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How are you, hacker? 🪐Want to know what's trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. Finance from First Principles By @chateaucapital [ 10 Min read ] Explore the evolution of financial markets from Finance 0....

Perplexity hit the scene just around the same time ChatGPT launched, but is it truly the be-all end-all one would have you believe?

In 1977, a BASIC version of ELIZA published in Creative Computing reached the growing personal computer community, sparking widespread interest in AI. This version, along with the personal computer boom, led to numerous ELIZA knock-offs, while the original MAD-SLIP ELIZA was forgotten until its rediscovery in 2021.

Joseph Weizenbaum created ELIZA as a research platform to study human interaction with AI, not as a true AI itself. However, Bernie Cosell's Lisp version of ELIZA quickly spread through ARPANet, overshadowing the original MAD-SLIP version and leading to a widespread misconception that ELIZA was a Lisp-based AI. This twist ironically highlighted the very misinterpretations Weizenbaum sought to investigate.

ELIZA, often misunderstood as a mere chatbot, was actually designed as a research platform for exploring human-machine communication and interpretation. Weizenbaum’s papers and archives suggest that ELIZA was intended to investigate how humans perceive and interact with AI, rather than serve as an intelligent agent. Despite this, its potential for research was underutilized, focusing more on education than the experimental insights Weizenbaum envisioned.

Interpretation, fundamental to cognitive processes, connects with recursion, lists, and graphs in AI. ELIZA exemplifies how users perceive AI intelligence through interpretation, despite the program's shallow processing. Understanding these connections reveals the illusion of AI intelligence and highlights the essential role of human cognitive processes in interpreting AI behavior.

Interpretation, the process of assigning meaning to experiences, is central to both human cognition and AI. While ELIZA lacked interpretive machinery, the interpretations by human users are crucial. Weizenbaum highlighted the need for improved interpretive capabilities to create more effective conversational AI.

Weizenbaum’s 1962 paper on gomoku highlights his concern about AI's ability to create an illusion of intelligence. He critiques how complex programs can fool users into perceiving intelligence, emphasizing the importance of human interpretation over the technical details of the algorithm.

SLIP, developed by Weizenbaum, built on IPL’s list-processing concepts, aimed at improving AI programming. Lisp, created by McCarthy, simplified and advanced symbolic computation, becoming a foundational AI language.

Newell, Shaw, and Simon’s IPL programming language introduced key AI concepts like list processing and symbolic computing. It led to early AI programs such as the Logic Theorist.

Alan Turing’s Universal Machine and Ada Lovelace's insights into symbolic computing laid the foundation for AI. This legacy influenced early AI projects, including ELIZA.

Weizenbaum built ELIZA as a research tool for human-machine communication, not to simulate psychoanalytic conversations. Its true purpose was later misinterpreted.

Joseph Weizenbaum's ELIZA, often considered the first chatbot, was actually designed for human-machine conversation research. Its accidental fame changed the course of AI history.

Korea Blockchain Week (KBW) 2024 has firmly established itself as one of the most significant events in the global blockchain calendar. As the event unfolded over the first three days, different projects captured the spotlight. Their impactful presence at the conference demonstrated why blockchain is a force to be reckoned with in the digital age.

AI companions are more than just a passing trend; they could become a $150 billion industry by 2030, according to a recent article by Ark Invest.

This article provides a comprehensive overview of blockchain development from a backend developer's perspective. It covers key concepts like decentralization, smart contracts, and the challenges of working with blockchain technology.

Lex Fridman's Roman Empire episode announcement. Elon Musk's "Foundation" on Mars plans. Our future is bright. Right?

In this article, you will learn the basics of authentication and authorization, and how to build a login and logout system using ExpressJS. I have chosen ExpressJS for this tutorial because it is flexible and has an easy learning curve. You will set up your development files, install dependencies and create a Mongo database.

I have recently cleared all interviews for the QAE II position at Amazon. I would like to share about the interview process, expectations, preparation tips and the resources I referred to during my preparation. Most of the information is already present on Web/YouTube. I am giving links to all resources here.

SenseCrypt introduces a first-of-its-kind face-based public key infrastructure (PKI) and electronic identity (eID) solution. SenseCrypt eID utilizes acts of encryption and decryption for registration and authentication, with no public/private keys stored anywhere. This means that even in the event of compromised keys, no biometrics or personally identifiable information (PII) is at risk.

NPM (Node Package Manager) and Bun have been gaining traction in recent years. While both tools share some similarities, they have distinct differences that can impact your development experience. NPM is renowned for its stability and maturity, making it a go-to choice for many developers. Bun aims to provide a faster, more efficient alternative to traditional package managers.

"Swarm is like a living organism that "eats" data, and once it has consumed a certain amount of data, it divides." This article is about the scaling mechanism of Ethereum Swarm, and how it optimizes storage usage through the incentive system and the protocol.

Bitunix ranks as the 13th global exchange on CoinGecko, categorized by trust score on September 2, 2024. This milestone comes on the heels of Bitunix unveiling its reserves through the implementation of Proof of Reserves (PoR), a move that has set a new standard for transparency in the industry.

The incredible growth of AI, particularly since the introduction of ChatGPT, has sparked excitement and apprehension across various sectors. While some view AI as a potential replacement for teachers, others maintain that the unique qualities of human educators remain irreplaceable. This article examines the potential benefits and drawbacks of AI in education, as articulated by experts in the field.