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OpenAI Debuts Agent Builder and AgentKit: A Visual-First Stack for Building, Deploying, and Evaluating AI Agents Understanding the Target Audience The target audience for OpenAI’s AgentKit includes AI developers, product managers, business analysts, and decision-makers within organizations looking to integrate AI solutions into their operations. This audience typically faces several pain points, including: Difficulty in…
A New Agency-Focused Supervision Approach Scales Software AI Agents With Only 78 Examples Understanding the Target Audience The target audience for this content primarily includes AI researchers, data scientists, software engineers, and business managers interested in implementing AI solutions. Their pain points include: Difficulty in effectively training AI models with limited data. Challenges in achieving…
StreamTensor: A PyTorch-to-Accelerator Compiler for Streaming LLM Intermediates Across FPGA Dataflows Understanding the Target Audience The target audience for StreamTensor includes: AI researchers and developers focused on optimizing machine learning models, particularly those working with large language models (LLMs). Data scientists and machine learning engineers who require efficient inference solutions for deployment on FPGA hardware.…
Salesforce AI Research Releases CoDA-1.7B: A Discrete-Diffusion Code Model with Bidirectional, Parallel Token Generation Understanding the Target Audience The target audience for the CoDA-1.7B release primarily includes: Data scientists and machine learning engineers looking for advanced code generation tools. Business managers and decision-makers in tech companies interested in leveraging AI for software development. Researchers and…
«`html Agentic Design Methodology: How to Build Reliable and Human-Like AI Agents using Parlant Understanding the Target Audience The target audience for the Agentic Design Methodology includes business leaders, AI developers, and product managers interested in building reliable AI agents. They often face challenges with traditional software development paradigms that do not translate well to…
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 In an era where voice interactions are becoming increasingly central to user experiences, it is crucial to evaluate voice agents beyond traditional metrics like Automatic Speech Recognition (ASR) and Word Error Rate…
«`html Understanding the Target Audience for Unsupervised Speech Enhancement The target audience for this research on Unsupervised Speech Enhancement (SE) encompasses professionals and academics in the fields of artificial intelligence, audio engineering, and business management. These individuals are typically involved in developing or implementing AI solutions for real-world applications, especially in communication and customer service…
A Coding Implementation to Build a Transformer-Based Regression Language Model to Predict Continuous Values from Text A Coding Implementation to Build a Transformer-Based Regression Language Model to Predict Continuous Values from Text In this tutorial, we will build a Regression Language Model (RLM), which predicts continuous numerical values directly from text sequences. Unlike traditional models…
Google Proposes TUMIX: Multi-Agent Test-Time Scaling With Tool-Use Mixture Understanding the Target Audience The target audience for TUMIX includes AI researchers, business leaders in technology, and data scientists focused on improving the efficiency and effectiveness of AI systems. Their pain points typically involve: High inference costs associated with tool-augmented AI models. Need for improved accuracy…
Can a Small Language Model Predict Kernel Latency, Memory, and Model Accuracy from Code? A New Regression Language Model (RLM) Says Yes Understanding the Target Audience The target audience for this research primarily includes software engineers, data scientists, and AI researchers who are interested in performance prediction within programming environments. These professionals often face challenges…