Glantz’s Post

🌟 Thrilled to announce the publication of my research paper, conducted under the guidance of Dr Anand Kulkarni! 🌟 Our paper introduces the Leader-Advocate-Believer (LAB) algorithm, a novel socio-inspired approach designed to tackle combinatorial optimization challenges, specifically focusing on the 0-1 Knapsack Problem (KP). This NP-hard problem plays a crucial role in resource allocation, logistics, and finance, making our findings particularly impactful. The LAB algorithm draws inspiration from cultural interactions, competitive behaviours, and societal dynamics, offering a fresh perspective on social-inspired algorithms. Our research includes successful implementations across various instances of the 0-1 KP, showcasing its efficacy in solving both Single Knapsack and Multidimensional Knapsack Problems. I invite you to explore the detailed insights and outcomes of our study. Attached below are the first page of our paper and the GitHub link to access our algorithm implementation. 📄 Link to the Paper: https://lnkd.in/d3cwdjGn   💻 Github Link: https://lnkd.in/d9zH9mHc Special thanks to Dr Anand Kulkarni for his invaluable guidance and mentorship throughout this research journey. #SocioInspiredAlgorithm, #GeneticAlgorithm, #ResearchPaper, #KnapsackProblem, #AlgorithmicResearch, #OptimizationMethods, #AIInnovationation

Big Picture Science Radio Show: Fuhgeddaboudit (ENCORE) A thousand years ago, most people didn’t own a single book. The only way to access knowledge was to consult their memory. But technology – from paper to hard drives – has permitted us to free our brains from remembering countless facts. Alphabetization and the simple filing cabinet have helped to systematize and save information we might need someday. But now that we can Google just about any subject, have we lost the ability to memorize information? Does this make our brains better or worse? Listen here: https://buff.ly/3YNfnjX

🛸 🛸 🛸 Greetings earthlings! I'm excited to announce the launch of my third book with Wiley - "LLM-based Solutions: How to Deliver Value with Cost-Effective GenAI Applications" https://lnkd.in/dMia-sXn If you are interested in / or already putting LLMs in production, you'll like reading about the tradeoffs between performance and cost across the GenAI application lifecycle. This book uses a cost optimization lens and explores several topics relevant to GenAI and LLMs, including the foundational technologies powering LLMs and GenAI, the three-layer GenAI stack, scaling laws and customization methods like PEFT, prompt engineering and model optimization techniques, the tug and pull between compact and general-purpose models, advanced approaches for batch tuning and inference optimization, and the important considerations around performance, cost, environmental impact, and building the ideal GenAI team. 🛸 🛸 🛸 (If you read this post until this point, first of all, thanks!) If you're wondering why there's a UFO on the cover 🛸 , I think its one of the coolest covers out there for a GenAI book. But, don't judge this book by its cover, grab your copy today from: Amazon - https://lnkd.in/dG4Dd2f6 Barnes and Noble - https://lnkd.in/dyz8qJ4x Wiley - https://lnkd.in/dSU5_TTf Harvard book store - https://lnkd.in/drArjdU8

Are you spending hours finding citations for your products on google scholar?⏱ Life science product citations are vital for vendors to show to researchers, demonstrating product credibility and enabling them to see if a reagent is right for their experiment. But collecting these citations, as well as experimental annotations and published images, can be challenging. In our new blog, we compare using a manual approach to outsourcing your citation collection ⬇ https://lnkd.in/eVsA9Rmb

'Genesis' looks at the future of artificial intelligence: Former Google CEO and Chairman, Eric Schmidt, joins Morning Joe to discuss his new book 'Genesis: Artificial Intelligence, Hope, and the Human ... http://dlvr.it/TGGZdM

In the era of mobile apps like Blinkit, Zepto and Instamart, the users have an insane array of options . So, the future of marketing delves into predicting the possibility that a user would favor an item suggested by Recommender system. Kudos to Srishti Bokadia Jain for yielding the challenge of researching such a novel domain of marketing and collaborating with Dr. Rushina Singhi to publish on such a versatile title. ASB Amity School of Business, AUUP

Research workflows can be a real challenge. I remember spending countless hours trying to connect the dots between different platforms. It was inefficient and exhausting. I wrote a Medium post explores how Simplifine can simplify this process. https://lnkd.in/dcxBUfZZ

Apples and machine learning – quite an unusual combination, right? Well, take a look for yourself... After a prolonged period of research, we've successfully leveraged machine learning to detect fungus-infected apples. I’m sure you’re curious to see how it works. Check out the paper below, which won the Best Presenter Award at an international conference and is recognized for its potential to make a significant societal impact. Cheers! https://lnkd.in/epYY9Gnt

Google just released Notebook LM for free in Europe, and it’s probably the most useful single-purpose GenAI application I’ve seen. Notebook LM allows you to upload a large number of documents and use GenAI to extract meaning, summarize, and create notes from those documents, making research much more straightforward. It also provides nudges to assist with your research. Notebook LM uses only the uploaded documents as a data source, significantly reducing the risk of hallucination. Additionally, it includes citations beside each point so you can check the source documents if in doubt. In the video below, I show a quick demo where I use Notebook LM to conduct research into the US packaged foods industry. #GoogleNotebookLM #GenAI #ResearchTools #DocumentManagement #AIInResearch 

Welcome to read and share the newly published paper "Closest Farthest Widest". This excellent paper is written by Kenneth Lange Read via: https://lnkd.in/e6qun2dp MDPI University of California, Los Angeles #algorithms