Justin Johns’ Post

Contrary to popular belief, AI isn't a magical problem-solver. It requires meticulous design and human guidance to tackle specific issues effectively. Problem definition plays a pivotal role in shaping AI solutions, emphasizing the need for precise delineation. Dive into the world of AI and uncover the truth behind its potential through this article https://ow.ly/T71x50QxRBH

In his blog post, Ivan Kozić delves into the topic of developers versus AI. Will artificial intelligence ever replace human developers? 🤖 Modern tools for automation and code generation are becoming increasingly sophisticated, capable of analyzing data, predicting behavior, and even creating new algorithms. On the other hand, humans are irreplaceable in their ability for creativity, understanding context, and solving complex problems. https://lnkd.in/d8rka7i3.. #ai #artificialintelligence #developer #softwaredeveloper

The AI and GenAI Explosion And yes, it is an explosion. So much so that the UK market research and insights industry is not keeping pace. Highly skilled individuals are needed in market research, and a third of researchers are outsourcing to find them. But let’s face it, after a decade of deploying machine learning, we would expect to see some of the best examples of AI-in-business to emerge from the data-busting market research sector. It is crucial to the industry. Current volatility paradoxically causes companies to want more information than ever to navigate an uncertain world. They want to anticipate market shifts, not just respond to them. They want to be aware of any fleeting gaps of opportunity in their market before their competitors jump in. 62% of researchers across 14 industries globally agree that their company now depends significantly on market research and insights. Tech Solutions: The AI systems most of us know are where machine or software systems make autonomous decisions normally requiring human intelligence. It acts, creates, evolves, or changes. While AI-powered tools are ever advancing in terms of speed, traditional market research is slow and unreliable. AI can identify trends faster than humans but still needs the human touch. It can take over the repetitive and tedious tasks, and frees up the market researcher’s time to add strategic value to initial insights. The time-saver means AI can also help bridge the skills gap, freeing researchers to upskill and train teams. AI is primarily for automation and improved efficiency. GenAI is the gamechanger. It is able to produce new content (text, images, audio, synthetic data or other media and computer code) based upon input training data, in response to prompts. Unlike previous deep learning models, Gen AI can process extremely large and varied sets of unstructured data, and multi-task. Large Language Models (LLMs) fall under its broad concept. They more specifically process huge amounts of existing information to understand, summarise, generate and predict new content. LLMs include Chat GPT, Bard, MetaAI, Meet Claude, GitHub Copilot and Stable Diffusion. They are distinguished by their ability to have a conversation with a user. Some would argue that GenAI’s automated AI predecessor has simply provided cheaper, faster research results at the cost of quality. But GenAI is starting to revolutionise the market research industry. Not only does it deliver faster and cheaper, but it can deliver better insights. What are your thoughts?

Google Working on Software for Reasoning AI: A Leap Toward Smarter Machines #Google is pushing the boundaries of #artificialintelligence (AI) once again with its latest initiative: the development of software aimed at enhancing reasoning AI. Unlike traditional #AI systems that rely on patterns in vast datasets, reasoning AI focuses on emulating the logical thinking and problem-solving capabilities of the #human mind. This #ambitious project aims to enable #AI systems to reason through complex problems, understand abstract concepts, and make #decisions based on #deeper #cognitive #processes. https://lnkd.in/dyty-qSp

Exploring the Impact of Retrieval-Augmented Generation (RAG) in AI. In the realm of artificial intelligence, the integration of retrieval-augmented generation (RAG) marks a pivotal shift towards more informed and contextually relevant AI models. By harnessing a diverse array of data sources, RAG empowers AI tools to provide insights that mirror the most current information and align with organizational knowledge bases. For enterprises, this translates to AI evolving from a static entity to a dynamic ally, capable of expanding alongside your data trove. The potential for heightened efficiency and spurred innovation is substantial. Have you pondered the implications of RAG for your AI initiatives? What are your views on the interplay between model training and the incorporation of real-time data to enhance AI responsiveness? Join the conversation on how AI customization is shaping our industries. Discover the role of RAG in revolutionizing AI: https://lnkd.in/dVRWPKd8 -- 👋 I’m Andrew, strategic thinker and digital innovator 💡 I offer insights and strategies on essential technologies, helping businesses adopt innovations for growth and a competitive edge. Loved what you’ve read? Craving more? Here’s how to stay in the loop: 🔔 Swing by my profile, hit that follow button, and turn on notifications for my channels so you’re always in the know. ❤️ Show some love with a like, drop a comment, and share your thoughts on what tech means to you and your organisation. #AI #MachineLearning #DataScience #Innovation #RAG

How do LLMs work, what is RAG, what is fine-tuning, how can I leverage it for my industry? In this blog below, I simplify these concepts to the best of my ability. Read if you are looking to enter the space... 👇 Why did I spend my Holi weekend writing this? I regularly speak with professionals across various industries. Many find the concepts of AI and LLMs too complex to understand, let alone deploy. I have realized that a big reason for that is all content around AI is way too technical, and doesn't focus on actual end applications. Lots of jargon and keywords create a barrier to adoption. In this blog, I've made a concerted effort to simplify these concepts and cut through the jargon. At Superteams.ai, our goal is to help industry insiders recognize the value of AI and leverage it for a competitive advantage. AI represents a Kodak moment for many industries; the sooner you adopt it, the greater your leverage will be in the long run. Please note - in writing this article, I've intentionally taken a few liberties with technical definitions to keep the explanation lucid and clear. #LLM #GenAI #enterprise

𝐂𝐮𝐫𝐢𝐨𝐮𝐬 𝐀𝐛𝐨𝐮𝐭 𝐀𝐈? 𝐇𝐞𝐫𝐞 𝐀𝐫𝐞 𝟏𝟎 𝐁𝐨𝐨𝐤𝐬 𝐭𝐨 𝐂𝐨𝐧𝐬𝐢𝐝𝐞𝐫: 1. Superintelligence by Nick Bostrom This book dives deep into the future of artificial intelligence. Lessons: • Understand the potential risks of AI • Explore the paths to safe AI development 2. Human Compatible by Stuart Russell A guide to creating AI that aligns with human values. Lessons: • Learn the principles of beneficial AI • Discover strategies to ensure AI safety 3. Life 3.0 by Max Tegmark A visionary look at the impact of AI on our future. Lessons: • Explore the concept of Life 3.0 • Understand the societal implications of AI 4. Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell An accessible introduction to AI for everyone. Lessons: • Grasp the basics of AI • Learn about the current state and future of AI 5. AI Superpowers by Kai-Fu Lee A look at how China and Silicon Valley are shaping the AI race. Lessons: • Understand the global AI landscape • Learn about the economic impact of AI 6. Prediction Machines by Ajay Agrawal, Joshua Gans, and Avi Goldfarb How AI is transforming business decision-making. Lessons: • Learn how AI predicts outcomes • Discover the business applications of AI 7. The Master Algorithm by Pedro Domingos A quest for the ultimate learning machine. Lessons: • Understand the five tribes of machine learning • Explore the potential of a unified algorithm 8. Machine, Platform, Crowd by Andrew McAfee and Erik Brynjolfsson A look at the intersection of AI, platforms, and crowdsourcing. Lessons: • Learn about the shift from products to platforms • Discover the power of the crowd in the AI era 9. The Fourth Industrial Revolution by Klaus Schwab A guide to understanding the changes brought by AI and other technologies. Lessons: • Understand the impact of AI on industries • Learn about the societal changes driven by AI 10. Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville The definitive textbook on deep learning. Lessons: • Grasp the fundamentals of deep learning • Learn about the latest advancements in AI research If you've read any of these, share your insights in the comments below ⬇️. P.S. Found this valuable? Repost to help others ♻️. And be sure to follow Agnes Goh for more!

Artificial Intelligence (AI) has evolved beyond mere processing of data; it now involves reasoning, decision-making, and problem-solving. One crucial aspect propelling AI into the realm of cognitive prowess is Automated Reasoning. In this blog post, we will embark on a journey into the fascinating world of automated reasoning in artificial intelligence, exploring its foundations, applications, and the transformative impact it brings to the AI landscape

🤖 Tech Talks: Exploring the Latest in AI and Machine Learning 🤖 In technology, few innovations hold as much promise and potential as artificial intelligence (AI) and machine learning (ML). Join us as we embark on a journey to explore the latest advancements, trends, and applications shaping the future of AI and ML. 🌟 Unlocking the Power of AI: From predictive analytics and natural language processing to computer vision and autonomous systems, AI is revolutionizing industries and reshaping how we live, work, and interact with technology. 🧠 Machine Learning in Action: Dive deep into the world of machine learning, where algorithms learn from data, identify patterns, and make intelligent decisions without explicit programming. Discover how ML is powering personalized recommendations, predictive maintenance, and intelligent automation across diverse domains. 🔬 Emerging Trends and Technologies: Stay ahead of the curve with insights into emerging trends and technologies in AI and ML. Explore topics such as federated learning, generative adversarial networks (GANs), and explainable AI, and discover how they're pushing the boundaries of what's possible. 🌐 Ethical AI and Responsible Innovation: As AI evolves, ethical considerations become increasingly important. Explore the ethical implications of AI and ML, from bias and fairness to privacy and transparency, and learn how we can harness the power of AI for positive societal impact. At Pleximus Inc, we're passionate about leveraging AI and ML to drive innovation, solve complex challenges, and unlock new opportunities. By staying at the forefront of AI and ML research and development, we empower our clients to thrive in a rapidly evolving digital landscape. Join the conversation and share your thoughts on the latest trends and developments in AI and ML. What excites you most about the future of artificial intelligence? Let's explore together! #AI #MachineLearning #TechTalks #Innovation #ArtificialIntelligence Image: Gencraftive