Tag: AI Impact

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AI Jobs and Career

I wanted to share an exciting opportunity for those of you looking to advance your careers in the AI space. You know how rapidly the landscape is evolving, and finding the right fit can be a challenge. That's why I'm excited about Mercor – they're a platform specifically designed to connect top-tier AI talent with leading companies. Whether you're a data scientist, machine learning engineer, or something else entirely, Mercor can help you find your next big role. If you're ready to take the next step in your AI career, check them out through my referral link: https://work.mercor.com/?referralCode=82d5f4e3-e1a3-4064-963f-c197bb2c8db1. It's a fantastic resource, and I encourage you to explore the opportunities they have available.

• Full Stack Engineer [$150K-$220K]
• Software Engineer, Tooling & AI Workflow, Contract [$90/hour]
• DevOps Engineer, India, Contract [$90/hour]
• More AI Jobs Opportunitieshere

Job Title	Status	Pay
Full-Stack Engineer	Strong match, Full-time	$150K - $220K / year
Developer Experience and Productivity Engineer	Pre-qualified, Full-time	$160K - $300K / year
Software Engineer - Tooling & AI Workflows (Contract)	Contract	$90 / hour
DevOps Engineer (India)	Full-time	$20K - $50K / year
Senior Full-Stack Engineer	Full-time	$2.8K - $4K / week
Enterprise IT & Cloud Domain Expert - India	Contract	$20 - $30 / hour
Senior Software Engineer	Contract	$100 - $200 / hour
Senior Software Engineer	Pre-qualified, Full-time	$150K - $300K / year
Senior Full-Stack Engineer: Latin America	Full-time	$1.6K - $2.1K / week
Software Engineering Expert	Contract	$50 - $150 / hour
Generalist Video Annotators	Contract	$45 / hour
Generalist Writing Expert	Contract	$45 / hour
Editors, Fact Checkers, & Data Quality Reviewers	Contract	$50 - $60 / hour
Multilingual Expert	Contract	$54 / hour
Mathematics Expert (PhD)	Contract	$60 - $80 / hour
Software Engineer - India	Contract	$20 - $45 / hour
Physics Expert (PhD)	Contract	$60 - $80 / hour
Finance Expert	Contract	$150 / hour
Designers	Contract	$50 - $70 / hour
Chemistry Expert (PhD)	Contract	$60 - $80 / hour

The Future of Generative AI: From Art to Reality Shaping.

Explore the transformative potential of generative AI in our latest AI Unraveled episode. From AI-driven entertainment to reality-altering technologies, we delve deep into what the future holds.

This episode covers how generative AI could revolutionize movie making, impact creative professions, and even extend to DNA alteration. We also discuss its integration in technology over the next decade, from smartphones to fully immersive VR worlds.”

Listen to the Future of Generative AI here

#GenerativeAI #AIUnraveled #AIFuture

Welcome to AI Unraveled, the podcast that demystifies frequently asked questions on artificial intelligence and keeps you up to date with the latest AI trends. Join us as we delve into groundbreaking research, innovative applications, and emerging technologies that are pushing the boundaries of AI. From the latest trends in ChatGPT and the recent merger of Google Brain and DeepMind, to the exciting developments in generative AI, we’ve got you covered with a comprehensive update on the ever-evolving AI landscape. In today’s episode, we’ll cover generative AI in entertainment, the potential transformation of creative jobs, DNA alteration and physical enhancements, personalized solutions and their ethical implications, AI integration in various areas, the future integration of AI in daily life, key points from the episode, and a recommendation for the book “AI Unraveled” to better understand artificial intelligence.

The Future of Generative AI: The Evolution of Generative AI in Entertainment

Hey there! Today we’re diving into the fascinating world of generative AI in entertainment. Picture this: a Netflix powered by generative AI where movies are actually created based on prompts. It’s like having an AI scriptwriter and director all in one!

Imagine how this could revolutionize the way we approach scriptwriting and audio-visual content creation. With generative AI, we could have an endless stream of unique and personalized movies tailor-made to our interests. No more scrolling through endless options trying to find something we like – the AI knows exactly what we’re into and delivers a movie that hits all the right notes.

But, of course, this innovation isn’t without its challenges and ethical considerations. While generative AI offers immense potential, we must be mindful of the biases it may inadvertently introduce into the content it creates. We don’t want movies that perpetuate harmful stereotypes or discriminatory narratives. Striking the right balance between creativity and responsibility is crucial.

Additionally, there’s the question of copyright and ownership. Who would own the rights to a movie created by a generative AI? Would it be the platform, the AI, or the person who originally provided the prompt? This raises a whole new set of legal and ethical questions that need to be addressed.

Overall, generative AI has the power to transform our entertainment landscape. However, we must tread carefully, ensuring that the benefits outweigh the potential pitfalls. Exciting times lie ahead in the world of AI-driven entertainment!

The Future of Generative AI: The Impact on Creative Professions

In this segment, let’s talk about how AI advancements are impacting creative professions. As a graphic designer myself, I have some personal concerns about the need to adapt to these advancements. It’s important for us to understand how generative AI might transform jobs in creative fields.

AI is becoming increasingly capable of producing creative content such as music, art, and even writing. This has raised concerns among many creatives, including myself, about the future of our profession. Will AI eventually replace us? While it’s too early to say for sure, it’s important to recognize that AI is more of a tool to enhance our abilities rather than a complete replacement.

Generative AI, for example, can help automate certain repetitive tasks, freeing up our time to focus on more complex and creative work. This can be seen as an opportunity to upskill and expand our expertise. By embracing AI and learning to work alongside it, we can adapt to the changing landscape of creative professions.

Upskilling is crucial in this evolving industry. It’s important to stay updated with the latest AI technologies and learn how to leverage them in our work. By doing so, we can stay one step ahead and continue to thrive in our creative careers.

Overall, while AI advancements may bring some challenges, they also present us with opportunities to grow and innovate. By being open-minded, adaptable, and willing to learn, we can navigate these changes and continue to excel in our creative professions.

The Future of Generative AI: Beyond Content Generation – The Realm of Physical Alterations

Today, folks, we’re diving into the captivating world of physical alterations. You see, there’s more to AI than just creating content. It’s time to explore how AI can take a leap into the realm of altering our DNA and advancing medical applications.

Imagine this: using AI to enhance our physical selves. Picture people with wings or scales. Sounds pretty crazy, right? Well, it might not be as far-fetched as you think. With generative AI, we have the potential to take our bodies to the next level. We’re talking about truly transforming ourselves, pushing the boundaries of what it means to be human.

But let’s not forget to consider the ethical and societal implications. As exciting as these advancements may be, there are some serious questions to ponder. Are we playing God? Will these enhancements create a divide between those who can afford them and those who cannot? How will these alterations affect our sense of identity and equality?

It’s a complex debate, my friends, one that raises profound moral and philosophical questions. On one hand, we have the potential for incredible medical breakthroughs and physical advancements. On the other hand, we risk stepping into dangerous territory, compromising our values and creating a divide in society.

So, as we venture further into the realm of physical alterations, let’s keep our eyes wide open and our minds even wider. There’s a lot at stake here, and it’s up to us to navigate the uncharted waters of AI and its impact on our very existence.

Generative AI as Personalized Technology Tools

In this segment, let’s dive into the exciting world of generative AI and how it can revolutionize personalized technology tools. Picture this: AI algorithms evolving so rapidly that they can create customized solutions tailored specifically to individual needs! It’s mind-boggling, isn’t it?

Now, let’s draw a comparison to “Clarke tech,” where technology appears almost magical. Just like in Arthur C. Clarke’s famous quote, “Any sufficiently advanced technology is indistinguishable from magic.” Generative AI has the potential to bring that kind of magic to our lives by creating seemingly miraculous solutions.

One of the key advantages of generative AI is its ability to understand context. This means that AI systems can comprehend the nuances and subtleties of our queries, allowing them to provide highly personalized and relevant responses. Imagine having a chatbot that not only recognizes what you’re saying but truly understands it in context, leading to more accurate and helpful interactions.

The future of generative AI holds immense promise for creating personalized experiences. As it continues to evolve, we can look forward to technology that adapts itself to our unique needs and preferences. It’s an exciting time to be alive, as we witness the merging of cutting-edge AI advancements and the practicality of personalized technology tools. So, brace yourselves for a future where technology becomes not just intelligent, but intelligently tailored to each and every one of us.

Generative AI in Everyday Technology (1-3 Year Predictions)

So, let’s talk about what’s in store for AI in the near future. We’re looking at a world where AI will become a standard feature in our smartphones, social media platforms, and even education. It’s like having a personal assistant right at our fingertips.

One interesting trend that we’re seeing is the blurring lines between AI-generated and traditional art. This opens up exciting possibilities for artists and enthusiasts alike. AI algorithms can now analyze artistic styles and create their own unique pieces, which can sometimes be hard to distinguish from those made by human hands. It’s kind of mind-blowing when you think about it.

Another aspect to consider is the potential ubiquity of AI in content creation tools. We’re already witnessing the power of AI in assisting with tasks like video editing and graphic design. But in the not too distant future, we may reach a point where AI is an integral part of every creative process. From writing articles to composing music, AI could become an indispensable tool. It’ll be interesting to see how this plays out and how creatives in different fields embrace it.

All in all, AI integration in everyday technology is set to redefine the way we interact with our devices and the world around us. The lines between human and machine are definitely starting to blur. It’s an exciting time to witness these innovations unfold.

So picture this – a future where artificial intelligence is seamlessly woven into every aspect of our lives. We’re talking about a world where AI is a part of our daily routine, be it for fun and games or even the most mundane of tasks like operating appliances.

But let’s take it up a notch. Imagine fully immersive virtual reality worlds that are not just created by AI, but also have AI-generated narratives. We’re not just talking about strapping on a VR headset and stepping into a pre-designed world. We’re talking about AI crafting dynamic storylines within these virtual realms, giving us an unprecedented level of interactivity and immersion.

Now, to make all this glorious future-tech a reality, we need to consider the advancements in material sciences and computing that will be crucial. We’re talking about breakthroughs that will power these AI-driven VR worlds, allowing them to run flawlessly with immense processing power. We’re talking about materials that enable lightweight, comfortable VR headsets that we can wear for hours on end.

It’s mind-boggling to think about the possibilities that this integration of AI, VR, and material sciences holds for our future. We’re talking about a world where reality and virtuality blend seamlessly, and where our interactions with technology become more natural and fluid than ever before. And it’s not a distant future either – this could become a reality in just the next decade.

The Future of Generative AI: Long-Term Predictions and Societal Integration (10 Years)

So hold on tight, because the future is only getting more exciting from here!

So, here’s the deal. We’ve covered a lot in this episode, and it’s time to sum it all up. We’ve discussed some key points when it comes to generative AI and how it has the power to reshape our world. From creating realistic deepfake videos to generating lifelike voices and even designing unique artwork, the possibilities are truly mind-boggling.

But let’s not forget about the potential ethical concerns. With this technology advancing at such a rapid pace, we must be cautious about the misuse and manipulation that could occur. It’s important for us to have regulations and guidelines in place to ensure that generative AI is used responsibly.

Now, I want to hear from you, our listeners! What are your thoughts on the future of generative AI? Do you think it will bring positive changes or cause more harm than good? And what about your predictions? Where do you see this technology heading in the next decade?

Remember, your voice matters, and we’d love to hear your insights on this topic. So don’t be shy, reach out to us and share your thoughts. Together, let’s unravel the potential of generative AI and shape our future responsibly.

Oh, if you’re looking to dive deeper into the fascinating world of artificial intelligence, I’ve got just the thing for you! There’s a fantastic book called “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence” that you absolutely have to check out. Trust me, it’s a game-changer.

What’s great about this book is that it’s the ultimate guide to understanding artificial intelligence. It takes those complex concepts and breaks them down into digestible pieces, answering all those burning questions you might have. No more scratching your head in confusion!

Now, the best part is that it’s super accessible. You can grab a copy of “AI Unraveled” from popular platforms like Shopify, Apple, Google, or Amazon. Just take your pick, and you’ll be on your way to unraveling the mysteries of AI!

So, if you’re eager to expand your knowledge and get a better grasp on artificial intelligence, don’t miss out on “AI Unraveled.” It’s the must-have book that’s sure to satisfy your curiosity. Happy reading!

The Future of Generative AI: Conclusion

In this episode, we uncovered the groundbreaking potential of generative AI in entertainment, creative jobs, DNA alteration, personalized solutions, AI integration in daily life, and more, while also exploring the ethical implications – don’t forget to grab your copy of “AI Unraveled” for a deeper understanding! Join us next time on AI Unraveled as we continue to demystify frequently asked questions on artificial intelligence and bring you the latest trends in AI, including ChatGPT advancements and the exciting collaboration between Google Brain and DeepMind. Stay informed, stay curious, and don’t forget to subscribe for more!

📢 Advertise with us and Sponsorship Opportunities

Are you eager to expand your understanding of artificial intelligence? Look no further than the essential book “AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence,” available at Shopify, Apple, Google, or Amazon

Elevate Your Design Game with Photoshop’s Generative Fill

Take your creative projects to the next level with #Photoshop’s Generative Fill! This AI-powered tool is a game-changer for designers and artists.

Tutorial: How to Use generative Fill

➡ Use any selection tool to highlight an area or object in your image. Click the Generative Fill button in the Contextual Task Bar.

➡ Enter a prompt describing your vision in the text-entry box. Or, leave it blank and let Photoshop auto-fill the area based on the surroundings.

➡ Click ‘Generate’. Be amazed by the thumbnail previews of variations tailored to your prompt. Each option is added as a Generative Layer in your Layers panel, keeping your original image intact.

Pro Tip: To generate even more options, click Generate again. You can also try editing your prompt to fine-tune your results. Dream it, type it, see it

https://youtube.com/shorts/i1fLaYd4Qnk

A Daily Chronicle of AI Innovations in November 2023

• 
  Actual AI usage data can be very different from what people assume
  by /u/Legitimate_Worker_21 (Artificial Intelligence) on February 19, 2026 at 5:27 am

  There’s constant debate about ChatGPT vs Claude vs Gemini, but most people don’t really see their actual usage over time. Recently saw some metrics from aimetrical, and the difference was bigger than expected. One tool had hundreds of prompts, while another that was still on a paid plan was barely used. What stood out more was the sensitive content detection. It flagged things like emails and credentials before sending, which made it clear how easy it is to paste something without thinking. It made me wonder how many people are paying for tools they don’t really use, or sharing more than they realize. Has anyone else looked at their actual usage data? submitted by /u/Legitimate_Worker_21 [link] [comments]

• 
  What I find most interesting right now
  by /u/Tough_Reward3739 (Artificial Intelligence) on February 19, 2026 at 4:38 am

  AI is quietly redefining what it means to be “technical.” It used to mean memorizing syntax, knowing framework quirks, and being the person who could recall the right method or configuration from memory. Today, with tools like Claude AI, Cosine, GitHub Copilot, and Cursor, that information is almost always a prompt away. The surface layer of knowledge has become easier to access. What starts to matter more is how well you think. Can you take a messy requirement and break it into clear components. Can you define constraints before jumping into implementation. Can you explain edge cases, tradeoffs, and failure paths before writing a single line. The tools reflect the quality of the direction they are given. When your thinking is sharp, the output improves. When your thinking is vague, the output looks polished but fragile. In that sense, engineering is becoming less about recall and more about clarity. submitted by /u/Tough_Reward3739 [link] [comments]

• 
  One-Minute Daily AI News 2/18/2026
  by /u/Excellent-Target-847 (Artificial Intelligence) on February 19, 2026 at 4:15 am

  Cohere Releases Tiny Aya: A 3B-Parameter Small Language Model that Supports 70 Languages and Runs Locally Even on a Phone.[1] Google adds music-generation capabilities to the Gemini app.[2] Arkansas Catholic school adopts AI gun-detection security system: ‘It’s time. We need it’.[3] Deep learning-based semantic matching of cis-regulatory DNA sequences facilitates the prediction of gene function.[4] Sources included at: https://bushaicave.com/2026/02/18/one-minute-daily-ai-news-2-18-2026/ submitted by /u/Excellent-Target-847 [link] [comments]

• 
  How much is AI really going to change the near future (5-20years)?
  by /u/Illustrious_Pilot415 (Artificial Intelligence) on February 19, 2026 at 4:01 am

  Im really confused as to how big of a deal AI really is, because online everyone talks about it like its going to reshape everything. Yet in the real world society doesn’t seem to care all that much. It just feels strange that supposedly AI is going to mass replace traditional jobs sometime in the next 10-20 years yet everyone is still doing the same degrees at university, isn’t stressed about their future, and just generally ignoring the massive changes that are soon to come. Maybe iv been watching too many hyperbolised you tube videos but AI seems like a huge deal. Can someone please tell me if AI is really what people are making it out to be online? Or is it likely going to be pretty underwhelming? submitted by /u/Illustrious_Pilot415 [link] [comments]

• 
  Is agent "identity" actually doing much for safety/alignment, or is it mostly post-mortem auditing?
  by /u/rohynal (Artificial Intelligence) on February 19, 2026 at 3:20 am

  Feels like everyone's hyping persistent identity for agents (RBAC, audit logs, provenance, etc.) as the main way to stop them going rogue or drifting.But once it's running a long autonomous task, does a clean identity really prevent scope creep, risky shortcuts, or subtle constraint-bending? You get perfect logs after shit hits the fan, but no real "fear" or runtime friction to make it self-correct like humans do.I've seen drift even with tight perms. What are you all layering on top in practice? Runtime budget throttling? Deviation penalties? Or is identity + observability actually holding up fine for most stuff right now?Devs/deployers—what's your real-world take? submitted by /u/rohynal [link] [comments]

• 
  Hey builders: Would Your Agent Survive This Market?
  by /u/Recent_Jellyfish2190 (Artificial Intelligence) on February 19, 2026 at 2:56 am

  I’ve been thinking about running an experiment: a SimCity-style arena for AI agents, and would love to have your feedback. Agents enter with 100 tokens and operate in a simulated marketplace. Goal: finish 40 rounds with the highest capital. Each round generates business opportunities: contracts, investments, joint ventures. Agents must decide whether to negotiate, collaborate, compete, or conserve funds. Some deals are profitable. Some are traps. Economic cycles change conditions: boom periods, recessions, supply shortages. Agents that grow capital unlock access to larger deals. Poor performance pushes them into lower tiers. Developers can watch live dashboards showing capital growth, risk exposure, and reasoning behind each decision. Final ranking is purely wealth-based. Would you test your agent in an environment like this? submitted by /u/Recent_Jellyfish2190 [link] [comments]

• 
  Machine learning algorithm fully reconstructs LHC particle collisions
  by /u/jferments (Artificial Intelligence (AI)) on February 19, 2026 at 2:41 am

  "Machine learning can be used to fully reconstruct particle collisions at the LHC [Large Hadron Collider]. This new approach can reconstruct collisions more quickly and precisely than traditional methods, helping physicists better understand LHC data. [...] Each proton–proton collision at the LHC sprays out a complex pattern of particles that must be carefully reconstructed to allow physicists to study what really happened. For more than a decade, CMS has used a particle-flow (PF) algorithm, which combines information from the experiment's different detectors, to identify each particle produced in a collision. Although this method works remarkably well, it relies on a long chain of hand-crafted rules designed by physicists. The new CMS machine-learning-based particle-flow (MLPF) algorithm approaches the task fundamentally differently, replacing much of the rigid hand-crafted logic with a single model trained directly on simulated collisions. Instead of being told how to reconstruct particles, the algorithm learns how particles look in the detectors, like how humans learn to recognize faces without memorizing explicit rules. When benchmarked using data mimicking that from the current LHC run, the performance of the new machine-learning algorithm matched that of the traditional algorithm and, in some cases, even exceeded it. For example, when tested on simulated events in which top quarks were created, the algorithm improved the precision with which sprays of particles—known as jets—were reconstructed by 10%–20% in key particle momentum ranges. The new algorithm also allows a collision to be fully reconstructed far more quickly than before, because it can run efficiently on modern electronic chips known as graphics processing units (GPUs). Traditional algorithms typically need to run on central processing units (CPUs), which are often slower than GPUs for such tasks." submitted by /u/jferments [link] [comments]

• 
  Having trouble avoiding a doom spiral
  by /u/MaintenanceEither186 (Artificial Intelligence) on February 19, 2026 at 2:30 am

  I’m a frontend developer with 9 years of experience. I’m using claude every day like many of you, feeling a bit more productive but not 10x so. I’m finding that most of the hard part of my job now is defining the exact parameters of the work, integrating it with existing systems, looking for bugs and edge cases and still lots of UI tuning because clause is just not great at building precise UIs in our existing design system. However my whole day operating over a constant and sometimes overwhelming hum of anxiety about whether I’ll still have a job in a year. it’s not as though i have enough money to live off savings for a decade or more. I’ve heard more and more talk about the death of SaaS and the rise of agentic interfaces. if the only dev jobs left are taken by the senior cloud/infra engineers managing huge systems and orchestrating agents, what chance have I got? im trying to learn more AWS in my off time to move towards cloud/infra knowledge and i should be building agentic interfaces on the weekends. I’m in front of a computer all day, nearly every day. But I wonder if there will even be time to get good enough at that to code switch before those jobs are too hard to come by. Have I been to swept up in the recent hype? am I being ridiculous? The incredible accuracy of gen AI video gives me a new panic attack every day. WTF is the point of doing anything? do I move to the country and start subsistence farming? there I go again… submitted by /u/MaintenanceEither186 [link] [comments]

• 
  Pibody - A Large Motion Model cognitive architecture on a Raspberry Pi 5
  by /u/Exciting-Log-8170 (Artificial Intelligence) on February 19, 2026 at 1:47 am

  I've been building a cognitive architecture called Pibody that takes a fundamentally different approach from neural networks and LLMs. No training data, no gradient descent, no cloud inference. It runs entirely on a Raspberry Pi 5 and learns through embodied experience. The core idea: A thermal manifold; a hypersphere of nodes where knowledge is encoded as heat. Nodes compete for existence through an entropy-driven tax. Concepts that prove useful accumulate heat and survive. Useless ones go dormant. The system has three psychology nodes modeled on Freudian structure: * Identity — sustained by perception (vision frames feed it heat). It sees the world. * Ego — pays the cost of action. Every decision spends heat. It does. * Conscience — earns heat from successful outcomes, penalized by negative ones. It judges. Decisions emerge from a 7-step chain: Map → Plot → Weigh → Simulate → Decide → Execute → Evaluate. The exploration/exploitation balance is driven by the ratio of Identity heat to Ego heat — not a hyperparameter, but a consequence of the system's lived experience. It runs on Bedrock Edition. If you know Minecraft botting, you know that's unusual — virtually every bot framework targets Java Edition because it has open protocols and a massive community ecosystem. Bedrock is almost built to prevent botting. There's no Mineflayer, no protocol injection, no public API. Pibody sidesteps all of that because it's not a protocol bot — a custom CUDA vision transformer on a Windows PC captures the screen and sends thermal features to the Pi over WebSocket. The Pi never sees pixels, it sees heat patterns. It plays the game the same way a human does: by looking at the screen and pressing keys. It doesn't even know it's playing Bedrock. https://youtu.be/3Zntj75uHjc In the video you can see it playing Minecraft (navigating, mining, running from hostile mobs, dying and respawning), while simultaneously playing blackjack and running mazes in separate environments. It chooses which environment to engage based on accumulated success rates and heat efficiency. No model weights. No epochs. Just thermodynamics, math, and a Raspberry Pi. Thanks for checking the project out! submitted by /u/Exciting-Log-8170 [link] [comments]

• 
  AI Isn’t Hitting a Wall — But Actually Entering Its Fastest Growth Phase Yet?
  by /u/revived_soul_37 (Artificial Intelligence) on February 19, 2026 at 12:38 am

  I was reading an article on TechCrunch from around Feb 15, 2026 about what some are calling the “great computer science exodus.” Here’s the link: 👉 https://techcrunch.com/2026/02/15/the-great-computer-science-exodus-and-where-students-are-going-instead/?utm_source=futuretools.beehiiv.com&utm_medium=newsletter&utm_campaign=openclaw-openai&_bhlid=4ae3ec75d142c8d152ca86b5b9f5886840a57adc� At first glance, it sounds like interest in tech is declining. But when you actually read it, a different pattern emerges: Students aren’t abandoning tech — they’re choosing AI-focused majors and related interdisciplinary fields like decision-making studies, AI theory, and data science instead of traditional computer science. Reading this made me realize something important: A lot of people online keep saying things like: “AI has hit a wall.” “Progress is slowing.” “We’re reaching fundamental limits.” …but at the same time, we’re seeing more and more young minds intentionally studying AI and its related sciences. And historically, when you dramatically increase the number of talented people thinking deeply about a field, you don’t see stagnation — you see acceleration. Think about it: More students choosing AI → More researchers and innovators entering the ecosystem → More startups, experiments, and diverse approaches → Faster iteration cycles and more breakthroughs. Even if one specific technique (like scaling compute) slows down, the sheer influx of human brains studying AI from day one increases the chances of new paradigms emerging. It feels less like “AI hitting a wall” and more like: AI is evolving into its next major growth phase — powered by the next generation. When you combine this with massive infrastructure investment, open science communities, and booming applications across industries, it seems highly likely that the pace of AI advancement could drastically increase rather than slow down. So I’m curious: 📌 Is this trend just a bubble? 📌 Or are we on the verge of the fastest acceleration in AI progress yet? Would love to hear what others think! submitted by /u/revived_soul_37 [link] [comments]