This content originally appeared on HackerNoon and was authored by Susie Liu
AI is the new pink sauce. Everyone’s drizzling it on everything, but not every drop is worth the hype. If you’re running a lean startup, you need more than buzzwords and shiny tech—you need marketing results. Let’s cut through the nonsense to spotlight what’s in the latest AI updates from YouTube, LinkedIn, Meta, Instagram, Snapchat, X, Amazon (technically not social media, but you’ll like this update), TikTok and Reddit. If you’re not a marketing geek like me who really wants the lowdown on the nitty gritty details, skip to the end, where I gauge the worth of these new features.
\ Let’s dive in.
The Rundown
YouTube: AI-Powered Shorts and Communities
What’s the deal:
YouTube’s AI-powered Shorts (Veo) will tap into Google’s DeepMind for AI-generated backgrounds and enables creators to generate 6-second videos from simple text prompts. Inspiration tab in the YouTube Studio app will enable creators to use AI to generate titles, thumbnails, and video ideas, and there’s an auto dubbing feature rolling out. But I think the real gem is Communities, which, while not brand new, has been seriously revamped. Think of it as a Discord-Reddit-Twitch engagement powerhouse anchored on the YouTube platform. Creators can post updates, run polls, share GIFs and images, and even host live events without needing to upload a new video—YouTube knows you need tribes, not viewers. The best part? Once a feature exclusive to channels with over 10k subscribers, Communities will now be available to all accounts with 500+ subscribers.
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- Google DeepMind: Automates video editing by analyzing large datasets to suggest optimal transitions, effects, and cuts based on past user engagement patterns.
- Natural Language Processing (NLP): Converts text prompts into fully produced video content, mapping written input to visuals and generating seamless transitions.
- Computer vision algorithms: Identify key visual elements in uploaded footage, intelligently adjusting framing, lighting, and effects for professional-quality videos.
- AI-driven content recommendation algorithms: DeepMind’s machine learning models analyze viewer engagement to personalize content suggestions for more targeted reach.
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LinkedIn: AI Content Recommendations and Premium Pages
\ What’s the deal:
LinkedIn’s AI updates feel like…a LinkedIn Feed. Tame, forgettable, with a dash of “trying too hard to be charismatic”. AI-driven content recommendations show you what’s “relevant” based on your interests (in the past your feed was just updates from your network and connections), and Premium Pages let companies dress up their profiles with custom CTAs and testimonials for a fee. They’re walking a weird line, trying to be laid-back and corporate at once.
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- Machine learning content curation: Collaborative filtering and natural language processing to recommend relevant posts and articles based on interests and browsing history.
- Neural networks for networking: Predicts meaningful connections between users by analyzing patterns in professional profiles, skills, and activity to suggest high-value contacts.
- AI-driven personalization: LinkedIn’s AI adjusts custom CTAs and testimonials based on user profiles, tailoring pages to optimize engagement and lead generation.
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Meta (Including Threads): AI Content Scheduling, Chatbots, and Moderation
\ What’s the deal:
Meta’s updates feel like a silent apology. Threads now supports AI-powered content scheduling, finally giving marketers a way to plan posts like a normal platform should. There’s also an upgrade to AI chatbots that handle more complex customer queries, and AI is stepping in for content moderation on Threads to reduce the chaos of unfiltered discussions. It’s practical, but we all know they should’ve made these changes ages ago.
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- Recurrent Neural Networks (RNNs): Power Meta’s AI content scheduling by predicting optimal posting times and formats for higher engagement.
- Natural language understanding (NLU): Enhances Meta’s chatbots, making interactions more conversational and capable of handling complex customer queries with ease.
- AI-powered workflow automation: Decision-tree algorithms to streamline customer service, routing issues to the most efficient resolution paths.
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Instagram: AI Stickers and Enhanced Messaging
\ What’s the deal:
Instagram’s AI stickers (cute, but why?) and post-send DM editing feel like something designed to distract from the fact that they haven’t innovated much recently. Slapping an AI-generated sticker on your Story or editing a DM isn’t changing the game. These updates might get a quick laugh or fix a typo, but for tech startups and marketers looking for meaningful engagement tools? It’s about as useful as a glitter bomb at a business meeting.
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- Generative AI for Stickers: AI models analyze image content and user preferences to generate custom stickers that can be applied to Stories, creating personalized visuals.
- NLP: Applying AI to detect and suggest corrections or improvements in text.
- AI-driven content suggestions: Algorithms suggest interactive elements like polls, questions, or GIFs for Stories to optimize engagement based on viewer behavior.
- Predictive engagement algorithms: AI analyzes user interactions to recommend the best times and formats for Story updates, boosting engagement and retention.
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Snapchat: Advanced AR Lenses and “My AI” Feature
\ What’s the deal:
Snapchat’s upgraded AR Lenses beyond average selfie filters. Using Lens Studio, devs can create custom, immersive augmented reality experiences—think virtual product try-ons, AR games, interactive demos—that interact with the real world. My AI, Snapchat's chatbot, is essentially their version of ChatGPT that focuses on image-based queries. This all sounds cool, but like with all Snapchat updates, the “is this really a marketing tool, or a fun distraction?” question looms.
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- World Mesh technology: Depth-sensing algorithms to create AR experiences that interact with real-world environments, allowing virtual objects to appear naturally within physical spaces.
- Depth mapping and computer vision: AI analyzes the spatial environment, providing more realistic placement and interaction for AR Lenses, making experiences like virtual try-ons highly immersive.
- Generative AI for 3D assets: Devs can quickly create animations and 3D models using text prompts.
- Image recognition AI (My AI): Snapchat’s chatbot uses deep learning models to identify objects in user Snaps, providing personalized suggestions or responses based on the visual content.
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X: AI-Powered Content Moderation and Chatbots
\ What’s the deal:
X is rolling out AI for content moderation and automated customer responses. On paper, the AI is supposed to keep the platform clean by flagging harmful or offensive posts and handling customer inquiries through chatbots. In reality? Feels like X needed some AI sprinkles to give their moldy muffin of a platform a minor facelift and push out a piece of news that’s unrelated to X’s chronic turbulence and brand trust issues. These are empty calories.
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- Reinforcement learning: Powers content moderation, dynamically learning from flagged posts to improve detection and removal of harmful or offensive content in real-time.
- Natural language generation (NLG): Enhances AI chatbots for “more personalized”, context-aware conversations with users, theoretically improving customer interaction
- Sentiment analysis: AI models scan posts and conversations for toxic language, misinformation, or harmful speech, moderating discussions and flagging problematic content.
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Amazon: AI Video Generator
\ What’s the deal:
Amazon isn’t technically social media, but I think their video generator might be a godsend for any digital marketer. You read it here first: you don’t need to sell on Amazon, or even have a physical product to use this – since it turns static images into video, you can just provide it with screenshots, infographics, or branding elements. Bonus is that it’ll create multiple iterations for A/B testing AND has multichannel capacity enabling formatting for different platforms including social media, email, and websites. If you do sell on Amazon, this could be your efficiency goldmine since it’s integrated with the platform’s e-commerce data and seamlessly connected with your advertising and analytics, allowing for real-time performance feedback and optimization. Video generation tools are dime a dozen, but few are wholly geared towards delivering business results.
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- Generative Adversarial Networks (GANs): Generates video content from static images or digital assets, producing realistic animations and dynamic effects without the need for physical product shoots.
- NLP: Thanks to Alexa, Amazon’s got a real edge here. In theory, the dynamic scripts and voiceovers will be more contextually relevant and natural and adaptable to customer personas. And for multiple languages.
- AWS Infrastructure: Provides scalability and speed, leveraging AWS’s machine learning services and computational power to handle high-volume video generation and optimization.
- Reinforcement learning & deep learning algorithms: Real-time A/B testing, optimizing video versions and editing based on click-through rates, conversions, and audience engagement.
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TikTok: AI-Powered Ad Targeting and Content Creation Tools
\ What’s the deal:
TikTok just went to the AI salon and got their roots touched up. Nothing adventurous, just continuous improvements to existing features that are already helping brands and creators sink their claws deeper in their audiences, like refining hyper targeted ads with AI. AI tools suggest trending music, effects, and transitions, streamlining the video production process, while TikTok’s beloved For You Page continues to serve hyper-personalized content. All pretty useful, all pretty vanilla. Maybe they’ve been too busy prepping for court.
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- Deep learning for ad targeting: AI models analyze user behavior, interests, and demographic data to serve hyper-targeted ads to the right audience, increasing relevance and engagement.
- Generative AI for content creation: Suggests music, effects, and transitions by analyzing real-time data on platform trends
- RNNs: Fuel TikTok’s For You Page algorithm, continuously learning from user behavior to surface highly personalized and engaging content.
- AI-enhanced analytics: Real-time machine learning models track ad performance, offering insights to optimize campaigns and adjust strategies on the fly.
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Reddit: AI-Powered Post Suggestions and Moderation
\ What’s the deal:
Reddit has the pandemic years to thank for bringing it back into the spotlight. They’re playing around with some basic AI, like recommending posts and conversations based on activity to help new users quickly find relevant subreddits and feel at home on the platform. On the moderation side, AI assists by flagging content that violates subreddit rules, so humans can go do more useful things. These AI tools aren’t specifically designed for marketers but are clearly intended to grow new users and streamlining platform operations.
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- NLP: Analyzes post content to understand context, relevance, and sentiment, flagging rule violations and suggesting posts based on user activity.
- Collaborative Filtering and Graph Theory: Recommends subreddits and posts by mapping relationships between users, communities, and engagement patterns for enhanced personalization
- Supervised learning for moderation: Automatically moderates content by detecting violations through pattern recognition trained on labeled data.
- Sentiment analysis: Assesses the emotional tone of posts, helping prioritize toxic or controversial content for moderation.
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The Round Up
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YouTube: Community Creation Catalyst
Temperature: Steaming HOT With A Scent Of Mint
Veo’s a good way to boost daily community engagement, but for me it’s all about Communities. This focus is a breath of fresh minty air, especially in a world where most platforms are just finding new ways to shove ads down our throats. Platform-juggling isn’t just inefficient and costly for creators—redirection annoys the hell out of users as well. This is a Pareto improvement—everyone wins. This is a much-needed shift in how we think about audience interaction, and it's about time more platforms followed suit.
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LinkedIn: All Bark, No Bite
Temperature: Lukewarm at best, reheated leftovers being passed off as a fresh meal LinkedIn’s AI updates are more cosmetic than functional. Content recs are helpful, but don’t expect killer insights. The Premium Pages features like custom CTAs and testimonials has “overdue homework” scrawled all over it. This is LinkedIn pretending to innovate while essentially giving you features they should’ve had in the first place. Useful? Yes. Exciting? No.
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Meta (Including Threads): Meh With A Side Of "Finally"
Temperature: Tepid, finally getting the basics right.
Meta’s that person who finally gets around to cleaning their garage—helpful, but you wonder why it took so long. It’s like Meta woke up one day and realized that social media managers need scheduling tools and their chatbots sound like robots. They’re playing catch-up here, adding features that make life easier for social media managers but won’t make anyone jump out of their seat. It’s all utility, no magic.
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Instagram: AI With All The Depth Of A Puddle
Temperature: Lukewarm—fluff masquerading as fire.
Instagram’s latest AI updates feel like someone took glitter, sprinkled it on a paper airplane, and called it a jet. AI stickers? Fun for a few seconds, but does it boost engagement or ROI? The ability to edit DMs post-send is useful in the way being able to fix a typo is useful. Instagram’s AI tools are more about keeping the platform playful than offering anything with substance. It’s like Instagram’s standing in the shallow end of the AI pool, splashing around, while the serious players are diving in deep.
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Snapchat: Forgettable Fireworks
Temperature: Volatile. Intermittent fevers.
Snapchat’s AR tech and PhotoGPT (yes, I coined that name) is fun and technically impressive, but it feels more like a sugar rush than a meal. Some karma points for creativity, but “fun” isn’t your startup marketing team’s main pain point. The problem remains: Snapchat excels at short bursts of engagement, not long-term strategy. Great for a flash-in-the-pan campaign, but not much else.
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X: More Desperation Than Innovation
Temperature: Single digits—is winter coming?
X looks like someone trying to look busy while the house is on fire. AI-powered content moderation and chatbots are theoretically helpful, but given the platform’s recent chaos, it’s hard to believe these updates are more than a desperate bid for stability. The reinforcement learning models trying to clean up harmful content feel like a Band-Aid on a sinking ship, and the NLP-powered chatbots might improve customer interactions, but for how long? This is more about keeping the ship afloat than leading any sort of AI marketing revolution. Marketers would be wise to watch from a safe distance.
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Amazon: The Silent Powerhouse
Temperature: RED-HOT—a practical, scalable game-changer.
Amazon’s AI video generator quietly outshines its competitors. It leverages GANs and NLP to turn basic digital content into polished video ads without needing physical products—a godsend for SaaS and tech companies. Add in the deep integration with e-commerce data and real-time A/B testing, and it’s a powerhouse for marketing. Amazon didn’t just add an AI video tool—it built a video content engine that’s fast, scalable, and smart.
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TikTok – AI OG That’s Watching The Clock
Temperature: Warm-ish, but with a ticking timer.
TikTok’s AI updates are like the fancy garnish on an already-pretty-decent dish. Honestly, they don’t even need AI hyper-targeting and creator tools—TikTok’s pull won’t be diminished any time soon as long as their For You algorithm can continue hooking users with content they didn’t know they needed. But let’s not forget TikTok is still wading through regulatory concerns, which does cast a shadow over its long-term potential for marketers.
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Reddit – Building For Users, Not Quite For Marketers
Temperature: Cool, but full of potential.
Reddit is laser focused on growing its user base, and their AI is all about making Reddit less intimidating for newcomers. Don’t expect any supercharged marketing features any time soon, but if I were you, I’d keep my eye on Reddit. The platform is distinctively quirky, authentic, highly engaged, and home to all the niches you can think of—if Reddit keeps up their growth streak, it could become a goldmine for marketers.
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Final Thoughts: The AI Hype Train—All Aboard, But Who’s Really Driving?
\ AI has become the tech world’s hottest accessory, and every social platform is rushing to wear it like the season’s must-have coat. Some are genuinely pulling it off, blending utility with innovation, while others seem more like they’ve hitched themselves to the AI bandwagon without really knowing where it’s headed.
\ AI is only as good as the problem it’s solving. YouTube’s keeping fans engaged without a cross-platform circus? Brilliant. Amazon’s letting SaaS companies make pro-level videos without ever touching a camera? Pure gold. But some of these updates feel like someone desperately trying to make AI happen just so they can say they’re “in the game.” AI-generated stickers on Instagram? Fun, sure. Game-changing? Not unless you’re marketing exclusively to teens with a penchant for glitter.
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The lesson? Not all AI is created equal, and not every “AI-powered” feature is worth your time. Before you buy into the hype, ask yourself: is this solving a problem, or just adding to the noise?
\ Because AI without substance is just another shiny distraction.
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This content originally appeared on HackerNoon and was authored by Susie Liu
Susie Liu | Sciencx (2024-10-01T15:09:19+00:00) The Definitive Guide to Social Media’s Latest AI Updates: From Gimmicky To Genius. Retrieved from https://www.scien.cx/2024/10/01/the-definitive-guide-to-social-medias-latest-ai-updates-from-gimmicky-to-genius/
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