Open Source AI: What’s the hype around it? Everything you need to know about it
7 min read
Introduction
Mark Zuckerberg recently shared a long post about open source AI being the path forward on his Facebook page. He shared a pretty good argument in favor of open source AI. He explained how switching from the closed-source Unix to the open-source Linux was a game-changer back in the day. And, how Linux now powers the most widely used device in the world—the mobile phone. He then discussed how open-source AI tools such as the Meta-developed Llama 3.1 405B will be the best choice for developers, businesses, and the world in general. But enough of what Mr. Zuckerberg said, let’s start with understanding the basics of open source AI.
So, what is Open Source AI?
In simple words, Open-Source AI means AI technologies developed under open-source licenses. This means, anyone can use, modify, and share these AI technologies' source code, models, and algorithms, as they are freely available in the public domain. You knew this already, didn’t you? 😛
Also Read: Why Open source?
Why is Open Source AI a Big Deal? Why do Developers and Businesses love it?
Most of us who aren’t exactly living in a utopia still believe in democracy – you know, the whole free and fair opportunity for everyone kind of a thing. And guess what? Open-source AI tools are totally on board with that vision!
Open-source AI Democratizes Technology!
Just like everyone deserves the essentials of life, like food, clothing, and shelter, everyone has the right to the world's cutting-edge technologies as well.
Open-source intelligence tools make just that possible.
They level the playing field, giving everyone access to powerful AI tools, not just those with deep pockets. So, if you are a developer with some intelligent tricks and skills up your sleeve that can make a difference in a new technology then open source is your thing.
Liberty to Customize
Duh! It’s obvious. It’s open, so anyone can customize it according to their needs. And, we engineers get our dopamine fix by delving deep into the codebase and modifying it to suit our needs. Open-source AI gives developers the freedom to develop tailor-made solutions to the different needs of different organizations.
For instance, consider an e-commerce business that wants to build this personalized recommendation system.
Sounds cool, right?
But how can one achieve this?
This is where open source AI swooshes in like a savior!
With the help of an open-source AI framework like TensorFlow, developers can customize the recommendation algorithm to fit their unique product catalog and user behavior.
They can tweak the model parameters, integrate additional data sources, and optimize the system for their specific performance needs.
This level of customization would be difficult with proprietary software. Have you seen their prices? Shoot! 🔫
Transparency and Trust
We, developers, like to peek under the hood because let’s accept it, coding is our superpower. And knowing exactly what our power can do helps us trust it, especially when we're in the middle of an apocalypse.
Open source AI offers exactly that – trust and transparency. Open source AI codes are open to review, so we can check them for any sneaky biases or nefarious tricks.
Transparency is our sidekick to ensure that our AI allies are as reliable as they are powerful!
Let’s take an example. Imagine you are building a financial app that uses AI to predict market trends.
If you use an open-source AI to build this predictive model, you get the authority to review the codes thoroughly, you can check if the default settings are skewing predictions, look for any hidden errors or biases, and build an app that is thorough, accurate, and most importantly, unbiased.
Also, you can assure your stakeholders and customers that your AI-modeled app is thoroughly vetted, reliable, and adheres to the best industry practices. All this is possible because you have the power to fit, alter, and change unlike with the proprietary AI system that offers you a black box approach, where you can’t see how predictions are made. This leads to a lack of visibility and distrust.
Interoperability and Migration
Is it not enough that we, mere mortals, are tied down by our own fate that now you have to tie us down within your closed AI ecosystem? Let us breathe and build. Phew!
Unlike closed source AI, open source AI offers a flexible ecosystem that allows businesses and developers to build their own systems offering seamless integration with other tools and systems. Switching from one open source tool to another or integrating multiple tools is generally easier without the constraints of proprietary systems.
Let me explain the interoperability that open source AI tools offer through an interesting case study
CERN, the European Organization for Nuclear Research, operates the world’s largest particle physics laboratory. Previously, CERN relied on proprietary tools like MATLAB and SAS for data analysis and management. They faced major challenges such as high costs, limited interoperability, and difficulties in upgrading with these closed source AI tools.
To address these issues, CERN adopted open source solutions like Apache Spark for large-scale data processing and TensorFlow for machine learning.
This switch enabled CERN to process and analyze large datasets efficiently, saving on software licensing fees and ensuring continuous integration of new technologies. By leveraging the open-source community, CERN not only improved its data analysis capabilities but also ensured that its systems could easily interact with other platforms and adapt to future needs.
This case study highlights how open-source AI can drive innovation, cost savings, and interoperability in complex, data-intensive environments.
Must Read: 5 Free AI Coding Copilots for Developers to Be More Efficient
Data Protection and Privacy - the Scary Ps
Remember when EU countries had a collective privacy freakout some time back? They were seriously spooked about how their data was being handled and shared.
But, with open source AI tools, governments and organizations got transparency and control over how their data was being processed and secured.
The open-source community actively reviews and improves code, ensuring data privacy and protection. This approach not only helps meet stringent regulations but also puts a smile on the faces of developers and businesses who can confidently navigate the privacy minefield with a clearer, more secure path.
Open Source AI is Light on the Pockets
We developers love open source AI tools as these don't cost us an arm and a leg. Most often they are available for free. For us, it’s like finding out that some chic coffee shop is offering unlimited refills of our favorite coffee! ☕
No pricey licenses. No pricey Starbucks Coffee 😛
Finally! What Open source AI means for the World
Open source is basically the secret ingredient for a future where it benefits everyone. Imagine AI turbocharging human productivity, and creativity, and making life better all around, while also giving the economy and research a serious boost. Keeping AI open source means more people get in on the action and prevents a handful of companies from hogging all the power. It also makes the tech safer.
Sure, there’s chatter about open source AI being risky, but I’m betting it’s actually less risky than the closed versions. Open source means more eyeballs checking out the code, which cuts down on those accidental blunders. And when it comes to intentional mischief, open source helps keep the troublemakers in check. Moreover, rigorous testing and transparency mean we catch issues before they become problems.
Middleware Open-source - A Game Changer for Your Engineering Team’s Productivity
At Middleware, we’re practically open source campaigners, so we have rolled out our own stellar open source DORA Metrics! This tool’s got your back with all the juicy details you need on deployment frequency, lead time, MTTR, and change failure rate.
Middleware’s open source version is the perfect tool for engineering managers juggling different projects with different engineering management teams. Now, get ready to transform your DevOps game with some next-level predictability and visibility!
Also read: How to get started with Middleware Open Source
FAQs
1. How does open source AI work?
Open source AI allows developers to access an AI tool and modify the underlying code without restrictions. Open-source AI offers a shared codebase that allows the global developers’ community to improve and add new features. This collaborative approach makes AI tools accessible and helps accelerate advancements.
2. How do I contribute to an open-source AI project?
To contribute to an open source AI project, first find a project that aligns with your interests and skills. Then, acquaint yourself with its codebase, documentation, and contribution guidelines. Finally, you can contribute by fixing bugs, adding features, improving documentation, or participating in discussions and reviews on platforms such as GitHub.
3. How do I stay updated with changes in an open source AI project?
In order to stay updated, keep track of the project’s repository, subscribe to alerts for the updates, and engage with the community through forums or chat channels. Regularly check the project’s documentation and changelogs for the latest information.