Veritasium has a fascinating video on the subject of the completeness, consistency, and decidability of mathematics.

3. The solvability of problems. From the work of Gödel, John von Neumann, and Alan Turing, we know that there are problems that are true, yet cannot be proven so. This is the ultimate limit of mathematics, and so it is also the ultimate limit of artificial intelligence.

Expanding this ability to be capable of reasoning across the entire human lexicon would require immeasurable effort to encode primitives, concept learning, stories, and analogical reasoning. This isn't exactly impossible, just monumentally time-consuming. This is the field of KBAI.

2. The ability to reason. Modern LLMs are not capable of reasoning in the robust way that we do with propositional logic. There are algorithms that are capable of constructing logical proofs, however they must be provided the logical building blocks.

1. The veracity of information. As the adage goes, "garbage in, garbage out". Without mechanisms to ensure the accuracy of information, AI algorithms will flounder in a cycle of learning inaccurate patterns on bad data, producing inaccurate results, publishing said results, and repeating.

You can read all my essays for free on Substack: deconstructivediscovery.substack.com

I aim to continue my analysis of this book. I aim to inform you of the truth about AI and its capabilities. We can avoid the disastrous future that this book hawks. Doing so requires us to be informed and to work for the benefit of others. I hope you’ll join me.

It is a tremendous tool. And like all powerful tools, it can be used for good or for evil. AI can be used to detect cancerous tumors with remarkable precision. It can also hunt down enemy combatants on the frontlines of modern wars.

I find it disheartening that people feel afraid of AI - though I empathize. The truth is that AI isn't anything new. We have had AI for centuries, implemented in other mechanical machines before our moden computers.

I know the relationships are there, but I fear the author's depiction. Such topics deserve the delicate precision of a neurosurgeon's scalpel, not a dull cleaver from the corner market’s butcher.

Still, I find myself lured to read further. The jacket promises an analysis of “the complex relationship between information and truth, bureaucracy and mythology, wisdom and power.”

So if an AI model denies your job application, it’s because a human would’ve denied it too. Thankfully (for the corporate psychopaths), the AI model doesn’t need healthcare and a retirement plan.

AI is anything but alien. Humans design and build every algorithm. Some algorithms call for training (i.e. machine learning). When the algorithm’s aim is to replicate a human’s decisions, humans train the model on human decisions.

I am a machine learning professional. I am also currently enrolled in a master’s program in computer science specifically to study AI. I fumed.

Evidently the author couldn’t withhold their fear-mongering campaign. The anterior flap of the book cover heralds “the age of AI - an alien information network that threatens to annihilate us”.

The New York Times bestselling author bills the book as “a brief history of information networks from the Stone Age to AI”. I expected the neutral, informative voice that is ubiquitous in non-fiction. How wrong was I.

That is why I was so excited to pick up Yuval Noah Harari’s latest book “Nexus”. After reading a few pages, I felt I was witnessing a horrific highway pileup - one tragedy of a paragraph slamming headlong into the next.