The Senate’s crypto market-structure bill needs seven Democratic votes to clear cloture. It has zero — and the ethics impasse that killed the bipartisan coalition has no obvious resolution before the August recess.
Samsung controls the device, the platform, and the AI layer. With regulators prying open Google’s wake-word lock-in, this week’s Unpacked becomes a test of whether hardware-native agents can leapfrog software-only incumbents.
What Agent Identity Means When an AI agent books a flight, signs a contract, or moves money, someone — or something — needs to vouch for it. That vouching system is agent identity: the credential, capability boundary, and action record that tell the rest of the system which agent is acting, what it is allowed…
What is Agentic AI? Agentic AI refers to autonomous, goal-driven systems capable of perceiving their environment, planning multi-step actions, invoking external tools, and self-correcting with little to no human supervision. Unlike passive models, these systems are designed to complete complex tasks rather than simply generate text or images. Think of the difference between a search…
Definition An AI capability that converts spoken language into text by analyzing audio signals, identifying phonemes and words, and transcribing them into written form. Also called automatic speech recognition (ASR), it is the technology that lets machines listen and understand human speech [1]. Analogy Imagine a stenographer in a courtroom who listens to every word…
Definition A field of artificial intelligence that gives machines the ability to interpret and understand visual information—images, video, and real-time camera feeds—by converting pixels into meaningful descriptions, categories, and actions. It is the AI equivalent of sight: the camera provides the raw visual signal, and computer vision algorithms extract what matters from it [1]. Analogy…
Synthetic data is AI-generated information that mimics real-world data patterns without containing actual records. Learn how synthetic data works, its use cases in healthcare and finance, and privacy-preserving techniques.
Think of agent evaluation like grading a student’s entire problem-solving process rather than just checking their final answer. Instead of only looking at the result, you watch how the student plans their approach, which tools they reach for, how they recover when they make a mistake, and whether they know when to ask for help…
What is AI Tokenization? At its core, AI Tokenization is the essential process of converting raw, human-readable text into numerical units—called tokens—that a Large Language Model (LLM) can actually process. Think of it as a translator that turns words into a language of numbers, which the model then maps to embedding vectors (mathematical representations of…
What is the Agent-to-Agent Protocol (A2A)? The Agent-to-Agent Protocol (A2A) is an open standard that allows AI agents built by different companies or using different technologies to communicate securely and work together. Originally created by Google and now managed by the Linux Foundation [2][3], A2A provides the connective tissue for multi-agent systems where specialized agents…