Taken from “An Introduction To Computer Networks”

Synchronicity 2025/12/30 In my online library was deleting book previews from my archive. Decided to delete one of the 1st non-fiction AI books I previewed. The next day my favourite Machine Learning podcast does a 4-hour interview with the author of the book on the book.

Taken from ‘Mathematics for Computer Science’ by E Lehman, F Leighton and A Meyer

After the Digital Age comes the Cybernetic Age. Not man using machines, but man coupled to them. Biological cognition and artificial intelligence merge into a single feedback system. A new modified cog in the ongoing complex perpectual motion of Life.

Money is a technological tool not to eat, build, drive or fly with. It is a tool used to save & spend time and energy enabling human & machine coordination at massive scales. Thoughts inspired by @jack mallers

What am I looking forward to most in 2026? The combined culmination of innovative & disruptive forces pushed forward by emerging technologies.

ChatGPT drew a pixelated image of my 2025😊

Journal entry 2025/12/30 Feedback report from ChatGPT regarding my chatting style🫶

‘Struggling is good for the soul.’ -Lex Fridman on solving problems

‘Whenever trying to understand technology,we put our own subjective human bias into it. It’s a problem because the goal of AI self-supervised learning is that it should learn naturally from the data.We use our own preconceived notions of what this model has learned.’ Thoughts from Ishan Misra on The Lex Fridman podcast. Episode titled: Self-supervised Deep Learning in Computer Vision dated 31/7/2021

Approaching reality through the cognitive lens of mathematics and physics, When pondering ‘Life’ one may come to see death either as a disease to be solved, or as a necessary finitude because it is limitation that allows suffering and suffering that gives meaning its weight.

Knowledge collapses time, annihilates distance and drives marginal cost toward zero. When embedded into technology, it produces structural deflation not by policy, but by physics. The more knowledge we accumulate, the cheaper reality becomes. Taken from The Infinite Alphabet: And the Laws of Knowledge by Prof César Hidalgo

“Like the uniqueness of snowflakes and fingerprints, knowledge is one of the more nuanced concepts in our world. It is not a thing, but an infinite alphabet. An ever-growing tapestry of unique ideas, experiences, and received wisdom.” Prof César Hidalgo

Taken from 𝕏 account ‘Learn Something’

‘Humans feel an attraction to objects (organic or artificial) that we’ve imbued with life or energy. The meaning of life could be to imbue as many objects with that life force as possible. At a fundamental level that life force is Love.’ Thoughts from Peter Wang on The Lex Fridman Podcast

“We have a world now that's starting to crumble under the weight of aging institutions that no longer even pretend to serve the purposes they were created for. We are creating technologies that are hurtling billions of people headlong into philosophical crises. To survive, you’re going to have to have a pioneer spirit. All of human reality around you is the result of the last few generations of humans agreeing to play certain kinds of games. A lot of those games no longer operate according to the rules they used to.” Peter Wang, one of the most impactful leaders and developers in the Python community. Also a physicist and philosopher.

A reminder.

‘General robots that do many things reliably are still far off but it’s encouraging & great to see more & more robots do one specific task & do it very reliably. Allowing robots to develop in this way is a better & more progressive bottom up approach to robotic development. Thoughts from Ken Goldberg on TIP Infinite Tech Show with host @npub1s5yq...6q7z discussing realistic expectations in the field of modern robotics.

“There's a historical analogy that before the periodic table, before we understood protons and electrons, practitioners of alchemy made real advances but without a principled foundation. Deep learning today may be in a similar position.We have powerful empirical results, but we lack the fundamental theory that would let us derive new architectures rather than just stumbling upon them. Categorical deep learning is an attempt to find that periodic table for neural networks.” Thoughts from The Machine Learning Street Talk podcast

When a critically acclaimed film ends and the credits roll…