标签：#t

How I got here On principle, you will never catch me parading myself as a some sort of expert data scientist. Technically, that's what I do in my day job, but I know I still have so much to learn because the field is broad, and to truly become expert requires dangerously ambitious levels of work ethic. I think I'm a functional data scientist who learns more as I encounter new problems daily. I'm writing this piece because in the last week or two, precisely three people have asked me questions related to transitioning into data science. As such, I thought to unify my thoughts around the topic so that I can refer anyone else who asks here--if anyone else ever asks. This article assumes you're already familiar with some of the data science entails such as data analysis, model training, prediction, etc, so I will not be doing a lecture series, just addressing some of the disconnects I have observed in conversation with people looking to transition to the field. Initial Excitement In 2026, it's easy to see what claude or chatGPT is doing and go "What sorcery is this? I must learn this trick!" and then reach out to the closest person you know who has ever mentioned anything about data or machine learning to find out how you can transition into AI. First of all, transitioning into "AI" is such a broad way to look at it. It is analogous to saying "I want to emigrate to Africa, show me how". But that's forgivable too. To cut short your initial excitement, or maybe redirect it, playing with a locally hosted LLM or making API calls to the DeepSeek endpoint is not data science, or machine learning or "AI". It's coding. And if you want to go down that route, you're better of focusing on software engineering. I say this because when you work with LLMs, the finished models to be specific, it's like using any other SaaS API out there. The difference being that you're interacting with a much less deterministic interface. But the rest of the work you do around it is pretty much a det

Most merchants know they have unused files. Far fewer realize they're accumulating AI-generated media they never intended to keep. There's a problem quietly growing inside thousands of Shopify stores right now. It's not abandoned carts. It's not slow page speeds. It's not even the 400 unused product images you already know you should deal with. It's something newer, and most merchants have no idea it's happening. The Rise of AI-Generated Commerce Content Over the past two years, AI image tools have gone from novelty to routine. Shopify Magic. Canva AI. Midjourney. ChatGPT image generation. Adobe Firefly. Background removers. Lifestyle photo generators. Product shot enhancers. Merchants are using these tools constantly — to mock up new products, test background options, generate seasonal variants, create ad creatives, experiment with lifestyle photography. The workflow feels clean: generate a few options, pick the best one, move on. Here's what's actually happening on the backend. Every time you use Shopify's native AI tools to generate, edit, or enhance an image, Shopify quietly deposits files into your media library. Not just the one you kept. All of them. The rejected generations. The experimental edits. The "let me try one more variant" files. The abandoned attempts from six months ago when you were testing a new product that never launched. Every. Single. One. Most merchants assume the files they don't choose disappear. They don't. The lifecycle looks something like this: ┌─────────────────────┐ │ AI Image Generation │ └──────────┬──────────┘ │ ▼ ┌─────────────────────┐ │ Rejected Variants │ │ • Drafts │ │ • Test Images │ │ • AI Edits │ └──────────┬──────────┘ │ ▼ ┌─────────────────────┐ │ Hidden Media Files │ │ Accumulate Over Time│ └──────────┬──────────┘ │ ▼ ┌─────────────────────┐ │ AI Clutter │ │ Invisible Technical │ │ Debt │ └──────────┬──────────┘ │ ▼ ┌─────────────────────┐ │ Reduced Media │ │ Governance │ │ • More Noise │ │ • Less Visibility │ │ • Hard

As I'm observing engineers, I notice that most of them share the same characteristic: unending loads of curiosity. You, software developers, are deeply interested in how things work underneath; you implement, break, troubleshoot, fix, and break again. You create apps that people use everyday and by doing so, you shape the digitalised world we live in today. Now let me share something personal: I am terrified of breaking things. I am often terrified to such an extent that I find it hard to breathe. I am suffering from something called Generalised Anxiety Disorder (GAD), which basically means I am allergic to uncertainty. While most people see trying something new as exciting, for me it's a source of stress. Every unknown step, every unfamiliar process, every situation where I don't know what comes next — it triggers something. My brain immediately goes to the worst-case scenarios. "I can't do this." "I'll do it wrong." "What if something breaks?" These thoughts don't just pop up and disappear — they pile on top of each other until they become paralyzing. But this story isn't about anxiety — it's about how good UX can change a moment from overwhelming to manageable. And how you, as a software developer, can make a real change for people who are struggling. The app that saved my day A few months ago I decided to change my mobile operator. The alternative offer had much better terms that sounded really appealing to me. No long-term contract, competitive prices, support for eSIM for travellers abroad – in short: very flexible. Head held high, I went to the new operator's office to ask them to transfer my number. But the agent quickly wiped the smile off my face. "Yes, this offer is flexible, but you need to do all the operational work yourself in the app. I can only offer you a regular long-term contract," he said. He gave me my new SIM card, and I, with a long face, went to the nearby cafe. The thought that I had to transfer my number myself felt daunting. "What if I do

This year's Summer Game Fest turned out to be a good one for fans of Japanese RPGs. First, the conclusion of the Final Fantasy VII remake trilogy was announced at SGF Live, and now we have the long-awaited return of the Persona series. Atlus confirmed Persona 6 exists with a brief teaser, but aside from […]

Notion's head of product said he was "astonished" at “the amount of people RT-ing this."

Microsoft has created a special edition Xbox Series X to celebrate 25 years of the console. The Xbox 25th-anniversary console takes design cues from the original Xbox console, with both the console and controller featuring a translucent green design. "For the first time, we're bringing a translucent design to Xbox Series X, drawing inspiration from […]

Minecraft Dungeons 2, a sequel to Microsoft's dungeon crawler spinoff Minecraft Dungeons, will be released on September 29th. The company originally revealed the game in a brief trailer in March, promising a fall 2026 release window. Here's how Microsoft described it at the time: Return to the world of Minecraft Dungeons in an all new […]

Just a few days after pushing Fable out of 2026, Microsoft showed off more footage of Fable, the first new entry in the storied RPG franchise since 2010's Fable III, at its Xbox Games Showcase on Sunday. The company also announced a specific release date: February 23rd, 2027. Though if you get the Premium Edition, […]

As part of its Xbox Games Showcase on Sunday, Microsoft revealed new details about Halo: Campaign Evolved, the upcoming remake of Halo: Combat Evolved's campaign mode. The remake will debut on Xbox Series S / X, PC, and PS5 on July 28th. Today's mission trailer includes a first look at Operation: Meteorite, a new three-mission […]

Apparently, the "return of Xbox" means a retreat from other platforms. At its Xbox Games Showcase today, Microsoft revealed that Gears of War: E-Day - which was previously rumored for a PS5 launch in addition to Xbox and PC - will not be coming to PlayStation. It'll be an Xbox console exclusive and is launching […]

Have you ever wondered what the most indispensable app is for your favorite musician or how the world’s tech CEOs stay focused? Well, that’s the sort of thing we aim to uncover in our Verge Weekend Questionnaire. Think of it as a spiritual successor to Five Minutes on the Verge. Every Saturday, a different guest […]

The console industry is in a weird place, and both Xbox and PlayStation have a chance to change the narrative a bit with their showcases at Summer Game Fest. Sony did that by focusing on the single-player titles it’s known for, and then it was Microsoft’s turn. The Xbox Games Showcase was focused mainly on […]

For enterprise AI/security teams, what would make AI SPM useful rather than just another category label? Is the important part AI asset inventory data access mapping, agent permissions, prompt/data monitoring, policy enforcement or something else? submitted by /u/Efficient_Western609 [link] [留言]

"Chat is dead" — at least, according to a senior OpenAI employee.

Welcome back to TechCrunch Mobility — your central hub for news and insights on the future of transportation.

Every online Fake Data Generator tool I used had the same quiet flaw: whatever you paste gets POSTed to someone's server. For a Fake Data Generator, that paste is often exactly the sensitive thing — a token, a config, an API response. So I built Fake Data Generator to not do that. Generate fake names, emails, UUIDs, addresses — custom columns, CSV/JSON export. 100% browser-side — and it runs entirely in your browser, so there's nothing to send and nothing to breach. You don't have to take my word for it: open DevTools → Network, use the tool, and watch the tab stay empty. One HTML file, View-Source-able. https://faker.platotools.com/ It's part of platotools.com — a set of single-purpose, client-side dev tools. Feedback and edge-case bug reports very welcome.

If you have an outdoor space that needs some extra lighting, either for fun or security reasons (or a mix of the two), the Govee outdoor lamp post light is a good pick that’s 23 percent off its regular price right now. Typically retailing for $260, the Govee outdoor lamp post light is available for […]

Somewhere along the way, computing became disposable. Devices became sealed. Systems became rented. Ownership became licensing. Repairability disappeared. Infrastructure moved away from the user and into distant cloud platforms. And I think we lost something important because of it. Lately, I’ve found myself becoming increasingly interested in hardware again. Not just software. Not just cloud systems. But actual computing devices. Servers. Home infrastructure. Repairable machines. Set-top systems. Local AI appliances. Sovereign computing. Because I believe the next era of computing will belong to people who own their infrastructure again. The Provider Box Realization One thing that kept sticking in my head was this: Almost every home in America already has a provider box. A Comcast box. An AT&T gateway. A router. A modem. A streaming box. People are already comfortable with the idea of a dedicated computing appliance sitting in their home quietly powering their digital life. That realization changed how I thought about computing infrastructure. What if those boxes worked for the user instead of the provider? What if they: hosted local AI, managed home storage, coordinated smart devices, powered media systems, handled automation, protected privacy, synchronized intelligently, and operated as sovereign infrastructure? That idea became part of the thinking behind KiwiHome. The Return Of Home Infrastructure For a long time, the industry moved toward centralization. Everything shifted toward: SaaS, subscriptions, streaming, cloud storage, cloud intelligence, and rented operational environments. Convenient? Absolutely. But also fragile. If: pricing changes, services disappear, companies shut down, APIs get revoked, or platforms change policies, entire workflows collapse overnight. I think people are starting to feel that tension. Especially creators. Especially businesses. Especially technical users. That’s why I believe we’re going to see a major resurgence in: home serv

This is a submission for the GitHub Finish-Up-A-Thon Challenge What I Built I built TradeWeave — a B2B + B2C fashion marketplace that connects small scale weavers and manufacturers directly to customers and retailers, eliminating middlemen entirely. The project started as a notebook idea at midnight: "What if factory workers and artisans could sell directly, keeping the full margin instead of losing 40% to supply chain bloat?" Demo 🔗 Live Demo — TradeWeave — Try it right now, no installation needed How to use: Hover over any dress card — it flips to reveal sizes Pick a size, adjust quantity, click "Add to cart" Click "Sign up" to see the premium registration flow Click the TradeWeave logo 5 times to unlock the hidden admin dashboard Click "Wholesale" tab to see direct manufacturer listings 💻 Source Code: github.com/Deeraj25/tradeweave The Comeback Story Before: Idea scribbled in a notebook at midnight Zero code written Zero deployment Tucked away under "someday projects" Status: Abandoned After: Full-featured marketplace in production ~550 lines of polished HTML/CSS/JavaScript Deployed live on Netlify + GitHub Pages Anyone can use it instantly Real product with real features Core fixes: Built the entire marketplace from scratch (this was a notebook idea, not existing code) Implemented hover-to-flip cards with CSS 3D transforms (perspective + rotateY) Created responsive product grid with auto-fill layout Built localStorage persistence for cart + admin state What Changed, Fixed, and Added Features added: 5 product categories with 20+ items Hover-flip interaction (no page reload needed) AI Try-On modal with upload UX Wholesale B2B portal with manufacturer data Hidden admin dashboard (5-click unlock) Aurora-style signup with animated hero and steps Real-time analytics dashboard (revenue, top categories, order table) Mobile-responsive design Keyboard + mouse support Polish & optimization: Custom animations (staggered reveals, floats, shimmers) Cormorant Garamond typograp

I built something I desperately needed: daily AI audio lessons from real developer trends (plus a Dutch coach for inburgering B1). The hardest part wasn't the AI. It was figuring out how to score genuine rising skills vs. one-day noise. I ended up building a cross-day momentum signal that rewards skills accelerating over 3+ days and dampers spikes. But I'm stuck on the next problem: how do you personalize this without storing user data? (I'm privacy-first, so no subscriber DB — Telegram holds the member list.) If you've solved this, I'd love your take. And if you're learning Dutch + coding, I'd appreciate you trying it and telling me what's useless. What I'm curious about: Is the momentum signal actually working — am I surfacing real trends or just noise? Would the Dutch coach be useful for expat developers in NL, or is it too niche? Technical details (for those who care): • 7 sources: GitHub Trending, HN (Who-is-Hiring + front page), Stack Overflow tag deltas, dev.to, Reddit, Lobste.rs • Map-reduce skill extraction with deterministic attribution (corpus scan, not LLM tally) • Grounded briefs: reads actual source text via Jina + Exa, cited sources • Delivered via Telegram (audio + PDF), Spotify podcast, email • Privacy: PII redacted at ingestion, no subscriber data stored Live: https://yusuprozimemet.github.io/LearnX-Radar/ GitHub: https://github.com/Yusuprozimemet/LearnX-Radar (P.S. This is still beta — I'm looking for feedback, not users. If you try it, tell me what's useless, not what's good.)