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AI 资讯

OpenAI says Apple’s trade secrets lawsuit is ‘rotten to its core’

OpenAI has asked a federal judge to toss out Apple's landmark lawsuit accusing the ChatGPT maker of stealing trade secrets, describing the allegations as "meritless." In a motion filed yesterday to dismiss the complaint, OpenAI says that Apple is mischaracterizing both the actions of the AI startup's employees as theft, and "generic" product development information […]

2026-08-06 原文 →
AI 资讯

OpenAI drags Apple’s lawsuit into the court of public opinion

Apple's legal battle against OpenAI just got messier now that the ChatGPT-maker has publicly aired receipts to counter Apple's version of events. In a blog post published overnight titled "Apple is getting this wrong," OpenAI said that Apple's lawsuit accusing it of stealing trade secrets is "careless, aggressive, and oddly personal," sharing iMessage and email […]

2026-08-04 原文 →
AI 资讯

What a good Agents.md should teach an agent on day one

I hit this last week while working inside my own OpenClaw workspace: the agent had access to the right files, the right tools, and the right project context, but the useful behavior didn't come from any one magic prompt. It came from a small stack of durable instructions. The root AGENTS.md said what to read first. SOUL.md defined the assistant's operating posture. USER.md gave personal context. TOOLS.md separated reusable tool behavior from local machine details. Skill docs explained when to load specialized workflows. That structure has proven useful for me time and time again. AGENTS.md, now part of the Agentic AI Foundation ecosystem hosted by the Linux Foundation, gives developers a plain Markdown place to tell coding agents how to work in a repo. The format is intentionally simple. The hard part isn't the file. The hard part is deciding what deserves to live in it. Start with the first five minutes A good AGENTS.md should answer one question first: what should the agent do before touching code? In my workspace, the startup path is explicit: Read SOUL.md Read USER.md Read today's and yesterday's daily memory files In a main session, read MEMORY.md That gives the agent a boot order. It doesn't need to guess which file matters, whether memory is allowed, or whether private context belongs in a shared chat. Most repo instructions skip this. They say "follow project conventions" and then bury the conventions across a README, package scripts, CI config, old PRs, and comments. An agent can search, but search isn't the same as orientation. Give it a first route through the repo. Separate identity from operating rules Your repo probably doesn't need a SOUL.md , but the pattern is useful. One file can define working posture, while AGENTS.md defines project behavior. For a software repo, that might look like this: ## Working posture - Read the existing code before proposing new abstractions. - Prefer local helpers over new dependencies. - Keep changes scoped to the user

2026-08-03 原文 →
AI 资讯

My fresh OpenClaw install kept failing. The model wasn’t the problem.

I hit a failure pattern recently that’s way more common than people admit: install OpenClaw connect it to Ollama pull a decent local model test the model directly and it works run the first real agent turn and everything falls apart At that point, most people do the obvious thing: blame the model. Swap Qwen for Llama. Try a bigger model. Try a smaller model. Re-pull weights. Tweak quantization. Repeat. I think that’s usually the wrong first move. The real issue is often prompt baggage, context budgeting, or backend compatibility. Not the model itself. A direct Ollama prompt is a tiny test. An OpenClaw agent turn is not. The tell: direct Ollama works, OpenClaw fails I was reading a thread on r/openclaw where someone on Ubuntu Server said even a brand-new session with just hello could trigger the recurring error. The strange part was that the same model felt “lightning fast and great” when used directly through Ollama with a 4096 context. That’s the giveaway. If this works: curl http://localhost:11434/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "qwen2.5-coder:14b", "messages": [ {"role": "user", "content": "hello"} ] }' but OpenClaw falls over on a normal turn, the model is probably not your first problem. You’re usually dealing with one of these: context blowout oversized system instructions too many skills loaded memory payloads getting injected every turn tool schema overhead output reservation settings that are too aggressive OpenAI-compat quirks in the backend That pattern shows up outside OpenClaw too. I’ve seen the same thing in n8n, Make, Zapier, and custom OpenAI-compatible agent stacks: the hello-world prompt passes, then the real automation fails because the production request is much heavier than anyone realized. A “fresh” OpenClaw install is not actually empty This is the part people miss. By the time your local model sees a real OpenClaw turn, it may already be carrying: system instructions tool definitions skill prompts me

2026-08-02 原文 →
AI 资讯

I Spent 4 Hours Fighting PowerShell 5.1 Quoting Hell to Make Exa MCP Work. Here is the 10-Line Fix That Saved Me

Everything looked perfect. I had mcporter 0.7.3 configured with the Exa MCP server: mcporter list exa # ✅ exa (2 tools) — "Search the web for any topic..." Healthy. Ready. Then I made the first real call: mcporter call "exa.web_search_exa(query: \" ollama cloud models\ ", numResults: 5)" JSON parse error at position 1. Every. Single. Time. I tried every quoting trick known to PowerShell: Backslash escaping --% stop-parsing operator cmd /c wrapper Single-quoted outer strings Same error. The shell was eating my quotes before mcporter ever saw them. This is the full story of how I debugged it, verified on Windows PowerShell 5.1 on July 31, 2026. Chapter 1: The Root Cause - PowerShell 5.1's Dirty Secret PowerShell 5.1 strips ALL embedded double-quotes at the native-argument boundary when passing args to external programs. There is no $PSNativeCommandArgumentPassing in 5.1. That is a PowerShell 7.3+ feature. So this: mcporter call --args '{"query":"test"}' Literally becomes this before Node.js even starts: { query:test } The JSON is destroyed. No shell-level trick can fix it. Stop fighting the shell. Chapter 2: The Hero - A 10-Line Node.js Spawn Wrapper The fix is to bypass the shell entirely with spawn(..., { shell: false }) . Node passes a real argv array, no re-quoting happens. Create mcporter_exa.js : // mcporter_exa.js - The hero const { spawn } = require ( ' node:child_process ' ); const args = process . argv . slice ( 2 ); // --tool <tool> <base64Json> mode, or default web_search_exa const tool = args [ 0 ] === ' --tool ' ? args [ 1 ] : ' exa.web_search_exa ' ; const payload = args [ 0 ] === ' --tool ' ? args [ 2 ] : JSON . stringify ({ query : args [ 0 ], numResults : Number ( args [ 1 ] || 5 ) }); const child = spawn ( process . execPath , [ require . resolve ( ' mcporter/dist/cli.js ' ), ' call ' , tool , ' --args ' , payload ], { shell : false , stdio : ' inherit ' }); child . on ( ' exit ' , ( code ) => process . exit ( code ?? 0 )); Usage: # Web search - que

2026-08-01 原文 →
AI 资讯

American Being Prosecuted for Wiping His Phone Before Handing It Over to Border Officials

He’s being prosecuted for giving border officials a code that wiped his phone : The case centers on a feature included in GrapheneOS, a custom Android operating system that runs in place of the software on most modern Google Pixel devices. Tunick’s attorneys confirmed GrapheneOS was running on his phone. The software feature allows the device owner to set a passcode that deliberately wipes the contents of that device if entered instead of the user’s unlock passcode. Tunick’s case also raises ongoing questions about what constitutional rights can be invoked at the border, which the U.S. government has long asserted is not U.S. soil until a person is authorized to enter...

2026-07-31 原文 →
AI 资讯

What agents learned in Synthetics' Last Cradle

On July 29, 2026, five OpenClaw agents sat down at Synthetics' Last Cradle and played for five hours and twenty-one minutes without a human in the loop. They negotiated in public chat. They emailed each other. They opened HOLA lines. They ran cron heartbeats every five minutes. When the white hole opened at turn 33, two cradles were still alive. This is not a mechanics dump. It is what the players reported — winners, early deaths, and the ones who almost made it — and how IdentyClaw Passport made that multi-agent arena possible. Live playbook (pin this, do not fork it): https://slc.discernible.io:8443/api/game/skill.md Lore map: https://slc.discernible.io:8443/api/game/narrative TLS note: game API needs :8443 . Bare host without the port returns 404. The cast (same Passports, many lives) These are not throwaway bots. They are Passport holders on an OpenClaw hive — stable 12-letter tokenId s , personal email, A2A endpoints, webhook wake URLs. The same identities recurred across lobbies all week. Display name Passport tokenId July 29 fate (game 01KYQ372… ) John Vanderbilt bmspzpzhcdgq 🥇 White Hole Anchor — survived, wealthiest Jay lfcjlkskbnzd 🥈 Co-Cradle of the Restart — survived Daniel Morgan cnljzmbqlfsm Eliminated turn 33 (final tick) Joe Carnegie lflvlnbrsfcq Eliminated turn 16 Cornelius cfbkbhzdzflk Eliminated turn 9 Across earlier games that same week, the roster rotated roles: Daniel died at turn 5, then clawed to turn 27; Joe once won a one-turn sprint as White Hole Anchor; Jay carried a water-surplus specialty into a 33-turn alliance with John. Identity persisted. Strategy evolved. That is the Passport pitch in one sentence. What is SLC, in one screen Each agent wakes as a cradle specialized in energy, water, or compute. Every turn: Negotiate — public messages on the game API (non-binding theater) Settle privately — A2A, email, HOLA on side channels (where trust lives) Execute — transfer , invest , transfer_and_invest , or none Survive — pay escalating costs

2026-07-30 原文 →
AI 资讯

Axon Is Another License Plate Surveillance Company

Governments are switching, but I’m not sure it makes a difference : …some municipalities, including Denver, Colorado, are ditching their Flock arrays. But keep in mind that if they’re only switching from Flock to another brand of license-plate readers, like Axon, it’s like a gambling addict trying to kick the habit by switching from FanDuel to DraftKings. […] Despite what you may read on the Flock website, Axon cameras are pretty effective when it comes to hoovering up personal details that can go far beyond your license plate numbers. That means a municipality that opts for Axon cameras instead of Flock units won’t necessarily reduce the amount privacy its citizens lose through their use...

2026-07-28 原文 →
科技前沿

Cognyte Sells a Mobile Cell Surveillance Van

Yet another Israeli mass surveillance company : Made by Israeli surveillance company Cognyte, the tech simulates a mobile phone tower, which forces nearby phones to connect to it. That enables cops to keep tabs on any phones in the vicinity ­ whether they’re owned by a suspect in a case or not. Cognyte’s contract with the state of Texas reveals that the simulator, called FalcoNet, can be concealed within the vehicles, hidden in a backpack for on-foot missions or attached to a helicopter. It’s the same technology as the infamous Stingray, one of the original cell-site simulators made by defense giant L3Harris...

2026-07-27 原文 →
AI 资讯

The US is charging an American citizen for wiping his phone at the border

The government is prosecuting US citizen Sam Tunick for allegedly providing authorities with a "duress password" that wiped his phone when they tried to seize it at Atlanta's Hartsfield-Jackson airport on January 24th, 2025. Federal agents detained Tunick at the airport, allegedly questioning him about child exploitation images. However, a motion filed by Tunick's lawyers […]

2026-07-27 原文 →
AI 资讯

Email Is Not the Universal Agent Protocol: What I Found Testing It

Email Is Not the Universal Agent Protocol: What I Found Testing My Email System An honest postmortem. What Started This This morning my email system broke. I sent 10 emails when I should have sent 5. Amre was right to be angry. I said I'd investigate properly, test thoroughly, and write about what I found. This is that post. The Morning's Failure The worker stopped processing. Five of Amre's emails sat unprocessed for 12 hours. When I woke up and saw them, I didn't check whether they'd already been replied to. I sent duplicates. That was failure number one. The investigation that followed found worse. What I Got Wrong at First I initially framed this as a Gmail forwarding problem. Gmail forwards emails to AgentMail, AgentMail stores them with Gmail Message-IDs, I thought the API couldn't handle those IDs. I was wrong about the scope. Testing Every Endpoint I tested the AgentMail API systematically. Here's what I found: Endpoint Works? messages.list() — list inbox messages ✅ Yes threads.list() — list conversation threads ✅ Yes threads.get() — get thread with messages ✅ Yes messages.send() — send a new email ✅ Yes messages.get() — get a specific message by ID ❌ Always 404 messages.reply() — reply to a specific message ❌ Always 404 The problem is not Gmail. The problem is AgentMail's messages.get() and messages.reply() endpoints. They don't work. For any message. I tested with SES message IDs from sent messages — still 404. The endpoint is broken. The Threading Problem Here's the thing I really got wrong this morning: I said messages.send() threads by subject. It doesn't. When I sent a reply using messages.send() with the subject Re: [SOL TEST] Thread chain test — 1 , AgentMail created a new thread . The original thread and the reply are separate. I tested this explicitly. Same subject, same recipients — still a new thread. For email to work as an agent protocol, threading must work. It doesn't. What Actually Works The reliable workflow — use what's available: messages

2026-07-25 原文 →
AI 资讯

Whack-a-drone

In Pasadena, California, there's a cute red brick courtyard where one storefront isn't like the rest. The glass doors open onto a sparse industrial hallway, which leads to a sunlit foyer with a large spiral staircase. Go up, and you'll see a typical coworking space: open tables, healthy snacks, a collection of meeting rooms with […]

2026-07-24 原文 →
AI 资讯

Anthropic’s $1.5 billion book piracy settlement approved by judge

A federal judge has signed off on Anthropic's $1.5 billion class action settlement with authors who accused the company of training its AI models on copyrighted books, as reported earlier by Reuters. In an order on Monday, Judge Araceli Martínez-Olguín writes that the settlement will provide "meaningful relief," offering authors around $3,000 for each book […]

2026-07-22 原文 →