𝗗𝗲𝗮𝗿 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗔𝗜 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 🤖🔥, we're approaching the 100 𝗺𝗲𝗺𝗯𝗲𝗿𝘀 𝗺𝗶𝗹𝗲𝘀𝘁𝗼𝗻𝗲 - we are #284 𝗶𝗻 𝗧𝗲𝗰𝗵 with an activity rate 𝘁𝗵𝗿𝗼𝘂𝗴𝗵𝗼𝘂𝘁 𝗮𝗹𝗹 𝗺𝗲𝗺𝗯𝗲𝗿𝘀 𝗼𝗳 78% - this is a great milestone and we're not stopping at all. 🚀 𝗔𝘀 𝗮 𝘀𝗽𝗲𝗰𝗶𝗮𝗹 𝗴𝗶𝗳𝘁 🎁 𝘄𝗲 𝗵𝗮𝘃𝗲 𝗱𝗲𝗰𝗶𝗱𝗲𝗱 𝘁𝗼 𝘂𝗻𝗹𝗼𝗰𝗸 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 😳 𝗳𝗼𝗿 𝘆𝗼𝘂 💪🏼 including what is the most requested courses: ⚙️ AI AUTOMATION 🦾 AI AGENTS Check out the classroom, when we 𝘀𝗮𝘆 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴, we 𝗺𝗲𝗮𝗻 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴. 🤩 🙌🏻 The whole journey! 🦾 Transforming a company or a department with AI is no walk in the park - We are supporting businesses every day on their journey, a key step is 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 to prepare for what is the goal - 𝗵𝗮𝘃𝗲 𝗶𝗻𝗱𝗶𝘃𝗶𝗱𝘂𝗮𝗹 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗽𝗲𝗿 𝗱𝗲𝗽𝗮𝗿𝘁𝗺𝗲𝗻𝘁 that super-charge the productivity of all employees. This is what the next step of the community will look like: - We will provide you with the 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗧𝗲𝗺𝗽𝗹𝗮𝘁𝗲𝘀 necessary to 𝗷𝘂𝗺𝗽-𝘀𝘁𝗮𝗿𝘁 your AI automation. - We are providing the 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗮𝗻𝗱 𝗺𝗼𝗱𝗲𝗹𝘀, with real-world examples that are ready to use. - We are 𝘀𝘂𝗽𝗽𝗼𝗿𝘁𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝘁𝗵𝗲 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 and 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗔𝗴𝗲𝗻𝘁𝘀. Let us know what else you need within our community and individually. 🧠🛠️💪🏼 Thank you for being with us from very early on. 𝗦𝗮𝘀𝗰𝗵𝗮 𝗕𝗢𝗥𝗡 & 𝗩𝗶𝗻𝗶𝗰𝗶𝘂𝘀 𝗔𝗟𝗩𝗘𝗦 on behalf of the whole 𝗧𝗲𝗮𝗺 @ 𝗔𝗜 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆

Mistral launches new AI models, including an enhanced ChatGPT competitor "Le Chat", while Gemini tops the LM Cy leaderboard and AI impacts nuclear security discussions. 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 & 𝗞𝗲𝘆 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 🆕 𝗠𝗶𝘀𝘁𝗿𝗮𝗹 𝗿𝗲𝗹𝗲𝗮𝘀𝗲𝘀 𝗻𝗲𝘄 𝗔𝗜 𝗺𝗼𝗱𝗲𝗹𝘀, 𝗶𝗻𝗰𝗹𝘂𝗱𝗶𝗻𝗴 𝗳𝗿𝗲𝗲 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗮𝗹𝘁𝗲𝗿𝗻𝗮𝘁𝗶𝘃𝗲𝘀. Mistral’s new models demonstrate the trend of free, high-quality AI tools, enhancing competition in the market. This could lead to wider adoption of AI in everyday applications. 🌐 𝗚𝗲𝗺𝗶𝗻𝗶 𝗿𝗮𝗻𝗸𝘀 #𝟭 𝗼𝗻 𝘁𝗵𝗲 𝗟𝗠 𝗖𝘆 𝗹𝗲𝗮𝗱𝗲𝗿𝗯𝗼𝗮𝗿𝗱, 𝗼𝘂𝘁𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗶𝗻𝗴 𝗖𝗵𝗮𝘁𝗚𝗣𝗧. Gemini’s success reflects the importance of user feedback in AI development, emphasizing the need for models that perform well in real-world scenarios. 💻 𝗢𝗽𝗲𝗻𝗔𝗜’𝘀 𝗱𝗲𝘀𝗸𝘁𝗼𝗽 𝘂𝗽𝗱𝗮𝘁𝗲 𝗮𝗹𝗹𝗼𝘄𝘀 𝗰𝗼𝗱𝗲 𝗿𝗲𝗮𝗱𝗶𝗻𝗴 𝗶𝗻 𝗺𝗮𝗷𝗼𝗿 𝗜𝗗𝗘𝘀. OpenAI’s desktop integration signifies a shift towards making AI more accessible in professional environments, enhancing productivity for developers. 🛡️ 𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗲𝘀 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗴𝗼𝘃𝗲𝗿𝗻𝗺𝗲𝗻𝘁 𝗼𝗻 𝗻𝘂𝗰𝗹𝗲𝗮𝗿 𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆. Anthropic’s partnership with the government signals a growing recognition of the ethical implications of AI technologies, especially regarding national security and sensitive data. 🤖 𝗔𝗜 𝗼𝘂𝘁𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝘀 𝗱𝗼𝗰𝘁𝗼𝗿𝘀 𝗶𝗻 𝗱𝗶𝗮𝗴𝗻𝗼𝘀𝘁𝗶𝗰 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆. The ability of AI to surpass human capabilities in diagnostics may revolutionize healthcare, allowing for faster and more accurate patient assessments. 🛒 𝗣𝗲𝗿𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗶𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗲𝘀 𝘀𝗵𝗼𝗽𝗽𝗶𝗻𝗴 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗳𝗼𝗿 𝘀𝗲𝗮𝗺𝗹𝗲𝘀𝘀 𝗼𝗻𝗹𝗶𝗻𝗲 𝗽𝘂𝗿𝗰𝗵𝗮𝘀𝗲𝘀. Perplexity’s shopping feature exemplifies the merging of AI and e-commerce, potentially reshaping how consumers interact with online marketplaces. 🔥 𝗡𝘃𝗶𝗱𝗶𝗮’𝘀 𝗻𝗲𝘄 𝗰𝗵𝗶𝗽𝘀 𝗳𝗮𝗰𝗲 𝗼𝘃𝗲𝗿𝗵𝗲𝗮𝘁𝗶𝗻𝗴 𝗶𝘀𝘀𝘂𝗲𝘀 𝗶𝗻 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻. Nvidia’s overheating issues with new chips highlight the challenges in scaling AI hardware, which could delay advancements in AI applications and affect market competitiveness. ♻️ If you have found this post insightful - share it with your network ♻️ Here is the Link to our Strategic AI Business Transformation community article: https://www.skool.com/netregie-ai/47-ai-news?p=09f0f55a

AI innovation is slowing down as major companies struggle with next-gen models, while new updates and partnerships emerge in the space. 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 & 𝗞𝗲𝘆 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 🚀 𝗔𝗜 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗮𝗿𝗲 𝗳𝗮𝗰𝗶𝗻𝗴 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗶𝗻 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗶𝗻𝗴 𝗻𝗲𝘅𝘁-𝗴𝗲𝗻 𝗺𝗼𝗱𝗲𝗹𝘀. Slower Innovation Pace: The struggle for AI companies to deliver major performance improvements indicates a potential plateau in technological advancements, emphasizing the complexity of scaling up AI models. 💻 𝗢𝗽𝗲𝗻𝗔𝗜’𝘀 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗵𝗮𝘀 𝘁𝗿𝗮𝗻𝘀𝗶𝘁𝗶𝗼𝗻𝗲𝗱 𝘁𝗼 𝘁𝗵𝗲 𝗰𝗹𝗲𝗮𝗻𝗲𝗿 𝗱𝗼𝗺𝗮𝗶𝗻 𝗰𝗵𝗮𝘁.𝗰𝗼𝗺. Domain Name Change: ChatGPT’s rebranding to chat.com signifies a strategic move to streamline its identity, which may enhance user engagement. 🌐 𝗢𝗹𝗹𝗮𝗺𝗮 𝗶𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗲𝗱 𝘃𝗶𝘀𝗶𝗼𝗻 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀 𝗶𝗻 𝘁𝗵𝗲𝗶𝗿 𝗺𝗼𝗱𝗲𝗹𝘀, 𝗲𝗻𝗵𝗮𝗻𝗰𝗶𝗻𝗴 𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹𝗶𝘁𝘆. Ollama’s Vision Capabilities: The introduction of vision support highlights the growing importance of multi-modal AI, allowing users to interact with models through various inputs. 🤖 𝗣𝗮𝗹𝗲𝗿 𝗽𝗮𝗿𝘁𝗻𝗲𝗿𝘀 𝘄𝗶𝘁𝗵 𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰 𝘁𝗼 𝗯𝗿𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹𝘀 𝘁𝗼 𝘀𝗲𝗰𝘂𝗿𝗲 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀. Government Partnerships: The collaboration between Paler and Anthropic underscores the trend of integrating advanced AI into sensitive sectors, raising ethical and security considerations. 📈 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗹𝗮𝘂𝗻𝗰𝗵𝗲𝗱 𝗧𝗶𝗻𝘆 𝗧𝗿𝗼𝗼𝗽, 𝗮𝗻 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗮𝗹 𝗣𝘆𝘁𝗵𝗼𝗻 𝗹𝗶𝗯𝗿𝗮𝗿𝘆 𝗳𝗼𝗿 𝘀𝗶𝗺𝘂𝗹𝗮𝘁𝗶𝗻𝗴 𝗮𝗴𝗲𝗻𝘁𝘀. Tiny Troop Initiative: Microsoft’s new project illustrates a creative approach to agent-based simulations, paving the way for future AI-driven interactive experiences. 📊 𝗧𝗦𝗠𝗖 𝗶𝘀 𝗿𝗲𝘀𝘁𝗿𝗶𝗰𝘁𝗲𝗱 𝗳𝗿𝗼𝗺 𝗺𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗰𝗵𝗶𝗽𝘀 𝗼𝘂𝘁𝘀𝗶𝗱𝗲 𝗧𝗮𝗶𝘄𝗮𝗻, 𝗶𝗺𝗽𝗮𝗰𝘁𝗶𝗻𝗴 𝗰𝗵𝗶𝗽 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻. Chip Manufacturing Restrictions: TSMC’s limitations on chip production outside of Taiwan could exacerbate global tech tensions, impacting supply chains and innovation. 🦾 𝗡𝗲𝘄 𝗮𝗱𝘃𝗮𝗻𝗰𝗲𝘀 𝗶𝗻 𝗿𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝘀𝗵𝗼𝘄𝗰𝗮𝘀𝗲𝗱 𝗮𝗴𝗶𝗹𝗶𝘁𝘆 𝗮𝗻𝗱 𝗮𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗶𝗻 𝗮 𝗖𝗵𝗶𝗻𝗲𝘀𝗲 𝗿𝗼𝗯𝗼𝘁 𝗱𝗲𝗺𝗼. Robotics Advancements: The demo of a highly agile robot reflects significant progress in robotics, suggesting future applications in various industries and daily life. ♻️ If you have found this post insightful - share it with your network ♻️

AI is on the brink of making unprecedented scientific discoveries, potentially leading to an “intelligence explosion” and transforming society. There is a recently published paper by Aidan Toner-Rodgers from MIT - here is why it is important.: 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 & 𝗞𝗲𝘆 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 🤖 𝗔𝗜 𝗰𝗮𝗻 𝗺𝗮𝗸𝗲 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝗶𝗲𝘀, 𝗮𝗱𝘃𝗮𝗻𝗰𝗶𝗻𝗴 𝗼𝘂𝗿 𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗼𝗳 𝗺𝗮𝘁𝗲𝗿𝗶𝗮𝗹𝘀 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝗼𝘂𝗻𝗱𝘀. AI’s Role in Science: AI’s capability to generate novel ideas and test them could revolutionize scientific discovery processes, making them far more efficient. This shift could lead to breakthroughs in fields previously limited by human capabilities. 📄 𝗠𝗜𝗧’𝘀 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝘀𝗵𝗼𝘄𝘀 𝗔𝗜 𝗮𝗶𝗱𝘀 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 𝗶𝗻 𝗶𝗱𝗲𝗮 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝘁𝗲𝘀𝘁𝗶𝗻𝗴, 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗶𝗻𝗴 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆. Productivity Boost: Research indicates that AI can automate significant portions of the research process, enabling researchers to focus on testing and innovation, which could dramatically enhance output and innovation rates. 📈 𝗔𝗜-𝗮𝘀𝘀𝗶𝘀𝘁𝗲𝗱 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 𝗶𝗻 𝟰𝟰% 𝗺𝗼𝗿𝗲 𝗺𝗮𝘁𝗲𝗿𝗶𝗮𝗹𝘀 𝗱𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝗲𝗱 𝗮𝗻𝗱 𝗮 𝟯𝟵% 𝗿𝗶𝘀𝗲 𝗶𝗻 𝗽𝗮𝘁𝗲𝗻𝘁 𝗳𝗶𝗹𝗶𝗻𝗴𝘀. Disparity in Benefits: While top researchers see a marked improvement in their work, others may not benefit similarly, highlighting a potential divide in the scientific community’s engagement with AI. 👩‍🔬 𝗧𝗼𝗽 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 𝗯𝗲𝗻𝗲𝗳𝗶𝘁 𝗺𝗼𝘀𝘁, 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲𝗶𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝗻𝗲𝗮𝗿𝗹𝘆 𝗱𝗼𝘂𝗯𝗹𝗶𝗻𝗴 𝗱𝘂𝗲 𝘁𝗼 𝗔𝗜 𝗮𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝗰𝗲. Disparity in Benefits: While top researchers see a marked improvement in their work, others may not benefit similarly, highlighting a potential divide in the scientific community’s engagement with AI. 😟 𝗗𝗲𝘀𝗽𝗶𝘁𝗲 𝗶𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝗱 𝗼𝘂𝘁𝗽𝘂𝘁, 𝟴𝟮% 𝗼𝗳 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀 𝗿𝗲𝗽𝗼𝗿𝘁 𝗿𝗲𝗱𝘂𝗰𝗲𝗱 𝗷𝗼𝗯 𝘀𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 𝗱𝘂𝗲 𝘁𝗼 𝗰𝗿𝗲𝗮𝘁𝗶𝘃𝗶𝘁𝘆 𝗹𝗼𝘀𝘀. Job Satisfaction Concerns: The paradox of increased productivity coupled with decreased job satisfaction raises questions about the future of work in creative fields and the importance of human input in scientific discovery. 🚀 𝗔𝗜 𝗺𝗮𝘆 𝗹𝗲𝗮𝗱 𝘁𝗼 𝗿𝗲𝗰𝘂𝗿𝘀𝗶𝘃𝗲 𝘀𝗲𝗹𝗳-𝗶𝗺𝗽𝗿𝗼𝘃𝗲𝗺𝗲𝗻𝘁, 𝗽𝘂𝘀𝗵𝗶𝗻𝗴 𝘂𝘀 𝘁𝗼𝘄𝗮𝗿𝗱 𝗮𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝘀𝘂𝗽𝗲𝗿𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲. Path to Superintelligence: The recursive self-improvement capabilities of AI may lead to an intelligence explosion, suggesting that AI could soon surpass human intelligence in various domains, fundamentally altering our understanding of intelligence.

Before I get to the issues realted to AI incest, I will explain what I mean with that. "AI incest" is a situation where new AI models are trained on outputs from other AI models instead of fresh, human-created data. This recycling of AI-generated content creates a feedback loop, potentially degrading quality over time. This could result for example in fake news from one AI being confirmed by another AI as they relate to each other. My general recommendations in order to prevent this: 1. Prioritize Human-Created Data: Ensure that training datasets are refreshed with human-generated content. 2. Limit AI Outputs in Training Sets: Minimize reliance on AI-generated data in new AI model training. 3. Audit and Filter Training Data: Regularly check for AI-generated content in datasets to maintain data diversity and accuracy. This point would also create new jobs again. What are your thoughts on this subject?