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OpenAI IMO Gold: Stunning Milestone Reveals AGI is Closer Than Ever

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OpenAI IMO Gold

In a move that has sent shockwaves through the tech world, OpenAI has announced a monumental achievement: one of their experimental models has secured a gold medal-level performance on the 2025 International Mathematical Olympiad (IMO). For decades, conquering the world’s most prestigious and difficult math competition has been seen as a “grand challenge” in artificial intelligence—a clear benchmark for AGI. The recent **OpenAI IMO Gold** performance signifies not just a leap in mathematical ability, but a fundamental breakthrough in general-purpose AI reasoning, bringing a future many thought was years away into sharp focus.

This achievement is a major milestone for both AI and mathematics, placing an AI’s reasoning capabilities on par with the brightest young human minds on the planet. But what makes this moment truly historic is how it was accomplished.

OpenAI officially announced their groundbreaking achievement on X (formerly Twitter).
OpenAI officially announced their groundbreaking achievement on X (formerly Twitter).

A Major Leap Beyond Specialized AI: General vs. Specialized Models

To understand the gravity of the **OpenAI IMO Gold** win, it’s crucial to compare it to previous efforts. Last year, Google DeepMind came incredibly close, earning a silver medal—just one point shy of gold. However, their success relied on two highly specialized AI models, AlphaProof and AlphaGeometry, which were specifically designed for mathematical and geometric proofs. Furthermore, the problems had to be manually translated by humans into a formal language the AI could understand.

OpenAI’s breakthrough is fundamentally different. As emphasized in their announcement and by CEO Sam Altman, this feat was achieved with a general-purpose reasoning LLM. It wasn’t a specialized “math AI”; it was a versatile model that read the problems in natural language—just like human contestants—and produced its proofs under the same time constraints.

Sam Altman clarified this on X, stating, “to emphasize, this is an LLM doing math and not a specific formal math system; it is part of our main push towards general intelligence.” This distinction is the core of the story: it’s a powerful demonstration of an AI’s ability to reason creatively and abstractly, not just execute a pre-programmed skill.

What Key Breakthroughs Led to This Success?

This achievement wasn’t just about scaling up old methods. According to OpenAI researchers Noam Brown and Alexander Wei, it involved developing entirely new techniques that push the frontiers of what LLMs can do.

Solving Hard-to-Verify Tasks

One of the biggest hurdles in AI has been training models on tasks that are difficult to verify automatically. It’s easy to reward an AI for winning a game of chess (a clear win/loss). It’s much harder to reward it for producing a multi-page, intricate mathematical proof that takes human experts hours to grade. Noam Brown explained that they “developed new techniques that make LLMs a lot better at hard-to-verify tasks,” marking a significant step beyond the standard Reinforcement Learning (RL) paradigm of clear-cut, verifiable rewards.

The Expanding “Reasoning Time Horizon”

Another crucial factor is the model’s “reasoning time horizon”—how long it can effectively “think” about a complex problem. AI progress has seen this horizon expand dramatically:

  • GSM8K Benchmark: Problems that take top humans about 0.1 minutes.
  • MATH Benchmark: Problems that take about 1 minute.
  • AIME: Problems that take about 10 minutes.
  • IMO: Problems that require around 100 minutes of sustained, creative thought.

This exponential growth in an AI’s ability to maintain a coherent line of reasoning over extended periods was essential for tackling problems at the IMO level.

Research shows the length of tasks AI can handle is doubling roughly every seven months.
Research shows the length of tasks AI can handle is doubling roughly every seven months.

A Glimpse of a New AI: The “Distinct Style” of Genius

Perhaps one of the most fascinating revelations is the unique way this advanced model communicates. The proofs it generated, available on GitHub, are written in a “distinct style.” It’s incredibly concise and uses a form of shorthand that is efficient but almost alien compared to typical human or LLM verbosity.

Phrases like “Many details. Hard.” or “So far good.” and “Need handle each.” showcase a thought process stripped of all pleasantries, focused purely on the logic. This terse style is reminiscent of chain-of-thought outputs seen in previous OpenAI safety research on detecting model misbehavior. It might be our first real look at how these advanced systems “think” without the layer of human-friendly chat fine-tuning we’re used to.

What’s Next? A Hint of GPT-5 and the AGI Threshold

While excitement is high, OpenAI has been clear: the model that achieved the **OpenAI IMO Gold** is an experimental research model and is not GPT-5. They plan to release GPT-5 “soon,” but a model with this specific, gold-medal math capability will not be publicly available for “several months.”

Even noted AI critic Gary Marcus, after reviewing the methodology, conceded that the achievement was “that’s impressive”—a significant acknowledgment of the progress made. As researcher Noam Brown noted, there’s a huge difference between an AI that is *slightly below* top human performance and one that is *slightly above*. By crossing that threshold, AI is now poised to become a substantial contributor to scientific discovery, pushing the boundaries of human knowledge.

This isn’t just a win in a competition. It’s a signal that the pace of AI development is exceeding even optimistic predictions, powered by new techniques that are more general and more powerful than ever before.

AI How-To's & Tricks

Google Translate Hidden Features: Discover This Powerful Workflow

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Google Translate Hidden Features

If you’re a language teacher or a dedicated student, you probably use Google Translate regularly. But are you using it to its full potential? Many users are unaware of several Google Translate hidden features that, when combined, create an incredibly efficient and powerful workflow for language acquisition. This guide will reveal a three-step process that transforms how you find, save, and practice new vocabulary, turning passive translation into active learning.

Combine Google's tools for a powerful language learning workflow.
Combine Google’s tools for a powerful language learning workflow.

Step 1: Save Translations to Create Your Custom Phrasebook

The first hidden feature is simple yet foundational: the ability to save your translations. Every time you translate a word or phrase that you want to remember, don’t just copy it and move on. Instead, look for the star icon next to the translated text.

Clicking this “Save translation” star adds the entry to a personal, saved list within Google Translate. You can access this growing collection of vocabulary and phrases anytime by clicking on the “Saved” button at the bottom of the translation box. This allows you to build a curated phrasebook of the exact terms you’re focused on learning, all in one place.

Step 2: Find Authentic Language with YouTube Transcripts

To make your learning effective, you need authentic content. YouTube is a goldmine for this, and another trick makes it easy to integrate with Google Translate. You can find real-world conversations, podcasts, and lessons on any topic in your target language.

Here’s how to leverage it:

  1. In the YouTube search bar, type your topic and add the language (e.g., “shopping in English” or “cooking in Polish”).
  2. Click the “Filters” button and select “Subtitles/CC”. This ensures all search results are videos that have a transcript available.
  3. Once you find a video, play it. Under the video description, click the “…more” button and scroll down until you see the “Show transcript” option.
  4. The full, time-stamped transcript will appear. Now you can easily highlight, copy, and paste any sentence or phrase directly into Google Translate to understand its meaning and save it to your phrasebook from Step 1!

 This method is one of many powerful techniques you can explore in our AI How-To’s & Tricks section.

Step 3: The Magic Button – Export to Google Sheets

This is one of the most powerful Google Translate hidden features that connects everything. Once you’ve built up your “Saved” list of vocabulary, how do you get it out of Google Translate to use elsewhere? With the magic “Export” button!

In your “Saved” translations panel, look for the three vertical dots (More options) in the top right corner. Clicking this reveals an option: “Export to Google Sheets.”

Effortlessly export your entire vocabulary list with just one click.
Effortlessly export your entire vocabulary list with just one click.

With a single click, Google will automatically create a new Google Sheet in your Drive, perfectly formatted with your source language in one column and the translated language in another. This simple export function is the key that unlocks endless possibilities for practice.

Bonus Tip: Turn Your Vocabulary List into Interactive Games

Now that your custom vocabulary list is neatly organized in a Google Sheet, you can easily import it into popular language learning tools to create interactive games and flashcards.

Two fantastic platforms for this are:

  • Quizlet: Visit the Quizlet website to learn more. Quizlet has a direct import function. Simply copy the two columns from your Google Sheet, paste them into Quizlet’s import box, and it will instantly generate a full set of flashcards. From there, you can use Quizlet’s various modes like Learn, Test, and Match to practice your new words.
  • Wordwall: [External Link Suggestion: Check out the activities on the Wordwall website.] Similarly, Wordwall allows you to paste data from a spreadsheet to create engaging classroom games like Match up, Anagrams, and Quizzes in seconds.

By following this workflow, you can go from watching an authentic YouTube video to playing a custom-made vocabulary game in just a few minutes. This is a game-changer for making language learning more efficient, personalized, and fun.

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AI How-To's & Tricks

AI Job Displacement: Unveiling the Ultimate Threat to Your Career

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AI Job Displacement

The debate around AI job displacement is heating up, with conflicting headlines leaving many confused. On one hand, some reports promise a net increase in jobs; on the other, top industry insiders are sounding the alarm. An ex-Google executive calls the idea that AI will create new jobs “100% crap,” while the CEO of Anthropic reaffirms his warning that AI will gut half of all entry-level positions by 2030. So, what’s the real story? The data reveals a complex and disruptive picture that isn’t about the total number of jobs, but rather a massive shift in which jobs will exist—and who will be left behind.

Conflicting reports paint a confusing picture of AI's impact on the job market.
Conflicting reports paint a confusing picture of AI’s impact on the job market.

The “100% Crap” Verdict from an Ex-Googler

Mo Gawdat, a former chief business officer at Google X, doesn’t mince words. He states that the widely circulated idea of AI creating a plethora of new jobs to replace the old ones is simply “100% crap.” His argument is grounded in the sheer efficiency of AI. He provides a stark example from his own startup, where an application that would have once required 350 developers was built by just three people using modern AI tools.

This isn’t a case of one job being replaced by another; it’s a case of hundreds of potential jobs being eliminated by a massive leap in productivity. According to Gawdat, even high-level executive roles, including CEOs, are at risk as AI-powered toolchains begin to automate complex decision-making and management tasks.

Anthropic CEO’s Dire Warning for Entry-Level Jobs

Adding to this concern is Dario Amodei, the CEO of AI safety and research company Anthropic. He has consistently warned that the most immediate and severe impact of AI will be felt at the bottom of the corporate ladder. He reaffirms his prediction that AI could wipe out half of all entry-level, white-collar jobs within the next five years.

Amodei points to specific roles that are highly susceptible to automation:

  • Law Firms: Tasks like document review, typically handled by first-year associates, are repetitive and perfect for AI.
  • Consulting & Finance: Repetitive-but-variable tasks in administration, data analysis, and financial modeling are quickly being taken over by AI to cut costs.

He argues that governments are dangerously downplaying this threat, which could lead to a significant and sudden spike in unemployment numbers, catching society unprepared.

Deceptive Data? What the World Economic Forum Really Says

At first glance, a recent report from the World Economic Forum (WEF) seems to offer a comforting counter-narrative. The headline projection is a net employment increase of 7% by 2030. Good news, right? Not exactly.

When you dig into the actual data, the picture becomes much more turbulent. The report projects that while 170 million new jobs will be created, a staggering 92 million jobs will be displaced. This represents a massive structural labor market churn of 22%.

The WEF report shows massive job churn, with millions of roles destroyed even as new ones are created.
The WEF report shows massive job churn, with millions of roles destroyed even as new ones are created.

This means that while the total number of jobs might grow, tens of millions of people will see their current roles vanish. The crucial question is whether the people losing their jobs will be qualified for the new ones being created.

The Great Divide: Growing vs. Declining Jobs

The WEF data highlights a clear and worrying trend. The jobs that are growing are not the same as the ones that are disappearing.

Top Fastest-Growing Jobs:

The roles with the highest projected growth are almost exclusively in high-tech, data-driven fields:

  • Big Data Specialists
  • FinTech Engineers
  • AI and Machine Learning Specialists
  • Software and Applications Developers
  • Data Analysts and Scientists

Top Fastest-Declining Jobs:

Conversely, the jobs facing the steepest decline are the very entry-level, white-collar roles that have traditionally been a gateway to a stable career:

  • Postal Service Clerks
  • Bank Tellers and Related Clerks
  • Data Entry Clerks
  • Administrative and Executive Secretaries
  • Accounting, Bookkeeping, and Payroll Clerks

This data directly supports the warnings from Amodei and Gawdat. The new jobs require advanced, specialized skills in AI and data science, while the jobs being eliminated are those that rely on codified, repetitive tasks that AI excels at automating.

The Productivity Paradox and the “Canary in the Coal Mine”

Economists and experts like Ethan Mollick are observing a pattern in macro data: unexpected decreases in employment are occurring alongside increases in productivity. While it’s too early to draw firm conclusions, Mollick notes this is exactly the pattern one would expect if AI were the cause. Companies can produce more with fewer people, leading to a productivity boom that doesn’t translate into broad job growth.

A recent Stanford study titled “Canaries in the Coal Mine” reinforces this, finding that early-career workers (ages 22-25) in the most AI-exposed jobs have already seen a 13% relative drop in employment compared to their less-exposed peers. This is happening even while overall employment is rising. The “canaries”—the youngest and most vulnerable in the workforce—are already feeling the effects.

Conclusion: The Future of Work is a Skill, Not a Job

The evidence strongly suggests that while AI may not lead to mass unemployment across the board, it will cause severe AI job displacement in specific, crucial sectors. The idea of a simple one-for-one replacement of old jobs with new ones is a dangerous oversimplification. The real challenge is a massive skills gap, where entry-level roles are automated away, while new high-skill roles are created that the displaced workers are not equipped to fill.

This hurts new graduates and young professionals the most, removing the very rungs on the career ladder they need to climb. The future of work won’t be about finding a job that’s “AI-proof,” but about continuously learning the AI skills needed to stay relevant, productive, and valuable in an increasingly automated world. The disruption is no longer a future prediction; it’s already here.

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AI How-To's & Tricks

Wordwall AI Trick: Secret Method to Unlock All Activities!

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Wordwall AI Trick

Wordwall is a powerhouse tool for educators, beloved for its ability to quickly create engaging quizzes, games, and printables for the classroom. With its new AI content generator, it’s become even more powerful. However, you might have noticed that the AI feature isn’t available on every activity template. But what if we told you there’s a simple yet brilliant Wordwall AI trick that lets you bypass this limitation and use AI-generated content for almost any activity type? In this guide, we’ll walk you through the secret method to supercharge your resource creation.

kes it easy to create custom teaching resources, and this AI trick makes it even faster.
Wordwall ma it easy to create custom teaching resources, and this AI trick makes it even faster.

The Challenge: Limited AI Access in Wordwall

When you go to “Create Activity” in Wordwall, you’ll see a fantastic array of templates like Match up, Quiz, Crossword, and Unjumble. The new AI feature, marked by a “Generate content using AI” button, is a game-changer. Unfortunately, it’s currently only enabled for a select few templates, such as “Match up.” If you select a template like “Crossword” or “Type the answer,” you’ll find the AI option is missing.

This can feel limiting, but don’t worry. The solution doesn’t require complex workarounds; it just requires knowing how to leverage Wordwall’s own features in a clever way.

The Ultimate Wordwall AI Trick: A Step-by-Step Guide

The core of this method is to generate your content in an AI-enabled template first and then transfer it to the template you actually want to use. It’s a simple, three-step process.

Step 1: Generate Your Content with an AI-Enabled Template

First, start by creating an activity using a template that does have the AI function, like Match up. This will be your starting point for generating the core content.

  1. Log in to Wordwall and click Create Activity.
  2. Select the Match up template.
  3. Click the ✨ Generate content using AI button.
  4. In the pop-up window, describe the content you want. Be as specific as you like regarding the topic, language level, and number of items. For example, the video creator used this effective prompt to create a vocabulary exercise:

Can you generate a list of adjectives in English with the opposites. I want something at level B2 in English so upper-intermediate type vocabulary.

  1. Click Generate. The AI will quickly populate the keywords and definitions for your Match up activity.
The "Switch template" feature is the secret to applying your AI content everywhere.
The “Switch template” feature is the secret to applying your AI content everywhere.

Step 2: Switch the Template to Your Desired Activity

Now that your content is generated, you don’t have to stick with the “Match up” game. On the right-hand side of the screen, you’ll see the Switch template panel. This is the key to the entire Wordwall AI trick.

  1. Once your activity is created, look at the Switch template panel on the right.
  2. Click on Show all to see every available activity type.
  3. Now, simply select the template you originally wanted to use, such as Crossword.

Wordwall will instantly take your AI-generated list of words and their opposites and reformat them into a fully functional crossword puzzle, complete with clues! You’ve successfully applied AI-generated content to a template that doesn’t natively support it.

Step 3: Duplicate and Save Your New Activity (The Pro Move)

You’ve switched the template, but to keep both the original “Match up” and the new “Crossword” as separate activities, you need to perform one final, crucial step.

  1. Below your new crossword activity, click on Edit Content.
  2. A dialog box will appear. Instead of editing the original, choose the option: Duplicate Then Edit As Crossword.
  3. This will create a brand new, independent copy of the activity. You can now rename the title (e.g., from “Adjectives and Their Opposites” to “Crossword – Adjectives and Their Opposites”).
  4. Click Done to save.

When you check your “My Activities” folder, you’ll now have two separate resources: the original Match up game and the new Crossword puzzle, both created from a single AI prompt. You can repeat this process for quizzes, word searches, anagrams, and more!

Enhancing Your AI-Generated Activities

Once your content is in place, don’t forget about Wordwall’s other great features to make your activities even better:

  • Add Audio: In the content editor, you can click the speaker icon next to a word to generate text-to-speech audio. This is fantastic for pronunciation practice in language learning.
  • Set Assignments: Use the “Set Assignment” button to easily share the activity with your students. You can get a direct link or a QR code, making it perfect for both in-person and online classrooms.

Conclusion: Supercharge Your Teaching with Wordwall AI

The Wordwall AI trick is a powerful way to maximize efficiency and create a wide variety of high-quality teaching resources in a fraction of the time. By starting with an AI-enabled template, generating your core content, and then using the “Switch template” and “Duplicate” features, you can unlock the full potential of AI across the entire Wordwall platform. Give it a try and see how much time you can save on lesson preparation!

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