#Turing Test

The Turing Test, simply and visually explained #ai #artificialintelligence #alanturing #turingtest #tech #technology #techexplained #aiexplained

if you ask me what keeps me up at night, it's thoughts about AI domination 😪 . . . . . . [AI, artificial intelligence, chatgpt, turing test, alan turing, the imitation game, benedic cumberbatch, science, tech] . . . . . . #ai #artificalintelligence #chatgpt #openai #deepseek #turingtest #alanturing #theimitationgame #theimitationgameedit #benedictcumberbatch #science #scifi #technology #tech #explorepage #fyp #reelsi̇nstagram #universityofcalifornia #research

#grok passed the Turing test!

Torque explained. Every Engineer should understand this concept 🧫 . . 🎥 Prof. Walter Lewin . #angularmomentum #torque #physics #engineeringstudents #engineeringprinciples #mechanicalengineeringstudent #electricalengineeringstudent #civilengineeringstudent #engineeringconcepts #dynamics #mechanicaldesign #mechanicalengineering #mechanicalengineer #mechanicalproblems #mechanicaleducation #physicsclass #physicsteacher #physicsmajor #physicslab #physicsfacts #physicslovers #physicslover #physicsisfun #mechanical_engineering #mechanicalproject

CAPTCHA stands for “Completely Automated Public Turing test to tell Computers and Humans Apart.” It’s a security test used online to check whether a user is a real human rather than a bot or automated script. It was created to prevent machines from abusing web services by making them solve tasks that are easy for humans but hard for bots.

How to turn at high speeds The Fastest Maze Solving Competition in the World - Part 6 Written by Tom Lum and @emilylinzhang Produced by Derek Muller, @sciencepetr and @emilylinzhang Hosted by Derek Muller #science #veritasium #physics #engineering #biology #mice #racing #robot

In 1991, we watched two machines have a conversation. At the time, it felt like science fiction. The T-800 and the T-1000 mimicking human voices, bypassing emotion, verifying reality through subtle cues. But look closer this wasn’t just a movie moment. It was one of the first cinematic depictions of AI speaking to AI. No humans in the loop. No passwords. No faces. Just data testing data. Two machines performing their own version of a Turing test. By copying John and Janelle’s voices, they weren’t just communicating — they were authenticating. Confirming identity. Running behavioral prompts disguised as small talk. Thirty-five years ago, Terminator 2 quietly introduced us to something we’re only now beginning to live with: A world where verification happens between algorithms. Where voices can be cloned. Where reality can be negotiated in milliseconds. Back then, it was Skynet. Today, it’s deepfakes. Voice AI. Autonomous systems checking each other before we even realize it’s happening. Terminator 2 wasn’t just about the future of war. It was about the future of truth. And we’ve officially arrived. Follow @mindvalore and start growing today. Elevate your mindset. Dominate your life. 💯 #ai #terminator #future #robots

Debate About Modern AI and the Turing Test Im straight bruh , it's just meme 💀judge Mt karna and kar v loge toh kya hi ho jayega 💀 People often debate what Alan Turing would think about modern AI systems like large language models (LLMs). One side of the argument says that LLMs are not real artificial intelligence. Their reasoning is that these systems mainly learn patterns from huge datasets and generate responses based on probability. They don’t truly understand meaning the way humans do, and they don’t have consciousness or real reasoning. Because of that, some people claim that if Turing were alive today, he might say these systems are advanced tools but not genuine AI. The other side disagrees. They argue that what matters is how the system behaves, not how it works internally. This idea connects to the Turing Test. In this test, a human communicates with both a machine and another human through text. If the human cannot reliably tell which one is the machine, then the machine is considered intelligent according to the test. Supporters say modern AI can already perform very well in conversations, so by this logic it could qualify as AI. So the joke in the meme is showing two people confidently arguing about what Turing would say, even though no one can actually know his opinion about today’s technology. The humor comes from how seriously people debate this hypothetical scenario. Tags #philosophy

In 1991, we watched two machines talk to each other in Terminator 2: Judgment Day. At the time, it felt like pure science fiction — the T-800 and the T-1000 mimicking human voices, stripping away emotion, verifying reality through subtle conversational cues. But beneath the action spectacle was something deeper: one of cinema’s earliest portrayals of AI speaking directly to AI. No humans involved. No passwords. No faces. Just data validating data. By copying John and Janelle’s voices, the machines weren’t simply communicating — they were authenticating, probing for behavioral tells, running a kind of machine-to-machine Turing test disguised as small talk. Thirty-five years later, that scene feels less fictional and more prophetic. What looked like Skynet paranoia now resembles our daily reality: deepfakes cloning voices, AI systems verifying identity in milliseconds, autonomous algorithms checking one another before we even notice. Terminator 2 wasn’t just foreshadowing the future of warfare — it was hinting at the future of truth itself. A world where verification happens between machines, and reality can be negotiated by code. And that future isn’t coming. It’s here.

In Berlin, Sam Altman and physicist David Deutsch proposed a new idea they call “Turing Test 2.0.” Instead of judging AI by conversation alone, they suggest a tougher test: if a machine can solve quantum gravity and clearly explain how it reached the answer, it would demonstrate human-level intelligence. Deutsch, who once believed computers could never sustain open-ended conversations, admitted that tools like ChatGPT can now hold meaningful dialogue. But he argues that real intelligence is something deeper. It means creating new knowledge and solving problems independently, the way Albert Einstein did. Follow us (👉@artificialintelligenceee) for everything latest from the AI world. Media: Axel Springer SE

The Turing Test, proposed by British mathematician and logician Alan Turing in 1950, is a measure of a machine's ability to exhibit intelligent behavior indistinguishable from that of a human. In his paper "Computing Machinery and Intelligence," Turing suggested a thought experiment where an interrogator interacts with both a human and a machine through a text-based interface, without knowing which is which. If the interrogator cannot reliably distinguish between the human and the machine, the machine is said to have passed the test, thereby demonstrating a form of artificial intelligence (AI). Turing's test was revolutionary in challenging traditional notions of intelligence and sparked philosophical debates on the nature of consciousness, thinking, and the limitations of machines. However, critics argue that passing the test doesn't necessarily mean a machine is truly "intelligent" but only that it can mimic human responses effectively. The Turing Test has since inspired advancements in AI research, leading to the development of natural language processing systems, chatbots, and large language models. Despite these advancements, the question of whether machines can possess genuine understanding or consciousness, as opposed to simulating it, remains an open and profound question in AI and cognitive science.

Just decided to share, btw IBM teachers (I attended their summer quantum school) show it exactly in the same manner. So now after this reel you are upgraded Tensor product increases the dimension of your final vector by the rule n*k - the dimension of the product. n - is the dim of your first vector (here we define vector as a column of components, the number of components = dimension), k - dim of 2nd vector, so if you have a tensor product of vector1 = (a b c)^T and vector2 = (d e)^T (i can’t write a column on ig, so I use T as a transposition operation sign), then the final dimension will be 3*2 = 6 vect1\otimes vect2 = (ad ae bd be cd ce)^T Easy breezy, keep learning! 💪🏼 #tensor #tensorproduct #qubit #quantum #quantumphysics #math #mathematics #physics #science #quantumcomputing #quantummachinelearning #physicist #theoreticalphysics #theoreticalphysicist #vquantpost