Open source AI platforms are helping humanity move toward a futuristic world faster than most anticipated.
OpenAI, Microsoft, and Google have had an outrageous month in the factitious intelligence (AI) space, and this field keeps accelerating.
What’s open source AI?
Defining this term requires understanding a number of others.
Open source is a software development term meaning any programmer can jump in and work with it, the goal being to develop robust software in a shorter period of time.
That is a fantastic method to leverage the novel ideas of the perfect minds to fuel progress in technology. Consider open source as a bunch project where humanity advantages from A+ work.
Artificial Intelligence is a branch of computer science that develops programs and algorithms (step-by-step processes designed to unravel an issue or answer an issue) that help make various machines operate in additional human-like ways.
There are several subfields of this science, including:
- Natural language processing (NLP), which focuses on developing natural interactions between humans and computers. Specialized software helps machines process human language, create comprehensible words, and interact with humans through language.
- Machine learning (ML), which prioritizes a machine’s ability to research information and use it to make recommendations or decisions based on the information sets it has provided.
- Computer vision, which is all about creating machines that may understand after which interpret visual information.
- Robotics that may physically perform tasks without human micromanagement, including interaction with humans.
Right away, corporations confirm we’re human by having us select photos from a set with one thing in common, reminiscent of cars or volcanoes. And if we were to see a automobile at the bottom of an lively volcano, we will extrapolate that the automobile shall be damaged. Machines are still developing these abilities.
Open source AI, then, may be defined as software engineers collaborating on various artificial intelligence projects which can be open to the general public to develop. The goal is to raised integrate computing with humanity.
We’d like one last bonus keyword that helps us tie open source AI to marketing: Industry 4.0.
Industry 4.0 is the concept that advanced computing and AI have unlocked a latest era in human productivity.
- The primary industrial revolution was about creating machines to do work via steam or water power.
- The second industrial revolution was after we converted machines to electric power and embraced mass production. Products were built by human assembly lines, assisted by electric conveyor belts that brought the work to their hands.
- The third industrial revolution was after we plugged computers into the machinery to spice up efficiency and automation. Automotive factories now have machines programmed to quickly and precisely construct cars without human assembly lines.
- And now the fourth industrial revolution — dubbed Industry 4.0 — is about how the industry is changing now that humanity and computing are so closely interconnected. Business doesn’t just occur in boardrooms and on factory floors anymore. We supply it in our pockets.
We will sell and reinvest stocks from our kitchens on the touch of a button. Without touching anything, a voice-activated computer can order groceries, add appointments to our digital calendars, and tell us jokes as we do business from home as an alternative of commuting to an office.
It’s this latest landscape, this latest era in production via interconnected technologies, where open source AI for marketing comes into play.
How can marketers use AI?
AI offers a huge range of functionality to marketers who wish to make the leap, from small assists all the way in which as much as running campaigns for you.
We’ll share some use cases to present you an idea of what’s on the market.
Automated Social Posts
One in all the smallest ways to leverage smart technology in marketing is to make use of a program that schedules and posts your pre-loaded social content.
You set the frequency (several times a day to once a month or more) after which load up your whole prepared content. It does the give you the results you want on your individual custom schedule.
That is an area where AI is booming. Marketers charged with creating written content have similar struggles across the industry. How do they keep coming up with ideas that can resonate with their audience? How can they produce content in less time to spice up conversion?
Corporations count on AI content to save lots of the time it takes to create the body of such work, spend less on writers, and call on their experienced wordsmiths to then dial in on quality.
Personalized Emails and Data Capture
Most of us have experienced follow-up emails to the effect of, “Hey, you left an item in your cart!” or, “There’s an item in your wish list that just dropped in price!”
People cannot possibly write these billions of every day emails customized to every consumer’s shopping habits — but AI can.
Algorithms have been devised to drag user data, analyze how each customer interacts with a brand, and create personalized email content. Then, AI schedules and sends that content, all with none human interaction after it’s been arrange.
Saying “Send a thanks note to Savannah” initiates an algorithm that pulls Savannah’s email address out of your contact list, creates a thanks email, and splices Savannah’s name into it. This system can send it then or read the note to you, allowing you to make changes before sending.
Ad Targeting and Pay-Per-Click Campaigns
In case you advertise on Google or Facebook, programs like AdWords provide you with deep insight and scalpel-minute details to provide help to gauge how your promoting campaigns are playing out. Additionally they facilitate pay-per-click (PPC) bidding so you possibly can efficiently allocate your ad budget.
AI can analyze who has been engaging together with your ads, then redirect ad spend to groups that market research may not have anticipated. You might be delightfully surprised by what number of leads you discover or conversions you gain.
Ethical Considerations Before Using Open Source AI
Nothing latest comes easy. Even the very best level of technology development has vital human elements that have to be addressed sooner relatively than later.
People write algorithms and datasets, and other people have biases — whether or not they know the unique lenses through which they see the world or not. Those influences can and do change what a program does, especially if the AI’s output is designed to alter based on human behavior in virtual spaces.
These problems grow to be apparent when looking for bias-charged words. You’ll wish to construct programs that avoid stereotypes and false information.
So how can programming be less biased? That is one among the most popular topics in AI without delay, and the solutions (and laws) are still being forged.
Incorrect or Incomplete Information
Simply because it’s on the web and AI finds it doesn’t mean it’s true. And simply because something’s popular doesn’t mean it’s right.
Likewise, simply because you’ve gotten true information doesn’t mean you’ve gotten the entire picture, regardless of how hard you push your search engine to search out the reality.
10 Top Open Source AI Platforms and Tools
Now to the foremost event: We’ve compiled a listing of open source AI tools to introduce you to a few of the perfect options as you wade through this topic, resolve if micro AI could help boost your ROIs, or if larger open source AI projects are what you’ll want to meet your organization’s goals.
TensorFlow is a complete support structure for programmers who wish to help one another create something novel while reaping the advantages of other experts’ existing models.
TensorFlow is one of the vital robust AI platforms and offers training videos to assist jumpstart your success.
PyTorch, like TensorFlow, is a one-stop shop for transforming ideas into functional applications. It’s a complete framework created to support various points of open source AI project development, including vast libraries and datasets to drag from.
This platform is simple to make use of for developers who already code with Python. Its object-oriented approach helps bundle up usable chunks of code that do exactly one job.
This known and reliable “object” can then be plugged right into a more extensive sequence to do a more complicated job, helping programmers help one another.
Pro tip: Programmers fluent in Python flourish here, nevertheless it also has a C++ interface for many who don’t code with Python.
Billed as being designed for humans, Keras is an application programming interface (API) that permits you to quickly and simply share the front end of your deep learning models.
You may export your models from Keras and run them in browsers, iOS, and Android. Their Python libraries are inclined to concentrate on artificial neural networks.
Best for: Programmers preferring a more streamlined user interface while working with the latest versions of TensorFlow, simplifying interaction with the software because it’s being built.
OpenAI is everywhere in the news, and for good reason — it’s changing the sport of natural language processing (NLP) AI programs. They provide a model called Codex that changes natural language into code within the programming language you specify.
What’s more, like other open source AI projects, you possibly can access their models and customize the code yourself.
OpenAI is mastering what Alexa/Siri does and taking the subsequent step in Industry 4.0. This AI can synthesize its own natural language answers from the data it finds as an alternative of just pointing to a web site and reading it. Incredible stuff, and you possibly can work with it!
Price: Free $18 credit to experiment for 3 months, then prices are token-based and rely on what you employ as you go.
OpenCV is well-known for its open source AI platform for computer vision. If TensorFlow has an undergrad degree generally AI, OpenCV holds a master’s in AI vision.
And it really works just about in every single place because its library was written in C, which it claims may be ported to all the things from “PowerPC Macs to robotic dogs.” It features a latest C++ interface, and wrappers have been developed for Java, Python, and other languages to encourage cross-language development.
Best for: Developing AI specifically for computer vision applications.
Price: Free, including for industrial use.
H2O.ai’s AI Cloud Platform copy claims that it’s “the fastest, most accurate AI platform on the planet” and appears to pay attention to ethical issues in AI.
They strive to democratize AI by making it available to anyone, empowering humanity to make use of it to affect the world positively.
A solid alternative for: Corporations that prioritize development speed and likewise plan to make use of AI to boost their offerings, working toward streamlined AI management across the board.
Price: Free to develop open source software and to make use of their H20 Wave API.
Rasa is great for constructing conversational AI (chatbots) and deploying it via the cloud free of charge. It’s flexible and touted as “future proof” since it’s been designed so you possibly can plug any NLP or ML model into Rasa to present you increasingly accurate results as technology improves with time.
Best for: Branded conversational AI for enterprises that comes with built-in integrations for social messaging like Slack and Facebook.
Price: Free. There are also paid pro options for enterprises.
8. Amazon Web Services (AWS)
If you’ve gotten code to run or want a well-recognized place to begin constructing, you possibly can do it free of charge on AWS/ The platform also stores the outcomes/output of your programs.
As well as, AWS offers quite a few value-added features for business marketing, reminiscent of customizing your code for his or her content delivery network and managing task coordination to your various cloud applications, all free of charge.
Best for: If you’ve gotten a handle on coding but could use some support services adjoining to development — including business features to provide help to level up toward Industry 4.0.
Price: Costs vary. There are short-term offers, 12 months free, and all the time free options.
No matter your chosen platform, the GitHub platform keeps collaborative work orderly.
GitHub is the most important name in programming cooperation. The platform helps organize projects when many hands touch the identical code, keeping track of version histories, notes, and Wikis.
Best for: Individuals or teams that don’t know one another but wish to work productively on a project.
Price: Basic $0, Team $44, Enterprise $231.
GitHub AI Projects: Instagram Spam Protection & Fake Product Review Identification
We’re including these open source AI projects in development on GitHub because a lot of promoting involves moderating your social networks once content is live.
These projects mean you can pull pre-existing datasets for training your programming models to do the work more thoroughly — higher protecting your brand to maintain those leads rolling in.
Pro tip: Google open-sourced their ALBERT model so that you can emulate. This system excels at natural language processing and is agile with language-specific issues like interpreting meanings in context.
The Future Unfolding Around Us
You should definitely keep your eye on the developing topic of AI. It’s happening quickly throughout us.
It’s sure to be a wild ride! The innovative of technology all the time is, and AI gets sharper, smarter, faster, more enmeshed by the day.