AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：I found my old iPhone 4 in a drawer and wondered: Does it work? Is it worth anything? What should I do with it? I went looking for answers.

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Hardware companies have realized that note-taking is one of the easiest AI use cases to build for, and consequently have been busy shoving mics into everything from pendants and rings to credit-card-sized pucks and wris…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：I didn't plan to let an AI manage my to-do list Eddie (my AI agent) now manages my to-do list.1 I hadn’t planned that. It kind of happened on its own. As I wrote in one of my previous posts, I like interacting with him…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：August 27, 2026 Responsibility & Safety Piloting the world's first double-blind AI evaluations William Isaac, Sol Messing and Kristian Lum Share Building trust in proprietary model benchmarks using cryptographically sec…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Birthday-first AI video maker AI Birthday Video Maker for Wishes, Invitations, and Share-Ready MP4s Create AI birthday videos online from rich templates and AI creative prompts. Make birthday wishes videos or birthday i…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Plaud has introduced a new AI wearable that's designed to record, transcribe, and summarize your conversations, only this time it looks like earbuds instead of a pin. The Plaud One Explorer Edition can be worn like traditional earbuds or used through its standalone charging case, and the case includes built-in 4G to upload and process conversations without relying on your phone or Wi-Fi to stay connected. Each earbud features 16MB of local storage (for a total of 32MB) and three microphones that can record at a distance of up to two meters. They can record for up to six hours according to Plaud, which is also the maximum estimated battery l … Read the full story at The Verge.

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：In the first blog of this series, we looked at how Lakebase Postgres is rewriting...

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：The companies are expanding their collaboration beyond GPUs into CPUs, government AI infrastructure and robotics.

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Can these new wearables deliver on the long-anticipated promises of AI earbuds?

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：NVIDIA’s Gamescom announcements are revealing what’s next for GeForce NOW, with new ways to play, more supported devices and platforms, and even more big PC games headed to the cloud. New NVIDIA DLSS 4.5 technology controls give members more ways to fine-tune gameplay, while expanded support for new Steam devices, GOG single sign-on, Firefox browser […]

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Plaud Inc., the maker of artificial intelligence-enabled note-taking devices, today introduced the Plaud One Explorer Edition, a pair of earbuds and a charging box that connect people to AI agents for work and everyday digital tasks. Both the Plaud One earbuds and the case can act as listening devices to record nearby conversations, and the […] The post Plaud unveils wearable earbuds with built-in agentic AI interface appeared first on SiliconANGLE.

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Adobe is rolling out an AI-heavy update for Photoshop that includes a new "optional" interface dedicated to its AI tools. Launching in beta, the "AI Assisted Editor" view will show all of Photoshop's AI features in a single toolbar, including its prompt-based image editor, background remover, an AI image extender, and more. There are also new ways to refine edits with AI, including a "markup" feature to draw directly on an image to show Photoshop's AI assistant what you'd like to change. That means you can "select areas to recolor, sketch arrows to indicate position, or brush in rough shapes to suggest new elements" without using a text pro … Read the full story at The Verge.

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：OpenAI's agentic ChatGPT Work can sign in to your online accounts without any interaction on your part. Is that a privacy risk?

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：GAO Report: Just Over One in Four F-35As Fully Mission Capable Audio of this article is brought to you by the Air & Space Forces Association, honoring and supporting our Airmen, Guardians, and their families. Find out m…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Press Release New Workday Research: Fragmented AI Is Creating a "Faster but Not Better" Reality for Employees in Hong Kong and Taiwan Download PDF Around a quarter Hong Kong and Taiwan workers spend a significant amount…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Idiolect — your AI drafts, in your voice

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：For the complete documentation index, see llms.txt. This page is also available as Markdown. Qwen3.8-Flash-Next is a new open-weight, 125B parameter MoE multimodal model from Qwen. Built on the new Qwen4 architecture, i…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：EngineerPrep — Become a production-ready AI engineer

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Presented by EDB As enterprises give AI agents more autonomy — the ability to plan, decide, and act across systems without a human approving each step — a hard question moves to the center of every architecture review: When an agent tries to complete an action that it was never authorized to do, what actually stops it? These are your agents, running on your models, touching your data in your infrastructure — and the responsibility for what they do sits with you. That responsibility can’t be met in hindsight or with a set of abstract policies that live on paper but not in practice. Agents need rules in the context of the moment, because they don’t exercise overriding judgment of their own actions. Consider a simple rule: Never open the car door. Followed literally, an agent could never get in or out of the car at all. But if you change the context (the car has just crashed, there’s a fire, someone is hurt and needs to get out), then the rule you actually want is the opposite. Context in the moment is everything. We are asking agents to do intelligent things; that requires intelligent rules. The instinct is to add guardrails around the agent: instructions, policies, and monitoring layered above the model. Those mechanisms matter, but they share a structural limit: The car-door rule is plausible right up until the moment you actually have to decide whether to open the door. Controls at the agent layer are only as reliable as the agent’s output is predictable, and autonomy is precisely the property that makes that output hard to predict. Governance that depends on reviewing an action before it happens cannot keep pace with a system that acts in milliseconds, across many systems at once. Governance has to become executable, and enforced where agents actually do their work: at the operational data layer, in the context, and exactly at the moment it is happening. The data layer is the enforcement point Agents create value by touching data. They query it, retrieve it, transform it, and increasingly act on it. A policy that says an agent should not reach a certain class of data is meaningful only if the system can deny that access at the moment the agent requests it. Additionally, a principle that says AI must be auditable is meaningful only if the organization can reconstruct what the agent did, what data it touched, which user it acted for, and what resulted. When governance lives at the data layer, it holds regardless of how the agent was built or how it behaves, because the control is a property of the database itself, not a promise made by the agent. Agent behavior may be probabilistic. Governance cannot be The enterprise should not rely on a model choosing to follow policy. The policy has to be enforced by the system. That is the difference between hoping an actor stays in bounds and constructing bounds it cannot cross to begin with. The controls that make this real are ones many enterprises already run at the data layer: role- and attribute-based access, row- and column-level security, classification and masking, policy as code, and complete audit trails. What agents change is not the mechanism, but who the mechanism has to recognize. Identity management has to treat the agent as a principal in its own right, with its own identity and a purpose declared when the session opens. Once purpose is bound to identity, the policy engine can evaluate it the same way it evaluates role or department today, and the record of what happened can capture not just who acted and what they touched, but what they declared they were there to do. In practice, this resolves into nine controls, grouped under three imperatives: Enforce it Role- and attribute-based access control enforced at query time, for agents as well as users Dynamic column masking driven by the same policy path Agent identity as a first-class principal, with declared purpose bound at session start and the acting user preserved See it and prove it Classification and tagging that drives policy Session-level audit logging that records which agent acted, for which user, and under what declared purpose Lineage across pipelines, so a result can be traced back to the request that produced it Unify and harden Centralized, portable policy management Encryption at rest and in transit Consistent enforcement across on-prem, cloud, and sovereign or air-gapped environments “Declared purpose is what makes the difference. It becomes an attribute the access layer already understands, evaluated in the same policy path as role and row-level security. The enforcement mechanism does not change. What changes is that the agent's purpose is part of what it evaluates, and part of what the record proves afterward,” says Priyanka Jain, VP, product management, data & AI governance, EDB. Wherever you are in your AI adoption journey, enforcement at the data layer is what lets you move faster rather than slower. The controls are already in the database. The difference is that agents now have to pass through them. A digital leash, not a locked door The goal is not to stop agents from doing useful work. It is to define how far an agent can go, what it can touch, what it can change, what requires escalation, and how the organization can reconstruct events if something goes wrong. Governed this way, agents are identified, scoped, monitored, and auditable. The enterprise can adopt them faster, because security, risk, and leadership teams trust the operating model underneath. Open, sovereign, and enforceable at the source Built on open source Postgres, this open foundation keeps enterprises in control of where their data lives, who can reach it, and under what policy, without ceding governance to a layer they don’t own or can’t inspect. For regulated industries, that combination of data sovereignty and source-level enforcement isn’t a nice-to-have; it’s the precondition for putting agents into production at all. Agentic systems will keep getting more capable and more autonomous. That is a reason to be deliberate about where control lives, not a reason to slow down. The enterprises that enforce governance at the data layer can move aggressively on AI, because the thing protecting their data is more than just wishful thinking. EDB Postgres AI is an open, enterprise-grade sovereign data and AI platform that unifies transactional, analytical, and AI workloads — with governance enforced where the data lives. For the full framework, see EDB’s white paper Governing Agentic AI at Enterprise Speed. Max Romanenko is Chief Technology Officer at EDB. Sponsored articles are content produced by a company that is either paying for the post or has a business relationship with VentureBeat, and they’re always clearly marked. For more information, contact [email protected].

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：The suit alleges that Meta designed its platforms to be addicting to young people.

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Looking to leave Windows? I've used Linux for years and there's never better a better time to make the leap.

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Hugging Bay | Find And Download Open AI Hugging Bay WebPage https://huggingbay.xyz/ https://huggingbay.xyz/.well-known/agent-discovery.json https://huggingbay.xyz/openapi.json https://huggingbay.xyz/api/mcp Open-source…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：The Independent AI Coding Community AI Tools Search & browse all AI tools AI Jobs International roles · opportunities Creative Studio Image · Video · Training AI Models Curated models, explained AI Skills Handy prompts,…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Notifications You must be signed in to change notification settings Fork 0 Star 0 BranchesTags Open more actions menu Latest commit History 4 Commits 4 Commits Folders and files NameName Last commit message Last commit…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Notifications You must be signed in to change notification settings Fork 3 Star 4 BranchesTags Open more actions menu Latest commit History 205 Commits 205 Commits Folders and files NameName Last commit message Last com…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Jensen Huang’s five-layer cake explains how intelligence is manufactured. The missing layer explains how quickly - and by whom - it can scale.

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：For a decade, identity and access management meant one thing: governing the humans who log in. Employee joins, gets provisioned, gets a manager, gets a departure date, gets offboarded. That loop is well understood. What changed is that the fastest-growing population inside enterprise environments is no longer human, and the governance playbook written for people […]

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Bindago - AI Message Personalisation for LinkedIn Outreach How It Works Write Once. Personalise for Everyone. You write one base message. AI generates a unique section for each lead using their real LinkedIn profile dat…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：GLM 5.3 Flash | Model APIs | RunInfra RunInfraby RightNow © 2026 RunInfra. All rights reserved. Join the communitySystem status Backed by Combinator AICPA Type II SOC 2 Ask AI about RunInfra Part of RightNow RunInfraby…

AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Senior Product Engineer ($220k-$300k + Equity) - NYC at Conveo | Y Combinator Conveo Confident decisions in days with AI-led interviews. Senior Product Engineer ($220k-$300k + Equity) - NYC $220K - $300K•New York Job ty…