Akhil Abraham George | akhilgeorge.com

Free VIN Decoder for Indian Vehicles

Sun, 08 Feb 2026 00:00:00 +0000

Every vehicle has a unique identity called a VIN (Vehicle Identification Number). This 17-character code provides important information about where the vehicle was made, its model, and other technical details. While this information is useful, most people in India find it hard to understand what their VIN actually means.

This challenge motivated me to create a simple VIN Decoder app specifically for Indian vehicles.

You can try it live here:
https://akhilgeorge.com/projects/vindecoder.html

Why I Built This Tool

I saw that when people want to check vehicle details, especially when buying a used car or bike, they often rely on complicated websites filled with ads and unnecessary features. Many of these sites are slow, confusing, or not fully relevant to Indian vehicle standards.

I aimed to create something different: a clean, fast, and user-friendly tool that provides useful information without distractions. My goal was to make VIN decoding simple and accessible for everyone.

How the VIN Decoder Works

The app lets users enter a VIN number and instantly see the decoded details. It focuses on providing meaningful information based on Indian vehicle formats and standards.

I designed the interface to be minimal, so users can concentrate only on what matters. There are no pop-ups, no sign-ups, and no complicated steps. You simply enter the VIN and get the result.

Since the tool runs directly in the browser, there’s no need to install anything. It works smoothly on both desktop and mobile devices.

Technology and Design Approach

While developing this app, I followed a clear principle: keep it light, fast, and easy to maintain. I avoided unnecessary dependencies and complex setups. The source of the information comes from Teambhp.

The entire project is open source and available on GitHub, so anyone interested can explore the code, learn from it, or contribute.

Project repository:
https://github.com/akhilgeo/VINDecoder

From “AI Assistants” to “AI Workers” - Anthropic Claude Cowork

Thu, 05 Feb 2026 00:00:00 +0000

Anthropic, the US AI startup behind the AI model Claude, recently unveiled Claude Cowork, a powerful AI tool that goes beyond traditional chatbot help. Instead of just generating text from prompts, Claude Cowork can carry out business tasks, workflows, and decision-making processes in areas like legal analysis, sales support, marketing, data review, finance operations, and more.

What makes Cowork unique:

It isn’t just a chat interface; it can perform multi-step actions on its own once given instructions.

Users can allow workspace access or connect plugins so Claude can create reports, draft legal summaries, improve data insights, and manage structured workflows without needing manual back-and-forth.

Anthropic added 11 plugins designed to integrate Claude into enterprise workflows, making the system much more capable than a standard AI assistant.

In short, Cowork turns Claude into a digital coworker, able to handle tasks that used to require many human specialists or dedicated software tools.

Why It Shook IT Stocks

When Anthropic announced its new capability, markets reacted sharply, especially in the software and IT services sectors.

Immediate Market Reaction

Global tech and software valuations dropped, with around $285 billion lost in software stocks according to various reports.

Major Indian IT companies like experienced significant declines in their share prices, causing the Nifty IT index to fall by about 6 to 7 percent.

Why Investors Are Scared

Traditionally, IT services companies earn money from:

Billable hours of developer and consultant teams
Software subscriptions for enterprise tools
Custom engineering and integration projects

But AI tools like Claude Cowork raise several concerns:

Disintermediation of software services: If an AI can handle complex workflows or automate tasks on a large scale, companies might need fewer engineers, analysts, and software licenses.

Margin pressure: As tasks that required large vendor teams become automated, traditional revenue sources based on labor and licensing could shrink.

Fear of obsolescence: Investors worry that generative AI might eventually replace or significantly reduce demand for existing enterprise software platforms and consulting services.

Some analysts have even labeled the reaction a “SaaSpocalypse,” a scenario where AI decreases reliance on Software-as-a-Service platforms and traditional IT contracts.

Lets wait and find out!

Introducing Image Optimizer: A Safe, Simple Way to Compress Your Images

Tue, 03 Feb 2026 00:00:00 +0000

I’m excited to announce the launch of Image Optimizer, a free web-based tool that makes image compression simple, fast, and completely private.

Why I Built This

In today’s web, image optimization is crucial. Large image files slow down websites, increase loading times, and frustrate users. But many existing tools require uploading your images to unknown servers, raising privacy concerns especially when dealing with personal photos, client work, or sensitive materials. I wanted to create something different: a tool that’s powerful yet respects your privacy completely.

What Makes Image Optimizer Different?

Your Images Never Leave Your Computer

This is our core principle. Image Optimizer runs entirely in your browser using modern web technologies. When you upload an image, it stays on your device. No servers. No cloud storage. No uploads. Period. You can verify this yourself by opening your browser’s developer tools and checking the network tab while using the tool. You’ll see no image data being transmitted anywhere.

Dead Simple to Use

I believe powerful tools should be easy to use. Here’s how it works:

Drag and drop your images (or click to browse)
Choose your format: WebP for best compression, or JPG for universal compatibility
Adjust quality with a simple slider
Click convert and watch the magic happen
Download everything as a convenient ZIP file

That’s it. No account creation. No sign-ups. No learning curve.

Fast and Efficient

Processing happens directly on your device, which means:

No waiting for uploads or downloads
No server queues or processing delays
Works offline once the page loads
Handle multiple images at once

See the Results

The tool shows you exactly how much space you’re saving with clear before-and-after statistics. Watch your multi-megabyte PNGs shrink to kilobytes while maintaining excellent visual quality. Key Features

Multiple format support: Convert PNG, JPG, and GIF images
Modern output formats: Choose WebP (up to 30% smaller) or JPG
Batch processing: Handle dozens of images at once
Quality control: Fine-tune compression with an adjustable slider
Preserved filenames: Original names stay intact, just the extension changes
Bulk download: Get all optimized images in one ZIP file
Real-time stats: See size reductions as you go

Perfect For

Web developers optimizing site assets
Bloggers reducing page load times
Photographers sharing portfolios online
Social media managers preparing content
Anyone who wants faster-loading images

For users with heightened security needs, you can download the HTML file and run it completely offline on your local machine. It works perfectly without any internet connection. Technical Excellence

Try It Now https://akhilgeo.github.io/ImageOptimizer—WebP/

Image Optimizer is completely free to use. No registration, no limits, no catches. Whether you’re a professional developer or someone who just wants to email photos without hitting attachment limits, Image Optimizer makes it easy.

Free Minimal Website Template for Developers - DeveloperFolio

Mon, 02 Feb 2026 00:00:00 +0000

I have just developed a new website template for developers who are looking for a clean and simple online portfolio. The template is free to use, simple to set up, and centered around what matters most – your work.

The template is minimal and simple, so your content is highlighted without any clutter. It is perfect for personal portfolios, developer profiles, or simple project showcases.

One of the most amazing things about this template is the automatic GitHub updates. Your projects are automatically fetched from your GitHub repositories, so whenever you update your code, your website will be updated automatically without any additional work.

This template is perfect for developers who:

Are looking for a quick and clean portfolio

Like minimal design

Don’t want to update project lists manually

Like open-source and simple setups

You are free to use it, modify it, and customize it according to your needs.

You can check out the template, learn more details, and download it from GitHub here:

https://github.com/akhilgeo/DeveloperPortfolio

If you are looking for a simple developer portfolio without any complexity, this template might be helpful for you.

Is the AI Boom an Investment Bubble? Lessons From the Dot-Com Era

Sun, 30 Nov 2025 00:00:00 +0000

In recent years, Artificial Intelligence has become a hot topic in technology and investment. Companies are eager to integrate AI into their operations, startups are raising millions based on prototypes, and stock prices of AI-focused firms have surged. This surge in enthusiasm raises an important question:

Are we experiencing an AI investment bubble similar to the dot-com bubble of the late 1990s?

While AI is clearly transformative, the current excitement mirrors the hype, speculation, and fast investments seen during the dot-com era. Let’s look at these similarities, consider what makes the current situation different, and discuss how investors and companies can prepare.

The Hype Cycle: History Repeating Itself

Dot-com era (1995–2000):

Investors poured money into any company with “.com” in its name. Many startups had vague business models but received high valuations simply for being part of the trend.

AI era today:

If the dot-com bubble was about websites, today’s equivalent is anything called AI-powered. Companies are adding “AI” to their pitches, sometimes without real capabilities. Valuations are rising sharply. Venture capital investments in AI startups have reached historic highs, similar to internet funding two decades ago.

2. Rapid Capital Influx and Overvaluation

Then:

Investors thought every internet company would become the next Amazon. Even unprofitable firms received billions in funding and high IPO valuations.

Now:

Tech giants and startups are attracting enormous investments for AI model development, data centers, and chip manufacturing. Some companies without proven revenue streams are being valued as future industry leaders, reflecting the mindset of investing now before it’s too late.

3. Technology Overestimation, Business Underestimation

Dot-com bubble:

The technology was groundbreaking, but many businesses failed because they did not grasp traditional economics—like customer acquisition costs, profit models, inventory, and logistics.

AI bubble parallel:

AI is powerful, but many companies chasing it lack:

Sustainable business models
Clear differentiation
Real-world use cases that generate revenue

The gap between technological potential and commercial viability is widening, a classic sign of a bubble.

4. Talent Shortage and Salary Inflation

Then:

Web developers and network engineers became scarce, leading to soaring salaries. Companies hired aggressively without clear job roles.

Now:

AI researchers, data scientists, and compute engineers are in high demand. Some professionals are earning salaries normally reserved for top executives. Startups often recruit expensive AI talent even before developing a profitable product.

5. The “Fear of Missing Out” (FOMO) Investment Pattern

FOMO drove the dot-com bubble. Investors feared missing the next big thing, leading them to invest in untested companies.

Today, the same pattern is evident:

Businesses are adopting AI before clarifying their strategies.
Investors are backing any AI startup to avoid getting left behind.
Companies are announcing AI initiatives to stay relevant in the news.

FOMO drives bubbles more than underlying fundamentals.

6. Infrastructure Overbuild — With Potential Upside

One positive similarity is the expansion of infrastructure.

In the 1990s, overbuilding of fiber optic networks occurred. Even after the bubble burst, that infrastructure became crucial for modern internet services.
Today, global AI infrastructure—GPUs, data centers, high-speed networks—is rapidly scaling. Even if the bubble partially bursts, this foundation will drive future innovations.

What Makes the AI Boom Different?

While bubble signs exist, there are also significant differences:

1. Clear, proven use cases

Unlike many early internet ideas, AI is already delivering real value through:

Code generation
Automation
Drug discovery
Customer service
Predictive analytics

2. Major tech giants lead the investment

During the dot-com boom, many players were small, untested startups. Today, trillion-dollar companies drive the AI push, equipped with real revenue streams to support long-term investment.

3. AI evolves faster than past technologies

Generative AI models improve significantly within months. This rapid evolution lowers the risk of the technology becoming obsolete before monetization can catch up.

Will the AI Bubble Burst?

Probably yes, but not entirely.

We may see:

Overvalued startups fail
Layoffs in overstaffed companies
Investor corrections
Consolidation of AI firms

However, the long-term impact of AI will not vanish. Just as the internet bubble burst but left us with Amazon, Google, and e-commerce giants, the AI era will produce a few dominant players that reshape the world.

The AI boom displays many traits of a typical investment bubble: hype, speculation, rapid capital flow, inflated valuations, and FOMO. But unlike the dot-com era, AI already has proven use cases and deep integration into business workflows.

Some bubbles burst because the idea was flawed. Others burst because the timing was early—not wrong.

AI belongs to the second category.

The bubble may shrink, but the innovation will continue. The real winners will be those who invest smartly, create practical solutions, and focus on sustainable growth.

Google Antigravity - Future of Dev?

Sun, 30 Nov 2025 00:00:00 +0000

The first time I opened Google Antigravity. At first glance, it looked like just another sleek editor. It was familiar enough not to intimidate me, yet different enough for me to sense something significant happening beneath the surface. I had heard all the buzz online about how this would change development forever, that programming was about to take a huge leap. But hype is hype, so I wanted to see for myself.

The real surprise came when I created my first project. Instead of staring at an empty editor waiting for me to type, Antigravity asked me what I wanted to build. Not in a dropdown menu or a scaffold wizard — it literally asked me in plain language.

So I typed something casual, like I was talking to a colleague: “Create passowrd generator with GUI.”

What I saw next was surreal. An AI agent appeared in the side panel and started planning. It outlined the flow, the endpoints, the validation rules, the database schema, and the testing approach. I hadn’t written a single line yet. Then it began working in real time: opening files, writing code, launching a terminal, running tests, and even opening a browser to simulate the flow. For the first time in my career, I wasn’t writing code line-by-line; I was orchestrating it. It Felt Like Having a Team Working Beside Me What really amazed me was realizing that Antigravity isn’t just a single AI assistant like we’re used to. I could launch multiple agents - one to build backend APIs, another to create a basic React UI, and another to generate test suites. They weren’t simply throwing code snippets at me. They were working together, finishing tasks, handing things off, and showing me progress almost like a team would.

On the Manager Surface, I could see everything happening in parallel - progress bars, decisions, and the artifacts being produced, like plans, test results, and session recordings. I wasn’t guessing what the AI was doing behind the scenes; I could see it. I could approve or reject steps or jump in and edit anything manually. It was clear, collaborative, and surprisingly fast. Suddenly, my role as a developer felt different. I wasn’t stuck typing boilerplate or debugging tedious setup errors.

I started thinking more like this: Does this design make sense? Does this flow match the user’s journey? Are the edge cases covered? What should the architecture look like next? I felt like I had leveled up - from coder to curator, from mechanic to engineer. This Changes Who Can Build Software After a few days, I realized that Antigravity isn’t just a productivity boost for those who already code. It actually opens the door for people who never thought they could build software. If you can explain what you need clearly - with requirements, goals, and use cases - Antigravity can create a working prototype faster than many junior teams. It doesn’t replace developers; it removes the blocks that slow innovation, like scaffolding, repeated setups, rewrites, UI wiring, and browser debugging. The mundane tasks vanish so you can focus on what really matters: ideas.

Yes, It’s Still Early Of course, it isn’t perfect. I’ve seen discussions online about security concerns: trusting AI agents with real workspace permissions is risky, and a compromised environment could lead to ongoing code execution. That’s something we can’t overlook. You also need strong engineering judgment. If you don’t understand design patterns, database choices, or security practices, you could lead the AI into chaos. Antigravity won’t replace people who think deeply, but it might replace those who only type quickly.

Where This Leaves Us After using Antigravity for several days?

I’m convinced I’ve seen a glimpse of how development will look in the near future. We’ll spend less time typing and more time shaping products. We’ll manage groups of intelligent agents the way we manage microservices today. Coding will become more about intent and architecture rather than syntax correctness. Google didn’t just build another tool. They introduced a new mindset: Software won’t always be built by humans typing into editors, but by humans directing intelligent systems. And honestly? It feels like stepping into the future of development - a future where creativity matters more than ever, where ideas become real faster, and where programming feels lighter. Maybe that’s why they called it Antigravity.

AI is reshaping IT industry - A Look at the 2–3 Year Roadmap

Tue, 03 Jun 2025 00:00:00 +0000

The IT sector is about to change radically. The industry has changed over the past few decades from on-premise infrastructure to the cloud; now it is entering the age of artificial intelligence (AI). It is a structural change in how software is conceived, created, tested, and kept, not just a wave of automation.

AI will speed this transition over the next 2–3 years, fundamentally changing the talent demands, delivery methods, and business value streams of the sector.

The Present: Artificial intelligence as a productivity enhancer

Presently, artificial intelligence serves as a co-pilot helping developers, testers, and analysts in their work. Instruments such as GitHub Copilot and Amazon CodeWhisperer speed up developers’ coding.

ChatGPT helps to create SQL queries, scripts, or even design ideas.
Among other AI-based QA tools, Testim and Mabl automate and self-heal test cases.
Jasper and Notion AI assist with the production of documentation, release notes, and knowledge articles.

Already assisting businesses finish projects with less resources and in less time are these instruments. But this is only the start.

The next two to three years will bring about what modifications?

1. AI-Native Development Environments

Most Integrated Development Environments (IDEs) will be AI-native by 2027, meaning:

Less than 30% of code will be written by developers by hand; the other 70% will be auto-generated depending on prompts or patterns already in use.
AI will immediately recommend reusable logic based on past commits and corporate databases.
Big language models (LLMs) will let non-developers—like business analysts—create working prototypes utilizing natural language.

Effect: The obstacle for software development will be removed. Low-code/no-code builders and citizen developers will become essential components of delivery teams.

2. QA Teams Will Shrink but Develop Smartness

AI-powered test automation solutions will:

Develop and sustain tests with little human involvement.
Project possible failure points based on historical defects.
Regularly verify user flows with synthetic data and production logs.

Impact: Jobs in manual QA will go drastically decreasing. Rather, hybrid roles such as Test Automation Engineers, AI QA Analysts, and Prompt QA Specialists will develop—targeted more on developing intelligent test plans than on executing test cases.

3. Smaller groups with greater impact

AI will serve as a force amplifier. Using artificial intelligence well, a five-member engineering team could beat a 20-member team operating manually. Expect:

Agile pods with 3–5 members providing full-stack solutions.
AI bots managing documents, surveillance, and low-level bug fixes.
Managers of projects employing artificial intelligence to monitor progress, forecast hazards, and create reports.

Companies will concentrate on value-based hiring—looking for multi-skilled people at ease with artificial intelligence rather than big headcounts.

4. Cost Optimization and Outsourcing Models Shift

Many classic outsourcing models based on large offshore teams will be challenged:

Clients will increasingly request more outcome-driven agreements in which artificial intelligence is crucial for lowering cost and time.
Repetitive support activities like password resets, report generation, and L1 debugging will be eliminated by artificial intelligence.
Cloud platforms will include more AI-native technologies, therefore lowering the requirement for customized development.

With a new emphasis on AI-driven managed services and automation-first delivery strategies, offshore-heavy delivery models may drop by 30–40%.

5. Fresh jobs will arise.

Some conventional roles might shrink, but fresh ones will appear:

AI Prompt Engineers
AI instructors and curators
Officers of ethical artificial intelligence
Model Performance Analyst
Cognitive UX Designers

Areas where artificial intelligence still lags, these positions will combine technology, subject matter knowledge, and human creativity.

The experts that will flourish are those who:

Early on, welcome artificial intelligence tools and learn how to assign regular tasks to machines.

Concentrating on domain knowledge, architectural design, and design thinking
Create hybrid skills by knowing both the technical and the commercial aspects of systems.

Particularly in fields like AI ethics, prompt engineering, cloud-native design, and DevOps, reskill often.

From Ancient to Arena: Why Dota 2 Players Feel Right at Home in Clash Royale

Sun, 18 May 2025 00:00:00 +0000

Dota 2 to Clash Royale: Why It’s So Natural to Make This Switch

You’re used to making high-pressure decisions, quick battles, and a race to outmaneuver your opponent as a Dota 2 player. But with more to do in life or a change in gaming rig, sometimes it’s not convenient to launch a full Dota game. That’s where Clash Royale comes in — not as a substitute, but as a natural extension of the same kind of game Dota players enjoy, in a mobile-ready setting.

Here’s why making a transition from Dota 2 to Clash Royale is simpler than you imagine — and why it could be an ideal fit.

1. Both Reward Strategy Over Speed

In Dota 2, as in Clash Royale, whoever has superior game sense, timing, and planning emerges victorious — not necessarily whomever taps the most.

DotA 2: Victory in fights comes from anticipating enemy actions, handling cooldowns, and timing/starting fights at appropriate moments.

Clash Royale: Victory comes from elixir management, strategic placement of units, as well as anticipating your opponent’s moves.

Why the transition is a breeze: If you’re comfortable thinking a couple of moves in advance in Dota, you’ll find yourself comfortable in Clash Royale’s tactical gameplay.

2. Unit Roles Are Familiar

In Dota, each hero belongs to a certain role category: tank, support, nuker, carry. Clash Royale provides a similar system with its cards:

Golem or Giant tanks imitate heroes such as Axe or Bristleback.

Swarm troops have a feeling of Dota creeps with synergy.

Support heroes such as the Electro Wizard can dictate the tempo of a game, such as a Crystal Maiden in a proper position.

Why it’s a transition: You’ll naturally understand unit behavior, counters, and synergies from your Dota instincts.

3. Hero Drafting = Deck-Building

Similar to assembling a balanced team in Dota, deck-building in Clash Royale is all about

Creating a synergy (e.g. Ravage + Black Hole → Freeze + Balloon)

Concealing deficiencies

Adapting to the meta

Why it’s a natural transition: The theorycraft aspect of Dota (item builds, team compositions, timing pushes) translates directly to crafting dominant Clash Royale decks.

4. You Still Get Those Clutch Moments

You feel it in Dota, landing that sweet Black Hole or getting a 1v3 win. Clash Royale has it as well — in those final 20 seconds of a game where both towers have low health, and all actions matter.

Why it’s a natural transition: The adrenaline high and requirement to stay cool in tense situations both happen in both games.

5. Competitive & Community-Driven

Dota 2 does have TI, MMR farming, and community-created content.

Global leaderboards and ranked ladders

Seasonal challenges and tournaments

Active Discord and Reddit communities

Friendly matches and donation systems in clans

Why it’s a seamless transition: You don’t lose that social or competitive feeling — it just happens on your phone.

6. Shorter Matches, Same Brainpower

The Dota games have a duration of 45-60 minutes. Clash Royale provides a complete strategic experience in 3-5 minutes per match.

Why it’s a breeze to transition: You still receive your strategy fix, but with no time needed from an entire evening or complete gaming rig.

If you play Dota 2, but want a game that honors your time, challenges your mind, and still provides you with the rush of beating your competitor — Clash Royale could not be more of a natural fit. It’s not a trade-off; it’s a complement.

Try Clash Royale next time you’re on-the-move or just feel like gaming without dedicating an hour — you might find that all those Dota habits still hold up, only in a new arena.

5 reasons why every SAP consultant must start using Lucidchart with AI

Sat, 26 Apr 2025 00:00:00 +0000

With today’s fast-paced SAP environment, time and clarity are of the essence. Whether you are documenting the Order-to-Cash (O2C) process for a customer or crafting a custom enhancement, precise visual communications are essential. Here, Lucidchart AI steps in to be a game-changer for SAP consultants.

What is Lucidchart AI?

It has been widely recognized for being an effortless tool for developing process diagrams, flowcharts, and system architecture. Now that there is AI integrated, it auto-generates flowcharts from document inputs or simple text prompts. Rather than dragging boxes and arrows by hand, you write out your process — and Lucidchart constructs the draft for you in seconds!

How it benefits an SAP Consultant

1. Quicker Documentation

Typically, while documenting SAP processes (such as pricing procedure determination, delivery process, correction of invoices, etc.), it may involve several hours to create an appropriate flowchart.

With Lucidchart AI, you just type: “Flowchart for SAP SD Billing Process from Delivery to Invoice to Accounting Document” — and it auto-generates a tidy diagram.

You invest your time refining, and not beginning from the basics.

2. Improved Client Communication

Non-SAP users learn flowcharts better and more quickly than SAP t-codes and tables.

Lucidchart AI assists you to instantly show clean, professional-looking diagrams for workshops, blueprint sessions, and UAT cycles.

3. Error Reduction

Manual flowcharting tends to result in missing steps.

Using AI, the initial draft itself includes fundamental logic, and you only adapt it for particular SAP instances such as various types of billing (F2, RE, G2) or types of delivery (LF, LO).

4. Saves time while designing Blueprints and Solutions

During the blueprinting process, consultants are pressed to develop Business Process Flow Diagrams (BPFD) within a short time.

Lucidchart’s AI saves you 50–70% of effort so that you can think more about the actual solution rather than diagram formatting.

5. Reusable Templates

Once you have refined a flowchart, you can save it as a template.

For instance: design templates for SAP procedures such as Contract Management (VA41–VA42), Order-to-Cash, or Third-Party Drop-Shipment — and use these repeatedly throughout various projects.

A Small Suggestion Suppose you wish to demonstrate the SAP Sales Order to Invoice process.

You type: “Begin: Order from Customer —> Sales order (VA01) created by SAP —> Delivery created (VL01N) —> Goods Issue is posted —> Billing document created (VF01) —> Accounting document posted (FI).” Lucidchart constructs a professional flowchart instantly, displaying every step and connectors and being ready to share.

Our task, being SAP consultants, is not only to configure — it is to communicate, to design, and to deliver more quickly. Lucidchart using AI is the perfect fit for this. It eliminates 60% of the tedious, hand diagramming labor, and you can then concentrate on solutioning and value to the clients. If you haven’t yet given it a shot, begin today — and observe how your documentation speed, quality, and client impact all dramatically change.

How to Make Ghibli-Style Images for Free Without ChatGPT?

Sat, 29 Mar 2025 00:00:00 +0000

If you’ve been on social media recently, you’ve probably seen the latest trend: Ghiblify. The trend is transforming your photos into beautiful Studio Ghibli-inspired paintings—a Japanese animation style that’s renowned for its watercolor texture, pastel color palette, and warm, cozy environments.

The ChatGPT Ghibli Image Generation Issue

One of the most popular ways people have been generating Ghibli-style images is through the image generation tool on ChatGPT. Although it was previously available only to premium users, OpenAI has started rolling it out to free users too. However, there is one major problem—server overload.

Several free-tier users are experiencing problems such as:

Rate limits: You might get a message that says, “System has reached its rate limit for image generation. Please wait for about 10 minutes before trying again.”

Multiple retries: Even after waiting, the system may still be too busy to generate an image.

If these limitations infuriate you, fear not! There is another method of Ghiblifying your images without spending a dime.

Alternative Method: Using Fotor’s GoArt

A great free substitute for the Ghibli image generator by ChatGPT is Fotor’s GoArt. You can use it as follows:

Visit GoArt by Fotor.
Register for a free account using your email ID.
Sign in and navigate to the “AI Tools” page.
Select “Ghibli Style” among the AI Filters provided.
Upload your photo and let the AI work its magic.
Download your Ghibli-esque photo (note: it will have a Fotor watermark).

Final Thoughts

While ChatGPT’s image generator is a great tool for creating Ghibli-style artwork, its free tier limitations can be frustrating. GoArt by Fotor provides a great alternative that’s easy to use and delivers results within less than a minute. So, if you wish to join the Ghiblify trend without the hassle of server constraints, give GoArt by Fotor a try!