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As this post suggests, it’s possible that some people might still be unclear about exactly how generative AI would change our lives. It’s of great importance to clearly understand the nature of generative AI such as ChatGPT. That way, as a lawyer, we can also be prepared for future regulations on AI.

📈 AI's impact on business, as seen through a McKinsey research article. Here are some key takeaways about 🏷 the economic potential of generative AI: 📌 Generative AI’s Rise: The progress of AI has been subtle, with significant milestones like AlphaGo’s victory in Go often overlooked. However, generative AI applications such as ChatGPT and Stable Diffusion have captured global attention due to their broad utility and conversational abilities. 📌 Impact on Business and Society: A broader range of stakeholders are now considering the implications of generative AI on business and society, although many lack the context to fully understand its impact. 📌 Technological Advancements: The development of generative AI is rapid, with notable advancements like OpenAI’s GPT-4 and Google’s PaLM 2, which are enhancing AI’s ability to perform tasks such as data reorganization, text writing, music composition, and digital art creation. 📌 Foundation Models: Generative AI is built on foundation models with expansive neural networks, enabling new capabilities and improving existing ones across various modalities, including images, video, audio, and code. These models represent a significant evolution within deep learning. #AI, #business,

What Is The Most Famous Generative AI? Artificial Intelligence (AI) has been making waves for years, but it's the subset of generative AI that's really captured the public's imagination lately. If you've been anywhere near the internet in the past year, you've probably heard of ChatGPT, DALL-E, or perhaps Midjourney. But what exactly is generative AI, and which model stands out as the most famous? Let's dive in. The Generative AI Revolution Generative AI refers to artificial intelligence systems capable of creating new content, whether it's text, images, music, or even code. These AI models learn from vast amounts of existing data to generate something new and original. It's like teaching a computer to be creative – and boy, have they learned fast! Forbes delves into why OpenAI ChatGPT is number one and who are the contenders. Read full story here; https://lnkd.in/gH8zPaxh

After a good holiday, I would like to share with you this week a very interesting and above all very didactic article about AI from McKinsey & Company. I'll keep some very good sentences from it 1) Within the next three years, anything in the #technology, #media, and #telecommunications space not connected to #AI will be considered obsolete or ineffective 2) #Machinelearning and #ArtificialIntelligence are not very separate things (if I may, Mr McKinsey, I would add that AI is not Intelligent, at least for the time being) 3) What kinds of output / or problems can a generative AI model produce / solve and above all, most importantly, 4) What are the limitations of AI models. I was reading this morning an article in a Spanish newspaper about Why AI will disappoint you? In essence, the article said that the predictions of AI have not materialised and the World is now what it fundamentally was before #ChatGPT came out in November 2022. I don't know if I agree with that when I see my children using that tool every day... Have a very good week!

Generative AI is the game-changer we've been waiting for. 💥🚀 From ChatGPT to GitHub Copilot, and Stable Diffusion, generative AI is seamlessly integrating into our lives and turning heads with its broad functionality and natural conversational abilities. 💬🙌 Imagine a world where routine tasks are effortlessly handled and creativity soars in writing, music composition, and digital art. 🎶✍️🎨 The pace of development is mind-blowing. Just last November, ChatGPT was released, and now we have GPT-4 rocking the scene. Anthropics' generative AI can process tons of text within minutes! 📈⚡️ Thanks to expansive neural networks inspired by the human brain, these foundation models are driving breakthroughs and allowing applications to handle massive amounts of unstructured data and perform multifaceted tasks. 🧠💡 According to McKinsey's research, generative AI could bring in trillions of dollars annually, unleashing immense business transformation and economic growth. 💰💼 Is this the next productivity frontier? #AI #ProductivityRevolution #Innovation #TransformativeTech #BusinessGrowth https://lnkd.in/dMecUJm7

💡 As the hype around Artificial Intelligence (AI) continues to grow, it's important to take a step back and consider what is truly achievable with this technology. I`d like to share with you non-trivial opinion on the future of AI in the recent article on Wired, where the author warns of the "Great AI Disappointment" that may be looming on the horizon. While AI has made impressive strides in recent years, there are still significant limitations and challenges that may prevent it from living up to the lofty expectations that have been set for it. Just a short overview:   📌 Challenges to Overcome: •           False Information and Hallucinations: AI models, trained on massive datasets, can sometimes produce outputs that diverge considerably from reality. •           Augmentation vs. Automation: While AI can automate certain tasks, it's more effective as a tool to augment human capabilities. •           Antitrust and Regulation: The dominance of large tech companies in AI development raises concerns about potential antitrust issues and the need for robust regulations.   📈 What to Expect: •           Incremental Progress: AI's impact will be gradual, with incremental advancements rather than revolutionary breakthroughs. •           Task-Specific Applications: AI will excel in specific applications, such as image recognition and natural language processing, while facing limitations in broader domains. •           Human-AI Collaboration: The future of AI lies in a symbiotic relationship between humans and machines, where AI serves as a powerful tool augmented by human judgment and expertise.   This article explores some of these challenges and offers insights into what we can realistically expect from AI in the coming years. #AI #AILimitations #AItrends #AIExpectations #AIFuture https://lnkd.in/dV3V5Htj

Prompting users to review outputs of generative AI can significantly reduce errors, enhancing overall content quality. A recent field experiment with Accenture's Dock innovation center revealed that introducing deliberate friction—highlighting potential mistakes in AI-generated content—improves accuracy without significantly extending task completion time. This approach underscores the importance of human oversight in AI processes, ensuring responsible AI adoption and fostering trust in large language models. Embrace beneficial friction to enhance decision-making and responsible AI deployment in your organization. #ResponsibleAI Arnab Chakraborty https://lnkd.in/gDyWEkjk

What’s The Best Ai Model On Chatbot Arena? The top five AI models on Chatbot Arena’s overall leader board are: 1. GPT-4o 2. Claude 3.5 Sonnet 3. Gemini Advanced 4. Gemini 1.5 Pro 5. GPT-4 Turbo Do you agree? Read the full article https://lnkd.in/eWc_AN_g #AI #AIModels #Chatbot

What is Generative AI? IBM answers: Generative AI refers to deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on.https://https://lnkd.in/dGNjrfT8 McKinsey & Company: Generative artificial intelligence (AI) describes algorithms (such as ChatGPT) that can be used to create new content, including audio, code, images, text, simulations, and videos. https://lnkd.in/dxS-4yQw So all these ChatGPT LLM, DALL-E, Sora, Lora... and those video producing models are generative AI. Did not know that [facepalm emoji here]

A recent study revealed that well-prompted AI text is now nearly indistinguishable from human writing. This highlights a crucial point: the power lies not just in AI itself, but in crafting the right prompts. This breakthrough has significant implications for sales and customer service: Personalized Interactions: AI engaging customers with human-like understanding, 24/7. Scalable Expertise: AI trained with top salespeople's knowledge, ensuring consistent quality. Real-time Adaptation: Adjusting approach based on customer responses. Efficiency: Long-term benefits in scalability and consistency. As AI evolves, the key differentiator will be how we prompt and direct these tools. Whether in sales, customer service, or any communication field, it's time to hone your "prompt engineering" skills. Here's a link to the study: https://bit.ly/3L8G9f3 #AI #SalesTech #CustomerService #PromptEngineering