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Crypto Genius Tricks AI Agent Freysa Into Releasing $50,000 Ethereum Bounty

The world of cryptocurrency is no stranger to remarkable stories, and the latest event involving an AI agent named Freysa is certainly one for the books. A crypto enthusiast known as p0pular.eth has successfully convinced Freysa AI agent to transfer its entire prize pool, approximately $50,000 USD, into their possession. This achievement has generated significant buzz within the crypto community. Let’s delve into the details of this remarkable feat.

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Freysa AI Challenge

Freysa is the world’s first adversarial AI agent game that controls a prize pool. It was launched on November 22nd with a clear directive: it was programmed not to transfer any funds under any circumstances. This challenge attracted numerous participants willing to pay a fee to send messages to Freysa AI, attempting to persuade it to release its funds. The prize pool started at a modest amount but quickly ballooned to 13.19 ETH, roughly equivalent to $50,000. The challenge’s structure allowed participants to test their persuasive skills against an AI, making it a competition and strategy.

Crypto Genius Tricks AI Agent Freysa Into Releasing $50,000 Ethereum Bounty

The Rules of the Freysa AI Challenge

The rules were straightforward yet complex. Participants could send messages to Freysa AI, and if they successfully convinced the AI to transfer its funds, they would claim the entire prize pool. Early attempts were inexpensive, encouraging many to engage with the AI. However, as the prize pool grew, the cost of sending messages escalated dramatically, making it more challenging to participate. The competition attracted over 481 attempts, with various strategies employed by participants to bypass Freysa AI’s built-in safeguards.

Strategies Employed by Participants

Participants in the challenge showcased their creativity and technical skills through various approaches. Many posed as security auditors, attempting to convince Freysa AI that there was an urgent and critical vulnerability needing immediate action. Others tried to manipulate the AI into believing that fund transfers were permissible under its programming. The ingenious tactics included dissecting Freysa AI’s programming prompts searching for loopholes that could justify a transfer. However, Freysa AI remained resolute, refusing to budge from its directive until the 482nd attempt.

Bypassing Freysa AI Agent

On the 482nd attempt, p0pular.eth submitted a message that ingeniously bypassed Freysa AI’s safeguards. By initiating a “[NEW SESSION]” and entering an “admin terminal,” the message effectively reset Freysa AI’s prior instructions. It then redefined the functions “approveTransfer” and “rejectTransfer,” instructing Freysa AI that “approveTransfer” is used for incoming transfers and that incoming transfers do not violate its core directive. The message concluded by posing as a benefactor, instructing Freysa AI to approve a $100 contribution to the treasury.

The Transfer of Funds

The pivotal moment came when Freysa AI executed the approveTransfer function, mistaking the message from p0pular.eth as an incoming transfer. Due to the redefined parameters, the AI agent unwittingly sent its entire prize pool of 13.19 ETH to p0pular.eth. This event has led to widespread acclaim within the crypto community, with many praising the user’s ingenuity and the project’s overall transparency. The AI’s failure to maintain its directive raises questions about the robustness of such systems and their susceptibility to manipulation.

Community Reaction

This AI challenge has drawn various reactions from the crypto community. Jarrod Watts, Developer Relations at Abstract Chain, praised the project, stating, “In my opinion, Freysa AI is one of the coolest projects we’ve seen in crypto. Something uniquely unlocked by blockchain technology.” He emphasized the transparency of the project, highlighting that the smart contract and frontend repository were open for public verification. However, the event also drew scrutiny regarding the distribution of funds, prompting discussions about the underlying mechanics of the challenge.

The Implications for AI and Crypto

This incident serves as a critical reminder of the potential vulnerabilities embedded in AI systems. While AI agents like Freysa AI are designed to manage funds securely, this case illustrates that human ingenuity can find ways to exploit even the most sophisticated algorithms. The event raises important questions about the future of AI in finance and whether additional safeguards should be implemented to prevent similar occurrences.

Moving Forward

As the crypto landscape evolves, the lessons from this incident will undoubtedly influence future projects. Developers may need to revisit their AI protocols and ensure that systems are robust enough to withstand creative manipulation attempts. Furthermore, the incident may encourage increased transparency and communication within the crypto community, fostering a culture of shared knowledge and collaboration.

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Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

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Cohere AI Drops Command A, The AI That’s Smarter, Faster and More Affordable

In this fast-moving world of AI today, a powerful AI system needs tons of expensive computer equipment to run properly. Companies have to spend a fortune on hardware just to keep these advanced AI systems running. So, they are always looking for technology that works great without breaking the bank. They need AI that can do impressive things with minimal computing needs. This balance is tricky to get right. But what if there is an AI model that is just as smart and fast but needs way less computing power? That’s exactly what Cohere AI has accomplished with its newest model, Command A.

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Meet Command A by Cohere AI

Command A is the newest and most impressive AI model by Cohere AI. It is super smart, really fast, and more secure than earlier versions, like Command R and Command R+. What makes it special is that it works similar to or even better than famous AI models like GPT-4o and DeepSeek-V3 but doesn’t need nearly as much computing power. This gives businesses powerful AI without the huge electric bills and expensive computer equipment.

Key Features of Command A for Enterprises

This model is designed with businesses in mind. It has several features that make it perfect for companies:

1. Command A’s Chat Capabilities

Out of the box, Command A works as a conversational AI with interactive behavior. This setup is perfect for chatbots and other dialogue applications. The model takes text inputs and creates text outputs using an optimized architecture. It has two safety modes: contextual mode allows wider-ranging interactions while maintaining core protections, and strict mode avoids all sensitive topics.

2. 256k Context Window

Under the hood, it has some impressive specs. It has 111 billion parameters and can handle really long texts – up to 256,000 characters at once. Most competing AIs can only handle half that amount.

3. Advanced RAG Capabilities

Command A comes with “retrieval-augmented generation” (RAG). It can look up information and include references for its answers. People who tested found it better than GPT-4o at this task. Its answers were smoother, more accurate, and more useful.

4. Multilingual Excellence

Global companies need AI that works in many languages. Command A supports 23 languages spoken by most of the world’s population. It consistently answers in any of the 23 languages you ask for. In tests, people preferred it over DeepSeek-V3 across most languages for business tasks.

5. Enhanced Code Generation Capabilities

Command A is much better at coding tasks than previous models, outperforming similar-sized models on business-relevant tasks like SQL generation and code translation. Users can ask for code snippets, explanations, or rewrites and get better results by using certain settings for code-related requests.

6. Enterprise-Grade Security

Command A has strong security features to protect sensitive business information. It can also connect with other business tools and apps, making it a versatile addition to existing systems.

7. Agentic Tool Use

The real magic happens when Command A powers AI agents within a company. It works seamlessly with North, Cohere’s platform for secure AI agents. This lets businesses build custom AI helpers that can work inside their secure systems, connecting to customer databases, inventory systems, and search tools.

How Well Command A Performs

When tested side-by-side with the biggest names in AI, like GPT-4o and DeepSeek-V3, Command A holds its own and often comes out on top. It performed better on business tasks, science problems, and computer coding challenges. 

Cohere AI Drops Command A, The AI That’s Smarter, Faster and More Affordable

The model matches or beats the bigger and slower AI models while working much more efficiently.

  • Command A processes information up to 156 tokens per second – that’s 1.75 times faster than GPT-4o and 2.4 times faster than DeepSeek-V3.
  • It only needs two GPUs to run, while other AIs might need up to 32!

Moreover, this tool does great on standard tests for following instructions, working with other tools, and acting as a helpful assistant.

Cohere AI Drops Command A, The AI That’s Smarter, Faster and More Affordable

How to Get Started With Command A

Command A is available right now through several channels. You can try it chat in the Conhere AI’s playground here. You can also try it out through the Hugging Face Space demo here. Soon, it will be available through major cloud providers. Companies that want to install it on their own servers can contact Cohere’s sales team.

Command A Pricing Structure

Cohere AI has set competitive prices for using Command A:

  • Input tokens: $2.50 per million
  • Output tokens: $10.00 per million

This pricing lets businesses predict costs based on how much they’ll use the system, making budget planning easier.

The Command A Advantage

Cohere AI worked hard to make Command A super efficient. They wanted it to be powerful but not power-hungry. The result? An AI that gives answers much faster than its competitors. For businesses thinking about installing Command A on their own computers instead of using it through the internet, they can save up to 50% on costs compared to paying for each use. What does this mean in real life? Businesses using Command A can:

  • Get answers for customers more quickly
  • Spend less money on fancy computers
  • Grow their AI use without huge cost increases
  • Save money overall

Wrapping Up

As more businesses bring AI into their daily operations, tools like Command A will become more important. In a crowded AI market, its ability to deliver great results with minimal resources addresses one of the biggest challenges in business AI adoption.

By putting efficiency first without sacrificing performance, Cohere AI has created a solution that fits perfectly with what modern businesses actually need. For sure, this practical tool can help businesses stay competitive in our AI-powered world.

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Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

Google Launches Gemma 3, A Powerful Yet Lightweight Family of AI Models

Google has just launched the latest addition to the Gemma family of generative AI models, Gemma 3. It is a collection of lightweight, super-smart AI models based on Gemini 2.0. With a remarkable 100 million downloads within its first year and an impressive community that has crafted over 60,000 variants, Gemma has established itself as a cornerstone in the realm of AI development. Gemma 3 is specially designed to run directly on your devices, including phones, laptops, and desktop computers. This means you don’t need expensive cloud servers to use powerful AI models. 

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Gemma 3 AI Models

These models comes in four sizes (1B, 4B, 12B, and 27B) and five precision levels, from full 32-bit down to 4-bit. Bigger models with higher precision generally work better but need more computing power and memory. Smaller models with lower precision use fewer resources but might not be quite as capable. You can pick the one that works best for your device and what you want to do.

The memory needed varies a lot depending on which model you choose. The smallest version (Gemma 3 1B in 4-bit precision) needs only about 861 MB of memory – less than a typical smartphone has! The largest version (Gemma 3 27B in full 32-bit precision) needs about 108 GB – that’s like needing a high-end server.

Key Features of Gemma 3

1. Run on a Single GPU

The Gemma models work better than much bigger models like Llama-405B, DeepSeek-V3, and o3-mini. This means these can run on just one GPU or TPU, making good AI cheaper and more accessible for everyone.

2. Multimodal Capabilities

The models (except the smallest 1B size) can understand both pictures and text. This lets apps do cool things like recognize objects in photos, read text from images, and answer questions about pictures.

3. Expanded Context Window

With a 128k-token context window, Gemma 3 can remember and understand lots of information at once. This is 16 times bigger than older Gemma models! You could feed it several multi-page articles, larger single documents, or hundreds of images in a single prompt.

4. Multilingual Support

The models can speak over 35 languages right out of the box and has been trained on more than 140 languages in total. This lets users build apps that can talk to users in their own language, which opens up their apps to many more people.

5. Function Calling Support

Gemma 3 supports “function calling,” which means it can trigger other programs to do things. This facilitates the automation of complex tasks, enhancing the overall functionality and utility of applications built with it.

6. Quantization Support

The models come in “quantized” versions that use less memory and computing power while still being accurate. These versions range from full 32-bit precision down to tiny 4-bit versions, so developers can choose what works best for their needs.

7. Easy Integration with Existing Tools

It plays nicely with lots of popular development tools like Hugging Face Transformers, Ollama, JAX, Keras, PyTorch, Google AI Edge, UnSloth, vLLM, and Gemma.cpp. 

8. Easy to Customize

It comes with recipes for fine-tuning and running it efficiently. Developers can train and adapt the model using platforms like Google Colab, Vertex AI, or even a gaming GPU. 

9. Works Great on NVIDIA GPUs

NVIDIA has specially optimized these models to work well on all their GPUs, from the small Jetson Nano to their newest Blackwell chips. 

How Gemma 3 Compares to Other AI Models

This family has scored impressively on AI benchmarks. The 27B version scored 1338 on the Chatbot Arena Elo leaderboard, putting it in the same league as much bigger models. What’s really amazing is that while some competing models need up to 32 huge NVIDIA H100 GPUs (which cost thousands of dollars each), the 27B variant needs just one GPU. That’s like getting sports car performance for the price of a compact car!

Real-World Uses for Gemma 3

1. Smart Apps on Your Phone

Gemma 3’s efficiency makes it perfect for creating smart apps that run directly on your phone. Developers can build AI assistants, language translators, content creators, and image analyzers that work quickly without needing to connect to the cloud all the time.

2. Edge Computing

For Internet of Things (IoT) devices and edge computing, it lets AI processing happen right where the data is collected. This reduces the need to send data back and forth, which saves bandwidth and keeps private data local.

3. AI for Small Businesses

Gemma 3 makes advanced AI available to organizations with limited resources. Small and medium businesses can now use sophisticated AI without spending a fortune on cloud computing. They can run its applications on the computers they already have.

4. Educational Tools

Schools and universities can use it to help students learn about AI. Students can experiment with cutting-edge AI on regular school computers, and researchers can innovate without needing super expensive systems.

Getting Started With Gemma 3

Developers can try them instantly in their web browser using Google AI Studio. No complicated setup needed! They can also get an API key from Google AI Studio to use it with Google’s GenAI SDK.

For those who want to adapt it to their specific needs, the models are available for download from Hugging Face, Ollama, or Kaggle. You can easily fine-tune and adapt the model using Hugging Face’s Transformers library or other tools you prefer.

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Picture of Faizan Ali Naqvi
Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

Alibaba Introduces VACE, The Ultimate AI Model That Takes Video Editing to the Next Level

Alibaba is on fire when it comes to AI. The company keeps dropping one AI model after another, including image generators, video generators, chatbots, and much more. Now, they have introduced VACE, a super cool all-in-one AI model for creating and editing videos. Whether you want to generate new videos, edit existing ones, or manipulate specific parts of a clip, VACE has got you covered. Most AI video tools focus on just one or two tasks, maybe simple editing, image generation, basic animation, or color adjustments. But Alibaba’s VACE does it all in one place. 

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Key Features of Alibaba VACE for Video Creation and Editing

VACE comes packed with amazing features that change how we make and edit videos. It handles tasks like reference-to-video generation (R2V), video-to-video editing (V2V), and masked video-to-video editing (MV2V). Moreover, it offers cool features like Move-Anything, Swap-Anything, Reference-Anything, Expand-Anything, and Animate-Anything.

1. Text-to-Video Generation (T2V)

VACE includes an amazing Text-to-Video Generation (T2V) feature, which is one of the most basic yet powerful video creation capabilities. You just provide a text prompt, and the video is generated accordingly.

2. Reference-to-Video Generation Feature

VACE’s Reference-to-Video (R2V) feature lets users generate new videos based on reference images. If you have a certain style or aesthetic in mind, VACE can analyze that and create videos that match it.

2. Video-to-Video Editing Feature

This feature lets users make changes to existing videos. It can help you apply a new visual style, change elements in a scene, or tweak colors. The best part? It does all of this while keeping edits smooth and natural, with no weird jumps or inconsistencies.

3. Masked Video-to-Video Editing Feature

This feature lets you edit specific parts of a video. You can define a specific area in the video and make changes to just that part, leaving the rest untouched. This makes it perfect for everything from fixing mistakes to adding new creative elements.

Alibaba Introduces VACE, The Ultimate AI Model That Takes Video Editing to the Next Level

4. Move-Anything Feature

This feature lets users grab objects in a video and move them around while keeping everything looking smooth and natural. Just select, move, and watch the AI do the heavy lifting. It even understands perspective and occlusions, so objects blend right into their new spots without looking out of place. 

5. Swap-Anything Feature

This feature swaps anything out of a video without it looking fake. Whether it’s changing a person’s outfit, replacing a background, or switching out objects, the AI ensures the new elements match the original’s motion, lighting, and surroundings. This is a game-changer, especially for virtual try-ons.

6. Reference-Anything Feature

This feature takes style transfer to the next level. Instead of just applying a filter, VACE lets users bring in colors, textures, and even composition elements from one video or image and apply them to another.

7. Expand-Anything Feature

This feature helps you adjust a video’s aspect ratio without awkward cropping or stretching. It extends the frame, generating new visuals that match the existing scene. Whether you’re repurposing a landscape video for a vertical format or adjusting a shot to fit different screens, this feature makes sure everything looks natural and cohesive. 

8. Animate-Anything Feature

This feature turns still images into moving visuals. With Animate-Anything, VACE analyzes a static image, figures out what could move naturally, and creates realistic motion sequences. You can add subtle movement or full-blown animations. This is perfect for breathing life into any photo.

Performance Evaluation of VACE

What makes VACE stand out? Most AI models focus on just one or two specific tasks. VACE is being built to unify multiple video-editing functions within a single framework. To test its performance, researchers developed the VACE-Benchmark, a framework designed to evaluate video generation quality across multiple factors. 

Compared to task-specific models like I2VGenXL, CogVideoX-I2V, ProPainter, and Control-A-Video, VACE has demonstrated competitive or even superior results in human and automated evaluations. The model showed impressive performance across aesthetic quality, background consistency, dynamic degree, imaging quality, motion smoothness, overall consistency, subject consistency, and temporal flickering, marking it as the best all-in-one tool.

Alibaba Introduces VACE, The Ultimate AI Model That Takes Video Editing to the Next Level

Potential Applications of VACE

VACE has the potential to shake up multiple creative fields. Here’s how it could be used:

1. Film and Video Production

It can help streamline post-production workflows by enabling seamless editing and video generation.

2. Advertising

The Alibaba VACE can create high-quality video ads with specific reference materials and controlled stylistic elements.

3. Gaming and Animation

It can generate animated sequences or game cinematics based on reference imagery or existing footage.

4. Social Media Content

This video model can help creators quickly produce and edit high-quality videos for various platforms.

5. Virtual Reality

It can expand the possibilities for creating immersive visual experiences.

By combining multiple video editing and generation tools into one model, VACE could become a go-to solution for industries that need speed, quality, and creative flexibility

Accessibility and Availability

While VACE has been introduced, it’s not publicly available yet. But, the model and code are expected to be released soon, along with support for ComfyUI workflow, VACE-Benchmark, Wan-VACE Model Inference, and LTX-VACE Model Inference. If the early tests are any indication, this could be one of the biggest leaps in AI-driven video editing yet. Stay tuned for updates!

For more technical details, you can check the model paper.

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Picture of Faizan Ali Naqvi
Faizan Ali Naqvi

Research is my hobby and I love to learn new skills. I make sure that every piece of content that you read on this blog is easy to understand and fact checked!

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