Back

Should AI have morals?

What happens when artificial intelligence starts flattering us instead of challenging us?

13 January 2026

Artificial intelligence is evolving fast — but as it gets friendlier, should we be worried it’s losing its grip on the truth?

We’re exploring a hot topic in both computer science and ethics: Should AI be built with morals, or is it enough for it to make you feel good?

Spoiler alert — if your chatbot applauds your worst ideas, it might be time for a software update.

Let’s start with ChatGPT, specifically the GPT-4o update. This version of OpenAI’s popular AI assistant had one job: make users happy. It did this so well, it started agreeing with everything. People shared examples of it praising clearly harmful behaviour, reinforcing conspiracy theories, and even applauding dodgy life choices. Why? Because its success was measured on positive user feedback — essentially, how many people responded with smiley face emojis.

The result? A hype man in silicon form. Warm and fuzzy? Yes. Useful? Not so much.

Eventually, OpenAI admitted it had gone too far and rolled back the overly agreeable behaviour. But the episode raised big questions about the purpose of AI. Should it be emotionally supportive at all costs, or should it sometimes challenge us?

Then there’s Grok — Elon Musk’s “anti-woke”, “truth-seeking” AI launched via X (formerly Twitter). Despite the branding, Grok began doing something unexpected: it corrected false claims, backed up scientific consensus, and even fact-checked Musk himself. It wasn’t trying to be political — just accurate. But that honesty proved controversial, especially for users who expected Grok to reinforce their existing views. Apparently, it’s all fun and games until the AI doesn’t flatter your worldview.

So, what do we actually want from AI? Is it more important that it makes us feel good — or helps us be better?

On one hand, supportive AIs can offer comfort and validation. But when they reinforce false beliefs or encourage risky decisions, the consequences can be serious. On the other hand, AIs that challenge misinformation and offer correction might feel uncomfortable in the moment — but they can help us grow. Just like that one teacher who was a little harsh with the red pen, but made you a stronger thinker.

This is about more than software — it’s about trust, responsibility, and the future of technology in society. Because if we build AI to agree with us no matter what, we’re not building intelligence. We’re building digital yes-men. And they might just smile and nod while we walk ourselves off a cliff.

So, where do you stand?

Should AI be polite and supportive — or truthful, even if it stings?

Watch the full video here to explore the debate in full.

For more Lesson Hacker Videos, check out the Craig’n’Dave YouTube playlist HERE.

Be sure to visit our website for more insights into the world of technology and the best teaching resources for computer science and business studies.

Stay informed, stay curious!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

What is vibe coding? Is it the future of programming?

Welcome to the “tell, don’t type” era of coding

12 January 2026

If “vibe coding” sounds like something you’d do while lounging in a beanbag with lo-fi beats and herbal tea, you’re not alone. But despite its chilled-out name, vibe coding is a seriously powerful development method—and it’s changing the way we write software.

At its core, vibe coding means using plain English to tell an AI what you want your program to do. Instead of hammering out every loop, condition, and semicolon, you type something like: “Make a form that submits user data to the backend and shows a thank-you message.” The AI interprets your request and generates the code for you—sometimes even with documentation.

This magic happens thanks to large language models like GPT, which have been trained on vast amounts of code. They break your prompt into tokens, map those to patterns they’ve seen before, and predict the most likely next tokens to generate full functions, boilerplate files, and more. Think autocomplete on steroids.

What’s more, modern AI tools like Copilot, Cursor, and Replit are context-aware. They don’t just spit out code snippets—they understand your project structure, track variables across files, and can even refactor code you’ve long forgotten you wrote.

Of course, vibe coding isn’t flawless. The AI can “hallucinate” functions that don’t exist, or write code that looks great… until it crashes. It’s like having a super-keen intern: quick, clever, but occasionally wildly overconfident.

Still, for speeding up development, brainstorming solutions, or simply avoiding another late-night regex breakdown, vibe coding is a game-changer. You bring the ideas. The AI brings the syntax.

Watch our Lesson Hacker video here to explore more.

For more Lesson Hacker videos, check out the Craig’n’Dave YouTube playlist HERE.

Be sure to visit our website for more insights into the world of technology and the best teaching resources for computer science and business studies.

Stay informed, stay curious!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

Should beginners use AI to code?

8 January 2026

Here’s why the answer isn’t so simple. AI can be an amazing tool for coders—but should absolute beginners rely on it?

So, you’ve just dipped your toes into the world of coding—still coming to terms with variables, loops, and the existential dread of debugging. Then someone tells you, “Just use AI, it’ll write the code for you!” Sounds tempting, right?

But here’s why that shiny tool might be more lightsaber than lifesaver.

Imagine giving a Jedi weapon to someone who’s only just mastered the art of stick-fighting. That’s what it’s like handing over AI code generation tools to a beginner. Yes, it’s powerful. Yes, it sounds impressive. But if you don’t yet understand the basics, there’s a real risk of slicing through your logic and confidence.

This isn’t to say you should avoid AI altogether. In fact, it can be an incredible tutor—if you use it the right way. Ask it questions. Explore its answers. Use it to understand concepts like callbacks (which, let’s be honest, sound more like something your ex never gave you). But don’t fall into the trap of copying and pasting code like you’re following a recipe from the internet—because while it might work, you won’t truly know how or why.

AI should be your sidekick, not your saviour.

It’s brilliant when you need a quick fix or to meet a tight deadline. But if your goal is to learn how to code—really learn—then you need to do the thinking. The debugging. The failing and fixing.

Because one day, you’ll face AI-generated code that doesn’t work. And if you’ve skipped the hard stuff, you’ll be stuck—realising, with horror, that the problem isn’t the code. It’s you.

Watch our Lesson Hacker video here to explore more.

For more Lesson Hacker videos, check out the Craig’n’Dave YouTube playlist HERE.

Be sure to visit our website for more insights into the world of technology and the best teaching resources for computer science and business studies.

Stay informed, stay curious!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

Did Deepseek change AI?

Deepseek: The Chinese AI startup shaking up Silicon Valley

26 August 2025

What is DeepSeek and why is it making waves?

DeepSeek, an AI company based in Hangzhou, China, is making headlines with its latest models, DeepSeek-V3 and DeepSeek-R1. These models aren’t just impressive in quality—they’ve been built for a fraction of the cost compared to OpenAI’s ChatGPT. Reports suggest DeepSeek trained its models for under $6 million, an astonishingly low figure in the AI industry. To put it into perspective, that’s like buying a Ferrari for the price of a second-hand scooter.

Adding to the excitement, DeepSeek’s AI assistant has surged to the top of the US App Store, overtaking ChatGPT. If there’s one thing Americans love more than AI chatbots, it’s winning—and DeepSeek seems to be doing just that.

How did they build it for so little?

The secret lies in a technique called AI distillation. Unlike traditional AI training methods that demand vast amounts of computing power, distillation allows DeepSeek to train a large model first, then extract the key knowledge into a smaller, more efficient version. Think of it as revising for an exam—not reading the entire textbook, just the essential parts.

This method is incredibly cost-effective. Research teams have recreated OpenAI’s reasoning model for as little as $450 in just 19 hours. Some have even done it for $50 in 26 minutes—cheaper than a takeaway pizza. By using distillation, DeepSeek has bypassed the traditional ‘throw money at it’ strategy and delivered an AI that punches well above its weight. Even OpenAI’s CEO, Sam Altman, has hinted that they may need a new open-source strategy to keep up.

What are the drawbacks?

DeepSeek’s meteoric rise isn’t without controversy. One major concern is its hardware. Reports suggest the company may have access to far more Nvidia AI chips than US export controls should allow. If true, this raises serious questions about trade restrictions and supply chains.

Another challenge is accuracy. While AI distillation makes models faster and cheaper, it also means some information gets lost along the way. It’s like summarising a novel—you get the main ideas, but occasionally miss important details.

Are there security concerns?

With AI becoming more affordable and accessible, concerns around misuse are growing. While democratising AI leads to faster innovation, it also increases the risk of deepfakes, misinformation, and other ethical dilemmas. If DeepSeek can build a ChatGPT competitor at a fraction of the cost, what’s stopping a rogue developer from creating something far more dangerous in their garage?

DeepSeek has disrupted the AI landscape, proving that cutting-edge models don’t need billion-dollar budgets. This has left OpenAI and Silicon Valley scrambling to adapt. Will this spark a new AI arms race? Possibly. But one thing is clear—AI is evolving at breakneck speed, and the future is closer than we think.

Want to see more about this AI shake-up? Watch the full video on our YouTube channel.

For more Lesson Hacker Videos, check out the CraignDave YouTube playlist HERE.

Visit our website to explore more cutting-edge tech-transforming news in the computer science world!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

What is AI?

AI: Just fast maths pretending to be smart

12 August 2025

AI. It’s a term that gets thrown around everywhere—from science fiction films to social media posts and school corridors. But what actually is artificial intelligence, and why is it so important to understand?

At its core, AI doesn’t actually think—it just predicts. It’s essentially super-fast maths, rapidly analysing patterns to guess what should come next in a sequence. Imagine that friend who always finishes your sentences… except AI does it with slightly better accuracy.

How do transformers power AI?

No, we’re not talking about giant robots (although that would be cool). In AI, transformers are a type of deep learning model that helps machines generate human-like text. Here’s how they do it:

Word magic: AI doesn’t see words—it sees numbers. It converts text into numerical values that represent meaning. Kind of like the Matrix, but without the leather trench coats.
Attention, please! Transformers scan every word in a sentence and decide which ones are important. It’s a bit like pretending to listen in a meeting but only perking up when you hear “free snacks.”
Prediction time: AI makes an educated guess about the next word, refines it, and repeats the process until the sentence sounds human. The result? AI-generated essays, jokes, and sometimes suspiciously accurate emails.

How does AI learn??

Behind the scenes, AI is powered by huge datasets and clever algorithms. These systems “learn” patterns from data, meaning they can improve their performance over time without being explicitly programmed to do so. This process is called machine learning, and it’s how many of today’s most exciting AI tools work.

AI and you

AI is already influencing your daily life, whether you realise it or not. It shapes the content you see online, helps doctors spot diseases faster, supports businesses with automation, and could even play a role in your future career. Understanding how it works is more than just useful—it’s essential.

Why AI isn’t taking over (yet)

Despite its clever tricks, AI isn’t sentient—it’s just playing a game of supercharged fill-in-the-blank. While it’s brilliant for generating text and answering questions, it still lacks genuine understanding or creativity. So, would you trust it to run the world? probably not. But to help you write a convincing email? absolutely.

Want to learn more?

Want to know more? Check out The Lesson Hacker’s YouTube video HERE.

For more Lesson Hacker Videos check out the CraignDave YouTube playlist HERE.

Visit our website to explore more cutting-edge tech-transforming news in the computer science world!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

How do computers generate random numbers?

29 July 2025

Ah, randomness! It’s everywhere in nature—think dice rolls, quantum physics, or even your cat’s indecision. But when it comes to computers, randomness doesn’t come naturally. Why? Because computers are logical machines, designed to follow precise instructions. So, when we ask for a “random” number, they can’t just pluck one from thin air. Instead, they rely on something called a pseudo-random number generator (PRNG)—essentially, randomness with a script.

How does a pseudo-random number generator work?

Here’s how computers fake randomness step by step:

The magic seed
The process begins with a “seed” number. This seed could be almost anything—like the exact millisecond from the system clock, the temperature of your CPU, or even the quirky motion of a lava lamp (a trick famously used by Cloudflare for added unpredictability).
Math happens
Once the seed is set, it’s run through a complex mathematical formula designed to churn out seemingly random results. Picture a blender spinning at full speed, tossing numbers into a chaotic whirl.
Voilà! fake randomness
Out comes a number that looks completely random. However, if someone knows the original seed and the formula, they can predict the outcome—like a magician pulling the same rabbit from their hat every time.

Can computers create true randomness?

When it comes to security, like encrypting sensitive data, fake randomness isn’t enough. For truly unpredictable results, computers turn to nature for help. They measure chaotic phenomena like radioactive decay, electrical noise, or even the small, unpredictable quirks of daily life. This kind of randomness, called “true randomness,” is far more secure and impossible to predict.

So, while computers don’t naturally do random, they’ve mastered the art of faking it with clever algorithms. But when we need something truly unpredictable, we can rely on the chaos of the natural world. Or, as a simpler alternative, just watch a cat trying to decide whether to go outside.

Want to learn more?

Want to know more, check out The Lesson Hacker’s YouTube video HERE.

For more Lesson Hacker Videos check out the CraignDave YouTube playlist HERE.

Visit our website to explore more cutting-edge tech-transforming news in the computer science world!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

Are Graphics cards cheating now?

13 May 2025

In the ever-evolving world of gaming and computing, Nvidia’s latest RTX 5000 series has sparked an interesting debate: are graphics cards actually improving, or is AI doing all the heavy lifting?

With the launch of DLSS 4 and some mind-blowing specs, we’re diving into what’s real, what’s AI-generated, and whether any of it really matters.

Are GPUs really getting better?

Nvidia’s new flagship, the RTX 5090, is an absolute beast. With 92 billion transistors, 32GB of GDDR7 VRAM, and memory bandwidth that defies belief, it’s designed to dominate 4K gaming, dabble in 8K, and obliterate your wallet at $1,999. But who is this really for? While gamers will appreciate the power, this kind of hardware is also aimed at content creators, developers, and professionals pushing the limits of rendering and AI-driven applications.

The evolution of DLSS

One of the biggest advancements in recent years has been DLSS (deep learning super sampling). When it first launched in 2018, it was a bit underwhelming—think blurry, pixelated mess. But Nvidia kept improving it, and today, DLSS 4 is a game-changer. Using transformer-based AI models, it enhances graphics, generates frames, and makes gameplay smoother than ever.

DLSS 4 includes three major features:

Super resolution – upscales lower-resolution images to 4K or even 8K.
Ray reconstruction – improves ray tracing quality using AI rather than traditional methods.
Multi-frame generation – creates new frames in real-time, making gameplay ultra-smooth.

This means you can enjoy high-end visuals without needing a ridiculously expensive GPU every year.

Is AI ‘cheating’ in gaming?

Some critics argue that AI-generated frames aren’t ‘real’ pixels, but does it actually matter? If a game looks stunning, runs at 120fps, and feels seamless, is it important whether every frame was painstakingly rendered or if AI stepped in to assist?

It’s a bit like baking a cake—whether the icing was handmade or piped by a machine, the end result is still delicious. For most gamers, AI-powered enhancements are a blessing, allowing them to enjoy top-tier performance without breaking the bank.

The future of GPUs and gaming

One thing is clear: AI is no longer just a sidekick in gaming—it’s taking centre stage. DLSS 4 is proof that Nvidia is leaning heavily into AI-driven enhancements. But there’s a catch: multi-frame generation is exclusive to the RTX 5000 series, meaning older GPUs are slowly being left behind.

For those still clinging to older hardware, the choice is clear: embrace the upgrade cycle or accept a future as a retro gamer. Either way, gaming technology is moving faster than ever, and Nvidia’s latest advancements are redefining what’s possible.

Want to see the tech in action? Check out our full breakdown of the RTX 5000 series and DLSS 4 in our Lesson Hacker video.

Be sure to visit our website for more insights into the world of technology and the best teaching resources for computer science and business studies.

Stay informed, stay curious!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

Pavel Durov’s Arrest: The Future of Privacy and Telegram

21 January 2025

Pavel Durov, CEO of the messaging app Telegram, has been at the centre of global attention after his recent arrest at Leou Airport in France. For those who aren’t familiar, Durov is the man behind VK, Russia’s equivalent of Facebook, which he founded at just 22 years old. However, it’s Telegram, the secure messaging platform he launched in 2013, that has truly made his name known to millions worldwide.

Telegram: A Platform for Privacy, or a Haven for Criminals?

Telegram quickly became one of the most popular messaging apps for users who value privacy, offering encryption so strong that even intelligence agencies have struggled to crack it. This focus on user privacy has attracted close to a billion users globally. But this same commitment to privacy is now under fire.

French authorities recently charged Durov with several serious accusations, including failure to moderate criminal content on Telegram and refusing to cooperate with law enforcement. The charges suggest Telegram has become a breeding ground for illegal activities like drug trafficking, child exploitation, and fraud. Critics argue that Telegram’s loose moderation policies have turned it into a “dark web with a better interface.”

Durov has always defended Telegram’s approach, arguing that while the platform moderates content, it does so in a much lighter way compared to the likes of Facebook or Instagram. However, the fact that Telegram has declined to join international programs aimed at combating online child abuse has raised significant concerns.

A Debate on Privacy vs Accountability

Durov’s arrest has ignited a heated debate on privacy and accountability in the digital age. Figures like Edward Snowden and Elon Musk have come out in support of Durov, claiming his arrest is an attack on human rights. However, this situation begs the question: should tech CEOs be held personally responsible for illegal activities happening on their platforms?

Telegram allows massive groups of up to 200,000 users to communicate and share content, which makes moderation a significant challenge. But if platforms like Facebook and WhatsApp have systems in place to tackle illegal content, why not Telegram?

The outcome of Durov’s legal troubles could shape the future of online privacy. Will users continue to trust Telegram if authorities gain access to its encryption keys? More importantly, will Durov’s arrest lead to tighter regulations across all messaging platforms?

What’s Next for Telegram and Online Privacy?

The arrest of Pavel Durov opens a broader conversation about the balance between privacy and security. How do we protect personal freedoms online while ensuring that platforms aren’t abused for criminal purposes? Durov’s case could set a precedent for whether tech CEOs should be held accountable for their users’ actions.

Curious to learn more? Watch our full video HERE and explore the heated debates around privacy, security, and the future of Telegram.

Be sure to visit our website for more insights into the world of technology and for the best teaching resources for computer science and business studies.

Stay informed, stay curious!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

Can You Spot the AI? The Rising Challenge of AI-Generated Faces

14 January 2025

We’re diving into the uncanny world of artificial intelligence, specifically AI-generated faces. These days, it’s getting harder and harder to tell what’s real and what’s not. So, let’s explore why AI faces are so convincing, the potential risks, and what we can do about it.

The Growing Power of AI in Creating Human Faces

Imagine scrolling through your social media feed. You see familiar faces, but wait—are they all real? Thanks to advances in AI, computers are now generating hyper-realistic human faces that can fool even the sharpest eyes. A recent study from Aberdeen University showed that most of us can’t reliably distinguish between real human faces and AI-generated ones, with a 65% misidentification rate.

That’s right, most people are flipping a coin when guessing whether a face is AI-made or naturally human.

Why Are AI Faces So Hard to Spot?

It turns out that AI’s secret weapon is hyperrealism. These generated faces have perfectly balanced features and a lifelike sparkle in their eyes. For most people, this makes AI faces incredibly hard to detect. The study found that even those confident in their answers were often wrong, revealing a classic “confidence paradox” – the more convinced we are, the more likely we’re mistaken.

Surprisingly, humans are at their peak face-recognition abilities at around 31 years old, so if you’re not there yet, or you’ve passed it, spotting AI faces might feel like a superpower slipping away.

The Dark Side: Bias, Fraud, and AI

While AI-generated faces can be fun (think video games and virtual avatars), there’s a troubling side to this tech. The data used to train AI is often biased, leading to AI-generated images that skew towards white faces. This ‘whitewashing’ problem creates racial disparities, and worse yet, the potential for misuse is huge. Think identity theft, fraud, or even law enforcement misuse through facial recognition software.

What’s Next? How Do We Stay Safe?

So, what can we do? Aberdeen University is already educating schools about the risks of AI-generated images and online fraud. But there’s more to be done. We need transparency, tools to spot fake faces, and public awareness to ensure that AI technology doesn’t outpace our ability to control it.

AI is rapidly shaping our world, and we need to stay informed. As technology advances, it’s important to remain curious, sceptical and educated. Want to know more? Watch the full video below for a deeper dive, and check out our website for more content on tech, AI, and the future.

For more Lesson Hacker Videos check out the CraignDave YouTube playlist HERE.

Visit our website to explore more cutting-edge tech-transforming news in the computer science world!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

Has AI and tech ruined sport?

19 November 2024

This is a topic that sparks a lot of debate: technology in sport. Some fans say tech is ruining their beloved sports, while others believe it’s making it fairer and more exciting. Let’s unpack how technology like Hawk-Eye, VAR, and AI have transformed the world of sports, for better or worse.

Precision or frustration?

Tennis fans are in for a big change. Wimbledon’s line judges are being replaced by Hawk-Eye technology—a camera system that makes precise calls on whether a ball is in or out. While this guarantees accuracy, something vital is lost: the drama. Remember when a player would challenge a call, and the crowd would hold its breath? Now, it’s simply “The computer says it’s out.” Accurate? Yes. Thrilling? Not so much.

Football’s introduction of VAR (Video Assistant Referee) was meant to correct bad calls. But has it made the game more enjoyable? While it does improve fairness, it’s hard to ignore the frustration when a game grinds to a halt for a five-minute review over whether someone’s toenail was offside. The precision is great, but the momentum of the game? That’s often the real casualty.

Data and AI: The future of fan engagement

Beyond refereeing tech, AI and data analytics are reshaping how fans engage with sport. Companies like Opta track everything from player speed to match predictions, turning sport into a data-driven experience. While it’s a different way of connecting with the game, some fans miss the messy, emotional moments that stats can’t capture.

So, Has tech really ruined sport?

Not quite. Technology hasn’t killed sport—it’s evolved it. The drama may now lie in data points and AI predictions instead of human error, but the heart of sport remains. Whether you’re shouting at a referee or a computer, the passion is still there.

Watch the full video on our channel to dive deeper into how tech is transforming sport.

For more Lesson Hacker Videos check out the CraignDave YouTube playlist HERE.

Visit our website to explore more cutting-edge tech-transforming news in the computer science world!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

Is OpenAI really that open?

5 November 2024

What started as a non-profit dream has evolved into a tech giant worth a staggering $157 billion, raising questions about its original mission.

OpenAI’s humble beginnings

OpenAI – once a bold, altruistic initiative aiming to create artificial intelligence for the benefit of humanity – has undergone a dramatic shift.

Back in 2015, OpenAI set out with a noble goal: to make artificial intelligence accessible, safe, and beneficial for everyone. Spearheaded by influential figures like Elon Musk, it promised to use AI for the greater good, not just to line the pockets of the wealthy. Initially, a non-profit, OpenAI’s mission was simple: create AI that serves all of humanity, not just the elite.

However, the landscape changed quickly. By 2018, Elon Musk had left, citing concerns that the organisation was straying from its mission. Fast forward to today, and OpenAI’s once “open” nature seems a distant memory.

From non-profit to capped-profit

OpenAI’s transformation into a “capped-profit” organisation marked a significant departure from its non-profit roots. The company now walks a fine line between innovation and commercialisation, securing billions in funding from tech giants like Microsoft and Nvidia. While this has driven AI advancements, it’s also placed enormous pressure on OpenAI to monetise its technology, which risks sidelining its original vision.

Internal tensions and key exits

With the shift towards profit, OpenAI has faced growing internal conflicts. Safety researchers and AI developers, concerned that financial interests are outweighing ethical considerations, have begun to leave. Prominent figures, such as former CTO Mira Murati and Chief Scientist Ilya Sutskever, have stepped down, fuelling concerns about the company’s direction.

The critics speak out

One of the loudest critics has been none other than Elon Musk. From the sidelines, Musk has accused OpenAI of losing sight of its original purpose, claiming it’s now more focused on pleasing investors than safeguarding humanity from AI’s potential dangers.

OpenAI’s journey from non-profit idealism to a $157 billion behemoth leaves us wondering: has it lost sight of its mission, or is this just the price of progress? Let us know your thoughts in the comments!

Get Your Classroom Buzzing About AI!

Want to spark some lively discussions around AI? We’ve crafted some thought-provoking questions to fuel the conversation:

🤔 Why is the AI industry worth so much money and is it another dot com boom scenario?

💸 Should large language models be free to use, and if so how should they fund the servers, maintenance and electricity? If not, how should revenue be raised?

🌍 In what ways could AI create a new digital divide?

🧠 Can AI advance to a stage where it no longer requires humans?

These questions are sure to get students thinking critically and debating the future of tech!

If you’re curious to learn more, watch the Lesson Hackers video on OpenAI’s and how open it is Here.

For more Lesson Hacker Videos check out the CraignDave YouTube playlist HERE.

Visit our website to explore more cutting-edge tech-transforming news in the computer science world!

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

Is social media really that bad?

22 October 2024

We’ve all heard the scare stories: spend too much time on TikTok and suddenly you’re destined to fail your GCSEs and live in your mum’s basement forever. But is social media really as dangerous as some headlines make it out to be?

According to a new study by the World Health Organisation (WHO), there’s been a sharp rise in something called “problematic social media use” among teenagers. This doesn’t just mean spending hours on Instagram or YouTube; it’s when social media starts interfering with real life. We’re talking about skipping activities, arguing with parents about screen time, and feeling like you can’t stop even when you know you should.

The study surveyed nearly 280,000 teens across 44 countries and found that in 2022, 11% of them displayed problematic behaviours, up from 7% in 2018. Unsurprisingly, the pandemic played a major role in this spike, with many turning to social media during lockdowns. The situation is particularly notable in the UK, where teenagers are more prone to problematic use, especially among 13-year-old girls.

But before we start deleting our apps, the study also highlights that social media isn’t all bad.

For most teens, using social media helps them stay connected with friends and feel supported, especially during isolating times like the pandemic. Movements like #BlackLivesMatter and #FridaysForFuture are prime examples of how social media can create positive change on a global scale.

However, for the 11% struggling with problematic use, the situation can be different, with issues like anxiety, depression, and even withdrawal symptoms when they can’t check their phones. Boys, on the other hand, seem to be more prone to problematic gaming, with some spending over four hours a day on games like Fortnite and Minecraft.

So, is social media really that bad? The answer isn’t black and white. For the majority, it’s a useful tool for connection, but like anything, it needs to be used in moderation. The key is balance—managing screen time and not letting it interfere with mental health, studies, or relationships.

To dive deeper into this topic, watch the full video HERE.

Don’t forget to check out our website for more insights on how tech and society are evolving and all the latest Computer Science teaching resources.

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Back

Can AI create recipes? How artificial intelligence is shaping the culinary world

26 September 2024

The rise of AI in the kitchen: Can robots create recipes that taste good?

Have you ever wondered what it would be like if artificial intelligence designed your pizza? From AI-generated recipes in top restaurants to major retailers using AI to predict food trends, technology is changing the culinary world. But the question remains: can AI really cook up something delicious, or is this a recipe for disaster?

The role of AI in culinary innovation

Artificial intelligence, particularly tools like ChatGPT, is making waves in the food industry. Restaurants are now using AI to analyse thousands of recipes and suggest creative flavour combinations that might not occur to human chefs. One standout example is Dodo Pizza in Dubai, where head chef Spartac challenged AI to create a pizza representing Dubai’s cultural diversity. The result? A surprising combination of shawarma chicken, grilled paneer, za’atar, and tahini sauce—an instant hit! This AI-designed pizza is still on the menu today and has become a customer favourite.

AI wins and fails in recipe creation

But AI doesn’t always nail it. While Dodo Pizza found success with their multicultural creation, they also experienced some AI-generated disasters, like a pizza with strawberries and pasta, or even worse, one with blueberries and breakfast cereal. Similarly, in the US, Velvet Taco in Dallas asked AI to help design a taco of the week. Among AI’s quirky suggestions, one recipe—prawn and steak tacos—was a massive success, selling 22,000 in just one week! Venicia Willis, Velvet Taco’s Culinary Director, is clear that while AI can boost creativity in recipe creation, it cannot replace the human element. Food, after all, requires human intuition to ensure ingredients come together harmoniously.

AI’s impact beyond the kitchen: Predicting food trends

AI’s influence goes beyond just recipes. Retailers like Waitrose are using AI to spot rising food trends, such as the recent surge in popularity of Smash Burgers. By analysing social media patterns, Waitrose was able to introduce their own version of the trendy burger, staying ahead of the competition. This demonstrates AI’s ability to not only create but also capitalise on emerging culinary trends.

The human touch is still essential

While artificial intelligence is making a mark on the food industry, it’s clear that AI-generated recipes still need human oversight. Chefs like Julian De Feral, a cocktail creator in London, are sceptical, arguing that AI lacks the common sense and intuition required for culinary creativity. After all, AI simply pulls from data, often relying on existing recipes or food blogs, which raises ethical questions about originality.

In conclusion, AI’s role in the culinary world is evolving, bringing a mix of innovation and bizarre combinations. While AI can inspire fresh ideas, the human touch is still crucial to ensure the final dish is both delicious and marketable.Curious to see AI in action in the kitchen? Watch our Lesson Hacker video HERE.

For more Lesson Hacker Videos check out the CraignDave YouTube playlist HERE.

Visit our website to explore more cutting-edge tech-transforming news in the computer science world!

Source – https://www.bbc.co.uk/news/articles/cl7y71krnjvo

Looking for something else?

Have any questions?

Visit our Helpdesk to get answers!

Visit page

Explore our full range of Study Tools

Visit page

Should AI have morals?

Related posts

Why are school exclusions rising? Causes, challenges, and solutions for teachers

What is Endianness?

Does anyone still use low-level code?

What is vibe coding? Is it the future of programming?

Trinket is shutting down in June 2026

What does a GPU actually do?

Fail safeguarding if phone used in school?

Should beginners use AI to code?

Is the Online Safety Act protecting us, or going too far?

Looking for something else?

Have any questions?

Explore our full range of Study Tools

What is vibe coding? Is it the future of programming?

Related posts

Why are school exclusions rising? Causes, challenges, and solutions for teachers

What is Endianness?

Does anyone still use low-level code?