Muhammad Sajid’s Post

This course gave me a better understanding of Artificial intelligence. You can check it out.

2024 Reading List: 5 Essential Reads on Artificial Intelligence

"[Proposal] Visual Boosting in Machine Learning with Human-in-the-Loop" Written by: Alice Williams & Boris Kovalerchuk. Proposed for AI Human Computer Interfaces 2025. Contributions: Visual solution to the 2003 Gödel Prize problem of AdaBoost classifier, by visual observation of options for different classifiers before selecting them for boosting, allowing alternative ways to build stronger classifiers, including directly building classifiers in a lossless visualization space. Continued experiments are looking promising! 🤞 Hoping for the best for the manuscripts acceptance.

"A key step is embracing the difference and utility of machine systems. Instead of focusing on the race to “artificial general intelligence”, we can focus on the unique strengths of the systems we have built – for example, the enormous creative capacity of image models. Shifting the conversation from automation to augmentation is also important. Rather than pitting humans against machines, let’s focus on how AI can assist and augment human capabilities." – Sandra Peter, Director of Sydney Executive Plus, University of Sydney Full article > https://lnkd.in/eY3EUfxt

𝐀𝐝𝐝𝐢𝐧𝐠 𝐜𝐨𝐧𝐭𝐞𝐱𝐭 𝐭𝐨 𝐮𝐬𝐞𝐫 𝐪𝐮𝐞𝐫𝐢𝐞𝐬 𝐢𝐬 𝐜𝐫𝐮𝐜𝐢𝐚𝐥 in our journey to minimize 𝐟𝐚𝐥𝐬𝐞 𝐩𝐨𝐬𝐢𝐭𝐢𝐯𝐞𝐬, 𝐰𝐡𝐢𝐜𝐡 𝐚𝐫𝐞 𝐧𝐨𝐰 𝐜𝐨𝐦𝐦𝐨𝐧𝐥𝐲 𝐫𝐞𝐟𝐞𝐫𝐫𝐞𝐝 𝐭𝐨 𝐚𝐬 "𝐡𝐚𝐥𝐥𝐮𝐜𝐢𝐧𝐚𝐭𝐢𝐨𝐧𝐬" 𝐢𝐧 𝐭𝐡𝐞 𝐰𝐨𝐫𝐥𝐝 𝐨𝐟 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈. . 𝐓𝐡𝐞 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥 𝐀𝐮𝐠𝐦𝐞𝐧𝐭𝐞𝐝 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐭𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞 has aptly recognized this need, marking a significant step forward in building Generative AI applications. 𝐈𝐧 2016, 𝐰𝐞 𝐞𝐦𝐛𝐚𝐫𝐤𝐞𝐝 𝐨𝐧 𝐚 𝐬𝐢𝐦𝐢𝐥𝐚𝐫 𝐞𝐱𝐩𝐥𝐨𝐫𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡𝐢𝐧 𝐭𝐡𝐞 𝐫𝐞𝐚𝐥𝐦 𝐨𝐟 𝐜𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐯𝐢𝐬𝐢𝐨𝐧, 𝐚𝐬 𝐝𝐞𝐭𝐚𝐢𝐥𝐞𝐝 𝐢𝐧 𝐨𝐧𝐞 𝐨𝐟 𝐨𝐮𝐫 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐩𝐚𝐩𝐞𝐫𝐬 𝐩𝐮𝐛𝐥𝐢𝐬𝐡𝐞𝐝 𝐰𝐢𝐭𝐡 Hindawi Publishing. 𝐈𝐧 𝐭𝐡𝐢𝐬 𝐩𝐚𝐩𝐞𝐫, 𝐰𝐞 𝐝𝐞𝐥𝐯𝐞𝐝 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐢𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐜𝐞 𝐨𝐟 𝐜𝐨𝐧𝐭𝐞𝐱𝐭𝐮𝐚𝐥𝐢𝐳𝐢𝐧𝐠 𝐮𝐬𝐞𝐫 𝐪𝐮𝐞𝐫𝐢𝐞𝐬 𝐰𝐢𝐭𝐡 𝐢𝐦𝐚𝐠𝐞 𝐝𝐚𝐭𝐚 𝐟𝐨𝐫 𝐜𝐨𝐧𝐭𝐞𝐧𝐭-𝐛𝐚𝐬𝐞𝐝 𝐢𝐦𝐚𝐠𝐞 𝐫𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥. Our approach involved classifying image queries based on their content and directing them to the relevant class. By doing so, we narrowed down the search scope, reducing false positives and improving precision. This methodical approach was meticulously detailed in our research article. 𝐅𝐨𝐫 𝐭𝐡𝐨𝐬𝐞 𝐢𝐧𝐭𝐞𝐫𝐞𝐬𝐭𝐞𝐝 𝐢𝐧 𝐞𝐱𝐩𝐥𝐨𝐫𝐢𝐧𝐠 𝐭𝐡𝐢𝐬 𝐟𝐮𝐫𝐭𝐡𝐞𝐫, 𝐭𝐡𝐞 𝐟𝐮𝐥𝐥 𝐚𝐫𝐭𝐢𝐜𝐥𝐞 𝐢𝐬 𝐚𝐯𝐚𝐢𝐥𝐚𝐛𝐥𝐞 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐭𝐡𝐞 𝐟𝐨𝐥𝐥𝐨𝐰𝐢𝐧𝐠 𝐥𝐢𝐧𝐤. https://lnkd.in/dCG3BgBx #artificialintelligence #computervision #generatieveai #hallucination #precision #imagerecognition #informationtechnology #researchimpact #researchers #researchdevelopment

2024 Reading List: 5 Essential Reads on Artificial Intelligence

For those of you who asked for a larger font view of The MAD - Machine Learning, AI, and Data Landscape 2024 - from FirstMark Capital, this link is even better and takes you to an interactive map. https://mad.firstmark.com/

In this post, we’re going to attempt to draw the fine line between the two seemingly competing technologies which are ArtificiaI Intelligence and Machine Learning.

Fine-tuning models is crucial for leveraging AI effectively. This Predibase article breaks down the process, benefits, and best practices of fine-tuning, highlighting how it enhances model performance and adaptability across various applications. Essential reading for those aiming to optimise their AI strategies. #AI #MachineLearning #AITuning #ModelOptimisation #TechInnovation #AIstrategy

Francois Chollet: OpenAI has set back the progress towards AGI by 5-10 years because frontier research is no longer being published and LLMs are an offramp on the path to AGI. ↓ Are you technical? Check out https://AlphaSignal.ai to get a weekly summary of the top trending models, repos and papers in AI. Read by 180,000+ engineers and researchers.