AI 资讯
Twitch will let parents stop their teens going live
Twitch is giving parents more control over how their children are using the streaming platform, including the ability to block them from broadcasting entirely. Parental controls are now available that allow guardians to link Twitch accounts with their 13- to 17-year-old children, providing account management features and a weekly email summarizing their teen's activity, including […]
AI 资讯
Google announces Gemini 3.6 Flash and cybersecurity AI, teases 3.5 Pro and Gemini 4
There are new 3.6 and 3.5 models today, but Google is already training Gemini 4.
AI 资讯
AgentManager
Never miss a Claude Code session waiting for your input Discussion | Link
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Overflight
Identify every aircraft in your sky. Discussion | Link
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 […]
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Motionly
AI-native motion graphics editor Discussion | Link
产品设计
Garmin CIRQA™ Smart Band
The screenless health + fitness tracker with no subscription Discussion | Link
工具
Instagram now lets you swap out the music in your old posts
With the new "Replace Audio" tool, users can update the music on their post at any time while keeping the post's existing likes, comments, shares, and reach intact.
开发者
Instagram will let users endlessly swap the audio on old posts
There's a symbiotic - and sometimes frustrating - relationship between social media sites and the creators that depend on them. Platforms need influencers' and creators' content to keep consumers on their apps; the creators, in turn, need to be able to reach those audiences to justify creating their content in the first place. Creators want […]
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Tesla Robotaxis go to Florida
It must be earnings day, because Tesla is making a Robotaxi announcement. The company said in a post on X that it was launching its Robotaxi service in Orlando and Tampa, attaching a pair of maps that show each city's service area. No word on fleet size or whether interested customers would be able to […]
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A Sneaky Hacking Tool Targeting AI Infrastructure Is Lurking in Victims’ Blind Spots
A new type of malware can worm deep into AI coding systems to steal data and logins—and can flip a “death switch” to destroy files and keep out real users.
科技前沿
Meta Horizon+ subscriptions now include Xbox Game Pass starter edition
Meta Horizon+ subscriptions are now bundled with the starter edition of Xbox Game Pass.
AI 资讯
Threads rolls out parental supervision tools
With the new tools, parents and guardians will be able to view their teen's time spent on Threads, set daily time limits, adjust sleep mode, and manage their privacy settings.
AI 资讯
How to build interactive experiences with canvases
Canvases turn AI into interactive workspaces where you can visualize information, explore workflows, and take action across complex tasks. The post How to build interactive experiences with canvases appeared first on The GitHub Blog .
AI 资讯
Fixing "Can't get distribution attribute of table" in GBase 8a
When a gbase database cluster experiences an unclean shutdown — a sudden power loss or kernel panic — some metadata that was still in memory may never make it to disk. This can leave the critical gbase.table_distribution table with missing rows, causing queries against certain tables to fail with the error: ERROR 1149 (42000): (GBA-02SC-1001) Can't get distribution attribute of table `testdb`.`t2_test`, please check your gbase.table_distribution. The Symptom The affected table enters a contradictory state: Dropping it returns Unknown table . Re‑creating it returns Table already exists . The data files exist on disk, but the metadata record that describes how the table is distributed is gone. Root Cause GBase 8a stores critical table metadata — distribution type (hash or random), replication status, hash column — in the system table gbase.table_distribution . After an abrupt shutdown, this table may have missing entries, causing the cluster to lose track of the table's distribution properties. Recovery Options Option 1: Re‑insert the Metadata Row (Keeps Data Intact) This is the recommended approach when the data must be preserved. Insert the missing row directly into gbase.table_distribution . -- Insert the lost metadata record INSERT INTO gbase . table_distribution VALUES ( 'testdb.t2_test' , 'testdb' , 't2_test' , 'NO' , NULL , NULL , NULL , 'NO' , 2 ); -- Verify the row is now present SELECT * FROM gbase . table_distribution WHERE index_name LIKE '%t2_test%' ; Key fields: isReplicate : YES if the table is replicated, otherwise NO . hash_column : The distribution key column name (if hash‑distributed); NULL for random distribution. data_distribution_id : A numeric ID. Copy the value from another healthy table in the same database to keep it consistent. After inserting, restart the gcluster service so the metadata takes effect (the table_distribution table is managed by gcluster, not gnodes): gcluster_services gcluster restart The table should now be queryable again.
AI 资讯
How to Use Kimi K3 with Claude Code, Cursor, and Cline
Kimi K3 took first place in Arena's Frontend Code evaluation the week it launched, and it holds a 1M-token context — but Moonshot doesn't ship a coding agent, and your coding agent doesn't ship Kimi K3. Claude Code is locked to Anthropic's API by default, Cursor to its own backend, Cline to whatever key you hand it. LLM Gateway bridges that gap. It speaks both the Anthropic and OpenAI API formats, so the tools you already use can run Kimi K3 — or any of 200+ models — with a base-URL change. Here is the exact setup for each tool. Kimi K3 in Claude Code Claude Code talks to any endpoint that speaks Anthropic's /v1/messages format, which LLM Gateway does natively. Three environment variables: export ANTHROPIC_BASE_URL = https://api.llmgateway.io export ANTHROPIC_AUTH_TOKEN = $LLM_GATEWAY_API_KEY export ANTHROPIC_MODEL = kimi-k3 claude That's the whole migration. Every request now routes through LLM Gateway to Kimi K3, and every request shows up in your dashboard with its exact cost, token counts, and cache-hit rate. One refinement worth adding: Claude Code uses a second, smaller model for routine background work, and you can point it at something cheap — or free: export ANTHROPIC_SMALL_FAST_MODEL = glm-4.7-flash-free That puts K3 on the hard reasoning and a $0 model on the housekeeping. Kimi K3 in Cursor Cursor routes its chat / plan panel (Cmd/Ctrl + L) through a custom OpenAI-compatible endpoint. Setup: Open Cursor Settings → Models Add your LLM Gateway key under OpenAI API Key Enable Override OpenAI Base URL and set it to https://api.llmgateway.io/v1 Add kimi-k3 as a custom model and select it Be aware of the boundary: Cursor's Composer, inline edit (Cmd/Ctrl + K), and autocomplete are locked to Cursor's own backend and will not route through any external endpoint. Plan and chat with K3's full 1M context in Cursor; if you want K3 driving the actual agent loop, use Claude Code or Cline instead. Kimi K3 in Cline Cline is the straightforward one — it's built to bring y
AI 资讯
Building a Production AI Pipeline for a UK FinTech Client at Tittri — What Actually Happened
After five years of shipping features at Tittri, the team gave me a piece of feedback that stung a little: I was good, but I only ever built what I was asked to build. And we delivered, end to end, every week. From dashboards to multi-step workflows to third party integrations, all of it to make dense workflows understandable. Somewhere along the way I'd become all about business critical web apps, where the frontend is not just visual, it's how people execute operations reliably. But it just wasn't enough for me. So in January 2026 I stopped waiting to be asked, and pitched an AI integration into a UK-based fintech client's product, one that handles real business loans. When I finally presented the idea to the team and the client, after enough brainstorming and planning and identifying the best way for the brokers to benefit from it, expectations rose. No prior AI integration experience, no matching tutorials, real users, real data, real money. Then I had to actually build it. What is the client and why AI The client is one of the UK's pre-eminent business finance brokers and comparison services that combines advanced technology with a team of finance experts to help small and medium-sized enterprises (SMEs) and their advisors find, compare, and apply for the most appropriate and affordable funding options from across the entire market. The client's B2B product is a commercial finance brokerage SaaS, where brokers manage deals, calls, emails, documents, lenders, AIPs (Agreement In Principle), credit/KYC, corporate structures, properties...etc. The brokers use the SaaS to run the whole lifecycle of a deal, and before AI every single step of it was manual. A typical deal goes like this: An enquiry comes in by call or email, something like "my client needs £400k to buy out a GP partner". The broker gets on a discovery call that can run 30–90 minutes, writes up the notes afterwards, creates the deal, and then starts gathering everything a lender will want to see. Finan
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A Practical WooCommerce Customer Support Workflow for Small Teams
Originally published at https://eveningdesk.cloud/blog/woocommerce-customer-support-workflow.html . WooCommerce support often starts in a shared mailbox and ends in several tabs. A customer asks where an order is. An agent searches the inbox, opens the store admin, finds the order, checks fulfilment, then returns to write a reply. That sequence is manageable at low volume. It becomes fragile when several people share the work or when the same question arrives all day. The goal is not to add a complicated service desk. It is to make the support workflow reliable: one owner, the right order context, and a reply a human has reviewed. Start With One Support Inbox Use a dedicated address for customer questions, such as support@yourstore.com , rather than mixing them with supplier, marketing, and personal email. Every incoming request should have a clear status: New, when nobody has handled it. Assigned, when one person owns the reply. Waiting, when the customer or carrier needs to respond. Resolved, when no further action is needed. The important part is ownership. If two people read the same message and neither knows who is replying, the customer waits. If both reply, the customer receives conflicting information. Keep Order Context Beside the Conversation Support agents should not guess about an order. A useful workflow links the conversation to the order reference, then checks the information that matters for the question: Order number and purchase date. Payment and fulfilment status. Items, quantities, and shipping method. Tracking or carrier information, when it exists. Previous support messages about the same order. For a connected WooCommerce store, eveningDesk can sync an order record into the support workspace. The agent still reviews the information and decides what to promise. The software provides context. It does not invent delivery dates or approve refunds on its own. Use a Repeatable Reply Process Most store questions fall into a small set of categories: d
AI 资讯
How Normal Software Engineers Actually Use AI in Their Daily Work
How Normal Software Engineers Actually Use AI in Their Daily Work Let's cut through the hype. You're not building the next AGI. You're a working software engineer with deadlines, legacy code, and a backlog that never shrinks. So how do you actually use AI tools in your day-to-day work? After surveying hundreds of developers and reflecting on real-world usage patterns, here's what normal software engineers are doing with AI—no Silicon Valley theatrics required. The Mundane But Invaluable: Code Completion and Boilerplate The most common use case is the least sexy: letting AI handle repetitive code. GitHub Copilot, Cursor, and similar tools excel at generating boilerplate that you'd otherwise copy-paste from Stack Overflow or previous projects. Real example: Writing CRUD endpoints in Express/TypeScript: typescript // Type this comment and let AI complete: // Create a REST endpoint for user registration with email validation app.post('/api/users/register', async (req: Request, res: Response) => { try { const { email, password, name } = req.body; // Email validation const emailRegex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/; if (!emailRegex.test(email)) { return res.status(400).json({ error: 'Invalid email format' }); } // Check if user exists const existingUser = await User.findOne({ email }); if (existingUser) { return res.status(409).json({ error: 'User already exists' }); } // Hash password and create user const hashedPassword = await bcrypt.hash(password, 10); const user = await User.create({ email, password: hashedPassword, name }); res.status(201).json({ userId: user.id, email: user.email }); } catch (error) { res.status(500).json({ error: 'Internal server error' }); } }); Did AI write perfect code? No. But it gave you scaffolding to refine, saving 10-15 minutes of typing. That's the real win. The Game-Changer: Explaining Legacy Code and Obscure APIs Every developer inherits someone else's mess. AI tools shine when deciphering undocumented code or unfamiliar libraries. Pract
AI 资讯
Lego just unveiled a 1,500-piece X-Files set, complete with Mulder, Scully and a grey alien
The first Lego X-Files set costs $200 and will be available in August.