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Innovate? An LMS? LXP? Learning Platform? Employee Dev Platform? Are you saying that any of these platform types are innovative? Wait, LMS? Oh, that is so traditional; there isn’t any innovation there. LXP? That’s where innovation comes in (hint- it doesn’t). A Learning Platform driven by brain-centric modalities? That must be innovative. AI-first platforms. Ok, that has to be innovation at the forefront. Huh? That isn’t an accurate statement, or any statement, for that matter.
Wait, are you telling me that the industry still suffers from a lack of innovation to such a degree that we are just seeing the same ol same 95% of the time?
Innovation is a word to toss around because its ambiguities are enough to put something through at the tiniest level, as though you are placing a piece of paper into a slot, and out it comes to your wonderful hands.
The whole LXP innovation pitch continues and is a load of month-old baloney. What I see today isn’t unique. Many of the initial feature sets that stood out—or that were enhanced and tweaked from a visibility standpoint—are gone. LMS vendors always had skills and capabilities.
Not where we are today, but then again, you shouldn’t compare a system from 2004 to one that is in play now, nor should you think that what folks seek in extensive skills capabilities within a system (assuming the employee is your core, and yes, some customers too—dependent on the case) wasn’t around in the early days because of different expectations and needs.
Just as you wouldn’t expect a new car version to be the same as one that exists today, think about it. Rear-view camera? Sensors if you go out of your lane? Most people didn’t need those in the 2000s. Nowadays, sensors are pretty much standard in all vehicles. Rear-view is an option; most of the time, it comes with the vehicle anyway. You now expect those things.
Seatbelts is another one. When I got my driver’s license in the early 80s, wearing a seatbelt wasn’t a federal requirement. I wore one with my driver’s test, but it was hit or miss after getting my license. Today? Seatbelts are mandatory when you drive a vehicle and, in many cases, on the passenger side (although I think many folks ignore that).
Where can you find innovation?
It is out there – yes, in some systems – i.e., the system itself, which I will note shortly. Then it is there, well, in any system, if you look, and yes, pick it out, and go WOW, that is different, unique, and I see it as the “Gold.”
That is something you should be looking for – if you are seeking a system or as a vendor, you should be examining it right now – is there something there that is unique – that if Craig looked at it, he would say, WOW.
Isn’t every system innovative?
No. Just because they say it is – “We do things differently. We are not a (fill in the blank – but often they use LMS). This is very unique,” doesn’t mean it is true. On the other side, I always hear people saying to me, “No system can do this.
We haven’t found a system that can do that. What we need just isn’t out there.” First off, it probably is if you expand your look and reach. The vendor may be horrible at marketing (often the case) or messaging (ditto on the case); therefore, you won’t know or hear of them.
That said, way too many – can’t grasp it. There are many whose whole design and approach is based on their biggest clients, or clients in general, that seek this or that. This, to me, is a big mistake – because you are supposed to be the expert, not the client. Trust me, a client won’t know everything out there or what is possible (today).
Then, some vendors will go down a rabbit hole because a couple of large clients asked for it. This goes at the bucket of worst ideas behind the decision to sell electrolyte flavor packs for water—bad, bad idea.
The Systems that do something different (that I have seen so far)
#1 Vendor doing something that goes beyond HOLY MOLY!
Kilo—They focus solely on the maritime industry (and also offer EdTech maritime training), using VR simulations. They also have an LMS, but what stands out to me is…
Their VR simulations, available for safety management, operations, and navigation, take the whole VR piece to a new level.
How? By dropping in a live instructor. The live (yes, human) instructor can bounce into the courses/content and add instructions on how to do things, etc.
It reminds me of the “group party” thing that many of the VR headsets have, where folks can go into the area and talk to others in real-time – despite them being anywhere in the world. The same applies here – except it is an instructor.
OnPoint took a different approach to VR. They developed a course/content that appears in the Apple Pro Vision. A learner can select the course and go right into it. The client that went with it is T-Mobile, who is adding the Apple Pro Vision headsets—one per store. I think it has potential. However, the APV has turned out to be a dud in terms of sales and other issues. Nevertheless, that isn’t due to OnPoint.
For what it is worth, OnPoint does fully customized LMSs – including mobile. I know you will say hey, Moodle does that, and blah blah. Moodle does okay, but the level of what OnPoint can do, plus the person behind it, Robert Gadd (an early pioneer of e-learning and a pioneer of mobile), differentiates it from the pack.
Pluralsight continues to be innovative in multiple ways. One is the data visualization and data points.
They provide data points that tell me my learning story—thus, true learning intelligence. It doesn’t cost me extra. It doesn’t require me to have a background in stats or tech; rather, it presents real useful information for your learning. They are IMO the best system out there for data visualization and metrics, as it relates to showing me my learning story.
I love the innovation when it comes to certification, which is popular with various companies and definitely associations. Here is their way of presenting (please note my screenshots are from a video—and Pluralsight approved the usage—viewing of it).
Another section I think is brilliant, and I have not seen this in any other learning system on the market. The system will show you the cost of the token fees tied to the characters and words you are using for the prompt. Tokens are charged based on the number of characters you type into a prompt, regardless of what you type.
The vendor – yep, gets charged a fee. While the price of the fees is quite inexpensive, it ramps up fast when folks are always using the prompts. They show the number of characters available to type into the prompt – another brilliant move. This is because every LLM has limitations on the number of words you can enter into a prompt. Some of it is massive – which you think rocks – however – those token fees.
The one downside here is that the token fees angle only works within their Playground, which is awesome by the way. However, the prompt—think Gen AI here—is not available anywhere else in the system.
Above the learner typed into the prompt – How do I learn tech skills? You can see the tokens used and the costs (Admin side).
Another tokens data and cost that appears on the admin side.
Compare the prompt options (see image below). Okay, you are on the admin side and are debating the cost based on various LLMs on the market. You can compare the fees by selecting an LLM (that is listed in the system vs. another).
Pluralsight does not have all these LLMs in its platform. The one minus is that Pluralsight doesn’t update the LLMs—thus, the ones it has today are dated and no longer utilized by many companies, even in Enterprise.
You won’t see GPT 4o (known as 4 omni), the latest with Claude, or Llama3 from Meta. Yes, new LLMs are coming out all the time, which is hard for a vendor to keep up with, but utilizing the prompt angle here, they need to do so—perhaps once a quarter.
Lastly, the feedback loop. I kid you not; I have seen feedback loops in less than ten systems. That isn’t very good. Especially since AI learns from itself, so, if the response is inaccurate (due to hallucinations – fake or false information or AI bias are just two), you – the learner – can’t change it. You – the learner – can’t edit in what is wrong, nor do you have a thumbs up or down option (common with feedback loops, although there are LLMs that it is a flag – indicating inaccuracies). Way too many vendors think learners know about fake or false information, AI bias, and so on. This is false. Not even close to being real. And while there are content creators that allow you to edit the text – it is only within the context of the course – and still there is not a feedback loop there – again, edit within the tool, can’t identify what is wrong in the feedback loop – and thus the AI has no idea.
To date, I have seen zero vendors with a feedback loop on the admin side. Seriously?
At least with Pluralsight, the learner does see a feedback loop, but this is only available in the Playground section.
You will see their angle – “Provide Feedback,” which opens the loop, and the text below around AI recommendations – which is a crucial piece of any AI within a system. The number of vendors I have seen note the “warning of fake info” is, again, less than ten – not just on the admin side – those numbers are awful, but those that have gone learner side too. Come to think of it, it’s not even two hands worth.
Cypher’s answer to using Gen AI to review the text you have entered when creating your content/course (admin side): It will review the text and provide a response. If it is correct, it says so. If the AI finds that something or something is wrong, it identifies “inaccuracies” and then shows what those inaccuracies are and recommends text. You can choose to accept it or not.
I like Crosscheck, but what I don’t like is no feedback loop. I mean, here – I accept the text because I assume it is accurate and hey it saves me so much time. What though if it is not correct – accurate? There is not one LLM out on the market, that has zero hallucinations. You can have dozens of LLMs in your system, with a RAG, and fine tuning and guardrails, and you will still get hallucinations.
Anyway, here is their screen. I think this has real potential if they add the feedback loop and the text (which appears when you create the course – that it may produce fake information).
Cypher has something else in the works—and it is very intriguing (yes, I have seen it), but once again, the output does not have a feedback loop. I’m at a loss here for why they ignored something they are fully aware of—a loop.
Anyway, as I’ve noted before, they have the best authoring tool with AI pieces within it, from synthetic audio to images.
Cornerstone acquired Skyhive this year and has already incorporated it into its system (Galaxy). If you have Learn (their learning suite), the skills piece is included. If you choose to go just with the LMS, there are skills in there, but the level of Skyhive is not.
The big win with this new piece is that it can compare in real time the latest labor, economic, and skills data parsed with their AI (Cornerstone). The labor data is important to me, more so than just adding a skills library or competencies of skills tied solely to a role.
Bottom Line
I am a fan of bucking the perceived notion that everything has to be the same. The idea of L&D or Training or others all want the same thing, regardless of their use case regarding the appearance and what the system can do. Sure, they may ask for something out of this world, but such inquiries as “I need a system that allows me to see a video,” “learning catalog that can be seen by X folks versus Y folks,” and “analytics and reporting on learners” are universal.
I am not a fan of where vendors rely on clients telling them what is needed, and then the vendor does it – ignoring that innovation isn’t coming from your clients – it has to come from you – the vendor, and the folks within it.
Out of the box in the consumer world that has hit the home runs and we use today – include streaming (initially, everyone was going VHS or DVD, who would think of trying this), bypassing commercials with the recording or stopping a live show, while you do something else, then pick it up again (TiVo – thank you for coming up with this idea), or this vendor called, Sony who decided that the next format should be Blu-Ray for DVDs, out thinking Toshiba’s HD format, whereas consumers never gravitated towards.
In other words, trying something different, taking that risk, isn’t about adhering to everything your favorite clients, or those who use your system the most, or even some small group you tap in a focus group spin.
It’s about – you being an innovator.
Not a follower.
Please note: There will not be any blog posts for the next two weeks (July 30th to August 9th), as I will be off on holiday!
For the past eight consecutive years, JavaScript has been the most commonly used programming language by developers who responded to Stack Overflow’s annual survey. The language’s popularity stems largely from its versatility.
While originally designed for front-end development, JavaScript’s extensive list of associated libraries and frameworks have extended its utility. Now, you can use it for just about anything — including back-end, mobile, and game development. Below, we’ll delve into the reasons behind the language’s popularity and its many applications.
If you’d prefer to get right into and start learning how to code with JavaScript, check out our Learn JavaScript course.
Why is JavaScript so popular?
When it was first developed in 1995, JavaScript was intended to be a lightweight language used to make web pages more dynamic. It added simple effects, like showing and hiding elements with the click of a button — but it wasn’t long before developers realized that it could do much more.
In time, JavaScript became one of the few languages that could be used in just about every web browser. Today, most of those other languages have fallen by the wayside, leaving JavaScript as the only programming language that can be used in every popular browser.
The next big break for JavaScript came when developers started experimenting with it outside of web browsers. They applied it to the back end of web servers, where it processed the data used by the front end. After the rise of smartphones, it found use in multiple mobile development tools that create apps that run on both the Android and iOS platforms.
JavaScript is used in every industry to create all types of applications. Let’s take a closer look at its uses in web development, mobile development, game development, and more.
Front-end web development
Front-end developers use JavaScript (along with HTML and CSS) to create the parts of a web page that users see and interact with in their browsers.
Before JavaScript, web pages only served static content. JavaScript gave developers the ability to provide their users with a dynamic web experience, adding animations and other interactive elements. When you click a button on a website, and a side panel opens or a modal slowly comes into view, that’s JavaScript at work.
But JavaScript does more than that on the web. You can also use it to create single-page applications (or SPAs) that run on one HTML page to give users a smooth navigational experience.
Back-end web development
JavaScript is also popular with back-end developers. Back-end web development (also known as server-side development) involves creating the code that runs on a web server. When a browser loads a web page, it makes a call to a remote server. Server-side code then parses the page’s URL to determine what the user is requesting before retrieving and transforming the required data to serve back to the browser.
Node.js is a JavaScript framework commonly used for back-end development — so much so that many back-end JavaScript developers refer to themselves as Node.js developers.
You can also use JavaScript to create 2D and 3D video games that run in web browsers. As browsers get more powerful, web-based video games are evolving beyond simple platformers. Now, JavaScript frameworks like Phaser.js allow you to create more advanced games quickly and easily right from your browser.
Mobile development
For years, mobile developers had to commit themselves to either Android or iOS, as each platform uses different programming languages. Android developers would learn Java or Kotlin, while iOS devs preferred Swift or Objective-C.
Now, with the rise of mobile development frameworks like React Native and Ionic, you can use JavaScript to create apps that run on both platforms.
Virtual reality (VR)
Virtual reality is a thing again, as devices like the Oculus Rift and Valve Index have made it more generally accessible. Now, you can use JavaScript to create applications for both of them.
A-Frame is a popular JavaScript framework used to build virtual reality experiences in web browsers. If you’re interested in building your own VR applications, start by Learning A-Frame.
Artificial intelligence (AI)
JavaScript is also used to develop artificial intelligence, as libraries like TensorFlow bring the power of machine learning to JavaScript developers. Developers can use these libraries to create machine learning models that predict future events based on past data and categorize data and images.
Learn more about JavaScript
JavaScript is no longer just a programming language used to create neat effects in web browsers. It’s a well-respected, powerful language that’s climbed to the top of popularity charts over the past three decades.
JavaScript’s versatility and wide range of applications make it a valuable addition to any developer’s tech stack.Ready to start using it yourself? Learn its basics in our introduction to JavaScript. Or, if you’re looking for something more advanced, check out our full list of JavaScript courses and tutorials.
Whether you’re looking for a new career or hobby, game development can be a great choice. Not only does it allow you to combine your creative and technical skills, but there’s a satisfaction that comes with watching people enjoy something you’ve poured your heart into. (Plus, it can also be pretty lucrative.)
But before you can start creating games, you’ll need to learn how to code — and the programming language you should learn depends on what type of games you want to make. Ahead, we’ll explore the best languages for game development and some of the benefits of each one.
You can also check out our free course Introduction to Game Development, which will give you a step-by-step look at the development process, including the programming languages, engines, and other technologies used in the industry.
Learn something new for free
1. C++
It’s no surprise that C++ is one of the top game-developing languages, especially because it’s such a popular, flexible solution. C++ is known for its high abstraction level, which allows you to have precise control over how a computer’s hardware interacts with your code.
C++ also provides more granular control over how graphics are processed by the system, which plays a very important role in game design.
Another key benefit of using C++ is it allows you to optimize special parts of your game design, giving them their own abstractions. This is akin to giving specific elements of the game their own infrastructure and resources. This level of detailed game development is difficult, if not impossible, with many other languages.
C++ has been used to make popular games like StarCraft, Football Pro, and Counterstrike. To get started crafting your own C++ games, check out courses like Learn C++ and C++ for Programmers.
2. Java
Even though Java doesn’t provide the same level of intricate control as C++, many see it as the best language for game development. Java’s popularity is partially due to its ease of use, which makes it a great solution for many new Game Developers.
The Java community also provides a deep treasure trove of tools and other open-source resources. This makes it much faster to develop games, especially because you can find code that’s already been written to use in your game. In some ways, Java can give the game development process a more plug-and-play feel than C++.
To dive into the world of Java development, check out our Learn Java course and Build Basic Android Apps with Java skill path. These will make it easier to bring the games floating around in your head to the screen.
3. JavaScript
When it comes to online game development, few languages make it easier than JavaScript. JavaScript plays well with both HTML and CSS, making it easier to develop games for multiple platforms.
Some programmers see JavaScript as a convenient all-around solution because you can use it to create animations and interactive elements. Plus, the online community behind JavaScript is huge, so you can find plenty of pre-designed elements to use in your own games.
JavaScript is the language behind gaming hits like American Girl, Angry Birds, and Aquaria. To get started with the language, try our Learn JavaScript course. We’ll provide you with the fundamentals you need to get comfortable with both front-end and back-end game development.
4. HTML5
HTML5 is another popular language for Game Developers, especially because programmers have created gaming engines that are specifically designed to make HTML5 games work better. Plus, you can use it with JavaScript interchangeably.
HTML5 is also known for its ability to construct games that work on multiple platforms and different kinds of browsers. This could make it easier to design games that appeal to wider audiences.
HTML5 has been used to create hit games like World Cup Penalty 2018 and Gods Will Be Watching. You can learn the basics of HTML5 with our Learn HTML course. This will provide you with the essential building blocks you need to create interactive, addictive games.
5. C#
Even though C# is considered an easier alternative to C++, it’s still a flexible, powerful programming language. Part of the reason why C# is such a useful language for developing games is Microsoft developed XNA for this exact purpose.
XNA is a set of tools specifically created to make game development easier and faster without sacrificing the experience of the end-user. C#’s flexibility is another big plus. You can build games that can run on a wide variety of platforms, including:
PlayStation
Windows
Android
iOS
This has made C# the language of choice for games like Super Mario Run and Pokémon Go. To start crafting your own game characters, check out our Learn C# course. Along with game development, this course will teach you the fundamentals behind virtual reality, websites, and mobile applications.
6. Lua
Lua is a flexible, general-purpose programming language that feels similar to JavaScript. While it’s not as popular as the other languages in this list, Lua’s been increasingly used to build video games over the past few years.
You’ll find Lua code in popular titles like Angry Birds, Baldur’s Gate, Civilization V, and The Elder Scrolls Online. And if you’re familiar with Roblox, you might already know that users can use Lua to write modifications.
Want to learn more? Check out our Learn Lua course.
With our courses, you can build the skills and experience you need to be a star Game Developer. We’ll show you how to run, hop, and blast your way to a successful career in game development — and other tech fields — help you build a portfolio, prepare for technical interviews, and more.
Check out our Introduction to Game Development to get started. Then, learn how to build your own game from scratch in Create Video Games With Phaser.js. Ready to get started? Sign up now!
Whether you’re looking to break into a new career, build your technical skills, or just code for fun, we’re here to help every step of the way. Check out our blog post about how to choose the best Codecademy plan for you to learn about our structured courses, professional certifications, interview prep resources, career services, and more.
Python is a general-purpose programming language used in just about any kind of software you can think of. You can use it to build websites, AI, servers, business software, and more.
Below, we explore some of the reasons behind Python’s popularity, along with its uses and applications in different fields. Or, if you’d rather jump right in and start learning it right away, check out our Learn Python 3 course.
What is Python?
Python is a high-level programming language known for its readability and versatility. It is used in various fields, including web development, data science, AI, and automation.
What are the advantages of Python?
Python’s many advantages make it a favorite among amateur and professional programmers alike. One of its biggest advantages is its (relative) simplicity. Python’s English-like syntax makes it easy to learn and read, and unlike some other languages, it uses simple line breaks instead of symbols to define code blocks.
Python also helps speed up development, with built-in classes and functions and an extensive selection of libraries that make writing code quicker and easier. Plus, as an interpreted language, you can execute and test your code right after writing it without an intermediate compilation process.
Another advantage Python holds over other languages is its versatility. Python is a portable, cross-platform language — meaning you can write and execute Python code on any operating system with a Python interpreter. With some other languages, you’d have to modify your code for each platform.
Python code examples
Here’s an example of some Python code that calculates the factorial of a number:
# Function to calculate the factorial of a number
def calculate_factorial(n):
result = 1
for i in range(1, n + 1):
result *= i
return result
# Example usage
number = 5
factorial = calculate_factorial(number)
print(f"The factorial of {number} is {factorial}")
What is Python used for?
Python’s versatility enables it to be used in a wide range of applications across various industries. Let’s take a look at some of the ways Python is used.
Data science: analytics and visualization
Data science is one of the most popular uses for Python. Data scientists and analysts use programming languages like Python and R to manipulate data for reporting, predictive analysis, and more. But while R can be a great choice, many Data Scientists prefer to learn Python because its English-like syntax can be easier to learn. Check out our free course Getting Started with Python for Data Science if you want to learn how to use Python to work with data.
Harvesting insights from data is no easy task, and data scientists don’t have time to waste with compiling and complicated syntax. Python’s simple syntax and extensive selection of third-party libraries make it a great choice for anyone considering a career in data science.
See an expert-led walkthrough of one of our Python data science projects.
Machine learning
While arguably a subfield of data science, machine learning deserves its own category because of its unique algorithms. Machine learning involves training systems to learn independently by using algorithms that constantly update themselves based on input data. These systems gradually learn to handle new situations by generating an output based on past datasets. Then, based on the outcome of this new situation, they update themselves to deal with the new variables, thus constantly evolving.
Web development: websites and web apps
Python is also widely used for back-end development, where it runs in the server of web applications and interacts with databases and APIs after a user requests data from the app’s front-end in the browser.
Much of Python’s popularity in web development stems from frameworks and libraries like Django and Flask that extend the language’s utility.
Financial analysis
In a recent HackerRank survey, Python was the number one programming language FinTech companies looked for when hiring developers. But it’s not only FinTech enterprises that use Python code. Python is used everywhere in the financial industry because of its data processing capabilities and various third-party libraries designed for financial analysis.
Desktop applications
You can also use Python to build desktop applications. Many Linux and open-source desktop applications use Python. Plus, with GUI libraries like Tk, wxWidgets, and Qt, you can use Python to build cross-platform applications that run on Windows, Mac, or Linux.
Business applications
Python lies at the heart of business software like Tryton and Odoo. These tools are used for enterprise development and can perform accounting, inventory, customer relationship management, and other tasks.
In short, many businesses rely on Python to do the heavy lifting. This has led to more and more startups including Python in their tech stacks for its ease of use and scalability.
Scripting and utility software
Python started as a language for writing utility scripts, and it’s still widely used for this purpose. Many of the utilities and scripts built into Linux operating systems are written in Python, and it’s also installed by default in the Mac OS. This makes Python the language of choice for automating tasks in an engineer’s day-to-day work.
Is Python hard to learn?
Python is considered one of the easier programming languages to learn due to its simple and readable syntax. Python’s creator, Guido Van Rossum, specifically designed the syntax to ensure that even newcomers could easily learn new programming ideas. On top of that, Python offers a wealth of pre-written libraries, tools, and frameworks, allowing you to tackle more complex tasks with the language sooner. Many beginners find Python approachable and manageable for starting their programming journey — you can learn more about how to choose a first programming language here.
How long does it take to learn Python?
Learning Python can take a few months to a year — it all depends on your prior programming experience and the amount of time you can dedicate to learning. The cool thing about our courses and paths is that you guide yourself, determining how much to learn, how often, and at what pace. You can stop and take breaks if you need to or amp up your learning routine if you have the bandwidth. Regular practice and building projects can help you learn Python more efficiently. To get a ballpark estimate on how much time you should commit to learning, first determine what your goal is.
How to learn Python
Learning Python involves understanding its syntax, basic data structures, and libraries. You can start experimenting with writing Python code and building projects in our course Learn Python 3. The course is beginner-friendly and a fan favorite among our learners. If you want to learn a particular domain of Python, like data science, we have targeted Python courses that will teach you the language and how to apply your skills to data scenarios. As you pick up programming concepts, start building projects. We have lots of real-world Python projects in our library that are suitable for all levels — you can even include some of them in your professional portfolio.
Getting started with Python
As you can see, Python is a programming language with a wide range of applications, such as web development, data science, and financial analysis.
Want to start using it yourself? We’ll teach you the basics of Python programming in Learn Python 3. Or, if you want to take it a step further, we’ll show you how to:
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Have you seen the viral AI-generated gymnastics video? The bizarre amalgamation of limbs flying and twisting through the air defies the laws of physics and anatomy — an amusing reminder of AI’s limits. While this AI gymnast has nothing on the world-class human gymnasts competing in the 2024 Paris Olympics, you can expect to see AI and other innovative technology used at the Games this year in new and unexpected ways.
Behind the scenes, cutting-edge technology helps athletes perform at their peak and enables spectators to enjoy the action around the world. From analyzing scoring data to deploying recommender systems so fans can watch their favorite events, here are some of the fascinating ways that tech, coding, and AI will be used during the 2024 Paris Olympics.
AI oversight initiative
In April, a group of experts from various fields, including AI scholars, athletes, and tech representatives, created the Olympic AI Agenda to manage AI use in the Olympic Movement. They identified potential AI risks and established best practices for mitigating them, like guidelines for reducing human bias in judging and refereeing and providing personalized coaching for athletes. The committee also detailed how AI can streamline event organization, transportation, and worker training. You can read the in-depth Olympic AI Agenda here.
Lots of organizations have guiding principles and policies when it comes to using AI ethically. We published our Codecademy AI principles, which outline our approach to using and building AI systems so that all our learners and community members can experience AI in a safe and fair way.
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Prepare for cyberattacks
The cybersecurity team for the 2024 Olympics is preparing for an unprecedented number of attempted attacks — potentially eight to 12 times more than the 450 million “security events” faced during the Tokyo 2021 Games, The New York Times reported. To counter these threats, Paris 2024 organizers are conducting extensive “war games,” which are exercises where ethical hackers test the systems and offer bug bounties for discovered vulnerabilities.
Curious about the unique professional opportunities you can have in cybersecurity? Read more about in-demand cybersecurity careers to understand the field, and check out these (totally legal) ways to practice ethical hacking.
Statistical analysis for judging fairness
Even Olympic judges get judged. Statistical tools are used to measure factors that can affect judging accuracy and fairness. This is especially important in sports with subjective scoring systems, like gymnastics.
Data Scientist Dr. Hugues Mercier leads an ongoing project that tracks Olympic judges’ performance over time, considering variables like fatigue and apparatus difficulty. This data is used to rank individual judges and ensure that overall judging quality remains excellent and backed by comprehensive data analysis.
AI-generated expert commentary
This year, Olympic highlights will feature AI-generated narration by the legendary sports broadcaster Al Michaels, thanks to a new initiative from NBCUniversal and Peacock. Instead of the announcer summarizing the events in real-time, an AI program trained on Al’s past NBC clips will create daily highlight reels narrated by an AI re-creation of his voice.
Streaming and recommender systems
AI is also transforming the way that people watch the 2024 Olympics from their couches around the world. The streaming platform Peacock has a new feature where subscribers can customize a reel of their favorite events and the types of highlights they want to see, like viral clips or gold medal moments. The AI assembles these personalized 10-minute packages each evening (with human oversight ensuring quality).
If you want to learn how streaming platforms (like Netflix and Spotify) use machine learning to make personalized recommendations, take our skill path Build a Recommender System.
Judging gymnastics using data
The Judging Support System (JSS) uses multiple high-definition cameras placed around a gymnastics apparatus to capture a 3D view of a gymnast’s performance, focusing specifically on their joints. An AI model that was trained on video footage of 8,000 routines can cross-check the performance against the Code of Points, the official rulebook that details how gymnastics skills should be executed and scored. The JSS can identify about 2,000 different gymnastics elements with about 90% accuracy, similar to human judges.
While it’s not clear if this will be used at the Olympics, JSS was used on every apparatus at the World Championships, the qualifying competition for the Games.
Protecting athletes from online abuse
The International Olympic Committee introduced an AI-powered system to protect athletes from online abuse during the Paris 2024 Games. This system monitors thousands of social media accounts in real-time, flagging abusive messages in over 35 languages before athletes can see them. It’s part of a broader safeguarding initiative that includes mental health support and well-being resources for athletes.
Precise review systems
The Decision Review System (DRS) in cricket is an advanced technology that helps review and confirm umpire decisions during a game. DRS employs a range of hi-tech tools including ball-tracking, ultra-motion cameras, sound sensors, and thermal imaging. When a team requests a review, sophisticated technologies come into play. For instance, systems like Hawk Eye or Virtual Eye analyze the ball’s trajectory and point of pitching to determine if it would have hit the stumps despite the batter’s position.
