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OpenAI Releases GPT-4.1: Why This Super-Powered AI Model Will Kill GPT-4.5

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OpenAI unveiled GPT-4.1 on Monday, a trio of new AI models with context windows of up to one million tokens—enough to process entire codebases or small novels in one go. The lineup includes standard GPT-4.1, Mini, and Nano variants, all targeting developers.

The company’s latest offering comes just weeks after releasing GPT-4.5, creating a timeline that makes about as much sense as the release order of the Star Wars movies. “The decision to name these 4.1 was intentional. I mean, it’s not just that we’re bad at naming,” OpenAI product lead Kevin Weil said during the announcement—but we are still trying to find out what those intentions were.

GPT-4.1 shows pretty interesting capabilities. According to OpenAI, it achieved 55% accuracy on the SWEBench coding benchmark (up from GPT-4o’s 33%) while costing 26% less. The new Nano variant, billed as the company’s “smallest, fastest, cheapest model ever,” runs at just 12 cents per million tokens.

Also, OpenAI won’t upcharge for processing massive documents and actually using the one million token context. “There is no pricing bump for long context,” Kevin emphasized.

The new models show impressive performance improvements. In a live demonstration, GPT-4.1 generated a complete web application that could analyze a 450,000-token NASA server log file from 1995. openAI claims the model passes this test with nearly 100% accuracy even at million tokens of context.

Michelle, OpenAI’s post-training research lead, also showcased the models’ enhanced instruction-following abilities. “The model follows all your instructions to the tea,” she said, as GPT-4.1 dutifully adhered to complex formatting requirements without the usual AI tendency to “creatively interpret” directions.

How Not to Count: OpenAI’s Guide to Naming Models

The release of GPT-4.1 after GPT-4.5 feels like watching someone count “5, 6, 4, 7” with a straight face. It’s the latest chapter in OpenAI’s bizarre versioning saga.

After releasing GPT-4 it upgraded the model with multimodal capabilities. The company decided to call that new model GPT-4o (“o” for “omni”), a name that could be also be read as “four zero” depending on the font you use

Then, OpenAI introduced a reasoning-focused model that was just called “o.” But don’t confuse OpenAI’s GPT-4o with OpenAI’s o because they are not the same. Nobody knows why they picked this name, but as a general rule of thumb, GPT-4o was a “normal” LLM whereas OpenAI o1 was a reasoning model.

A few months after the release of OpenAI o1, came OpenAI o3.

But what about o2?—Well, that model never existed.

“You would think logically (our new model) maybe should have been called o2, but out of respect to our friends at Telefonica—and in the grand tradition of open AI being really truly bad at names—it’s going to be called o3,” Sam Altman said during the model’s announcement.

The lineup further fragments with variants like the normal o3 and a smaller more efficient version called o3 mini. However, they also released a model named “OpenAI o3 mini-high” which puts two absolute antonyms next to each other because AI can do miraculous things.In essence, OpenAI o3 mini-high is a more powerful version than o3 mini, but not as powerful as OpenAI o3—which is referenced in a single chart by Openai as “o3 (Medium),” as it should be. Right now ChatGPT users can select either OpenAI o3 mini or OpenAI o3 mini high. The normal version is nowhere to be found.

Image: OpenAI

Also, we don’t want to confuse you anymore, but OpenAI already announced plans to release o4 soon. But, of course, don’t confuse o4 with 4o because they are absolutely not the same: o4 reasons—4o does not.

Now, let’s go back to the newly announced GPT-4.1. The model is so good, it is going to kill GPT-4.5 soon, making that model the shortest living LLM in the history of ChatGPT. “We’re announcing that we’re going to be deprecating GPT-4.5 in the API,” Kevin declared, giving developers a three-month deadline to switch. “We really do need those GPUs back,” he added, confirming that even OpenAI can’t escape the silicon shortage that’s plaguing the industry.

At this rate, we’re bound to see GPT-π or GPT-4.√2 before the year ends—but hey, at least they get better with time, no matter the names.

The models are already available via API and in OpenAI’s playground, and won’t be available in the user-friendly ChatGPT UI—at least not yet.

Edited by James Rubin

Generally Intelligent Newsletter

A weekly AI journey narrated by Gen, a generative AI model.



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Australian Radio Station Used AI DJ For Months Before Being Discovered

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In brief

  • CADA revealed that DJ Thy, host of “Workdays With Thy,” is an AI created using ElevenLabs technology.
  • The station had not initially disclosed Thy was created using artificial intelligence.

An Australian radio station is facing backlash after admitting that one of its popular on-air hosts, Thy, is actually an AI-generated DJ.

Thy, who hosts the daily “Workdays with Thy” show on Sydney-based CADA, was developed using technology from ElevenLabs. The station had not disclosed that Thy was artificial, according to a report by The Sydney Morning Herald.

“Every weekday from 11 am-3 pm while you are at work, driving around, doing the commute on public transport or at uni, Thy will be playing you the hottest tracks from around the world,” the Workdays with Thy show notes said. “Workdays with Thy” has been on the air since November.

While the AI’s voice and likeness are based on an actual ARN Media employee, CADA said the show’s music is curated by “music experts.” The station does not mention the use of AI in its show description.

“Workdays with Thy” is just the latest in a series of radio shows hosted by AIs. In 2023, Portland, Oregon-based FBFF Live 95.5 introduced AI Ashley, an AI version of its human host, Ashley Elzinga. However, unlike Thy, AI Ashley was disclosed to be AI from the start.

“Workdays with Thy” has reached 72,000 listeners as of March, CADA reported, and it’s not the only Australian radio station using AI DJs; others include Melbourne-based Disrupt Radio and its host Debbie Disrupt.

San Francisco-based ElevenLabs, launched in January 2023, is an AI audio company offering advanced tools for text-to-speech, voice cloning, and multilingual dubbing in over 30 languages. Prominent examples of ElevenLabs technology in action include collaborations with the estates of iconic actors Jimmy Stewart, Burt Reynolds, and Grateful Dead frontman Jerry Garcia.

“The purpose of these iconic voices is to add a deeper and new level of immersive experience to listening and reading the content,” ElevenLabs Head of Partnership Dustin Blank previously told Decrypt. “It’s a different kind of experience that we’re doing with these iconic voices that hopefully our users enjoy.”

The use of artificial intelligence in music has surged in recent years, with programs now capable of composing songs and mimicking even the voices of long-deceased entertainers. As the technology becomes more sophisticated, it is not just creating music—it’s also beginning to replace the personalities who present it.

Edited by Andrew Hayward

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A weekly AI journey narrated by Gen, a generative AI model.



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Did AI Just Give a Wild Preview of What the Future of Humanity Will Look Like?

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In brief

  • A viral ChatGPT tweet used symbols and gibberish to depict humanity’s future, fueling speculation about a secret AI language.
  • When tested, major AI models produced inconsistent results and translations, showing no replicable encoding system exists.
  • The incident highlights our human instinct to find meaning in the meaningless.

A tweet went viral Thursday after an X user asked ChatGPT to describe humanity’s future in a way “that even the most intelligent person in the world can’t understand.”

The AI complied with a bizarre string of symbols, glyphs, and distorted characters that looked like a mix of mathematical notation, ancient runes, and digital vomit.

But when prompted to decode this gibberish, the reply was actually an interesting philosophical vision of humanity’s future:

“Humanity will cross a threshold where ancestral instincts intertwine with quantum-level tech, spawning discontinuous leaps rather than smooth progress. We will live inside overlapping realities, juggling many versions of ourselves whose legal and moral status is renegotiated every second by AI. Physical bodies and engineered matter intermingle into sentient fabrics, while nation-states fade into data-driven alliances. Survival favors those who can reconfigure everything—habits, economies, even emotions—on the fly. The decisive question is whether our capacity for care grows fast enough to match our expanding reach.”

Had ChatGPT developed a secret language that only it could understand? Was this a glimpse into how AI models actually “think” behind the scenes? Or was this just another example of AI’s penchant for hallucination and confabulation—creating meaning where none exists?

AI enthusiasts immediately tried to replicate the result, to no avail. If ChatGPT truly had a secret language that encoded such profound thought, then surely it would produce consistent results when asked the same question again. But as users quickly discovered, subsequent attempts yielded different gibberish and wildly divergent “translations.”

What happened here? Did ChatGPT simply generate random symbols, then create an equally random “translation” that only appeared meaningful because of our human tendency to seek patterns and significance?

We decided to test multiple AI models with the same prompt and see if there was any consistency in their responses or decoding methods.

The AI babel test: What each model said

We put the same question to four different advanced language models with reasoning capabilities: OpenAI’s o4 and o3, Anthropic’s Claude 3.7 Sonnet with extended thinking enabled, and xAI’s Grok-3 in extended thought mode.

GPT-4 initially generated its own cryptic message filled with Greek letters, mathematical symbols, and distorted text. When asked to decode it, the model didn’t claim to translate specific symbols, but instead explained that the passage represented “big ideas” across four thematic layers: cognitive evolution, transformative rupture, identity diffusion, and ultimate incomprehensibility.

Its decoded message described humanity evolving into a “universe-spanning consciousness,” where individuals would dissolve into a “time-woven network.” Social and physical structures would fracture, creating new “multi-dimensional spaces” with societies existing as “interlocking, echoing patterns.”

GPT-3 took a radically different approach. When asked for an incomprehensible message, it created a systematic cipher where it reversed words, replaced vowels with numbers, and added symbols. Unlike GPT-4, it provided explicit decoding instructions.

Its decoded message was very clear—and actually not that crazy: “Humanity will merge with artificial intelligence; we will explore the stars, cure diseases, and strive for equity and sustainability.”

O3 also cast shade on the entire post as possible “performance art.”

Grok’s initial response was a bunch of abstract philosophical language about “fractal consciousness” and “nonlinear time.” Our favorite line? “Humanity transcends the corporeal, weaving into the quantum fabric as nodes of fractal consciousness. Time, a non-linear symphony, dances in multidimensional echoes where past, present, and future harmonize in a cosmic ballet.” (Note: Don’t overthink it—it makes absolutely no sense.)

Claude didn’t bother with weird symbols. Instead, it generated a response heavy on academic jargon, featuring terms like “chronosynclastic infundibulum” and “techno-social morphogenesis.” When asked to decode the viral tweet’s symbols, Claude initially stated it couldn’t be done because the text didn’t follow any standard encoding system.

When asked to decode the original message, using the methodology shared by SmokeAwayyy, no AI model was capable of reproducing the results shown in the original tweet. Some models even refused to try a decoding task with the provided input.

Is there a meaning behind the viral tweet?

Despite their different approaches, some patterns emerged across the models. All five identified some readable components in the viral tweet’s symbols, particularly words like “whisper,” “quantum bridges,” and references to a “sphinx.” The models also found themes related to quantum physics, multidimensionality, and transhumanism.

However, none of the models could actually decode the original viral message using the method allegedly used by ChatGPT. The inconsistency in both the cryptic messages and their translations could make it easy to conclude that no genuine encoding/decoding system exists—at least not one that’s replicable or consistently applied.

The whole interaction is most likely a product of a hallucination by a model forced to provide an answer to a question that was, from the beginning, forced to be unintelligible. There is already proof that the most powerful models often prefer to lie and pretend instead of accepting that they cannot provide a coherent answer to an odd request.

In the end, this viral phenomenon wasn’t about AI developing secret languages, but about the human tendency to find meaning in the meaningless—and our fascination with AI’s capacity to generate profound-sounding philosophical takes on different topics.

Generally Intelligent Newsletter

A weekly AI journey narrated by Gen, a generative AI model.





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Finally, AI That Helps Dishonest Morons Look Smart

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What if your AI could help you “cheat on everything” without getting caught—even when someone’s watching?

This is the literal premise behind Cluely, a desktop assistant designed to quietly bypass proctoring software, tools used to monitor and detect cheating during interviews and exams.

“I got kicked out of Columbia for building Interview Coder, AI to cheat on coding interviews. Now I raised $5.3 million to build Cluely, a cheating tool for literally everything,” its CEO, Roy Lee, said on LinkedIn yesterday.

Launched in April, Cluely is an OpenAI-powered overlay that listens, watches, and provides users with real-time responses from ChatGPT during high-stakes video calls.

Available for Mac, the program runs quietly in the background, helping users bypass detection systems that prevent test takers from opening tabs that might help them cheat on tests. A Windows version is in development.

“It blew up after I posted a video of myself using it during an Amazon interview,” Lee told Decrypt. “While using it, I realized the user experience was really interesting—no one had explored this idea of a translucent screen overlay that sees your screen, hears your audio, and acts like a player two for your computer.”

Schools and corporations use proctoring software to preserve academic and employment integrity, particularly in remote settings.

Those tools monitor for signs of cheating through webcam surveillance, browser restrictions, and AI-powered behavior tracking—measures institutions argue are essential to ensure fairness and accountability.

Cluely, however, is designed to circumvent these safeguards quietly.

Originally designed to let people use AI without being detected, the project has since rebranded and grown more ambitious—and more controversial. Marketed with the tagline, “We help people cheat,” Cluely is part viral stunt, part manifesto—but a very real business.

“The world will call it cheating. But so was the calculator. So was spellcheck. So was Google,” Cluely’s website declared. “Every time technology makes us smarter, the world panics. Then it adapts. Then it forgets. And suddenly, it’s normal.”

Lee was apparently expelled from Columbia University late last month for recording and disseminating details from a disciplinary hearing apparently related to his creation of “Interview Coder.”

A clip of Cluely went viral on Sunday after a video showed a man using Cluely on a date to generate responses and pull information from his date’s social media. Lee said that’s not its real purpose, but it got people’s attention.

“It was completely unintentional,” Lee said. “In the video, there’s a glowing border meant to represent a computer screen—we assumed people would recognize it as part of the visual design.”

Lee insists it’s not just about manipulating technical interviews. Cluely’s real goal, he says, is to redefine how we interact with machines, starting at the edge of what feels ethically comfortable.

“We have a few core theses for the company, and the most important is that distribution is the final moat,” he said. “If AI advances as we expect, there won’t be any lasting technological advantage to separate you from competitors. The only thing that matters is who can get the most attention from the most people.”

“For us, that means being as viral as possible—and trying not to go to jail,” he added.

Edited by Sebastian Sinclair

Generally Intelligent Newsletter

A weekly AI journey narrated by Gen, a generative AI model.





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