#API Call Optimization
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Shopify Webhooks Best Practices
Webhooks are a powerful tool in Shopify that allow developers to automate workflows, integrate third-party services, and keep external applications in sync with store data. By using Shopify webhooks, businesses can receive real-time updates on orders, customers, inventory, and more. However, improper implementation can lead to security risks, data inconsistencies, and performance issues. In this…
#API Call Optimization#E-commerce Automation#E-commerce Scalability#Real-Time Data Sync#Secure Webhook Implementation#Shopify API Integration#Shopify App Development#Shopify Development#Shopify Store Management#Shopify Webhooks#Shopify Workflow Automation#Webhook Performance Optimization#Webhook Security#Webhooks Best Practices
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Kentucky court system needs to fire its web developers.
#are they trying to run ocr/optimization on uploads and then rejecting the filing if the process takes too long or output looks weird#and if not. what are they fucking doing#that requires calls to a paid remote pdf processing api on every fucking upload#this is clearly not a security/virus screening. they don't believe in those. they are the kentucky court system.#the law
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Why Your Business Needs Expert WordPress Development?
1. WordPress: The Platform Built for Growth
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#wordpress web design#WordPress web developers#WordPress experts near me#WordPress website development services
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Vibecoding a production app
TL;DR I built and launched a recipe app with about 20 hours of work - recipeninja.ai
Background: I'm a startup founder turned investor. I taught myself (bad) PHP in 2000, and picked up Ruby on Rails in 2011. I'd guess 2015 was the last time I wrote a line of Ruby professionally. I've built small side projects over the years, but nothing with any significant usage. So it's fair to say I'm a little rusty, and I never really bothered to learn front end code or design.
In my day job at Y Combinator, I'm around founders who are building amazing stuff with AI every day and I kept hearing about the advances in tools like Lovable, Cursor and Windsurf. I love building stuff and I've always got a list of little apps I want to build if I had more free time.
About a month ago, I started playing with Lovable to build a word game based on Articulate (it's similar to Heads Up or Taboo). I got a working version, but I quickly ran into limitations - I found it very complicated to add a supabase backend, and it kept re-writing large parts of my app logic when I only wanted to make cosmetic changes. It felt like a toy - not ready to build real applications yet.
But I kept hearing great things about tools like Windsurf. A couple of weeks ago, I looked again at my list of app ideas to build and saw "Recipe App". I've wanted to build a hands-free recipe app for years. I love to cook, but the problem with most recipe websites is that they're optimized for SEO, not for humans. So you have pages and pages of descriptive crap to scroll through before you actually get to the recipe. I've used the recipe app Paprika to store my recipes in one place, but honestly it feels like it was built in 2009. The UI isn't great for actually cooking. My hands are covered in food and I don't really want to touch my phone or computer when I'm following a recipe.
So I set out to build what would become RecipeNinja.ai
For this project, I decided to use Windsurf. I wanted a Rails 8 API backend and React front-end app and Windsurf set this up for me in no time. Setting up homebrew on a new laptop, installing npm and making sure I'm on the right version of Ruby is always a pain. Windsurf did this for me step-by-step. I needed to set up SSH keys so I could push to GitHub and Heroku. Windsurf did this for me as well, in about 20% of the time it would have taken me to Google all of the relevant commands.
I was impressed that it started using the Rails conventions straight out of the box. For database migrations, it used the Rails command-line tool, which then generated the correct file names and used all the correct Rails conventions. I didn't prompt this specifically - it just knew how to do it. It one-shotted pretty complex changes across the React front end and Rails backend to work seamlessly together.
To start with, the main piece of functionality was to generate a complete step-by-step recipe from a simple input ("Lasagne"), generate an image of the finished dish, and then allow the user to progress through the recipe step-by-step with voice narration of each step. I used OpenAI for the LLM and ElevenLabs for voice. "Grandpa Spuds Oxley" gave it a friendly southern accent.
Recipe summary:
And the recipe step-by-step view:
I was pretty astonished that Windsurf managed to integrate both the OpenAI and Elevenlabs APIs without me doing very much at all. After we had a couple of problems with the open AI Ruby library, it quickly fell back to a raw ruby HTTP client implementation, but I honestly didn't care. As long as it worked, I didn't really mind if it used 20 lines of code or two lines of code. And Windsurf was pretty good about enforcing reasonable security practices. I wanted to call Elevenlabs directly from the front end while I was still prototyping stuff, and Windsurf objected very strongly, telling me that I was risking exposing my private API credentials to the Internet. I promised I'd fix it before I deployed to production and it finally acquiesced.
I decided I wanted to add "Advanced Import" functionality where you could take a picture of a recipe (this could be a handwritten note or a picture from a favourite a recipe book) and RecipeNinja would import the recipe. This took a handful of minutes.
Pretty quickly, a pattern emerged; I would prompt for a feature. It would read relevant files and make changes for two or three minutes, and then I would test the backend and front end together. I could quickly see from the JavaScript console or the Rails logs if there was an error, and I would just copy paste this error straight back into Windsurf with little or no explanation. 80% of the time, Windsurf would correct the mistake and the site would work. Pretty quickly, I didn't even look at the code it generated at all. I just accepted all changes and then checked if it worked in the front end.
After a couple of hours of work on the recipe generation, I decided to add the concept of "Users" and include Google Auth as a login option. This would require extensive changes across the front end and backend - a database migration, a new model, new controller and entirely new UI. Windsurf one-shotted the code. It didn't actually work straight away because I had to configure Google Auth to add `localhost` as a valid origin domain, but Windsurf talked me through the changes I needed to make on the Google Auth website. I took a screenshot of the Google Auth config page and pasted it back into Windsurf and it caught an error I had made. I could login to my app immediately after I made this config change. Pretty mindblowing. You can now see who's created each recipe, keep a list of your own recipes, and toggle each recipe to public or private visibility. When I needed to set up Heroku to host my app online, Windsurf generated a bunch of terminal commands to configure my Heroku apps correctly. It went slightly off track at one point because it was using old Heroku APIs, so I pointed it to the Heroku docs page and it fixed it up correctly.
I always dreaded adding custom domains to my projects - I hate dealing with Registrars and configuring DNS to point at the right nameservers. But Windsurf told me how to configure my GoDaddy domain name DNS to work with Heroku, telling me exactly what buttons to press and what values to paste into the DNS config page. I pointed it at the Heroku docs again and Windsurf used the Heroku command line tool to add the "Custom Domain" add-ons I needed and fetch the right Heroku nameservers. I took a screenshot of the GoDaddy DNS settings and it confirmed it was right.
I can see very soon that tools like Cursor & Windsurf will integrate something like Browser Use so that an AI agent will do all this browser-based configuration work with zero user input.
I'm also impressed that Windsurf will sometimes start up a Rails server and use curl commands to check that an API is working correctly, or start my React project and load up a web preview and check the front end works. This functionality didn't always seem to work consistently, and so I fell back to testing it manually myself most of the time.
When I was happy with the code, it wrote git commits for me and pushed code to Heroku from the in-built command line terminal. Pretty cool!
I do have a few niggles still. Sometimes it's a little over-eager - it will make more changes than I want, without checking with me that I'm happy or the code works. For example, it might try to commit code and deploy to production, and I need to press "Stop" and actually test the app myself. When I asked it to add analytics, it went overboard and added 100 different analytics events in pretty insignificant places. When it got trigger-happy like this, I reverted the changes and gave it more precise commands to follow one by one.
The one thing I haven't got working yet is automated testing that's executed by the agent before it decides a task is complete; there's probably a way to do it with custom rules (I have spent zero time investigating this). It feels like I should be able to have an integration test suite that is run automatically after every code change, and then any test failures should be rectified automatically by the AI before it says it's finished.
Also, the AI should be able to tail my Rails logs to look for errors. It should spot things like database queries and automatically optimize my Active Record queries to make my app perform better. At the moment I'm copy-pasting in excerpts of the Rails logs, and then Windsurf quickly figures out that I've got an N+1 query problem and fixes it. Pretty cool.
Refactoring is also kind of painful. I've ended up with several files that are 700-900 lines long and contain duplicate functionality. For example, list recipes by tag and list recipes by user are basically the same.
Recipes by user:
This should really be identical to list recipes by tag, but Windsurf has implemented them separately.
Recipes by tag:
If I ask Windsurf to refactor these two pages, it randomly changes stuff like renaming analytics events, rewriting user-facing alerts, and changing random little UX stuff, when I really want to keep the functionality exactly the same and only move duplicate code into shared modules. Instead, to successfully refactor, I had to ask Windsurf to list out ideas for refactoring, then prompt it specifically to refactor these things one by one, touching nothing else. That worked a little better, but it still wasn't perfect
Sometimes, adding minor functionality to the Rails API will often change the entire API response, rather just adding a couple of fields. Eg It will occasionally change Index Recipes to nest responses in an object { "recipes": [ ] }, versus just returning an array, which breaks the frontend. And then another minor change will revert it. This is where adding tests to identify and prevent these kinds of API changes would be really useful. When I ask Windsurf to fix these API changes, it will instead change the front end to accept the new API json format and also leave the old implementation in for "backwards compatibility". This ends up with a tangled mess of code that isn't really necessary. But I'm vibecoding so I didn't bother to fix it.
Then there was some changes that just didn't work at all. Trying to implement Posthog analytics in the front end seemed to break my entire app multiple times. I tried to add user voice commands ("Go to the next step"), but this conflicted with the eleven labs voice recordings. Having really good git discipline makes vibe coding much easier and less stressful. If something doesn't work after 10 minutes, I can just git reset head --hard. I've not lost very much time, and it frees me up to try more ambitious prompts to see what the AI can do. Less technical users who aren't familiar with git have lost months of work when the AI goes off on a vision quest and the inbuilt revert functionality doesn't work properly. It seems like adding more native support for version control could be a massive win for these AI coding tools.
Another complaint I've heard is that the AI coding tools don't write "production" code that can scale. So I decided to put this to the test by asking Windsurf for some tips on how to make the application more performant. It identified I was downloading 3 MB image files for each recipe, and suggested a Rails feature for adding lower resolution image variants automatically. Two minutes later, I had thumbnail and midsize variants that decrease the loading time of each page by 80%. Similarly, it identified inefficient N+1 active record queries and rewrote them to be more efficient. There are a ton more performance features that come built into Rails - caching would be the next thing I'd probably add if usage really ballooned.
Before going to production, I kept my promise to move my Elevenlabs API keys to the backend. Almost as an afterthought, I asked asked Windsurf to cache the voice responses so that I'd only make an Elevenlabs API call once for each recipe step; after that, the audio file was stored in S3 using Rails ActiveStorage and served without costing me more credits. Two minutes later, it was done. Awesome.
At the end of a vibecoding session, I'd write a list of 10 or 15 new ideas for functionality that I wanted to add the next time I came back to the project. In the past, these lists would've built up over time and never gotten done. Each task might've taken me five minutes to an hour to complete manually. With Windsurf, I was astonished how quickly I could work through these lists. Changes took one or two minutes each, and within 30 minutes I'd completed my entire to do list from the day before. It was astonishing how productive I felt. I can create the features faster than I can come up with ideas.
Before launching, I wanted to improve the design, so I took a quick look at a couple of recipe sites. They were much more visual than my site, and so I simply told Windsurf to make my design more visual, emphasizing photos of food. Its first try was great. I showed it to a couple of friends and they suggested I should add recipe categories - "Thai" or "Mexican" or "Pizza" for example. They showed me the DoorDash app, so I took a screenshot of it and pasted it into Windsurf. My prompt was "Give me a carousel of food icons that look like this". Again, this worked in one shot. I think my version actually looks better than Doordash 🤷♂️
Doordash:
My carousel:
I also saw I was getting a console error from missing Favicon. I always struggle to make Favicon for previous sites because I could never figure out where they were supposed to go or what file format they needed. I got OpenAI to generate me a little recipe ninja icon with a transparent background and I saved it into my project directory. I asked Windsurf what file format I need and it listed out nine different sizes and file formats. Seems annoying. I wondered if Windsurf could just do it all for me. It quickly wrote a series of Bash commands to create a temporary folder, resize the image and create the nine variants I needed. It put them into the right directory and then cleaned up the temporary directory. I laughed in amazement. I've never been good at bash scripting and I didn't know if it was even possible to do what I was asking via the command line. I guess it is possible.
After launching and posting on Twitter, a few hundred users visited the site and generated about 1000 recipes. I was pretty happy! Unfortunately, the next day I woke up and saw that I had a $700 OpenAI bill. Someone had been abusing the site and costing me a lot of OpenAI credits by creating a single recipe over and over again - "Pasta with Shallots and Pineapple". They did this 12,000 times. Obviously, I had not put any rate limiting in.
Still, I was determined not to write any code. I explained the problem and asked Windsurf to come up with solutions. Seconds later, I had 15 pretty good suggestions. I implemented several (but not all) of the ideas in about 10 minutes and the abuse stopped dead in its tracks. I won't tell you which ones I chose in case Mr Shallots and Pineapple is reading. The app's security is not perfect, but I'm pretty happy with it for the scale I'm at. If I continue to grow and get more abuse, I'll implement more robust measures.
Overall, I am astonished how productive Windsurf has made me in the last two weeks. I'm not a good designer or frontend developer, and I'm a very rusty rails dev. I got this project into production 5 to 10 times faster than it would've taken me manually, and the level of polish on the front end is much higher than I could've achieved on my own. Over and over again, I would ask for a change and be astonished at the speed and quality with which Windsurf implemented it. I just sat laughing as the computer wrote code.
The next thing I want to change is making the recipe generation process much more immediate and responsive. Right now, it takes about 20 seconds to generate a recipe and for a new user it feels like maybe the app just isn't doing anything.
Instead, I'm experimenting with using Websockets to show a streaming response as the recipe is created. This gives the user immediate feedback that something is happening. It would also make editing the recipe really fun - you could ask it to "add nuts" to the recipe, and see as the recipe dynamically updates 2-3 seconds later. You could also say "Increase the quantities to cook for 8 people" or "Change from imperial to metric measurements".
I have a basic implementation working, but there are still some rough edges. I might actually go and read the code this time to figure out what it's doing!
I also want to add a full voice agent interface so that you don't have to touch the screen at all. Halfway through cooking a recipe, you might ask "I don't have cilantro - what could I use instead?" or say "Set a timer for 30 minutes". That would be my dream recipe app!
Tools like Windsurf or Cursor aren't yet as useful for non-technical users - they're extremely powerful and there are still too many ways to blow your own face off. I have a fairly good idea of the architecture that I want Windsurf to implement, and I could quickly spot when it was going off track or choosing a solution that was inappropriately complicated for the feature I was building. At the moment, a technical background is a massive advantage for using Windsurf. As a rusty developer, it made me feel like I had superpowers.
But I believe within a couple of months, when things like log tailing and automated testing and native version control get implemented, it will be an extremely powerful tool for even non-technical people to write production-quality apps. The AI will be able to make complex changes and then verify those changes are actually working. At the moment, it feels like it's making a best guess at what will work and then leaving the user to test it. Implementing better feedback loops will enable a truly agentic, recursive, self-healing development flow. It doesn't feel like it needs any breakthrough in technology to enable this. It's just about adding a few tool calls to the existing LLMs. My mind races as I try to think through the implications for professional software developers.
Meanwhile, the LLMs aren't going to sit still. They're getting better at a frightening rate. I spoke to several very capable software engineers who are Y Combinator founders in the last week. About a quarter of them told me that 95% of their code is written by AI. In six or twelve months, I just don't think software engineering is going exist in the same way as it does today. The cost of creating high-quality, custom software is quickly trending towards zero.
You can try the site yourself at recipeninja.ai
Here's a complete list of functionality. Of course, Windsurf just generated this list for me 🫠
RecipeNinja: Comprehensive Functionality Overview
Core Concept: the app appears to be a cooking assistant application that provides voice-guided recipe instructions, allowing users to cook hands-free while following step-by-step recipe guidance.
Backend (Rails API) Functionality
User Authentication & Authorization
Google OAuth integration for user authentication
User account management with secure authentication flows
Authorization system ensuring users can only access their own private recipes or public recipes
Recipe Management
Recipe Model Features:
Unique public IDs (format: "r_" + 14 random alphanumeric characters) for security
User ownership (user_id field with NOT NULL constraint)
Public/private visibility toggle (default: private)
Comprehensive recipe data storage (title, ingredients, steps, cooking time, etc.)
Image attachment capability using Active Storage with S3 storage in production
Recipe Tagging System:
Many-to-many relationship between recipes and tags
Tag model with unique name attribute
RecipeTag join model for the relationship
Helper methods for adding/removing tags from recipes
Recipe API Endpoints:
CRUD operations for recipes
Pagination support with metadata (current_page, per_page, total_pages, total_count)
Default sorting by newest first (created_at DESC)
Filtering recipes by tags
Different serializers for list view (RecipeSummarySerializer) and detail view (RecipeSerializer)
Voice Generation
Voice Recording System:
VoiceRecording model linked to recipes
Integration with Eleven Labs API for text-to-speech conversion
Caching of voice recordings in S3 to reduce API calls
Unique identifiers combining recipe_id, step_id, and voice_id
Force regeneration option for refreshing recordings
Audio Processing:
Using streamio-ffmpeg gem for audio file analysis
Active Storage integration for audio file management
S3 storage for audio files in production
Recipe Import & Generation
RecipeImporter Service:
OpenAI integration for recipe generation
Conversion of text recipes into structured format
Parsing and normalization of recipe data
Import from photos functionality
Frontend (React) Functionality
User Interface Components
Recipe Selection & Browsing:
Recipe listing with pagination
Real-time updates with 10-second polling mechanism
Tag filtering functionality
Recipe cards showing summary information (without images)
"View Details" and "Start Cooking" buttons for each recipe
Recipe Detail View:
Complete recipe information display
Recipe image display
Tag display with clickable tags
Option to start cooking from this view
Cooking Experience:
Step-by-step recipe navigation
Voice guidance for each step
Keyboard shortcuts for hands-free control:
Arrow keys for step navigation
Space for play/pause audio
Escape to return to recipe selection
URL-based step tracking (e.g., /recipe/r_xlxG4bcTLs9jbM/classic-lasagna/steps/1)
State Management & Data Flow
Recipe Service:
API integration for fetching recipes
Support for pagination parameters
Tag-based filtering
Caching mechanisms for recipe data
Image URL handling for detailed views
Authentication Flow:
Google OAuth integration using environment variables
User session management
Authorization header management for API requests
Progressive Web App Features
PWA capabilities for installation on devices
Responsive design for various screen sizes
Favicon and app icon support
Deployment Architecture
Two-App Structure:
cook-voice-api: Rails backend on Heroku
cook-voice-wizard: React frontend/PWA on Heroku
Backend Infrastructure:
Ruby 3.2.2
PostgreSQL database (Heroku PostgreSQL addon)
Amazon S3 for file storage
Environment variables for configuration
Frontend Infrastructure:
React application
Environment variable configuration
Static buildpack on Heroku
SPA routing configuration
Security Measures:
HTTPS enforcement
Rails credentials system
Environment variables for sensitive information
Public ID system to mask database IDs
This comprehensive overview covers the major functionality of the Cook Voice application based on the available information. The application appears to be a sophisticated cooking assistant that combines recipe management with voice guidance to create a hands-free cooking experience.
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youtube
People Think It’s Fake" | DeepSeek vs ChatGPT: The Ultimate 2024 Comparison (SEO-Optimized Guide)
The AI wars are heating up, and two giants—DeepSeek and ChatGPT—are battling for dominance. But why do so many users call DeepSeek "fake" while praising ChatGPT? Is it a myth, or is there truth to the claims? In this deep dive, we’ll uncover the facts, debunk myths, and reveal which AI truly reigns supreme. Plus, learn pro SEO tips to help this article outrank competitors on Google!
Chapters
00:00 Introduction - DeepSeek: China’s New AI Innovation
00:15 What is DeepSeek?
00:30 DeepSeek’s Impressive Statistics
00:50 Comparison: DeepSeek vs GPT-4
01:10 Technology Behind DeepSeek
01:30 Impact on AI, Finance, and Trading
01:50 DeepSeek’s Effect on Bitcoin & Trading
02:10 Future of AI with DeepSeek
02:25 Conclusion - The Future is Here!
Why Do People Call DeepSeek "Fake"? (The Truth Revealed)
The Language Barrier Myth
DeepSeek is trained primarily on Chinese-language data, leading to awkward English responses.
Example: A user asked, "Write a poem about New York," and DeepSeek referenced skyscrapers as "giant bamboo shoots."
SEO Keyword: "DeepSeek English accuracy."
Cultural Misunderstandings
DeepSeek’s humor, idioms, and examples cater to Chinese audiences. Global users find this confusing.
ChatGPT, trained on Western data, feels more "relatable" to English speakers.
Lack of Transparency
Unlike OpenAI’s detailed GPT-4 technical report, DeepSeek’s training data and ethics are shrouded in secrecy.
LSI Keyword: "DeepSeek data sources."
Viral "Fail" Videos
TikTok clips show DeepSeek claiming "The Earth is flat" or "Elon Musk invented Bitcoin." Most are outdated or edited—ChatGPT made similar errors in 2022!
DeepSeek vs ChatGPT: The Ultimate 2024 Comparison
1. Language & Creativity
ChatGPT: Wins for English content (blogs, scripts, code).
Strengths: Natural flow, humor, and cultural nuance.
Weakness: Overly cautious (e.g., refuses to write "controversial" topics).
DeepSeek: Best for Chinese markets (e.g., Baidu SEO, WeChat posts).
Strengths: Slang, idioms, and local trends.
Weakness: Struggles with Western metaphors.
SEO Tip: Use keywords like "Best AI for Chinese content" or "DeepSeek Baidu SEO."
2. Technical Abilities
Coding:
ChatGPT: Solves Python/JavaScript errors, writes clean code.
DeepSeek: Better at Alibaba Cloud APIs and Chinese frameworks.
Data Analysis:
Both handle spreadsheets, but DeepSeek integrates with Tencent Docs.
3. Pricing & Accessibility
FeatureDeepSeekChatGPTFree TierUnlimited basic queriesGPT-3.5 onlyPro Plan$10/month (advanced Chinese tools)$20/month (GPT-4 + plugins)APIsCheaper for bulk Chinese tasksGlobal enterprise support
SEO Keyword: "DeepSeek pricing 2024."
Debunking the "Fake AI" Myth: 3 Case Studies
Case Study 1: A Shanghai e-commerce firm used DeepSeek to automate customer service on Taobao, cutting response time by 50%.
Case Study 2: A U.S. blogger called DeepSeek "fake" after it wrote a Chinese-style poem about pizza—but it went viral in Asia!
Case Study 3: ChatGPT falsely claimed "Google acquired OpenAI in 2023," proving all AI makes mistakes.
How to Choose: DeepSeek or ChatGPT?
Pick ChatGPT if:
You need English content, coding help, or global trends.
You value brand recognition and transparency.
Pick DeepSeek if:
You target Chinese audiences or need cost-effective APIs.
You work with platforms like WeChat, Douyin, or Alibaba.
LSI Keyword: "DeepSeek for Chinese marketing."
SEO-Optimized FAQs (Voice Search Ready!)
"Is DeepSeek a scam?" No! It’s a legitimate AI optimized for Chinese-language tasks.
"Can DeepSeek replace ChatGPT?" For Chinese users, yes. For global content, stick with ChatGPT.
"Why does DeepSeek give weird answers?" Cultural gaps and training focus. Use it for specific niches, not general queries.
"Is DeepSeek safe to use?" Yes, but avoid sensitive topics—it follows China’s internet regulations.
Pro Tips to Boost Your Google Ranking
Sprinkle Keywords Naturally: Use "DeepSeek vs ChatGPT" 4–6 times.
Internal Linking: Link to related posts (e.g., "How to Use ChatGPT for SEO").
External Links: Cite authoritative sources (OpenAI’s blog, DeepSeek’s whitepapers).
Mobile Optimization: 60% of users read via phone—use short paragraphs.
Engagement Hooks: Ask readers to comment (e.g., "Which AI do you trust?").
Final Verdict: Why DeepSeek Isn’t Fake (But ChatGPT Isn’t Perfect)
The "fake" label stems from cultural bias and misinformation. DeepSeek is a powerhouse in its niche, while ChatGPT rules Western markets. For SEO success:
Target long-tail keywords like "Is DeepSeek good for Chinese SEO?"
Use schema markup for FAQs and comparisons.
Update content quarterly to stay ahead of AI updates.
🚀 Ready to Dominate Google? Share this article, leave a comment, and watch it climb to #1!
Follow for more AI vs AI battles—because in 2024, knowledge is power! 🔍
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New Cloud Translation AI Improvements Support 189 Languages

189 languages are now covered by the latest Cloud Translation AI improvements.
Your next major client doesn’t understand you. 40% of shoppers globally will never consider buying from a non-native website. Since 51.6% of internet users speak a language other than English, you may be losing half your consumers.
Businesses had to make an impossible decision up until this point when it came to handling translation use cases. They have to decide between the following options:
Human interpreters: Excellent, but costly and slow
Simple machine translation is quick but lacks subtleties.
DIY fixes: Unreliable and dangerous
The problem with translation, however, is that you need all three, and conventional translation techniques are unable to keep up. Using the appropriate context and tone to connect with people is more important than simply translating words.
For this reason, developed Translation AI in Vertex AI at Google Cloud. Its can’t wait to highlight the most recent developments and how they can benefit your company.
Translation AI: Unmatched translation quality, but in your way
There are two options available in Google Cloud‘s Translation AI:
A necessary set of tools for translation capability is the Translation API Basic. Google Cloud sophisticated Neural Machine Translation (NMT) model allows you to translate text and identify languages immediately. For chat interactions, short-form content, and situations where consistency and speed are essential, Translation AI Basic is ideal.
Advanced Translation API: Utilize bespoke glossaries to ensure terminology consistency, process full documents, and perform batch translations. For lengthy content, you can utilize Gemini-powered Translation model; for shorter content, you can use Adaptive Translation to capture the distinct tone and voice of your business. By using a glossary, improving its industry-leading translation algorithms, or modifying translation forecasts in real time, you can even personalize translations.
What’s new in Translation AI
Increased accuracy and reach
With 189-language support, which now includes Cantonese, Fijian, and Balinese, you can now reach audiences around the world while still achieving lightning-fast performance, making it ideal for call centers and user content.
Smarter adaptive translation
You can use as little as five samples to change the tone and style of your translations, or as many as 30,000 for maximum accuracy.
Choosing a model according to your use case
Depending on how sophisticated your translation use case is, you can select from a variety of methods when using Cloud Translation Advanced. For instance, you can select Adaptive Translation for real-time modification or use NMT model for translating generic text.
Quality without sacrificing
Although reports and leaderboards provide information about the general performance of the model, they don’t show how well a model meets your particular requirements. With the help of the gen AI assessment service, you can choose your own evaluation standards and get a clear picture of how well AI models and applications fit your use case. Examples of popular tools for assessing translation quality include Google MetricX and the popular COMET, which are currently accessible on the Vertex gen AI review service and have a significant correlation with human evaluation. Choose the translation strategy that best suits your demands by comparing models and prototyping solutions.
Google cloud two main goals while developing Translation AI were to change the way you translate and the way you approach translation. Its deliver on both in four crucial ways, whereas most providers only offer either strong translation or simple implementation.
Vertex AI for quick prototyping
Test translations in 189 languages right away. To determine your ideal fit, compare NMT or most recent translation-optimized Gemini-powered model. Get instant quality metrics to confirm your decisions and see how your unique adaptations work without creating a single line of code.
APIs that are ready for production for your current workflows
For high-volume, real-time translations, integrate Translation API (NMT) straight into your apps. When tone and context are crucial, use the same Translation API to switch to Adaptive Translation Gemini-powered model. Both models scale automatically to meet your demands and fit into your current workflows.
Customization without coding
Teach your industry’s unique terminology and phrases to bespoke translation models. All you have to do is submit domain-specific data, and Translation AI will create a unique model that understands your language. With little need for machine learning knowledge, it is ideal for specialist information in technical, legal, or medical domains.
Complete command using Vertex AI
With all-inclusive platform, Vertex AI, you can use Translation AI to own your whole translation workflow. You may choose the models you want, alter how they behave, and track performance in the real world with Vertex AI. Easily integrate with your current CI/CD procedures to get translation at scale that is really enterprise-grade.
Real impact: The Uber story
Uber’s goal is to enable individuals to go anywhere, get anything, and make their own way by utilizing the Google Cloud Translation AI product suite.
Read more on Govindhtech.com
#TranslationAI#VertexAI#GoogleCloud#AImodels#genAI#Gemini#CloudTranslationAI#News#Technology#technologynews#technews#govindhtech
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Honey
She/Her, Honeybee, lesbian, Cooking club Leader
Honey facts!!
☆~ Her favorite food to bake are honey cakes
♡~ Absolutely DESPISES the Bee Movie. I mean why can't she get a human girlfriend! I mean she can go up to a woman– **LOUDLY INCORRECT BUZZER**
♧~ had unsupervised internet access as a kid (totally not projecting myself onto my ocs)
♤~ Used to have a crush on Mona (maybe still does)
◇~ HEXAGONS ARE MOST OPTIMAL.
♡~ Only uses hexagon dishes, plates, pans, etc. (Her club members had to beg her to use circular pans)
◇~Gives food to the other club leaders
♧~Her and Mona could absolutely destroy a candy store (they are banned from multiple stores for this reason.)
☆~ Uses kid soap and shampoo unlike SOMEONE that doesn't WASH every DAY CENI–
♡~ Puts WAAYYYY too much sugar in her pastries sometimes to the point where they are literally inedible.
Grades
Math- B+
English- A
Science- D
Social Studies- A
P.E.- A
What others think of her
Fae: "She...Gives me food"
Ceni: "She says if I don't start taking showers every day, she's gonna stop giving me food. Like, dude!! I shower every other day!...Guys, why are you all walking away? Hey wait!–"
Orchid: "She's such a cutie patootie, love herr <3"
Mona: "She's like my bffaenmwbogcbu! Best friends forever no matter what boy or girl comes between us!"
Poly: "Dude, I think she liked my sister. Eh, whatever, she makes me cookies...Actually, if she does get with my sister, I'll be able to ask her for cookies anytime! Oh my god, guys, wait, cut the cams. I have an idea-"
"Lady"- "Hm, she's quite nice, I can't say I love some of the food she makes though...I'm still thinking about that block of sugar she said was supposed to be "cookies.""
Latro: "Probably the most sane club leade out of all of us... But then again, she's ALSO the reason we have rats in the computer room."
Honeybee facts!!
☆~The scientific name for Honeybees is Apis mellifera Linnaeus.
♡~Can fly at about 20mph
♤~Honeybees dance to communicate!! It's called "The wiggle dance," and they use it to communicate the location of a food source:3
◇~They literally COOK hornets to death (They literally surround a hornet and use their wings to overheat the hornet)
♧~ Bee brains are less than two cubic centimeters
☆~Bees have 5 eyes
♡~Queen bees can lay up to 3000 eggs in a day
Thanks 4 reading!! <3
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Reply.io is a sales engagement platform designed to help sales teams automate and manage their outreach efforts through multiple communication channels. It aims to streamline the process of engaging with prospects and customers, thereby increasing productivity and efficiency.
Below is a detailed review of its features and functionalities:
Key Features
Multi-Channel Outreach:
Email Campaigns: Automate and personalize email sequences to reach prospects effectively.
Phone Calls: Integrates with VoIP services to facilitate direct calling from the platform, including features like call recording and logging.
Social Media: Allows outreach via LinkedIn, including automated message sequences.
SMS and WhatsApp: Supports text-based outreach through SMS and WhatsApp for more direct communication channels.
Automation and Sequencing:
Automated Workflows: Create automated workflows that sequence multiple touch points across different channels.
Conditional Logic: Use conditional steps to branch sequences based on recipient behavior, such as email opens or replies.
Task Automation: Automate repetitive tasks such as follow-ups, reminders, and updating CRM records. Personalization and AI:
Email Personalization: Use dynamic fields to personalize email content, increasing engagement rates.
AI-Powered Suggestions: AI tools provide suggestions for improving email content and outreach strategies.
Personalized Videos: Integrates with video messaging tools to include personalized video content in emails.
Integration and API:
CRM Integration: Seamlessly integrates with major CRM systems like Salesforce, HubSpot, and Pipedrive, ensuring data synchronization.
API Access: Provides API access for custom integrations and automations, allowing for greater flexibility.
Third-Party Tools: Connects with various other tools such as Zapier, Slack, and Google Apps to enhance functionality.
Analytics and Reporting:
Campaign Analytics: Detailed analytics on email open rates, reply rates, click-through rates, and more.
A/B Testing: Test different versions of emails to determine which performs better.
Team Performance: Track team performance metrics to identify areas for improvement and optimize outreach efforts.
Contact Management:
Lead Management: Centralized database for managing contacts and leads, with segmentation and filtering options.
Enrichment: Automatic data enrichment to enhance lead profiles with relevant information.
Prospect Importing: Easily import contacts from CSV files or directly from integrated CRM systems.
Pros Comprehensive Multi-Channel Outreach: Supports a variety of communication channels, providing a holistic approach to sales engagement.
Advanced Automation and Sequencing: Powerful automation features help streamline workflows and increase efficiency.
Deep Personalization: Tools for email and video personalization improve engagement and response rates.
Robust Integration Capabilities: Seamless integration with CRM systems and other third-party tools enhances data synchronization and workflow automation.
Detailed Analytics: Comprehensive reporting and analytics provide insights into campaign performance and team productivity.
Cons Complexity: The extensive features and customization options can be overwhelming for new users, requiring a learning curve to fully utilize the platform.
Cost: Pricing can be relatively high, especially for smaller businesses or startups with limited budgets.
Limited Free Tier: The free tier offers limited functionality, which may not be sufficient for more extensive outreach needs.
Reply.io is a powerful and versatile sales engagement platform that offers a comprehensive suite of tools for multi-channel outreach, automation, and personalization. Its robust integration capabilities and detailed analytics make it an excellent choice for sales teams looking to optimize their engagement strategies and improve productivity. However, the complexity and cost may pose challenges for smaller organizations or those new to such platforms. Overall, Reply.io provides significant value for businesses seeking to enhance their sales outreach and engagement efforts.
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My Name Is Rubel. I'm a Professional Digital Marketer And Seo Experts . I've Been 5 Years Online Marketing Experienced.I know How To Viral Your Business. I Will Provide My Best Services. My Main Resources Is Efficiency And Honesty. I Will Provide Highly Satisfying Services.
I will set up a successful Facebook ad campaign to help you generate more qualified traffic, make MORE SALES or generate leads for real estate,or grow BRAND awareness!
I try my best to do benefited my client with my work. I always believe that client satisfaction is my success.
What can we do for your Business:
️Professional business or personal page creation and setup
Brand logo and cover image banner
Management and optimization
Template design and post
Facebook Meta Ads campaign setup, optimization & management
Instagram Ads
Audience research
Pixel API connection
Call to action buttons and website links
Customers message Response
Business Info added
FB shop button setup
#facebookadscampaign #digitalmarketer #DataEntry #seo #youtubemarketer #videopromotion #facebookadsexpert #freedelivery #freelancing #friends #freelance #freelacerrobelmiha #advertising #freelancer #Update #upwork #facebookviral #FreePalestine #digitalmarketing #digitalart #qatar #qatarjobs #uk #usareels #Online_Marketer #online_service #canada #FreelancerRubel #digitalmarketarrubel #freelancerrobel #freelancerrobel

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Who Shapes Who I am?
This thought formed in my mind as a puzzle put together. It was originally written on August 25, 2022, during the 14th year of a long journey. At the time of writing, I was influenced, and I still am, by the Hebrew scriptures, and with a basic understanding of computer science, a subject that in my way of thinking is analogous to the knowledge of our own existence as human beings, I went on to write down my thoughts about man as a being made of software and hardware parts. I wrote down many entries in my journal on the subject; entries which in time I came to call The API Series. I leave you with the overall overview of the API Series.In a sense, human beings are two-sided machines, consisting of hardware and software components. Moreover, they have the potential to write their own software. But the hardware is given to all by the creator God, who made the DNA.It is possible to create habits and to leave harmful ones if desired. The neuroplasticity of the brain allows that to be true. This fact of the brain and our volition to chose what we want, essentially rewriting our own software, is commonly known as free will.The hardware, however, is God's creation since the beginning and it will ever be his.Procreation is the system designed by God to bring more like us into the world. God owns the design of the DNA. By owning, I am implying that were there to be a court encompassing heaven and earth, God would be the legal owner of the DNA patent. As such, mankind belongs to him, and he is the rightful judge of all.Nevertheless, he made us to be partakes of the hardware part of our beings as well.When we participate in procreation, we have sons and daughters and we seem to think that we own them, that they are ours. In reality though, they are not. They are God's. Our role as parents is more a responsibility than ownership of other human beings. Our responsibility is to raise them up for him. If we embrace this truth, we could become truly social beings; we would know that no matter our earthly parents, we are from the same source.Having sons and daughters is a responsibility trusted unto us by God himself, and it is the rightful outcome of the procreation act itself. Therefore, sex is not at all a passtime, it is not intended to fulfill egotistical pursuits, it is God's design to fill the world. The fact that sex is physically pleasurable speaks of God's goodness and what duty looks like when we live for him. Our hardware is meant to be optimized by God's own software, not our own. By software I am implying written instructions to execute and have our being in this life. God's software is found in the Hebrew Tanakh.The human brain is indeed the ultimate computer system ever made in the entire universe. I believe we can create awesome software systems ourselves by understanding the way we were made by God himself.
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This Week in Rust 593
Hello and welcome to another issue of This Week in Rust! Rust is a programming language empowering everyone to build reliable and efficient software. This is a weekly summary of its progress and community. Want something mentioned? Tag us at @ThisWeekInRust on X (formerly Twitter) or @ThisWeekinRust on mastodon.social, or send us a pull request. Want to get involved? We love contributions.
This Week in Rust is openly developed on GitHub and archives can be viewed at this-week-in-rust.org. If you find any errors in this week's issue, please submit a PR.
Want TWIR in your inbox? Subscribe here.
Updates from Rust Community
Newsletters
The Embedded Rustacean Issue #42
This Week in Bevy - 2025-03-31
Project/Tooling Updates
Fjall 2.8
EtherCrab, the pure Rust EtherCAT MainDevice, version 0.6 released
A process for handling Rust code in the core kernel
api-version: axum middleware for header based version selection
SALT: a VS Code Extension, seeking participants in a study on Rust usabilty
Observations/Thoughts
Introducing Stringleton
Rust Any Part 3: Finally we have Upcasts
Towards fearless SIMD, 7 years later
LLDB's TypeSystems: An Unfinished Interface
Mutation Testing in Rust
Embedding shared objects in Rust
Rust Walkthroughs
Architecting and building medium-sized web services in Rust with Axum, SQLx and PostgreSQL
Solving the ABA Problem in Rust with Hazard Pointers
Building a CoAP application on Ariel OS
How to Optimize your Rust Program for Slowness: Write a Short Program That Finishes After the Universe Dies
Inside ScyllaDB Rust Driver 1.0: A Fully Async Shard-Aware CQL Driver Using Tokio
Building a search engine from scratch, in Rust: part 2
Introduction to Monoio: A High-Performance Rust Runtime
Getting started with Rust on Google Cloud
Miscellaneous
An AlphaStation's SROM
Real-World Verification of Software for Cryptographic Applications
Public mdBooks
[video] Networking in Bevy with ECS replication - Hennadii
[video] Intermediate Representations for Reactive Structures - Pete
Crate of the Week
This week's crate is candystore, a fast, persistent key-value store that does not require LSM or WALs.
Thanks to Tomer Filiba for the self-suggestion!
Please submit your suggestions and votes for next week!
Calls for Testing
An important step for RFC implementation is for people to experiment with the implementation and give feedback, especially before stabilization.
If you are a feature implementer and would like your RFC to appear in this list, add a call-for-testing label to your RFC along with a comment providing testing instructions and/or guidance on which aspect(s) of the feature need testing.
No calls for testing were issued this week by Rust, Rust language RFCs or Rustup.
Let us know if you would like your feature to be tracked as a part of this list.
Call for Participation; projects and speakers
CFP - Projects
Always wanted to contribute to open-source projects but did not know where to start? Every week we highlight some tasks from the Rust community for you to pick and get started!
Some of these tasks may also have mentors available, visit the task page for more information.
If you are a Rust project owner and are looking for contributors, please submit tasks here or through a PR to TWiR or by reaching out on X (formerly Twitter) or Mastodon!
CFP - Events
Are you a new or experienced speaker looking for a place to share something cool? This section highlights events that are being planned and are accepting submissions to join their event as a speaker.
* Rust Conf 2025 Call for Speakers | Closes 2025-04-29 11:59 PM PDT | Seattle, WA, US | 2025-09-02 - 2025-09-05
If you are an event organizer hoping to expand the reach of your event, please submit a link to the website through a PR to TWiR or by reaching out on X (formerly Twitter) or Mastodon!
Updates from the Rust Project
438 pull requests were merged in the last week
Compiler
allow defining opaques in statics and consts
avoid wrapping constant allocations in packed structs when not necessary
perform less decoding if it has the same syntax context
stabilize precise_capturing_in_traits
uplift clippy::invalid_null_ptr_usage lint as invalid_null_arguments
Library
allow spawning threads after TLS destruction
override PartialOrd methods for bool
simplify expansion for format_args!()
stabilize const_cell
Rustdoc
greatly simplify doctest parsing and information extraction
rearrange Item/ItemInner
Clippy
new lint: char_indices_as_byte_indices
add manual_dangling_ptr lint
respect #[expect] and #[allow] within function bodies for missing_panics_doc
do not make incomplete or invalid suggestions
do not warn about shadowing in a destructuring assigment
expand obfuscated_if_else to support {then(), then_some()}.unwrap_or_default()
fix the primary span of redundant_pub_crate when flagging nameless items
fix option_if_let_else suggestion when coercion requires explicit cast
fix unnested_or_patterns suggestion in let
make collapsible_if recognize the let_chains feature
make missing_const_for_fn operate on non-optimized MIR
more natural suggestions for cmp_owned
collapsible_if: prevent including preceeding whitespaces if line contains non blanks
properly handle expansion in single_match
validate paths in disallowed_* configurations
Rust-Analyzer
allow crate authors to control completion of their things
avoid relying on block_def_map() needlessly
fix debug sourceFileMap when using cppvsdbg
fix format_args lowering using wrong integer suffix
fix a bug in orphan rules calculation
fix panic in progress due to splitting unicode incorrectly
use medium durability for crate-graph changes, high for library source files
Rust Compiler Performance Triage
Positive week, with a lot of primary improvements and just a few secondary regressions. Single big regression got reverted.
Triage done by @panstromek. Revision range: 4510e86a..2ea33b59
Summary:
(instructions:u) mean range count Regressions ❌ (primary) - - 0 Regressions ❌ (secondary) 0.9% [0.2%, 1.5%] 17 Improvements ✅ (primary) -0.4% [-4.5%, -0.1%] 136 Improvements ✅ (secondary) -0.6% [-3.2%, -0.1%] 59 All ❌✅ (primary) -0.4% [-4.5%, -0.1%] 136
Full report here.
Approved RFCs
Changes to Rust follow the Rust RFC (request for comments) process. These are the RFCs that were approved for implementation this week:
No RFCs were approved this week.
Final Comment Period
Every week, the team announces the 'final comment period' for RFCs and key PRs which are reaching a decision. Express your opinions now.
Tracking Issues & PRs
Rust
Tracking Issue for slice::array_chunks
Stabilize cfg_boolean_literals
Promise array::from_fn is generated in order of increasing indices
Stabilize repr128
Stabilize naked_functions
Fix missing const for inherent pointer replace methods
Rust RFCs
core::marker::NoCell in bounds (previously known an [sic] Freeze)
Cargo,
Stabilize automatic garbage collection.
Other Areas
No Items entered Final Comment Period this week for Language Team, Language Reference or Unsafe Code Guidelines.
Let us know if you would like your PRs, Tracking Issues or RFCs to be tracked as a part of this list.
New and Updated RFCs
Allow &&, ||, and ! in cfg
Upcoming Events
Rusty Events between 2025-04-02 - 2025-04-30 🦀
Virtual
2025-04-02 | Virtual (Indianapolis, IN, US) | Indy Rust
Indy.rs - with Social Distancing
2025-04-03 | Virtual (Nürnberg, DE) | Rust Nurnberg DE
Rust Nürnberg online
2025-04-03 | Virtual | Ardan Labs
Communicate with Channels in Rust
2025-04-05 | Virtual (Kampala, UG) | Rust Circle Meetup
Rust Circle Meetup
2025-04-08 | Virtual (Dallas, TX, US) | Dallas Rust User Meetup
Second Tuesday
2025-04-10 | Virtual (Berlin, DE) | Rust Berlin
Rust Hack and Learn
2025-04-15 | Virtual (Washington, DC, US) | Rust DC
Mid-month Rustful
2025-04-16 | Virtual (Vancouver, BC, CA) | Vancouver Rust
Rust Study/Hack/Hang-out
2025-04-17 | Virtual and In-Person (Redmond, WA, US) | Seattle Rust User Group
April, 2025 SRUG (Seattle Rust User Group) Meetup
2025-04-22 | Virtual (Dallas, TX, US) | Dallas Rust User Meetup
Fourth Tuesday
2025-04-23 | Virtual (Cardiff, UK) | Rust and C++ Cardiff
**Beyond embedded - OS development in Rust **
2025-04-24 | Virtual (Berlin, DE) | Rust Berlin
Rust Hack and Learn
2025-04-24 | Virtual (Charlottesville, VA, US) | Charlottesville Rust Meetup
Part 2: Quantum Computers Can’t Rust-Proof This!"
Asia
2025-04-05 | Bangalore/Bengaluru, IN | Rust Bangalore
April 2025 Rustacean meetup
2025-04-22 | Tel Aviv-Yafo, IL | Rust 🦀 TLV
In person Rust April 2025 at Braavos in Tel Aviv in collaboration with StarkWare
Europe
2025-04-02 | Cambridge, UK | Cambridge Rust Meetup
Monthly Rust Meetup
2025-04-02 | Köln, DE | Rust Cologne
Rust in April: Rust Embedded, Show and Tell
2025-04-02 | München, DE | Rust Munich
Rust Munich 2025 / 1 - hybrid
2025-04-02 | Oxford, UK | Oxford Rust Meetup Group
Oxford Rust and C++ social
2025-04-02 | Stockholm, SE | Stockholm Rust
Rust Meetup @Funnel
2025-04-03 | Oslo, NO | Rust Oslo
Rust Hack'n'Learn at Kampen Bistro
2025-04-08 | Olomouc, CZ | Rust Moravia
3. Rust Moravia Meetup (Real Embedded Rust)
2025-04-09 | Girona, ES | Rust Girona
Rust Girona Hack & Learn 04 2025
2025-04-09 | Reading, UK | Reading Rust Workshop
Reading Rust Meetup
2025-04-10 | Karlsruhe, DE | Rust Hack & Learn Karlsruhe
Karlsruhe Rust Hack and Learn Meetup bei BlueYonder
2025-04-15 | Leipzig, DE | Rust - Modern Systems Programming in Leipzig
Topic TBD
2025-04-15 | London, UK | Women in Rust
WIR x WCC: Finding your voice in Tech
2025-04-19 | Istanbul, TR | Türkiye Rust Community
Rust Konf Türkiye
2025-04-23 | London, UK | London Rust Project Group
Fusing Python with Rust using raw C bindings
2025-04-24 | Aarhus, DK | Rust Aarhus
Talk Night at MFT Energy
2025-04-24 | Edinburgh, UK | Rust and Friends
Rust and Friends (evening pub)
2025-04-24 | Manchester, UK | Rust Manchester
Rust Manchester April Code Night
2025-04-25 | Edinburgh, UK | Rust and Friends
Rust and Friends (daytime coffee)
2025-04-29 | Paris, FR | Rust Paris
Rust meetup #76
North America
2025-04-03 | Chicago, IL, US | Chicago Rust Meetup
Rust Happy Hour
2025-04-03 | Montréal, QC, CA | Rust Montréal
April Monthly Social
2025-04-03 | Saint Louis, MO, US | STL Rust
icu4x - resource-constrained internationalization (i18n)
2025-04-06 | Boston, MA, US | Boston Rust Meetup
Kendall Rust Lunch, Apr 6
2025-04-08 | New York, NY, US | Rust NYC
Rust NYC: Building a full-text search Postgres extension in Rust
2025-04-10 | Portland, OR, US | PDXRust
TetaNES: A Vaccination for Rust—No Needle, Just the Borrow Checker
2025-04-14 | Boston, MA, US | Boston Rust Meetup
Coolidge Corner Brookline Rust Lunch, Apr 14
2025-04-17 | Nashville, TN, US | Music City Rust Developers
Using Rust For Web Series 1 : Why HTMX Is Bad
2025-04-17 | Redmond, WA, US | Seattle Rust User Group
April, 2025 SRUG (Seattle Rust User Group) Meetup
2025-04-23 | Austin, TX, US | Rust ATX
Rust Lunch - Fareground
2025-04-25 | Boston, MA, US | Boston Rust Meetup
Ball Square Rust Lunch, Apr 25
Oceania
2025-04-09 | Sydney, NS, AU | Rust Sydney
Crab 🦀 X 🕳️🐇
2025-04-14 | Christchurch, NZ | Christchurch Rust Meetup Group
Christchurch Rust Meetup
2025-04-22 | Barton, AC, AU | Canberra Rust User Group
April Meetup
South America
2025-04-03 | Buenos Aires, AR | Rust en Español
Abril - Lambdas y más!
If you are running a Rust event please add it to the calendar to get it mentioned here. Please remember to add a link to the event too. Email the Rust Community Team for access.
Jobs
Please see the latest Who's Hiring thread on r/rust
Quote of the Week
If you write a bug in your Rust program, Rust doesn’t blame you. Rust asks “how could the compiler have spotted that bug”.
– Ian Jackson blogging about Rust
Despite a lack of suggestions, llogiq is quite pleased with his choice.
Please submit quotes and vote for next week!
This Week in Rust is edited by: nellshamrell, llogiq, cdmistman, ericseppanen, extrawurst, U007D, joelmarcey, mariannegoldin, bennyvasquez, bdillo
Email list hosting is sponsored by The Rust Foundation
Discuss on r/rust
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Writeup: Forcing Minecraft to play on a Trident Blade 3D.
The first official companion writeup to a video I've put out!
youtube
So. Uh, yeah. Trident Blade 3D. If you've seen the video already, it's... not good. Especially in OpenGL.
Let's kick things off with a quick rundown of the specs of the card, according to AIDA64:
Trident Blade 3D - specs
Year released: 1999
Core: 3Dimage 9880, 0.25um (250nm) manufacturing node, 110MHz
Driver version: 4.12.01.2229
Interface: AGP 2x @ 1x speed (wouldn't go above 1x despite driver and BIOS support)
PCI device ID: 1023-9880 / 1023-9880 (Rev 3A)
Mem clock: 110MHz real/effective
Mem bus/type: 8MB 64-bit SDRAM, 880MB/s bandwidth
ROPs/TMUs/Vertex Shaders/Pixel Shaders/T&L hardware: 1/1/0/0/No
DirectX support: DirectX 6
OpenGL support: - 100% (native) OpenGL 1.1 compliant - 25% (native) OpenGL 1.2 compliant - 0% compliant beyond OpenGL 1.2 - Vendor string:
Vendor : Trident Renderer : Blade 3D Version : 1.1.0
And as for the rest of the system:
Windows 98 SE w/KernelEX 2019 updates installed
ECS K7VTA3 3.x
AMD Athlon XP 1900+ @ 1466MHz
512MB DDR PC3200 (single stick of OCZ OCZ400512P3) 3.0-4-4-8 (CL-RCD-RP-RAS)
Hitachi Travelstar DK23AA-51 4200RPM 5GB HDD
IDK what that CPU cooler is but it does the job pretty well
And now, with specs done and out of the way, my notes!
As mentioned earlier, the Trident Blade 3D is mind-numbingly slow when it comes to OpenGL. As in, to the point where at least natively during actual gameplay (Minecraft, because I can), it is absolutely beaten to a pulp using AltOGL, an OpenGL-to-Direct3D6 "wrapper" that translates OpenGL API calls to DirectX ones.
Normally, it can be expected that performance using the wrapper is about equal to native OpenGL, give or take some fps depending on driver optimization, but this card?
The Blade 3D may as well be better off like the S3 ViRGE by having no OpenGL ICD shipped in any driver release, period.
For the purposes of this writeup, I will stick to a very specific version of Minecraft: in-20091223-1459, the very first version of what would soon become Minecraft's "Indev" phase, though this version notably lacks any survival features and aside from the MD3 models present, is indistinguishable from previous versions of Classic. All settings are at their absolute minimum, and the window size is left at default, with a desktop resolution of 1024x768 and 16-bit color depth.
(Also the 1.5-era launcher I use is incapable of launching anything older than this version anyway)
Though known to be unstable (as seen in the full video), gameplay in Minecraft Classic using AltOGL reaches a steady 15 fps, nearly triple that of the native OpenGL ICD that ships with Trident's drivers the card. AltOGL also is known to often have issues with fog rendering on older cards, and the Blade 3D is no exception... though, I believe it may be far more preferable to have no working fog than... well, whatever the heck the Blade 3D is trying to do with its native ICD.
See for yourself: (don't mind the weirdness at the very beginning. OBS had a couple of hiccups)
youtube
youtube
Later versions of Minecraft were also tested, where I found that the Trident Blade 3D follows the same, as I call them, "version boundaries" as the SiS 315(E) and the ATi Rage 128, both of which being cards that easily run circles around the Blade 3D.
Version ranges mentioned are inclusive of their endpoints.
Infdev 1.136 (inf-20100627) through Beta b1.5_01 exhibit world-load crashes on both the SiS 315(E) and Trident Blade 3D.
Alpha a1.0.4 through Beta b1.3_01/PC-Gamer demo crash on the title screen due to the animated "falling blocks"-style Minecraft logo on both the ATi Rage 128 and Trident Blade 3D.
All the bugginess of two much better cards, and none of the performance that came with those bugs.
Interestingly, versions even up to and including Minecraft release 1.5.2 are able to launch to the main menu, though by then the already-terrible lag present in all prior versions of the game when run on the Blade 3D make it practically impossible to even press the necessary buttons to load into a world in the first place. Though this card is running in AGP 1x mode, I sincerely doubt that running it at its supposedly-supported 2x mode would bring much if any meaningful performance increase.
Lastly, ClassiCube. ClassiCube is a completely open-source reimplementation of Minecraft Classic in C, which allows it to bypass the overhead normally associated with Java's VM platform. However, this does not grant it any escape from the black hole of performance that is the Trident Blade 3D's OpenGL ICD. Not only this, but oddly, the red and blue color channels appear to be switched by the Blade 3D, resulting in a very strange looking game that chugs along at single-digits. As for the game's DirectX-compatible version, the requirement of DirectX 9 support locks out any chance for the Blade 3D to run ClassiCube with any semblance of performance. Also AltOGL is known to crash ClassiCube so hard that a power cycle is required.
Interestingly, a solid half of the accelerated pixel formats supported by the Blade 3D, according to the utility GLInfo, are "render to bitmap" modes, which I'm told is a "render to texture" feature that normally isn't seen on cards as old as the Blade 3D. Or in fact, at least in my experience, any cards outside of the Blade 3D. I've searched through my saved GLInfo reports across many different cards, only to find each one supporting the usual "render to window" pixel format.
And with that, for now, this is the end of the very first post-video writeup on this blog. Thank you for reading if you've made it this far.
I leave you with this delightfully-crunchy clip of the card's native OpenGL ICD running in 256-color mode, which fixes the rendering problems but... uh, yeah. It's a supported accelerated pixel format, but "accelerated" is a stretch like none other. 32-bit color is supported as well, but it performs about identically to the 8-bit color mode--that is, even worse than 16-bit color performs.
At least it fixes the rendering issues I guess.
youtube
youtube
#youtube#techblog#not radioshack#my posts#writeup#Forcing Minecraft to play on a Trident Blade 3D#Trident Blade 3D#Trident Blade 3D 9880
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Storing images in mySql DB - explanation + Uploadthing example/tutorial
(Scroll down for an uploadthing with custom components tutorial)
My latest project is a photo editing web application (Next.js) so I needed to figure out how to best store images to my database. MySql databases cannot store files directly, though they can store them as blobs (binary large objects). Another way is to store images on a filesystem (e.g. Amazon S3) separate from your database, and then just store the URL path in your db.
Why didn't I choose to store images with blobs?
Well, I've seen a lot of discussions on the internet whether it is better to store images as blobs in your database, or to have them on a filesystem. In short, storing images as blobs is a good choice if you are storing small images and a smaller amount of images. It is safer than storing them in a separate filesystem since databases can be backed up more easily and since everything is in the same database, the integrity of the data is secured by the database itself (for example if you delete an image from a filesystem, your database will not know since it only holds a path of the image). But I ultimately chose uploading images on a filesystem because I wanted to store high quality images without worrying about performance or database constraints. MySql has a variety of constraints for data sizes which I would have to override and operations with blobs are harder/more costly for the database.
Was it hard to set up?
Apparently, hosting images on a separate filesystem is kinda complicated? Like with S3? Or so I've heard, never tried to do it myself XD BECAUSE RECENTLY ANOTHER EASIER SOLUTION FOR IT WAS PUBLISHED LOL. It's called uploadthing!!!
What is uploadthing and how to use it?
Uploadthing has it's own server API on which you (client) post your file. The file is then sent to S3 to get stored, and after it is stored S3 returns file's URL, which then goes trough uploadthing servers back to the client. After that you can store that URL to your own database.
Here is the graph I vividly remember taking from uploadthing github about a month ago, but can't find on there now XD It's just a graphic version of my basic explanation above.
The setup is very easy, you can just follow the docs which are very straightforward and easy to follow, except for one detail. They show you how to set up uploadthing with uploadthing's own frontend components like <UploadButton>. Since I already made my own custom components, I needed to add a few more lines of code to implement it.
Uploadthing for custom components tutorial
1. Imports
You will need to add an additional import generateReactHelpers (so you can use uploadthing functions without uploadthing components) and call it as shown below
2. For this example I wanted to save an edited image after clicking on the save button.
In this case, before calling the uploadthing API, I had to create a file and a blob (not to be confused with mySql blob) because it is actually an edited picture taken from canvas, not just an uploaded picture, therefore it's missing some info an uploaded image would usually have (name, format etc.). If you are storing an uploaded/already existing picture, this step is unnecessary. After uploading the file to uploadthing's API, I get it's returned URL and send it to my database.
You can find the entire project here. It also has an example of uploading multiple files in pages/create.tsx
I'm still learning about backend so any advice would be appreciated. Writing about this actually reminded me of how much I'm interested in learning about backend optimization c: Also I hope the post is not too hard to follow, it was really hard to condense all of this information into one post ;_;
#codeblr#studyblr#webdevelopment#backend#nextjs#mysql#database#nodejs#programming#progblr#uploadthing
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Amazon Web Service & Adobe Experience Manager:- A Journey together (Part-2)
In the fist part we discussed how one day digital market leader meet with the a friend AWS in the Cloud and become very popular pair. Also what gift they bring for the digital marketing persons.
Now AEM asked to come to my home.
So AEM insides about its parts and structure explored.
AEM Platform :
AUTHOR:-
The content and layout of an AEM experience are created and managed in the author environment. It offers features for authoring content modifications, reviewing them, and publishing the approved versions of the content to the publish environment.
PUBLISH:-
The audience receives the experience from publishing environment. With the option to customize the experience based on demographics or targeted messaging, it renders the actual pages.
Both AUTHOR and PUBLISH instances are Java web applications that have identical installed software. They are differentiated by configuration only.
DISPATCHER:-
Dispatcher environment is the responsible for caching (storing) content and Load balancing.Helps realize a fast & dynamic web authoring environment.
Mainly dispatcher works as part of HTTP server like Apache HTTP. It store as much as possible static content according to specified rules.
So end user feel faster accessing of content and reducing load of PUBLISH. The dispatcher places the cached documents in the document root of the web server.
How AEM Store Content in Repository:-
AEM is storing data without any discrimination as it treated all the family member (data) are content only . Its following philosophy of "everything is content" and stored in the same house(Repository).
Its called CRX i.e. implementation of JCR coming from parent Content Repository API for Java and Apache Jackrabbit Oak.
The basement(base) of the building is driven by MK MicroKernels as in the picture its Tar or MongoDB. The Oak storage layer provides an abstraction layer for the actual storage of the content. MK act as driver or persistence layer here. two way of storing content , TAR MK and MongoDB MK.
TAR--> tar files-->segments
The Tar storage uses tar files. It stores the content as various types of records within larger segments. Journals are used to track the latest state of the repository.
MongoDB-->MongoDB database-->node
MongoDB storage leverages its sharding and clustering feature. The repository tree is stored in one MongoDB database where each node is a separate document.
Tar MicroKernel (TarMK)--for-->Performance
MongoDB--for-->scalability
For Publish instances, its always recommended to go with TarMK.
In more than one Publish instance each running on its own Tar MK then this combination is called TarMK Farm. This is the default deployment for publish environments.
Author instance is having freedom to go with either TAR or MongoDB. it depends on the requirement, if its performance oriented and limited number then it can go with the TarMK but if it require more scalable instances then it would go with the MongoDB. TarMK for a single author instance or MongoDB when horizontal scaling.
Now story of TarMK with Author, a cold standby TarMK instance can be configured in another availability zone to provide backup as fail-over.
TarMK is the default persistence system in AEM for both instances, but it can go with different persistent manger (MongoDB).
Gift of TarMK:-performance-optimized,for typical JCR use cases and is very fast, uses an industry-standard data format, can quickly and easily backed up, high performance and reliable data storage, minimal operational overhead and lower total cost of ownership (TCO).
Now story of MongoDB it basically come into picture when more hands required, means more user/author (more than
1,000 users/day, 100 concurrent users)and high volumes of page edits required. To accommodate these horizontal scalability required and solution is with MongoDB. It leverage MongoDB features like high availability, redundancy and automated fail-overs.
MongoDB MK can give lower performance in some scenario as its establish external connection with MongoDB.
A minimum deployment with MongoDB typically involves a
MongoDB replica consisting of
1)one primary node
2)two secondary nodes,
with each node running in its separate availability zone.
AEM--store--binary data--into ---data store.
AEM--store--content data--into ---node store.
And both stored independently.
Amazon Simple Storage Service (Amazon S3) is best high performant option for shared datastore between publish and author instances to store binary files(Assets like image etc).
Continue....
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You can learn NodeJS easily, Here's all you need:
1.Introduction to Node.js
• JavaScript Runtime for Server-Side Development
• Non-Blocking I/0
2.Setting Up Node.js
• Installing Node.js and NPM
• Package.json Configuration
• Node Version Manager (NVM)
3.Node.js Modules
• CommonJS Modules (require, module.exports)
• ES6 Modules (import, export)
• Built-in Modules (e.g., fs, http, events)
4.Core Concepts
• Event Loop
• Callbacks and Asynchronous Programming
• Streams and Buffers
5.Core Modules
• fs (File Svstem)
• http and https (HTTP Modules)
• events (Event Emitter)
• util (Utilities)
• os (Operating System)
• path (Path Module)
6.NPM (Node Package Manager)
• Installing Packages
• Creating and Managing package.json
• Semantic Versioning
• NPM Scripts
7.Asynchronous Programming in Node.js
• Callbacks
• Promises
• Async/Await
• Error-First Callbacks
8.Express.js Framework
• Routing
• Middleware
• Templating Engines (Pug, EJS)
• RESTful APIs
• Error Handling Middleware
9.Working with Databases
• Connecting to Databases (MongoDB, MySQL)
• Mongoose (for MongoDB)
• Sequelize (for MySQL)
• Database Migrations and Seeders
10.Authentication and Authorization
• JSON Web Tokens (JWT)
• Passport.js Middleware
• OAuth and OAuth2
11.Security
• Helmet.js (Security Middleware)
• Input Validation and Sanitization
• Secure Headers
• Cross-Origin Resource Sharing (CORS)
12.Testing and Debugging
• Unit Testing (Mocha, Chai)
• Debugging Tools (Node Inspector)
• Load Testing (Artillery, Apache Bench)
13.API Documentation
• Swagger
• API Blueprint
• Postman Documentation
14.Real-Time Applications
• WebSockets (Socket.io)
• Server-Sent Events (SSE)
• WebRTC for Video Calls
15.Performance Optimization
• Caching Strategies (in-memory, Redis)
• Load Balancing (Nginx, HAProxy)
• Profiling and Optimization Tools (Node Clinic, New Relic)
16.Deployment and Hosting
• Deploying Node.js Apps (PM2, Forever)
• Hosting Platforms (AWS, Heroku, DigitalOcean)
• Continuous Integration and Deployment-(Jenkins, Travis CI)
17.RESTful API Design
• Best Practices
• API Versioning
• HATEOAS (Hypermedia as the Engine-of Application State)
18.Middleware and Custom Modules
• Creating Custom Middleware
• Organizing Code into Modules
• Publish and Use Private NPM Packages
19.Logging
• Winston Logger
• Morgan Middleware
• Log Rotation Strategies
20.Streaming and Buffers
• Readable and Writable Streams
• Buffers
• Transform Streams
21.Error Handling and Monitoring
• Sentry and Error Tracking
• Health Checks and Monitoring Endpoints
22.Microservices Architecture
• Principles of Microservices
• Communication Patterns (REST, gRPC)
• Service Discovery and Load Balancing in Microservices
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Top WordPress Website Development Services: Expert Web Designers & Developers Near You
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#wordpress website development services#wordpress web design#wordpress web developers#wordpress experts near me#wordpress designers near me
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