Deep Learning – Artificial Intelligence, Computer Science & Mathematics

At Davos. Elon Musk says robot for all humans on Earth- Feasible? What do you want in the future? Tell?

Smart machines or robots, what would you choose? Or would humans work? What do you want? Yes, there would be robots in places like Antarctica, the Arctic, and more. But one robot each for everyone on Earth? Even the poor will have a robot? How would he maintain the robot? Is the battery charging forContinue reading “At Davos. Elon Musk says robot for all humans on Earth- Feasible? What do you want in the future? Tell?”

At Davos. Elon Musk says robot for all humans on Earth- Feasible? What do you want in the future? Tell?

We don’t want a world filled with Robots, but those who exist must be identified as Robots Evolve with Experiences.

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.”

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”

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”