AI Explained - Did AI Just Get Commoditized? Gemini 2.5, New DeepSeek V3, & Microsoft vs OpenAI
Gemini 2.5 Pro, Google's latest AI model, is claimed to be their most intelligent yet, excelling in benchmarks like humanity's last exam, which tests obscure trivia and complex reasoning. Despite its strengths, the model's performance is converging with others like Claude 3.7 and OpenAI's models, indicating a trend towards commoditization in AI. This convergence suggests that AI models are improving together, with performance differences narrowing across various tasks such as mathematics, science, and coding.
DeepSeek V3, another new model, shows similar trends of convergence. It performs comparably to OpenAI's GPT 4.5 in several areas, challenging the notion that any single company holds a significant lead in AI development. This convergence is further supported by Microsoft's claims that their AI models can nearly match leading models from OpenAI and Anthropic. The commoditization of AI models implies that the primary differentiator is now the amount of compute power a company can afford, rather than unique technological advancements.
Key Points:
- Gemini 2.5 Pro excels in benchmarks but shows performance convergence with other models.
- DeepSeek V3 performs comparably to OpenAI's GPT 4.5, indicating no clear leader in AI.
- AI model performance is becoming commoditized, with compute power as the main differentiator.
- Microsoft claims their AI models nearly match leading competitors, supporting commoditization.
- AI models are improving together, narrowing performance gaps across various tasks.
Details:
1. 🚀 New AI Models Released
- Multiple new AI models, including GPT40 image generation, DeepSeek V3, and Gemini 2.5 Pro, were released simultaneously, highlighting rapid advancements in AI technology.
- Gemini 2.5 Pro is highly regarded at Google as potentially the best AI language model, but it lacks ultra or nano versions, indicating a focused development approach.
- While DeepSeek V3's open-weight release suggests transparency, Gemini 2.5 Pro's architecture details remain undisclosed, emphasizing competitive secrecy in AI.
- Microsoft's CEO views AI models as commoditized, purchased for performance, reflecting a shift towards AI as a standard technology rather than scarce innovation.
- The CEO's comments imply that companies like OpenAI are transitioning from exclusive AI research to broader product-focused strategies, indicating a maturing industry.
- These developments suggest that the AI industry is moving towards democratization and standardization, raising questions about the future of AI innovation.
2. 🔍 In-Depth Analysis of Gemini 2.5
- Gemini 2.5, Google's latest AI model, was released shortly after Gemini 2, demonstrating rapid development and deployment.
- The model excels in knowledge-intensive benchmarks, showcasing superior performance in obscure trivia and complex translations, surpassing many competitors.
- In science-related tasks, Gemini 2.5 Pro matches the performance of leading models like Claude 3.7, indicating its strong capabilities in difficult scientific queries.
- Gemini 2.5 leads in visual understanding tests, achieving near-human performance in the Vista benchmark by Scale AI, highlighting its advanced visual processing abilities.
- Despite the improvements, the AI field is seeing a convergence in performance, with many models delivering similar results when given equal computing resources.
- Gemini 2.5 sets a new state-of-the-art in reading tables and charts, enhancing its utility in data analysis tasks.
- The model's performance on the MMU benchmark is particularly notable, underscoring its advanced capabilities in integrating visual and logical reasoning tasks.
- There remains a significant performance gap in the language model arena, with Gemini 2.5 maintaining a leading position over other models.
3. 📈 Explaining Deep Seek V3
- Gemini 2.5 Pro can process up to a million tokens, approximately 750,000 words, surpassing other models that handle less than a quarter of that capacity.
- Performance across different AI model families is converging, suggesting similar capabilities are being developed.
- Gemini 2.5 Pro is currently available for free on Google's AI studio, but this is subject to change.
- The model includes a search capability, a feature also available in Chat GBT and soon in Claude.
- In the Simplebench benchmark for common sense reasoning, Gemini 2.5 Pro scored 5 out of 10, an improvement from Gemini 2 Pro's score of 1, aligning with Claude 3.7's performance.
4. 📉 Commoditization of AI Models
- Deep Seek V3 announced as a new base model, analogous to GPT 4.5, expected to support the upcoming R2 reasoning model.
- Performance convergence observed across AI models, with Deep Seek V3 and GPT 4.5 showing comparable capabilities.
- Deep Seek V3 demonstrates superior performance in mathematics and coding compared to GPT 4.5, but slightly underperforms in science and general knowledge.
- OpenAI's GPT 4.5 was anticipated to be significantly ahead of Chinese AI models, yet they are now comparable, indicating rapid advancements in Chinese AI development.
- Commoditization of AI suggests that the primary differentiator is the amount of financial investment in computing power, rather than inherent model capabilities.
- The commoditization of AI models implies a shift in competitive advantage towards those with greater computational resources, potentially reducing the impact of unique technological breakthroughs.
5. 🛠️ Microsoft and OpenAI's Rivalry
- Microsoft's internal AI unit, led by Mustafa Suleyman, is actively pursuing the development of AGI, reflecting a strategic push into advanced AI capabilities.
- Tensions arose between Microsoft and OpenAI when Microsoft was denied access to OpenAI's technical advancements, highlighting competitive dynamics.
- Microsoft reports that their AI models now perform comparably to leading models from OpenAI and Anthropic on benchmarks, indicating significant progress in AI capabilities.
- The company is leveraging AI technologies to boost revenues, notably through increased sales of cloud and AI services to clients like the Israeli army during the Gaza conflict, as reported by 972 Magazine.
- CEO Satya Nadella has expressed confidence in Microsoft's AI strategy by indicating that AI models are commoditizing, suggesting a strategic focus on broad applicability rather than being the top performer.
6. 💡 The Future of AI in Coding
- Anthropic's CEO predicts that AI will soon write 90% of code within 3 to 6 months and potentially all code within the next 12 months, indicating a rapid progression in AI capabilities.
- Despite these predictions, Anthropic continues to hire software engineers with competitive salaries, suggesting that human expertise remains crucial in the development process.
- Current AI models, such as Claude, exhibit limitations, struggling with tasks like playing Pokémon, demonstrating that AI has not yet reached human-level problem-solving abilities in all areas.
- The release of Google's Gemini is described as a convergence in AI technology rather than a groundbreaking advancement, contrasting with the innovations seen in OpenAI's Image Gen.
- The potential impact of AI writing code includes significant changes in the job market for software engineers, highlighting the need for adaptation in skillsets and roles.
- Background on AI's current capabilities, such as the ability to automate repetitive coding tasks, is necessary to understand the shift towards AI-driven development.