OpenAI's latest image generation model has taken the world by storm, delivering unprecedented capabilities that have left the competition in the dust. This cutting-edge tool has the ability to create stunning images in the style of Studio Ghibli, showcasing its remarkable versatility.

To demonstrate the power of this model, let's take a look at a conversation our team member, Dom, had with the new OpenAI image generation tool. He started by creating a 3D model of a black Labrador on a transparent background, and then prompted the model to generate a different view of the Labrador. The tool seamlessly transitioned to creating a screenshot of a video game, with the Labrador character integrated into a 2D pixel art-styled adventure game.

This example highlights the remarkable flexibility of the OpenAI image generator. It seamlessly blends language model capabilities with image creation, allowing users to explore a wide range of creative possibilities. From generating unique character designs to crafting entire game scenes, this tool is a game-changer in the world of generative AI.

If you haven't had a chance to explore this incredible release, be sure to check out the two in-depth videos we've already published on the channel. We're also working on a dedicated use case video, as there is simply so much you can do with this tool that it deserves an entire video to showcase its capabilities.

Google's Gemini 2.5 Pro model is a remarkable advancement in the world of large language models. This cutting-edge AI system has been hailed as potentially the best thinking model ever released, with the only potential competition being OpenAI's GPT-4.

When it comes to benchmarks, Gemini 2.5 Pro outperforms many of the top models, including Claude 3.5, Sonnet, and GPT-4 mini. It boasts an impressive 18.8% score on the notoriously challenging Benchmark, showcasing its exceptional capabilities.

One of the standout features of Gemini 2.5 Pro is its impressive 1 million token context window. This allows the model to maintain and utilize an extensive amount of contextual information, leading to exceptional performance even with long-form inputs. In fact, at 120,000 tokens of context, Gemini 2.5 Pro scores an impressive 90.6 out of 100, far surpassing the competition.

While the benchmarks and specifications of Gemini 2.5 Pro are undoubtedly impressive, the real test lies in its real-world adoption and usage. As the model is integrated into Google's Gemini Studio, users can leverage the robust tooling and features that come with the platform. However, the timing of the Gemini 2.5 Pro release was overshadowed by the highly anticipated OpenAI image generation announcement, which may impact its initial reception.

Nonetheless, Gemini 2.5 Pro represents a significant advancement in the field of large language models, and its performance on various benchmarks and its long-context capabilities make it a compelling option for those seeking a powerful thinking model.

China's DeepSEEK has once again made waves in the AI community with the release of their latest model, DeepSEEK V3E. This non-thinking model is a direct competitor to the likes of GPT-4.5 and Sonnet 3.7, and it crushes the benchmarks.

What sets DeepSEEK V3E apart is its open-source nature. The model has been released under the MIT license, meaning anyone can download and use it in their own applications, without the need for an API or paying per usage. This move by DeepSEEK is a game-changer, as it provides free access to a high-performing language model that can rival the best in the industry.

When compared to the top non-thinking models, DeepSEEK V3E stands toe-to-toe, if not surpassing them in certain benchmarks. This open-source release is a clear challenge to the Western AI companies, pushing them to innovate and release their own cutting-edge models.

The availability of DeepSEEK V3E as an open-source model means developers and researchers can integrate it into their projects without the constraints of proprietary APIs or licensing fees. This democratization of AI technology is a significant step forward, empowering a wider range of individuals and organizations to leverage the power of advanced language models.

In summary, DeepSEEK V3E is a remarkable open-source AI model that showcases the continued progress and innovation in the field of generative AI. Its performance, coupled with its accessibility, makes it a compelling option for those looking to incorporate state-of-the-art language capabilities into their applications.

Anthropic has released an exciting new "think" tool that enables their language model, Claud, to selectively pause and think in complex situations. This represents a significant step forward in the evolution of AI models.

Currently, AI models can be divided into two categories: non-thinking models and thinking models. Non-thinking models simply generate responses without any internal deliberation, while thinking models take the time to ponder before providing an answer.

Anthropic's new tool bridges this gap by allowing a non-thinking model, like Claud, to engage in selective thinking. When the model encounters a situation that warrants deeper consideration, it can utilize the "think" tool to pause, analyze the problem, and then generate a more thoughtful response.

This approach is likely the future of many AI products. Rather than forcing users to choose between different model types, the models will adaptively decide when to think and when to simply respond. This will provide a more seamless and intelligent user experience, without the need for the user to understand the intricacies of the underlying model architecture.

Anthropic's innovation in this area demonstrates their forward-thinking approach and positions them as a leader in the development of advanced AI systems. As the field of generative AI continues to evolve, we can expect to see more innovative solutions that blur the lines between thinking and non-thinking models, ultimately delivering more capable and user-friendly AI assistants.

Last Thursday, OpenAI released new developer tools to make it easier than ever to create voice-enabled chatbots. These tools cover all aspects of voice AI, including text-to-speech, speech-to-text, and transcription, powered by updated models like an enhanced Whisper and new speech-to-text models.

With these new API endpoints, any app developer can now integrate high-quality voice AI features into their products. The OpenAI audio API ranks among the top options, alongside services like Scribe and Sonix, based on our extensive testing and comparisons.

For consumers, services like Scribe and Sonix provide a great balance of performance and affordability for transcription needs. But for app developers looking to build voice-enabled experiences, the OpenAI audio tools are hard to beat in terms of quality and ease of integration.

This release is another step forward in making conversational AI more accessible and ubiquitous across various applications. As the AI landscape continues to evolve rapidly, tools like these from OpenAI are crucial in empowering developers to bring voice-powered features to life.

Andre Karpiński, the head of AI at Tesla and a co-founder of OpenAI, has demonstrated the power of AI in building iOS applications. In a series of chats with ChatGPT, Karpiński was able to create a legitimate iOS application, despite having limited experience in iOS development.

The process Karpiński followed is fascinating, as it showcases the potential of "vibe coding" - a term he himself coined. Through a step-by-step approach, Karpiński was able to leverage ChatGPT's natural language processing capabilities to guide him through the development process, from ideation to implementation.

The chats Karpiński shared provide a unique insight into the thought process and prompting techniques used to build the iOS app. By carefully crafting his requests and providing context, Karpiński was able to extract the necessary code, design elements, and even troubleshoot issues that arose during the development.

This use case highlights the transformative potential of AI in the realm of software development. As language models continue to evolve, the ability to create complex applications, such as mobile apps, using natural language interactions becomes increasingly feasible. This approach could democratize app development, empowering individuals with limited coding experience to bring their ideas to life.

The success of Karpiński's project serves as a testament to the rapid advancements in AI and its potential to reshape various industries, including software engineering. As the AI landscape continues to evolve, we can expect to see more innovative applications of these technologies in the development of mobile apps and beyond.

If you're viewing this video, chances are you realize how fast AI moves - a new feature or brand new model every single week. For most, it's almost impossible to keep up. That's why I want to show you two things - one that's completely free, and one that's paid. Both are created by us at the AI Advantage.

The free option is the LLM rankings that you might already know about. This really is the answer to the question "Hey, if I only have 10 minutes a month and I want to stay on top of AI, what do I do?" You simply check out our rankings, which we update every single month. With a quick glance, you'll be able to see what tools are at the top right now for that particular month. If you're curious about one of them, you can scroll down and look at the reasoning. This is freely accessible, and we do this across LLM platforms, image generation tools, and video generation tools every single month.

If you're looking for more in-depth knowledge, that's why we built the AI Advantage community. One of the things we do in the community is release brand new guides and resources on a weekly basis. You can get a taste for some of these in the free area of our community, where we share various guides and previews of courses we have inside.

But let me just go inside the paid area of the community, sort these by the most popular ones, and show you this massive guide on cannabis and all the hidden features within. There really is a lot here, including various little tips and tricks that you might not have known, and there's a comment section underneath where people share their own encounters and solutions.

You might think to yourself, "Hey, AI moves so quickly. What's the point of doing all these guides if they're going to be outdated anyway?" Well, actually, in March 2025, we went through the work, and all 12 members of the team updated every single guide in our community - that's over 150 guides. Some had to go through a complete overhaul, some just needed minor updates, but pretty much two-thirds of these needed some editing to them, and all of them are updated for today.

Whether you want to put yourself into movie scenes or get step-by-step workflows from the latest features, this is the place to get it. And one final note here is that you can really use these guides in a creative way. For example, you can copy-paste the whole guide and then run a prompt like "Which one of these OpenAI deep research prompts could I use to improve this?" The AI assistant will look at all the content and use the step-by-step tutorials and knowledge inside the guide to suggest prompts that could work really well with your current project.

So you don't even have to read the guide - you just have to know how to copy-paste, and then the AI will suggest complementary use cases that you might not have thought of yourself. And you can do this with every single one of the 150 guides, all of which are handwritten, step-by-step guides with all the details that ChatGPT needs to help you with your tasks.

It's not just that you have access to them by joining the community - it's also that your AI assistant gets access to these, and you get all that and so much more inside the AI Advantage Community. That's just a quick little hack that I wanted to share with you today.

When it comes to text-to-image generation, the competition is fierce. We ran a series of comparison prompts to put OpenAI's GPT-4 image generation, Ideogram, and R to the test.

One prompt we used was a "photo of a highway road with a large billboard by the side of the road that says this text written in bold letters on the billboard - cars passing by." Let's take a look at the results:

OpenAI GPT-4 Image Generation: The text on the billboard is flawless, and the overall realism of the image is impressive.

Ideogram: The text on the billboard also looks great, with only a few minor letter inconsistencies when running the prompt multiple times. The image quality is fantastic.

R: The text is perfect every time, but the image quality has a few quirks, like the wooden posts disappearing into nowhere and some odd car placements.

Overall, while all three models perform exceptionally well, GPT-4 and Ideogram seem to have a slight edge when it comes to both text accuracy and overall image quality. The convenience of having image generation directly within the ChatGPT interface also makes GPT-4 a strong contender.

However, the competition is fierce, and each model has its own strengths. I encourage you to try out these tools and see which one works best for your specific needs.

As the AI landscape continues to rapidly evolve, we've seen a flurry of groundbreaking releases this week. From OpenAI's impressive image generation capabilities to Google's Gemini 2.5 Pro model and the open-sourcing of DeepSEEK v3, the advancements in generative AI are truly remarkable.

The benchmarks and capabilities of these models are pushing the boundaries of what's possible, with Gemini 2.5 Pro showcasing exceptional performance, especially in long-context scenarios. Meanwhile, the open-sourcing of DeepSEEK v3 further democratizes access to high-quality language models.

Anthropic's developments, including the integration of web browsing and the "think tool" for selective reasoning, highlight the ongoing efforts to create more versatile and intelligent AI assistants. The adoption of Anthropic's MCP protocol by OpenAI is a significant step towards a more interoperable ecosystem.

The release of OpenAI's new audio models and the insights provided on the various options available for voice-enabled applications further demonstrate the breadth of advancements in the field.

As the AI wars continue, it's clear that the pace of innovation shows no signs of slowing down. Staying up-to-date with the latest developments can be challenging, but resources like the AI Advantage community and the monthly LLM rankings can help you navigate this rapidly evolving landscape.

Whether you're a developer, a creative professional, or simply someone interested in the latest AI breakthroughs, the tools and insights covered in this episode provide a glimpse into the future of generative AI. As we move forward, the ability to leverage these powerful technologies will become increasingly crucial, and the AI Advantage team is committed to equipping you with the knowledge and resources to stay ahead of the curve.