The Future of AI
Overview of Pick and Place Robotics Technology Introduction to the Concept Pick and place robots, the tireless maestros of precision movement, are revolutionizing industries from electronics assembly to pharmaceuticals. But beyond their impressive dexterity, a fascinating world of technology and evolution unfolds. Let’s dive into the diverse types, rich history, and cutting-edge AI integration that … Read more
Last month, The New York Times claimed that tech giants OpenAI and Google have waded into a copyright gray area by transcribing the vast volume of YouTube videos and using that text as additional training data for their AI models despite terms of service that prohibit such efforts and copyright law that the Times argues … Read more
Neural radiance fields (NeRFs) slowly become the next hot topic in the world of Deep Learning. Since they were originally proposed in 2020, there is an explosion of papers as it can be seen from CVPR’s 2022 submissions. Time magazine recently included a variation of NeRFs, called instant graphics neural primitives, in their best inventions … Read more
The complexities of managing and deploying ML infrastructure continue to grow and can indeed be daunting. Some time ago, we shared “A Step-by-step Guide To Setting Up MLflow On The Google Cloud Platform,” which was well-received. However, as time has passed, advancements in technology have offered us the potential to simplify and automate this process … Read more
In a world where time is the most valuable commodity, productivity has become a top priority. We all want to improve our daily routines, streamline chores, and make the most of each minute. Thankfully, advancements in artificial intelligence have birthed innovative solutions, and one such marvel is Yatter AI. This personalized AI chatbot, accessible through … Read more
Evolutionary Computation is under-appreciated. Objections include “Evolution takes millennia” and “I don’t get the point”. They are (or should be) very important to people in the AI community because they are a primitive precursor to intelligence. Understanding Evolutionary Computation (EC) will make understanding LLMs easier. In order to not have to define “AI” again, I … Read more
object(WP_Post)#7552 (24) { [“ID”]=> int(35056) [“post_author”]=> string(2) “36” [“post_date”]=> string(19) “2024-10-10 00:11:13” [“post_date_gmt”]=> string(19) “2024-10-10 00:11:13” [“post_content”]=> string(6835) ” The role –and nature– of news and journalism is constantly evolving, from how it is consumed to which voices are trusted. New platforms, the rise of citizen journalists, and shifting news consumption habits are continuing to … Read more
Photo provided by author The adoption of AI in software development is continuously growing. According to the fresh data from Market.us Scoop, it is expected to reach $287 billion in ten years, with a compound annual growth rate of 21.5%. By the end of 2023, 45% of surveyed developers reported that they use generative AI … Read more
New Trends in AI-RAG and Graphs. I’ve been doing a bit of research on how to improve RAG with graphs. I’m especially interested in augmenting agentic-RAG with the knowledge graph. A while back, Maya @Neo4j wrote a nice article on The Future of AI: Machine Learning and Knowledge Graphs. I think that makes sense to … Read more
In the ever-evolving world of artificial intelligence (AI), large language models have proven instrumental in addressing a wide array of challenges, from automating complex tasks to enhancing decision-making processes. However, scaling these models has also introduced considerable complexities, such as high computational costs, reduced accessibility, and the environmental impact of extensive resource requirements. The enormous … Read more