We don’t want a world filled with so many robots, especially humanoid robots that look like humans, that it is difficult to identify who is a robot and who is human. So, then why all these guidelines on robots and in robotics? Well, if they exist, they must be registered with regulations! And if theyContinue reading “We don’t want a world filled with Robots, but those who exist must be identified as Robots Evolve with Experiences.”
Category Archives: llm
Passport and ID Card of Named Robots- The full name and the Surname of Robots and AI models #future #futurist #ai
A robot’s identity card can display its name. This can be used to register the robots as authentic. If a robot from one country is imported into another, it should comply with the new country’s rules and regulations. We must have universal identification for robots in a country. Why do we need identity cards forContinue reading “Passport and ID Card of Named Robots- The full name and the Surname of Robots and AI models #future #futurist #ai”
Certifications for robots or models! Artificial Specialized Intelligence! Why one model fits all?
We live in an era where robotics is taking over many jobs, or, more simply, robotics automation is advancing rapidly. The rate is faster than any construction company could even imagine. What are we constructing? Manufacturing? Or producing? Robots? If so, what are the features of the robots? What kind of features would you wantContinue reading “Certifications for robots or models! Artificial Specialized Intelligence! Why one model fits all?”
We need constraints in Generative AI Models Now
Enough of unconstrained generative AI outputs. It often leads to wrong or harmful outputs. How to make LLM safe? Time for constraints in models. How can constraints help? — — No unintended outputs — — By controlling models, we control the right outputs — — The regularization of gen AI can be done by governmentsContinue reading “We need constraints in Generative AI Models Now”
Unconstrained LLMs, How Long? Safe, secure, and trusted constraint-based LLMs
Note: This is a duplicate copy of original fine with DOI:10.13140/RG.2.2.15511.02722. The pdf can be accessed at, (PDF) Unconstrained LLMs, How Long? Safe, secure, and trusted constraint-based LLMs Abstract: Most LLMs are unconstrained optimization problems (UMP). The problems of hallucinations and dangerous images and texts produced by LLMs persist. How can this problem be solved? WhyContinue reading “Unconstrained LLMs, How Long? Safe, secure, and trusted constraint-based LLMs”
Is Scientific Research with AI Possible? Correct? Is it Valuable? Your inputs and AI Intrigue: Case study: Model for Fuzzy Rough Set-based TW — SVM
Greetings, New year time, let’s see where AI has reached. AI claims a lot, but now, let’s see if AI can generate a research model in tandem with a human intrigue researcher? Let’s see if scientists need to use AI research tools? Would using AI tools by scientists would be for betterment of research? WouldContinue reading “Is Scientific Research with AI Possible? Correct? Is it Valuable? Your inputs and AI Intrigue: Case study: Model for Fuzzy Rough Set-based TW — SVM”
Memory Learning, Model Titans (Behrouz et al, 2024)
“Titans: Learning to memorize at test time. arXiv preprint arXiv:2501.00663” This paper (Behrouz et al, 2024) [1] aims to build a memory learning model that is efficient, uses less memory, and learns and predicts more. Neural learning is the basis of memory-based learning. Forgetting is important too, and too much forgetting can lose essential data about the input.Continue reading “Memory Learning, Model Titans (Behrouz et al, 2024)”
Nested Learning: Part II
#ai #llm #deeplearning #ml Here is the video lecture, subscribe for updates, https://www.youtube.com/watch?v=qDwAm1f0JBY Some concerns, it catches the forgetting behavior of LLMs, the context once gone can be looked into nested memories and hence can be revised if nested parameters and memories are referenced. The pre training can’t be edited but the computation of temporaryContinue reading “Nested Learning: Part II”
Nested Learning- Part I-Associated Memory and Momentum
Here we discuss one of the latest paper in 2025 in AI from Google Research given in [1] reference. The paper is titled, “Nested learning: The illusion of deep learning architectures” and is published in “Neural Information Processing Systems” . The contributors are: Behrouz, A., Razaviyayn, M., Zhong, P., & Mirrokni, V. The Authors suggest thatContinue reading “Nested Learning- Part I-Associated Memory and Momentum”
Can Animals learn from AI? Do we need AI to do it for our pets?
Imagine your pets at home when you are outside in the office? What if you can see them? There are three kinds of learning: supervised, unsupervised, and semi-supervised. AI can teach in any of these modes, if pets are receptive to it. What if an Intelligent Pet AI App on your TV can guide yourContinue reading “Can Animals learn from AI? Do we need AI to do it for our pets?”
Artificial Intelligence, Computer Science & Mathematics 