Merge pull request #65 from UCLAIS/blog6

Author: kwabenankyi

blog/2025-01-28-blog-5.md renamed to blog/2025-01-28-ww2-shaping-ai.md

@@ -0,0 +1,38 @@
+---
+slug: first-neural-network
+title: >-
+    The First Neural Network: Foundations of Modern AI
+authors: [rivan]
+tags: [history, neural networks, turing, deep learning]
+---
+Neural networks have shaped the way we interact with the world. From the deep learning technologies behind self-driving cars to the Natural Language Processing enhancements that power intelligent systems, neural networks are at the forefront of modern AI. But to truly appreciate the deep learning applications we use today, it’s important to examine the foundational theories that lay the groundwork for the field. By first looking at what a neural network is and then exploring the concepts underlying McCulloch and Pitts' theoretical neural network design, we can better appreciate the ingenuity of the technology that has transformed modern AI.
+
+### What is a Neural Network?
+A neural network is a computational model inspired by the structure of the brain. Neural networks typically consist of layers of nodes, or artificial neurons—an input layer, one or more hidden layers, and an output layer—connected to each other in a way that mimics the interconnected nature of neurons in the brain. Each node has its own weight and threshold associated with it. If the output of any individual node is above the specified threshold value, it becomes activated, passing information to the next layer. The network "learns" by adjusting the weights of these connections through a process called backpropagation, which minimizes errors over multiple training iterations.
+
+Modern neural networks are complex multi-layered networks capable of solving intricate tasks like image recognition, natural language processing, and autonomous driving. They have had a profound impact on modern technology, revolutionizing and enriching people's lives through their application in solutions ranging from large language models like GPT-4 to advancements in healthcare, such as disease detection and drug discovery.
+
+![How an artificial neural network works: input layer, hidden layers, output layers. (Image source: Facundo Bre)](/img/blog/neural-network-1.png)
+
+### The Turing Machine
+To truly appreciate modern neural networks, it’s important to look at the story of their first theoretical inception. The origins of neural networks are intertwined with the origins of artificial intelligence itself, beginning in Cambridge in 1936, where a mathematician named Alan Turing was quietly laying the foundation for modern AI.
+
+In 1936, Turing was tasked with the *Entscheidungsproblem*, a question posing whether there is an algorithm that can determine the truth or falsity of any statement within a specified system. To prove that no such algorithm exists for sufficiently complex systems, Turing invented a theoretical problem-solving machine called a Turing Machine. A Turing Machine consists of an infinite tape divided into cells, a head that can read and write symbols on the tape, and a set of rules. The machine operates by moving the head along the tape, reading symbols, and following the rules to write new symbols and move left or right, allowing it to simulate any algorithm given to it.
+
+Using this, he answered the *Entscheidungsproblem* by proving that no algorithm can universally decide whether an arbitrary Turing machine will halt or run forever on a given input. This became known as the Halting Problem, which he detailed in his 1936 paper *“On Computable Numbers, with an Application to the Entscheidungsproblem.”* Turing’s insight—that any computable function could be broken down into simple operations through reading and writing symbols on an infinite tape—was a revolutionary idea that sparked the development of all artificial intelligence fields that followed.
+
+![The Universal Turing machine: complete with Turing Machine descriptions, tape, and transitions. (Image source: MIT)](/img/blog/neural-network-2.gif)
+
+### The First Neural Network
+Inspired by Turing’s 1936 paper, Warren McCulloch, a neuroscientist, and Walter Pitts, a logician, published their influential 1943 paper *"A Logical Calculus of the Ideas Immanent in Nervous Activity"* in which they explored how the brain might perform computations. Turing’s paper provided a theoretical basis for thinking of computation in strictly formal terms and had shown that any computable function could be realized by a Turing machine. Pitts and McCulloch saw a parallel between Turing’s machine and the way groups of neurons might process and transmit information.
+
+They proposed that neurons could be modeled as binary on-off units, firing when inputs exceeded a certain threshold (akin to receiving enough excitatory signals). By connecting these idealized neurons in various configurations, they demonstrated that the systems could implement basic logical operators like AND, OR, and NOT. This offered the possibility that these systems might simulate logical operations or even more complex computations. They were the first to describe what later researchers would call a neural network.
+
+![The McCulloch-Pitts Neuron Model. (Image source: available under fair use, Creative Commons)](/img/blog/neural-network-3.png)
+
+Although their model was only theoretical and faced several limitations, their mathematical approach to neural functioning inspired subsequent generations of researchers—paving the way for cybernetics and later the field of artificial intelligence. Their work ultimately shaped the path for modern AI and deep learning, which are now deeply embedded in our everyday lives.
+
+### References
+A. Turing, “On Computable Numbers, with an Application to the Entscheidungsproblem,” 1936. Available: https://www.cs.virginia.edu/~robins/Turing_Paper_1936.pdf.
+
+W. S. Mcculloch and W. Pitts, “A LOGICAL CALCULUS OF THE IDEAS IMMANENT IN NERVOUS ACTIVITY*,” Bulletin of Mathematical Biology, vol. 52, no. 2, pp. 99–115, 1943, Available: https://www.cs.cmu.edu/~./epxing/Class/10715/reading/McCulloch.and.Pitts.pdf.

blog/2025-03-02-first-neural-network.md

@@ -0,0 +1,31 @@
+---
+slug: undead-internet
+title: The Undead Internet
+authors: [anthony]
+tags: [internet, bots, social media, dead internet theory]
+---
+
+*"They look like people, they act like people, but there are no people left. Well, there's you and maybe a few others, but you can't tell the difference, because the bots wear a million masks."* - Robert Mariani, The Dead Internet to Come.
+
+Bots are everywhere on the Internet. I’m sure you’ve noticed them selling concert tickets in your WhatsApp chats, popping up on customer support websites, replying to your tweets (X posts now?) with ostensibly human-like parlance. They don’t seem to be going anywhere, and that’s a problem.
+
+Take the social media platform X. The [number of botted accounts on there has exploded since the October 2022 buyout by Elon Musk](https://mashable.com/article/x-twitter-elon-musk-bots-fake-traffic), despite his promises to eliminate them. And they’re smarter than ever now. No more hashtag spamming and non sequiturs. They’re contributing to legitimate conversations, [(not always with good intentions)](https://globalwitness.org/en/campaigns/digital-threats/no-ifs-many-bots-partisan-bot-like-accounts-continue-to-amplify-divisive-content-on-x-generating-over-4-billion-views-since-the-uk-general-election-was-called/), garnering interactions and attention from humans and other bots alike. ChatGPT was its printing press.
+
+One social media platform wouldn’t be a big issue. But generative AI (genAI) results [on Pinterest](https://futurism.com/pinterest-ai-slop) too? Fake true crime documentaries on YouTube? Strange image search results? [Then even sports journalism?](https://futurism.com/sports-illustrated-ai-generated-writers)
+
+Doctor Who fans reading this blog may recall the second episode of its 2005 reboot, in which the Ninth Doctor and Rose Tyler visit the Earth minutes before it is due to be engulfed by the red giant Sun. On their space station, the “Last Human” attempts to pull off an insurance scam by arresting the ship with robotic spiders, hidden in gifts offered by her servient robots, the Adherents of the Repeated Meme. (By the way, the “Last Human” is really a 2000-year-old skin graft and was granted that name based on being the last born of two full humans, around 5 billion years into the future.)
+
+Mapped literally, we already see internet entertainment such as memes heading this direction. Of course, let people enjoy things…
+
+…but I do find it interesting how easy it is for meta-posting and “brainrot” to spread as far as mainstream culture. The jokes are easy to make – in fact, the joke is the fact that it’s a joke, by some tautology. Give a model a database of viral tweets, common tropes, some Druski and LeBron gifs, and you’ll probably be looking at a 100k-like TikTok post in a few hours. A personal favourite of mine has got to be @multimedia2012. Whether or not that account steal posts from X and Facebook then packages it up a genAI video of that scenario, its TikToks are unfortunately quite funny.
+
+Back to the bigger picture. I see that episode’s parallels in how actual human users employ genAI. Churning out such content further pollutes the sea of information noise that is the modern Internet, making it substantially more difficult to fish out unique content. And to reiterate the common point, you are damaging creative integrity, especially if used where the human touch is expected.
+
+The honest, carefree Internet as we knew it is dead. Yet, we, out of ignorance or insanity, have replaced the robots that killed it by creating freakish cyborg-zombies from what we once despised.
+
+As the phrase goes, the only thing worse than flogging a dead horse is betting on one. There doesn’t seem to be anyone left to stop us going all-in.
+
+### Further reading
+R. Mariani, “The Dead Internet to Come,” The New Atlantis, vol. 73, no. 73, pp. 34–42, 2023, doi: https://doi.org/10.2307/27244117.
+
+A. Hern, “TechScape: On the internet, where does the line between person end and bot begin?,” The Guardian, Apr. 30, 2024. Available: https://www.theguardian.com/technology/2024/apr/30/techscape-artificial-intelligence-bots-dead-internet-theory

blog/2025-03-07-undead-internet.md

@@ -27,4 +27,9 @@ anthony:
 sofiya:
   name: Sofiya Flenova
   title: Content Executive
-  image_url: /img/committee/sofiya_flenova.jpeg
+  image_url: /img/committee/sofiya_flenova.jpeg
+
+rivan:
+  name: Rivan Chanian
+  title: Content Executive
+  image_url: /img/committee/rivan_chanian.jpg