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🎭 73% Fooled by GPT-4.5 Human Mask

GPT-4 Will Die Soon?

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Read time: 5 minutes

Something strange just happened in a lab. A group of people sat down, 73% thinking they were chatting with another human. They were wrong. Most of them didn’t even realize “that human” is GPT-4.5? And it wasn’t even trying that hard to fool them!

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AI INSIGHTS

gpt-4-5-fooled-humans-73-percent-of-the-time

Is it possible that an AI now feels more human than actual humans? OpenAI’s model has become the first large language model (LLM) to do that. But it also raises ethical concerns, as it didn’t just “pass” in many cases, it seemed more human than actual people.

How the Three-Party Turing Test Works:

  • One human interrogator interacts with two unseen entities: one human and one AI. They evaluated 4 different types of AI system in the witness role: GPT-4.5, LLaMa-3.1-405B, GPT-4o, and ELIZA.

  • People judged based on “vibes”.

  • The interrogator asks both questions and must guess which one is the human.

  • GPT-4.5 was judged to be human more often than the actual humans it competed against.

GPT-4.5 Passed the Original, Hardest Version of the Turing Test

  • Meta’s LLaMa-3.1 fooled participants 56% of the time, still beating the original Turing prediction (30% error rate or better).

  • GPT-4o performed below chance (21%), grouped closer to ELIZA (23%) than its GPT predecessor.

  • GPT-4.5, with its 73%, was clearly the best-performing model.

=> AI is now mimicking human behavior more convincingly than ever. Is it good for more human-like AI agents for conversations and support?

Why it matters: The scary part is that people connected with AI emotionally, often more than with actual people. Scammers will love this. Brands will weaponize it. And most users won’t even notice. It’ll replace the parts of being human we’re too lazy to protect.

TODAY IN AI

AI HIGHLIGHTS

🛠️ OpenAI’s next “agentic” AI agent called "A-SWE" is a self-testing software engineer that does all the things that coders hate to do. OpenAI’s effort to stay ahead of xAI and Perplexity.

📦 OpenAI is closing the GPT-4 chapter in 2 weeks. It will be fully replaced but still available via API. This signals OpenAI’s push toward new model families like GPT-4.1, o3, and o4-mini.

🚀 DeepSeek signals next-gen R2 model, unveils novel approach to scaling inference with SPCT. Shift in AI paradigm: From pre-training to post-training, following the lead of OpenAI’s o1 model.

🔍 OpenAI, Anthropic, and Elon Musk claim AGI is just 2–3 years away. But AGI is being hyped, vague, misunderstood, and often misused. So, are any of these “really” AGI?

📢 Meta blames the internet for its AI’s left-leaning bias even though Facebook is the internet for many people. Llama 4 is trying to reposition itself as a "politically neutral" & please the new MAGA crowd.

🧠 We are the real AI. AI is us. AI isn’t the problem, we are. AI copies, reflects, and learns from everything we do. “AI Mirror” shows our true inner code.

💰 AI Daily Fundraising: Autonomous vehicle startup Nuro secured $106 million in funding, bringing its valuation to $6 billion. The company plans to use the funds to scale its AI capabilities and advance commercial partnerships.

AI SOURCES FROM AI FIRE

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AI QUICK HITS

  1. 🚀 Access to future AI models in OpenAI’s API may require a verified ID.

  2. 🧬 MIT built a faster way to protect sensitive AI training data without hurting accuracy.

  3. 🗣 A new push to cut AI costs by cloud giants like Amazon and Google are rising dangers for Nvidia.

  4. 🎥 Netflix uses OpenAI-powered search engine based on users’ current intent.

  5. ☢️ For the first time, AI is being used at a nuclear power plant.

AI CHART

ai-created-the-first-google-maps-of-the-human-cell

We’ve known for centuries that cells are complex. We even have names for thousands of proteins inside them. But until now, no one knew how they all fit together, so they used: 20,000+ images of glowing proteins inside cells and specifically GPT-4 to analyze, name, and describe these protein clusters.

And the result was a map of over 5,100 proteins, organized into 275 distinct “protein machines” inside the cell. And most of this has never been seen before.

For the first time, GPT-4 has created the most detailed and interactive map of a human cell. This cellular atlas reveals over 975 previously unknown protein functions and turns 400 years of cell research into a zoomable, Google Maps-style blueprint.

The project was led by UC San Diego, with contributions from Stanford, Harvard Medical School, UCSF, and University of British Columbia. Combines AI (GPT-4) + microscopy + protein interaction data for high accuracy.

Huge Scope and Protein Coverage:

  • The study uncovered 975 new protein functions using GPT-4.

  • GPT-4 was used to:

    • Interpret protein function from scientific literature.

    • Summarize how proteins work together in assemblies.

    • Propose names and functions for protein clusters in the map.

=> This dramatically sped up work that would take researchers years manually. Despite knowing all the proteins, scientists never had a complete parts list + assembly guide for any human cell type until now.

The online U2OS cell map is zoomable and interactive. Users can explore protein assemblies, locations and functional communities. The team plans to make resolution even higher in future versions => It’s like Google Maps for cell biology.

It’s also proof that AI + science = more than automation, it’s collaboration for discovery. Instead of focusing on rare mutations, we can now see which “cellular machines” are most likely being hijacked or broken.

AI JOBS

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