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AI 资讯

Google will now tell you if an ad was made with AI

You can see if ads on Google Search, Google Discover, and YouTube were made or edited using AI from a new section in Google's "My Ad Center," as reported earlier by TechCrunch. The update, announced on Thursday, adds a "created or edited with AI" label under the "how this ad was made" tab. Users can […]

2026-07-10 原文 →
开发者

Google’s Nest Thermostat has hit its best price of the year

If you’re looking for a relatively affordable way to cut down on cooling costs, Google’s Nest Thermostat can help. It’s packed with smart controls and energy-saving features, and right now it’s on sale in white for $79 ($50 off), which is its best price of the year, at Amazon. The smart thermostat is quick to […]

2026-07-10 原文 →
AI 资讯

Microsoft’s patch Tuesdays are about to get bigger

Windows 11 updates could soon include fixes for more security issues at once. Microsoft said in a blog post on Thursday that it's now using AI to "identify potential issues earlier," which means "customers will see a higher volume of security updates included in each security release." Hackers, even amateurs, have increasingly been using AI […]

2026-07-10 原文 →
产品设计

The PocketMage resurrects the PDA with an e-paper screen

Personal digital assistants like the iconic Palm Pilot were one of many devices we thought went extinct with the arrival of the smartphone. But similar to Canon resurrecting a nearly decade-old digital camera to appeal to point-and-shoot fans, Talisman Design is crowdfunding a clamshell PDA called the PocketMage that combines a tactile keyboard with both […]

2026-07-09 原文 →
AI 资讯

Meta says its new AI model is ready to compete on coding

After reentering the AI race with its first in-house Muse Spark model in April, Meta is now opening up the doors to developers with a new model that can plug into AI coding software with the new Meta Model API. Meta says that Muse Spark 1.1 is a "step-change" from the first generation, with improvements […]

2026-07-09 原文 →
AI 资讯

Character.AI wants a piece of the microdrama pie

Character.AI's plan to become more than just an LLM-powered chatbot platform is going beyond interactive books, comics, and audio dramas. Today, the company announced the debut of c.ai Series - short-form, episodic videos designed to be watched and interacted with - on your phone. Unlike traditional microdrama services that feature cheaply produced, live-action shows starring […]

2026-07-09 原文 →
AI 资讯

Insurance Might Be the Most Underrated AI Agent Wedge in YC 2026

AI founders love the glamorous agent stories: coding agents, sales agents, AI doctors, AI lawyers. But if you dig through the YC 2026 batch data, one of the more interesting signals is decidedly unglamorous: insurance . Out of 477 real-ish company records in the current snapshot, 25 match insurance-related keywords — about 5.2% — and 8 companies sit in the Fintech → Insurance subindustry. Not a tidal wave. But it's enough to suggest something worth paying attention to: insurance is quietly becoming one of the better wedges for AI agents that actually ship. The reason is simple. Insurance is wall-to-wall documents, rules, judgment calls, exceptions, approvals, claims, underwriting, and cross-system coordination. In other words: wall-to-wall work that agents can do and humans hate doing. Insurance is not fintech's leftover category Most people file insurance under "slow fintech": aging distribution, legacy systems, long processes, heavy regulation. From an AI builder's perspective, that list of flaws reads more like a list of opportunities. Insurance workflows are highly structured — but not fully structured. Policies, claims files, medical records, photos, repair estimates, payout history, compliance clauses: the inputs are messy and heterogeneous. Yet every step has a crisp objective: is this covered, what documents are missing, how should this risk be priced, can this pass approval. That's not a chatbot problem. It's an agent problem — reading documents, following procedures, calling systems, leaving audit trails, handling exceptions. And precisely because it's complex, insurance is more likely to command real budget than yet another AI writing tool. Agents die without boundaries; insurance comes with them built in The most common failure mode for early agent products: they sound like they can do everything and end up doing nothing well. Insurance workflows hand you boundaries for free: Inventory and asset processes can be automated end to end Medical prior authori

2026-07-09 原文 →
AI 资讯

Prompt Engineering Mastery: The Art of Getting Better AI Responses

Why Prompts Matter More Than You Think The difference between a great AI response and a mediocre one isn't always the model. It's the prompt. Experience this: You ask ChatGPT a vague question and get a vague answer. You ask the same AI a perfectly crafted prompt and get something incredible. The skill gap is massive. Companies are paying prompt engineers $150K+ because mastering prompts directly impacts: Response quality Token usage (costs) Speed of inference User satisfaction The Science of Better Prompts Rule #1: Be Specific, Not Vague BAD : "Write me something about AI" GOOD : "Write a technical explanation of how transformer attention mechanisms work, suitable for a developer with 2 years of ML experience" Specificity reduces hallucinations and increases relevance by 10-50x. Rule #2: Use Roles & Context You are an expert senior software engineer with 15 years of experience. You specialize in system design and scalability. Respond in a way that balances technical accuracy with accessibility. Target audience: Mid-level engineers. How would you design a real-time chat system for 10 million concurrent users? Role-based prompting improves response depth and tone. Rule #3: Provide Examples (Few-Shot Prompting) Classify the sentiment of these reviews: Example 1: "This product is amazing!" → Positive Example 2: "Terrible experience, would not recommend" → Negative Example 3: "It's okay, nothing special" → Neutral Now classify: "The service was slow but the staff was friendly" Examples guide the AI toward your exact expectations. Rule #4: Break Complex Tasks Into Steps Instead of: "Analyze this code and find bugs" Use: "1. First, read through this code carefully Identify any logical errors Check for performance issues List potential security vulnerabilities Provide a summary of findings with severity levels" Step-by-step prompts (Chain-of-Thought) improve reasoning by 20-40%. Rule #5: Specify Output Format Respond in JSON format: { "summary" : "brief explanation" , "key_

2026-07-09 原文 →