SAI Conferences’ Post

My Take on AI Technology Trends, Scaling Laws, Metacognition: read full article on Medium, https://lnkd.in/eXrQx_XQ And GPT-4o generated summary of my article here: 🚀 Excited for AI's Future, Advocating for Responsible AI 🌍 I’m optimistic about AI's continued technical developments over the next decade and beyond. At the same time, I firmly advocate for Responsible AI. We need better guardrails and respect for copyrights, especially for human-created content. 📜 🧠 Leopold Aschenbrenner's Insight: Leopold contends GPT-4 is as intelligent as a smart high schooler for most tasks. He believes unhobbling the models will unlock latent capabilities, predicting that by 2027, GPT will perform at the level of an AI researcher/engineer, driven by scaling laws. 📈 🔍 Gary Marcus on Scaling Laws: Gary highlighted Bill Gates' prediction that scaling laws will hold for two more iterations, reaching intelligent AI researchers by 2026 and surpassing human intelligence in specific tasks by 2029. If scaling laws phase out, it could benefit the global carbon footprint, but quantum computing may extend these laws post-2030. ⚛️🌱 🛠️ Skeptics and Future Data: In their AI Snake Oil blog, Arvind Narayan and Sayash Kapoor express skepticism about scaling laws due to potential data shortages. However, I believe integrating large language and multimodal models with robots will provide new data from the physical world, leading to significant AI advancements. 🤖🌐 💡 AI Hype and Reality: The AI hype cycle is real in venture capital funding. While current AI excels in narrow tasks, it lacks human-level general intelligence and reflection abilities. Meta-cognition may evolve as an emergent property, similar to human consciousness. 🧩🧬 Let’s push for Responsible AI while embracing its potential! 🌟 #AI #ResponsibleAI #FutureTech #Innovation #womeninai #llms

Enhancing AI Efficiency with Chunking 💥💥 GET FULL SOURCE CODE AT THIS LINK 👇👇 👉 https://lnkd.in/dXxK-9m3 Chunking is a fundamental technique in artificial intelligence (AI) aimed at improving the efficiency of machine learning models. By dividing complex tasks into smaller, manageable chunks, AI systems can learn faster, reduce errors, and scale better. In this video, we'll delve into the concept of chunking and its applications in AI, exploring how it can be used to enhance efficiency in various domains. Chunking enables AI models to focus on specific tasks, reducing the complexity and improving the accuracy of predictions. This technique is particularly useful in natural language processing, computer vision, and expert systems. By breaking down tasks into smaller chunks, AI models can learn from smaller datasets, reduce overfitting, and improve generalization. Chunking also has implications for AI architecture design. It suggests that AI systems should be designed with modularity and scalability in mind, allowing for easy integration of new modules and adaptation to changing requirements. Additional Resources: * "Chunking in Machine Learning: A Review" by A. K. Mishra et al. * "Chunking in Natural Language Processing: A Survey" by Y. Liu et al. * "Modularizing AI: A Guide to Chunking in AI Systems" by M. A. Smith et al. #stem #ArtificialIntelligence #MachineLearning #Chunking #AIefficiency #NaturalLanguageProcessing #ComputerVision #ExpertSystems Find this and all other slideshows for free on our website: https://lnkd.in/dXxK-9m3 #stem #ArtificialIntelligence #MachineLearning #Chunking #AIefficiency #NaturalLanguageProcessing #ComputerVision #ExpertSystems https://lnkd.in/dTiA2Psf

Everyday there is an innovation in AI technology. What we are experiencing is a clear evidence that soon the game will be changed

We Are Probably Creating Machines We Can’t Control: But we are dumbed laughing about how GPT cannot count the number of “r”s in the word strawberry. Continue reading on Generative AI » #genai #generativeai #ai

The Pulse on AI - CSPARNELL Sam Altman's Bold Vision for AI's Future: Insights from Stanford Q&A In a recent and stirring Q&A session at Stanford University, OpenAI CEO Sam Altman offered profound insights into the future trajectory of artificial intelligence development, particularly discussing the upcoming GPT-5, the pursuit of Artificial General Intelligence (AGI), and the strategic importance of compute power. Altman's candid reflections on the current state and the ambitious future of AI technologies give us a peek into the evolving landscape of AI. What did Sam Altman say? Altman described the current GPT-4 as "mildly embarrassing at best," hinting at its limitations and setting the stage for its successor, GPT-5, which he suggests will significantly outperform previous models. His remarks underscore the rapid pace of improvement in AI technologies, where each iteration aims to be substantially smarter than the last. Why is this important? Altman's disregard for the financial cost—whether "500M or 50B a year"—as long as it contributes to the AGI mission, underscores a bold and singular commitment to advancing AI technology. This approach highlights a vision where financial inputs are viewed purely as fuel for innovation and breakthroughs. Impact on society Altman also emphasized the importance of global access to compute resources, aligning with OpenAI’s mission to democratize AI benefits. Making advanced AI models like ChatGPT free for widespread use is not just a technical achievement but a societal commitment, aiming to empower as many users as possible across the globe. Practical applications today and tomorrow Today, Altman’s vision manifests in increasing the accessibility of AI tools, enhancing user engagement, and promoting ethical AI usage. In the future, these advancements will likely lead to more robust, universally accessible AI platforms that could revolutionize industries and everyday life, bridging the gap between advanced technology and global users. Conclusion Sam Altman’s discussion at Stanford, filled with frank admissions and visionary projections, not only sets a high bar for the next versions of AI but also reiterates OpenAI’s commitment to ethical, powerful, and universally beneficial AI development. As we look forward to GPT-5 and beyond, the potential for transformative impacts on society and individual lives appears both immense and imminent. #SamAltman #OpenAI #GPT5 #AIForEveryone #FutureOfAI #StanfordTalk #AGI

Learn about all things GenAI in this Federal News Network AI & Data Exchange Interview with #GuidehouseExpert Bassel Haidar. In this session, Bassel dives into the cutting-edge machine learning algorithms behind ChatGPT-4 and other AI applications, the evolution of large language models (#LLM), mitigating and reducing AI bias with good governance models, and more. Listen in: https://lnkd.in/eMiReYuJ #GenerativeAI #GenAI #ArtificialIntelligence #Data #MachineLearning #AIBias #AIGovernance #ChatGPT #ERM #RiskManagement #DataAnalytics #DataGovernance

Generative AI represents a revolutionary shift in computing, allowing machines to generate creative, original content rather than just classify data. Large language models like GPT-3 are trained on massive datasets to predict sequences of words, gaining an understanding of language and concepts. Though imperfect, they can communicate, problem-solve, and complete intellectual tasks previously only possible for humans. This exponential progress means generative AI will impact every person and company. Adopting a balanced, opportunity-focused mindset is key to thriving versus just surviving this change. View AI as a collaborative tool - a genius but quirky colleague. Effective human + AI combinations outperform either alone. Prompt engineering is an essential skill - providing context and iterating based on results. Autonomous AI agents represent the next frontier, accomplishing high-level goals with minimal oversight. Mastering this technology requires moving beyond hype to practical application. Understand capabilities, limitations, and use cases. Experiment actively, incorporating AI into daily work to unlock new potential. View it not as a threat, but as an opportunity to augment human intelligence if harnessed responsibly. The future is human and AI together - with careful, ethical human oversight shaping how this technology develops. Generative AI represents a massive opportunity to augment human abilities if harnessed ethically through prompt engineering, practical application, and responsible oversight. #generativeai #ai #gpt #llm https://lnkd.in/gYZBpmwb

Had the pleasure of attending ‘Can we trust AI?’, the second lecture by The Alan Turing Institute and Knowledge Quarter, presented by Abeba Birhane. This insightful session unpacked the biases in data 📊 that impact AI systems 🤖 and how they can lead to unfair outcomes in our lives. I now feel better equipped to ask critical questions about AI technologies and understand the importance of rigorous testing and accountability in shaping a fairer future for all. 🙋🏻#AI #EthicsInAI #DataBias #TechForGood

Top Tip - AI is bigger than machine learning too !

Here is a great video link explaining Gen AI. Many non-tech industry colleagues are asking what does AI mean and what is Generative AI, even though there is huge success of Open AI's Chat GPT, which in my view, democratized the underpinnings of AI/machine and made it mainstream. I recently explained to a friend who in an attorney in how they can make their legal firm data , augmented with ties in public information to improve research, results, drafts, & opinions by simply having their data "read" and analyzed. Ultimately this could be their own private, specialized vertical "LLM" for them to use and using both structured and unstructured data (think legal notes read by OCR). I am currently assisting companies in health, video games, and other areas and the currency is gaining momentum and working in many use cases such as Lovelace AI and CIPRA.ai. Three years ago I used to have a slide on AI in my power point and often there would be this "deers in a headlight look", thus I took it out for many audiences. Now the opposite is true. The beauty of technology. Also keep in mind predictive AI (the main AI before GenAI) is getting stronger with better data sets. #embraceai https://lnkd.in/gjJpqZ8x