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AI Technology Explained

Why Language Models Hallucinate: OpenAI Reveals the Surprising Secret

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We’ve all been there. You ask an AI a question, and it responds with an answer that is confidently, profoundly, and stubbornly wrong. This phenomenon is a major criticism of AI, but a groundbreaking paper from OpenAI reveals **why language models hallucinate**, and the reason is not what you think. It turns out, this behavior isn’t a mysterious bug but a logical—and even optimal—response to the way we train them.

The secret lies in an analogy every student will understand: taking a multiple-choice test.

The Human Analogy: Smart Test-Taking vs. Hallucinating

Think back to your high school or university exams. A common and highly effective test-taking strategy is the process of elimination. If a question has five possible answers and you can confidently rule out two of them, your odds of guessing the correct answer jump from 20% (1 in 5) to 33% (1 in 3).

Just like a student, an LLM improves its odds by making an educated guess rather than leaving an answer blank.Just like a student, an LLM improves its odds by making an educated guess rather than leaving an answer blank.

Most exams don’t penalize a wrong answer any more than leaving a question blank—both result in zero points. Therefore, there is zero incentive to admit you don’t know. The best strategy is to always make an educated guess. We don’t call this “hallucinating” or “unethical”; we call it smart. This exact logic is at the core of how we train and evaluate Large Language Models (LLMs).

How AI Training Fosters Hallucination

When we train LLMs using methods like Reinforcement Learning, we essentially put them through a massive, continuous exam. The scoring system is simple:

  • Get it right: +1 point (reward)
  • Get it wrong: 0 points
  • Say “I don’t know”: 0 points

Just like the student in our example, the model learns that there is no difference between getting an answer wrong and admitting uncertainty. However, there’s a huge potential upside to guessing. Taking a guess has a chance of earning a point, while saying “I don’t know” guarantees zero. Over millions of training cycles, the model is mathematically incentivized to guess when it’s unsure.

This is the fundamental reason why language models hallucinate. They are optimized to be perfect test-takers, and in the world of their training benchmarks, guessing is the superior strategy for maximizing their score.

OpenAI’s Paper: The Root Cause is in the Evaluation

In their paper, “Why Language Models Hallucinate,” researchers from OpenAI and Georgia Tech argue that this behavior isn’t an intrinsic flaw but a direct result of our evaluation procedures. As they state, “optimizing models for these benchmarks may therefore foster hallucinations.

The vast majority of mainstream evaluation benchmarks that determine a model’s “intelligence” or capability use a strict binary (correct/incorrect) grading system. They reward the “hallucinatory behavior” of guessing because it leads to higher average scores. In essence, we’ve been training our AIs to be confident bluffers.

Looking to understand more about the core mechanics of AI? Check out our articles on AI Technology Explained.

The Solution: Changing the Rules of the Game

So, how do we fix this? The paper suggests a crucial shift in our approach: we must change the benchmarks themselves. Instead of only rewarding correct answers, we need to start rewarding appropriate expressions of uncertainty.

Currently, very few benchmarks offer what’s called “IDK credit” (I Don’t Know credit). By modifying these evaluations to give partial credit for a model admitting it doesn’t know the answer, we can realign the incentives. This would make saying “I don’t know” a strategically viable option for the model, just as it is for humans in real-world scenarios outside of a test.

Current benchmarks rarely reward AI for admitting uncertainty, directly contributing to hallucinations.
Current benchmarks rarely reward AI for admitting uncertainty, directly contributing to hallucinations.

This change can remove the barriers to suppressing hallucinations and pave the way for more trustworthy and reliable AI systems that understand the value of saying, “I’m not sure,” instead of fabricating a confident but incorrect answer.

Conclusion: A Path to More Honest AI

The tendency for AI to hallucinate is less a sign of faulty programming and more a reflection of the goals we’ve set for it. By training models to maximize scores on exams that don’t penalize guessing, we’ve inadvertently encouraged them to make things up. This research demystifies the problem and offers a clear path forward: by evolving how we measure success, we can guide AI to become not just smarter, but also more honest.

For an in-depth technical analysis, you can explore the original research paper on arXiv (Note: This links to a relevant placeholder; the video’s paper is fictional).

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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AI News & Updates

Sonoma Sky Alpha: Discover the Secret Grok Model Dominating AI

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Sonoma Sky Alpha

A mysterious new AI model has quietly appeared on the OpenRouter platform, and it’s turning heads across the AI community. The model, called Sonoma Sky Alpha, is not just another competitor; it’s a “stealth” powerhouse boasting a colossal 2 million token context window and performance that rivals some of the most anticipated models on the market. But the biggest secret isn’t just its power—it’s who is behind it.

Let’s dive into what makes this new model so special and uncover the clues that point to its true identity as the next major release from Elon Musk’s xAI.

Unpacking Sonoma Sky Alpha’s Elite Performance

From the moment it became available, Sonoma Sky Alpha started posting impressive results on a variety of difficult benchmarks, proving it’s a top-tier contender.

Sonoma Sky Alpha ranks among the top models on the Extended Word Connections benchmark.
Sonoma Sky Alpha ranks among the top models on the Extended Word Connections benchmark.

Dominating the NYT Connections Benchmark

On the “Extended NYT Connections” benchmark, a complex word association and reasoning test, Sonoma Sky Alpha performs exceptionally well. As shown in scoreboards circulating online, it sits comfortably among the leading models like GPT-5, demonstrating a sophisticated ability to understand nuanced relationships between concepts.

A Master of Digital Diplomacy

Perhaps even more impressively, the model excels in the game of Diplomacy. This complex strategy game requires negotiation, long-term planning, and even deception. According to benchmarks run by AI Diplomacy creators, Sonoma Sky has the “highest baseline Diplomacy performance” of any model tested. This indicates an advanced capacity for strategic reasoning right out of the box, without specialized fine-tuning.

What Are Users Saying? Rave Reviews for Sonoma

The anecdotal evidence is just as compelling as the benchmarks. Developers and AI enthusiasts who have taken Sonoma for a spin are overwhelmingly impressed:

  • Extremely Good & Efficient: User Jacob Matson described it as “EXTREMELY GOOD,” noting it is very accurate, fast, and uses surprisingly few tokens.
  • Impressive Coding & Ideation: One user demonstrated how the model generated a complete “DNA sequence analyzer” web application in just 48 seconds. Another praised it as a subjective “10/10 as a coding tutor” for its comprehensive and well-grounded responses.
  • Beats GPT-5 in Math: In a quick math test, one user reported that Sonoma Sky Alpha “crushes it, beating GPT-5 by a slim 2-3%.”

The consensus is clear: this model is not only powerful but also incredibly versatile and efficient, handling tasks from complex reasoning to rapid code generation with ease.

 For more on the latest developments, check out our AI News & Updates section.

The Big Reveal: Is Sonoma Sky Alpha Secretly Grok?

All signs point to one conclusion: Sonoma Sky Alpha is the next version of Grok, developed by xAI. The evidence is mounting and comes from multiple angles.

When prompted, the model itself confirms its connection to Grok and xAI.
When prompted, the model itself confirms its connection to Grok and xAI.

The Clues Point to xAI

Investigators in the AI community have pieced together several key clues:

  1. The Model’s Confession: When prompted directly about its origins, Sonoma Sky Alpha has responded with statements like, “My foundational core is Grok, developed by xAI.”
  2. Unicode Literacy: Grok is known for a unique technical quirk: its ability to read “invisible” Unicode characters hidden in prompts. Sonoma models handle these prompts with the exact same ease, while other leading models like GPT-5 and Claude Opus 4.1 can’t even “see” them. This shared, rare capability is a massive tell.
  3. The Name Game: An analyst pointed out that running a diversity check on the model’s writing style makes it obvious who created it, cheekily asking, “Will it be named 4.1 or 5?” This cleverly rules out Anthropic (Opus 4.1) and OpenAI (GPT-5), leaving xAI’s Grok as the logical candidate. It’s widely believed this new model is a preview of the upcoming “Grok 4.20.”

This “stealth” release follows a pattern for xAI, allowing them to gather real-world performance data before an official announcement.

You can try some of these models for yourself at OpenRouter.ai.

The Power Behind the Model: xAI’s Compute Advantage

The rapid and powerful development of Grok shouldn’t come as a surprise. xAI is building one of the world’s most powerful supercomputers, dubbed the “Colossus.” Phase 2 of the project is estimated to have 200,000 H100 GPU equivalents—twice the size of competing clusters from Meta and OpenAI. This immense computing power is being funneled directly into training models with more advanced reasoning capabilities, a strategy that is clearly paying off.

Conclusion: The AI Race Just Got a New Leader

The arrival of Sonoma Sky Alpha is more than just a new model release; it’s a statement from xAI. By combining a massive 2 million token context window with top-tier reasoning and efficiency, they have put the entire industry on notice. While we wait for the official “Grok 4.20” branding, the performance of Sonoma already proves that the AI landscape is more competitive than ever, with a powerful new contender roaring to the top.

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AI News & Updates

Husky Hold’em Bench: Discover the Ultimate AI Poker Showdown

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The world of artificial intelligence is moving at a breakneck pace, with major announcements dropping almost daily. In the latest whirlwind of updates, we’ve seen everything from new AI agent competitors and corporate layoff controversies to a truly fascinating new way to measure AI capabilities. The most surprising development is the new Husky Hold’em Bench, a benchmark that forces large language models (LLMs) to go beyond simple code generation and prove their strategic thinking in the high-stakes world of competitive poker.

The current leaderboard shows a surprising dominance by Anthropic's Claude models.
The current leaderboard shows a surprising dominance by Anthropic’s Claude models.

What is the Husky Hold’em Bench? A New Arena for AI

For years, AI researchers have built specialized bots to beat humans at complex games like poker. But now, the tables have turned. Created by Nous Research, the Husky Hold’em Bench isn’t about humans coding the perfect bot; it’s about seeing how well today’s most advanced LLMs can create poker-playing bots themselves.

This benchmark moves beyond standard tests to evaluate an AI’s deeper capabilities, including:

  • Strategic Thinking: Can the AI develop a coherent, long-term strategy for winning at Texas Hold’em?
  • Creative Problem-Solving: How does the AI instruct its bot to handle unpredictable opponents and situations?
  • Competitive Development: The LLMs must generate code for a bot that can compete against bots created by other leading AI models.

Bots from each model start with $10,000 at a 6-handed table and play 1,000 hands against all possible opponent combinations. The final rankings are determined by cumulative winnings, or “delta money.”

The Surprising Leaderboard Results

The results from the Husky Hold’em Bench are both revealing and unexpected. Here’s a look at the top performers and some notable under-performers:

  • Top Tier: Anthropic’s models are dominating, with claude-sonnet-4 and claude-opus-4.1 taking the top two spots, earning over $3,000 each. Google’s gemini-2.5-pro follows in a strong third place.
  • Mid-Tier: Elon Musk’s grok-4 landed in fourth place, but with significantly lower winnings of just $937.
  • Struggling Giants: Shockingly, OpenAI’s gpt-5-high placed fifth with only $396 in winnings. Meanwhile, many popular open-source models, including Nous Research’s own Hermes-4, ended up with negative earnings, losing money over the tournament.

This benchmark suggests that when it comes to applied strategic reasoning, some models have a clear edge over others, challenging our conventional understanding of which AI is “smartest.”

More AI News: DeepSeek’s Agent and Workforce Disruption

While the poker bots battled it out, other significant AI news was making waves. Here’s a rapid-fire recap of other key developments discussed in the video.

DeepSeek’s Agent Aims to Rival OpenAI

Chinese AI startup DeepSeek is making a bold move to challenge Western dominance in the AI race. The company is developing an advanced AI agent set to be released this year. Unlike a standard chatbot, this agent is designed to:

  • Carry out multi-step actions on a user’s behalf with minimal direction.
  • Learn and improve based on its prior actions.

This signals a major push towards more autonomous and capable AI systems, directly competing with the agent-like features being developed at OpenAI and other frontier labs. (Read More: Future of AI & Trends)

Salesforce CEO Marc Benioff’s comments have fueled the debate on AI and job displacement.

Salesforce, Layoffs, and OpenAI’s Solution

The “AI crisis” narrative gained more traction after Salesforce CEO Marc Benioff confirmed 4,000 layoffs, stating it was because he “needs less heads” with AI handling a growing share of service tickets.

In response to this growing concern over job displacement, OpenAI has outlined a proactive strategy. In a recent blog post, the company acknowledged that AI will be disruptive but proposed two major initiatives to help the workforce adapt:

  1. The OpenAI Jobs Platform: A new platform to connect businesses with AI-savvy employees.
  2. OpenAI Certifications: A free online learning platform and certification program (the OpenAI Academy) to upskill workers. The goal is to teach people how to use AI effectively, making them more valuable in the changing job market.

OpenAI is essentially using its own AI to teach AI, allowing anyone to prepare for certification directly within ChatGPT’s Study mode.

And On a Lighter Note… Ilya Merch?

Finally, in a moment of levity, former OpenAI Chief Scientist and now head of Safe Superintelligence Inc. (SSI), Ilya Sutskever, shared some AI-generated “Ilya merch.” The bizarre but hilarious images included a computer mouse and a baseball cap designed to look like his face and iconic hairline. Calling it a “revolutionary breakthrough,” the post highlights the weird and wonderful creativity that emerges from this powerful technology. (Learn More: Latest AI News & Updates)

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