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Can language models reason?

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  Illustration by Rajashree Rajadhyax Large language models are an impressive technology that excels at providing answers based on vast knowledge of the world. However, they often struggle with reasoning and logic-based questions. To overcome this limitation, the Chain-of-Thought (CoT) method was introduced. This technique emulates how humans solve problems by reasoning step-by-step. Just as we break down complex problems into smaller, manageable parts for analysis and logical resolution, CoT guides language models to adopt a similar approach. By mimicking this natural, structured problem-solving process, CoT enhances the models’ ability to handle logic-driven tasks with greater accuracy and reliability. This approach, however, requires more time and computational effort because it involves processing more tokens . Tokens are the building blocks of text, like words or parts of words, that the model uses to understand and generate responses. Since the Chain-of-Thought method involv...
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AI implementation myths

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  Visionary leaders recognize the importance of adopting cutting-edge technologies to enhance their business operations. This is a bold move, especially in the early stages when few businesses have embraced it. Generative AI is currently at such a juncture. Although AI has experienced several setbacks over the years, recent advancements in foundational models like large language models (LLMs) have reignited interest and investment in the field. Generative AI never fails to impress those who see it in action. At Cere Labs, my company, we have developed a Gen AI framework, and whenever I demonstrate it, the feedback is unanimously positive, with many stating it is "useful." However, despite this enthusiasm, there is hesitation when it comes to integrating this technology into business practices. Addressing certain misconceptions and concerns could help leaders more easily adopt Generative AI to enhance their operations. With my 8 years of experience assisting businesses in inco...
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Homework 2.0: The science behind homework and why it still matters in the AI age!

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  Illustration by Rajashree Rajadhyax I recently came across an article about how teachers are coming up with methods to distinguish between homework done by students and that done by AI. This effort by teachers is not without cause; a recent case in Massachusetts saw a student penalized for using AI in their history paper, highlighting the need for such measures. I found it intriguing and couldn’t help but reflect on this shifting trend.  Homework! Does that word bring back memories? The race to finish it as fast as possible so you could finally go play! Holidays would’ve been so much better without it, don’t you think? I know I felt that way, and I’m pretty sure you did too. And let’s not forget those classmates with endless excuses for not doing it. The most common one? “I wasn’t feeling well!” 🤒 Some would even throw in a few coughs just to make it believable 😏. I was that kid on the opposite end. Just before a holiday, I’d be sneaking in some homework during lunch break...
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AI vs. Human Poetry: Can You Tell the Difference?

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  🎭 AI vs. Human Poetry: Can You Tell the Difference? 🤖✍️ A fascinating study from Kyoto University in Japan shows how AI-generated poetry is becoming almost indistinguishable from human-written works. Surprisingly, non-experts were more likely to think AI poems were human-made than even pieces by famous poets! 📑 Key Findings: 👉 Hard to Spot: Readers correctly identified AI poems only 46.6% of the time—worse than random guessing. 👉 AI Takes the Lead: AI poems scored higher on rhythm and beauty, praised for their accessibility and relatability. 👉 Bias at work: When labeled as AI, the ratings dropped—but without labels, AI poetry often shined. For those who want to know more about this experiment, I've attached the link in the comment. 💭 My Take: This is exciting but also gives us a lot to think about. AI is proving to be incredibly creative, offering a fresh, utilitarian perspective that’s often relatable and useful. But—and this is important—it doesn’t mean AI replaces orig...
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