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Today:

• Sakana.AI’s System Writes Research Paper

• OpenAI Launches o1-Pro AI Model

• xAI, Nvidia Join $30B AI Fund

• Retailers Face OpenAI Agent Challenge

• xAI Launches Image Generation API

• Microsoft Unveils Model Context Protocol

Sakana's "AI SCIENTIST" just did it…

An AI system developed by Sakana.AI successfully generated a peer-reviewed scientific paper, marking a milestone in AI-driven research. The AI independently formed a hypothesis, designed experiments, ran tests, analyzed data, and wrote the paper. 

While its work was high-quality, it contained errors, including misattributed citations. This raises questions about AI’s role in science, bias in evaluation, and the broader implications of AI surpassing human capabilities in research and innovation.

WATCH THE VIDEO ON YOUTUBE

OpenAI Launches o1-Pro AI Model

OpenAI launched o1-pro, a more powerful version of its o1 AI model, in its developer API. It uses more computing power to improve accuracy but comes at a high price—$150 per million tokens for input and $600 per million tokens for output. While OpenAI hopes its better performance justifies the cost, early reviews suggest only slight improvements over the original o1, raising doubts about its value.

Why It Matters

1. High Cost Barrier – o1-pro's pricing limits access to elite developers, affecting AI accessibility.

2. Incremental Gains – Modest improvements raise concerns about the trade-off between power and cost.

AI Model Competition – Challenges OpenAI’s dominance as competitors may offer better performance at lower prices.

xAI, Nvidia Join $30B AI Fund

​Elon Musk's xAI and Nvidia have joined forces with BlackRock, Microsoft, and Abu Dhabi's MGX to launch the AI Infrastructure Partnership, aiming to raise an initial $30 billion, with plans to reach up to $100 billion, to develop data centers and energy projects essential for AI advancements. ​

Why This Matter

1. Enhanced AI Infrastructure: The substantial investment addresses the growing demand for robust infrastructure, facilitating the development and deployment of advanced AI applications.​
   

2. Collaborative Industry Effort: The partnership exemplifies a significant collaboration between leading technology companies and financial institutions, highlighting the critical importance of AI in various sectors.​
   

3. Energy Consumption Focus: By targeting energy projects, the initiative acknowledges and aims to manage the increasing energy requirements associated with large-scale AI operations, promoting sustainable AI growth.

Retailers Face OpenAI Agent Challenge

OpenAI’s AI "agents" can browse the web to automate tasks like shopping, threatening companies like DoorDash, which rely on human visitors for ad revenue. As AI agents improve, they could replace consumer apps, making AI firms dominant intermediaries. Some companies, like Walmart, consider building their own AI agents. While AI-driven referrals may help businesses, the rise of agents could shift power from retailers to AI platforms.

Why This Matters

AI Disrupts Digital Markets: AI agents could change how businesses attract customers, impacting ad-driven models.

1. AI as an Intermediary: If AI agents dominate, companies may lose direct customer relationships.

2. AI-Powered Competition: Businesses may need their own AI agents to stay relevant in a shifting market.

🧠RESEARCH

RWKV-7 "Goose" with Expressive Dynamic State Evolution

RWKV-7 "Goose" is a new AI model that processes language efficiently with constant memory and speed. It outperforms similar models on multilingual tasks despite using fewer training data. It introduces improved learning techniques and can track information better than Transformers. The team has open-sourced the model, dataset, and training code.

DAPO: An Open-Source LLM Reinforcement Learning System at Scale

DAPO is an open-source system for training AI models using reinforcement learning (RL) at scale. It reveals key training techniques that other major AI labs keep secret. Using the Qwen2.5-32B model, it achieves high reasoning performance. The team shares their code and data to help researchers improve large-scale AI training.

Impossible Videos

The Impossible Videos study explores AI’s ability to create and understand videos that defy reality, like breaking physics or biology rules. The team introduces IPV-Bench, a benchmark to test these capabilities. Their findings highlight current limitations and suggest improvements for future AI video models in creativity and reasoning.

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Claid AI - AI-powered photo enhancement platform designed specifically for e-commerce businesses to improve user-generated content and product imagery.

DeepBrain AI - Create hyper-realistic AI-generated videos and virtual human avatars. 

Magical AI - AI-powered productivity tool designed to streamline repetitive tasks and enhance workflow efficiency across various platforms.

AI Code Converter - AI-powered platform that simplifies and accelerates the coding process across multiple programming languages.

Character AI - AI-powered chatbot platform that allows users to interact with a wide variety of virtual characters through text-based conversations. 

📲SOCIAL MEDIA

🗞️MORE NEWS

• Elon Musk’s xAI launched an image-generation API, offering a single model at $0.07 per image. Unlike competitors, it lacks customization features. xAI seeks revenue growth and funding while expanding its AI capabilities and data center operations.

• Microsoft introduced Model Context Protocol (MCP) in Copilot Studio, enabling seamless integration of AI apps and data sources. MCP simplifies agent management, supports enterprise security, and allows dynamic actions.

• Nvidia has reportedly acquired Gretel, a synthetic data startup, for over $320 million. Gretel’s technology will integrate into Nvidia’s AI services. The acquisition aligns with industry trends as tech giants increasingly rely on synthetic data for AI training.

• Hugging Face urges the Trump administration to back open-source AI, arguing it boosts competition, security, and economic growth. Their proposal contrasts with Big Tech’s push for minimal regulation and centralized AI development in the U.S.

• Raj Aggarwal, AWS’ generative AI lead, is leaving to start a new company. He previously founded and sold two startups. His AWS contributions include Bedrock AI and Amazon Q. Details about his new venture remain undisclosed.

• Razer unveils Wyvrn, a game development platform featuring AI-driven tools like AI QA Copilot for automated bug testing and AI Gamer Copilot for real-time gameplay tips. Wyvrn also includes haptics, audio enhancements, and expanded RGB integration.

• OpenAI's Noam Brown suggests AI reasoning models could have emerged 20 years earlier with the right approach. Speaking at Nvidia's GTC, he highlighted test-time inference as key to improving AI accuracy. Brown also noted academia’s role in AI research despite limited computing resources.