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Think #AI can really think? Dive into this insightful article by #LatinXinAI community member Alberto Robles, which explores the truth behind artificial intelligence, breaking down what’s real and what’s just a misconception. #DataScience #ComputerScience

Reflection 70B: The Future of AI The strawberry R's problem is solved 1. Understands and Corrects Itself Imagine an AI that not only answers questions but also thinks about its responses and corrects itself. That’s (Llama) Reflection 70B. Like a smart friend who double-checks before speaking. ❌ "Here’s the answer" ✅ "Wait, let me make sure I’m right" 2. Outperforms Expensive Models Reflection 70B is beating costly and secretive AI models in many tests. And it’s available for everyone to download and use. ❌ "Only big companies have powerful AI" ✅ "Anyone can access top-tier AI" 3. Constant Improvement The creators are already working on an even more powerful version. This is just the beginning. ❌ "This is the final product" ✅ "Expect even greater versions soon" 4. Humility in AI Reflection 70B admits when it’s wrong and corrects itself. A trait we all could learn from. ❌ "I’m always right" ✅ "I can be wrong, and that’s okay" 5. Accessible to All Reflection 70B is not just for tech giants. It’s for everyone who wants to explore advanced AI. ❌ "AI is for experts only." ✅ "AI is for everyone." Reflection 70B is a game-changer in the AI world. It’s smart, "humble", and available to all, thanks Mark (Zuckerberg) 😉.

Hey everyone, I just came across the incredible #Llama3.1 and had to share! This new AI model is taking innovation to the next level, with amazing capabilities that are set to change the game. If you’re as passionate about #AI and #MachineLearning as I am, you’ll want to dive into what Llama 3.1 offers. It’s perfect for enhancing projects and driving business success. I’ve been keeping up with all the latest trends through Learnbay and I highly recommend checking them out for more insights into cutting-edge tech like this. Stay tuned for more updates, and let’s explore the future together! Learn more NOW: https://lnkd.in/dw-suGVD #ai #ml #futuretech #innovation #learnbay

Fascinating perspective from Joe McKendrick and Constellation Research, Inc.'s Andy Thurai in Harvard Business Review on using #AI for critical decisions. Many examples show the maximum positive impact when #human and # intelligence are combined. They also give great recommendations on how to get on this path https://lnkd.in/gx7J5K_p #GenAI #datascience #machinelearning #ml #mlops #llmops #EnterpriseAI #AIatscale

AI Meets Human Intelligence - Co-authored with #geminiai - Experiment starting with a blog for future of #supplychainai #AI #SupplyChainAI #HumanIntelligence #FutureofWork

We’ve been misled about Artificial Intelligence (AI) for too long. The common belief that AI is here to assist humans, as just another tool in the toolbox, is not only outdated—it’s wrong. AI is no longer a servant; it’s an Agent, capable of making decisions and executing tasks in ways humans simply can’t. The real problem? Most businesses are clinging to old models, underestimating AI’s role, and ultimately falling behind.   How to challenge the status quo: Stop Clinging to Human Control: The obsession with manual processes is an anchor holding your business back. Research shows that AI can outperform human effort in repetitive, low-value tasks. It’s time to let go. Reframe Your Thinking: Don’t ask, “Where can AI assist?” Instead, ask, “Where is human input actually necessary?” The answer will be far fewer areas than you think. Run Bold Experiments: Don’t dip your toes in AI—dive in. Choose one area where humans are still unnecessarily involved, hand it over to AI, and let the results prove themselves. Rethink Human vs. AI Roles: Let’s get real. AI isn’t here only to support humans; it’s here to outperform them. If you’re not willing to embrace this new reality, your competitors will.

Some gems from Ethan Mollick's new book “Co-Intelligence – Living and Working with AI" (recommended) Mollick postulates FOUR RULES FOR CO-INTELLIGENCE 1️⃣ Always invite AI to the table. 2️⃣ The Jagged Frontier of AI. 3️⃣ Treat AI like a person (but tell it what kind of person it is). 4️⃣ Assume this is the worst AI you will ever use. Let's focus on 1️⃣, for a minute. This is the part that excites me personally the most about working with genAI it its current state: We don’t even know, nor do the top AI researchers, what the current frontier models are capable of. Hence, this is not only about application, but about exploration, as in where ‘no human has set foot before’. ”The path to proficiency in AI is paved with practical experience, exploring its capabilities through direct application and experimentation.” Think about it this way: ➡️ We are dealing with a General-Purpose Technology. ➡️ Hands-on experience is key to develop expertise. ➡️ Working (and living) with AI, now broadly accessible, is showing to achieve superior outcomes for those who can effectively integrate AI into their workflows, enhancing their capabilities and decision-making processes. If you tried working with a model such as Chat-GPT and have been underwhelmed, "assume this is the worst AI you will ever use." ---- I’m curious to hear what your experience has been so far, and where you agree or disagree. Leave a comment.

AI Creating a New Way of Thinking, But Overdependence Could Harm Human Critical Thinking: Scientists Warn Artificial intelligence (AI) is changing the way we think, but some scientists are concerned about what this could mean for our future. In a new article published in Nature Human Behaviour, experts warn that over-relying on AI might put human critical thinking at risk, leaving us too dependent on machines to solve problems. The article introduces a concept called “System 0,” which represents a new form of thinking where we outsource certain cognitive tasks to AI. AI can handle massive amounts of data and perform complex calculations far beyond what humans can do. While this sounds impressive, the danger lies in how much we might depend on it."The risk is that if we lean too much on System 0, we could lose the ability to think critically on our own," the experts explained. "If we simply accept whatever solutions AI gives us without questioning them, we might lose our creativity and our ability to come up with new ideas." In a world that's becoming more automated every day, it’s more important than ever that we continue to challenge and question what AI presents to us.View full details: https://shorturl.at/JOvBE

📝 "A Strategic Roadmap to Business-AI Fit" - AI's impact on the bottom line In our last thought piece, we introduced the powerful new concept of Product-AI Fit, which focuses on the end-user experience with AI. In today's article, we delve into the concept of Business-AI Fit: how artificial intelligence applies to the parts of your business that your customers might not see. By balancing these two concepts when integrating AI, you can ensure maximal positive impact on both your customers and your business. If you're wondering how this might apply to your business, reach out to us at hello@pompeiilabs.com or directly on LinkedIn for more information. https://lnkd.in/dRyXxAJc Jack Ferguson Matty Hogan Hunter Davis Carlos Parga #AI #BusinessAIFit #BusinessDevelopment #ProductAIFit #Innovation #TechInsights #PompeiiLabs

‘AI still makes mistakes’ – in my view one of the most annoying things to read about AI... [This is the first in a mini-series of posts I intend write about my main bugbears with common views about AI. These are things that annoy me when I read them, and I will explain why.] So, what bugs me about ‘AI still makes mistakes’? Well, it suggests that AI is somehow deficient and that it must be ‘fixed’. And that it’s only a matter of time until it's fixed and flawless (after all, it’s AI, right?). This thinking is quite prevalent in public discourse. Yet, it ignores the very nature of AI. Unlike traditional computing, which is precise and accurate, AI is probabilistic. It encodes patterns from data and then makes predictions, either in the form of classifications (like with image recognition), or in the form of content generation. But predictions can, and always will to some degree be ‘wrong’. In principle! No matter how much fine-tuning, retraining or whatever computational improvements we throw at the technology, it will not change its nature as a probabilistic technology. There will always be some misclassifications, inaccuracies, or ‘hallucinations’. But let’s not forget, it is the probabilistic nature that makes AI so powerful, with abilities that can exceed humans on a range of tasks. We just need to be careful where we employ it, and put safeguards in place when decisions have severe consequences, like keeping humans closely in the loop. And there’s a final thing that bugs me – the notion of ‘still’ implies that it might be better to wait until the technology is perfect, until its somehow no longer ‘beta’. Well, such a waiting game can risk falling behind, when industries and competitors are already adopting AI for productivity and transformation. AI will still make mistakes, regardless of how powerful it might become. And that’s ok, when we understand its nature, how to manage it and what structures to build around it. AI fluency is key. #AI #generativeai #genai