable Diffusion Models are Secretly Good at Visual In-Context Learning Apple Machine Learning Research

Responsible AI: How PowerSchool safeguards millions of students with AI-powered content filtering using Amazon SageMaker AI Anjali Vijayakumar Artificial Intelligence

​[[{“value”:” This post is cowritten with Gayathri Rengarajan and Harshit Kumar Nyati from PowerSchool. PowerSchool is a leading provider of cloud-based software for K-12 education, serving over 60 million students in more than 90 countries and over 18,000 customers, including more than 90 of the… Read More »Responsible AI: How PowerSchool safeguards millions of students with AI-powered content filtering using Amazon SageMaker AI Anjali Vijayakumar Artificial Intelligence

A New Agency-Focused Supervision Approach Scales Software AI Agents With Only 78 Examples Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Do curated, tool-grounded demonstrations build stronger software agents than broad piles of generic instruction data? A team of researchers from Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) proposes LIMI (“Less Is More for Agency”), a supervised fine-tuning method that turns… Read More »A New Agency-Focused Supervision Approach Scales Software AI Agents With Only 78 Examples Asif Razzaq Artificial Intelligence Category – MarkTechPost

Introduction to KV Cache Optimization Using Grouped Query Attention Puneet Mangla PyImageSearch

​[[{“value”:” Home Table of Contents Introduction to KV Cache Optimization Using Grouped Query Attention Understanding the KV Cache Grouped Query Attention What Is Grouped Query Attention? How Grouped Query Attention Reduces KV Cache? Implementing KV Caching via Grouped Query Attention Grouped Query Attention Toy Transformer… Read More »Introduction to KV Cache Optimization Using Grouped Query Attention Puneet Mangla PyImageSearch

Mapping the Design Space of AI Coding Assistants Sam Lau and Philip Guo AI & ML – Radar

​[[{“value”:” Just a few years ago, AI coding assistants were little more than autocomplete curiosities—tools that could finish your variable names or suggest a line of boilerplate. Today, they’ve become an everyday part of millions of developers’ workflows, with entire products and startups built around… Read More »Mapping the Design Space of AI Coding Assistants Sam Lau and Philip Guo AI & ML – Radar

StreamTensor: A PyTorch-to-Accelerator Compiler that Streams LLM Intermediates Across FPGA Dataflows Michal Sutter Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Why treat LLM inference as batched kernels to DRAM when a dataflow compiler can pipe tiles through on-chip FIFOs and stream converters?StreamTensor is a compiler that lowers PyTorch LLM graphs (GPT-2, Llama, Qwen, Gemma) into stream-scheduled dataflow accelerators on AMD’s Alveo U55C FPGA. The… Read More »StreamTensor: A PyTorch-to-Accelerator Compiler that Streams LLM Intermediates Across FPGA Dataflows Michal Sutter Artificial Intelligence Category – MarkTechPost

Salesforce AI Research Releases CoDA-1.7B: a Discrete-Diffusion Code Model with Bidirectional, Parallel Token Generation Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Salesforce AI Research released CoDA-1.7B, a diffusion-based language model for code that generates by denoising whole sequences with bidirectional context, updating multiple tokens in parallel rather than left-to-right next-token prediction. The research team published both Base and Instruct checkpoints and an end-to-end training/evaluation/serving stack.… Read More »Salesforce AI Research Releases CoDA-1.7B: a Discrete-Diffusion Code Model with Bidirectional, Parallel Token Generation Asif Razzaq Artificial Intelligence Category – MarkTechPost

How to Evaluate Voice Agents in 2025: Beyond Automatic Speech Recognition (ASR) and Word Error Rate (WER) to Task Success, Barge-In, and Hallucination-Under-Noise Michal Sutter Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Table of contents Why WER Isn’t Enough ? What to Measure (and How) ? Benchmark Landscape: What Each Covers Filling the Gaps: What You Still Need to Add A Concrete, Reproducible Evaluation Plan References Optimizing only for Automatic Speech Recognition (ASR) and Word Error… Read More »How to Evaluate Voice Agents in 2025: Beyond Automatic Speech Recognition (ASR) and Word Error Rate (WER) to Task Success, Barge-In, and Hallucination-Under-Noise Michal Sutter Artificial Intelligence Category – MarkTechPost