News from the AI & ML world
DeeperML
Alexey Shabanov@TestingCatalog
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OpenAI has recently unveiled its latest reasoning models, o3 and o4-mini, representing state-of-the-art advancements in AI capabilities. These models are designed with a focus on tool use and efficiency, leveraging reinforcement learning to intelligently utilize tools like web search, code interpreter, and memory. OpenAI's o3 demonstrates agentic capabilities, enabling it to function as a streamlined "Deep Research-Lite," capable of delivering rapid responses to complex queries within seconds or minutes, significantly faster than the existing Deep Research model.
While the o3 model excels on benchmarks such as the Aider polyglot coding benchmark, achieving a new state-of-the-art score of 79.6%, its high cost is a point of concern. The model's expense is estimated at $150 per million output tokens, marking a 15-fold increase over GPT-4o. The o4-mini offers a more cost-effective alternative, scoring 72% on the Aider benchmark while costing three times more than Gemini 2.5. However, a combination of o3 as a planner and GPT-4.1 can achieve an even higher score of 83% at 65% of the o3 cost, though this remains an expensive option.
Despite the cost concerns, the agentic nature of o3 allows it to overcome limitations associated with LLM-based searches. By actively planning and using tools iteratively, it provides coherent and complete answers, automatically performing multiple web searches to find up-to-date information. OpenAI is also experimenting with a "Deep Research Mini" tool for free ChatGPT users, powered by a version of o4-mini, aiming to democratize access to advanced AI reasoning capabilities. In related news, The Washington Post has partnered with OpenAI to integrate its journalism into ChatGPT’s search experience, ensuring that users receive summaries, quotes, and direct links to the publication's reporting.
ImgSrc: www.testingcata
References :
While the o3 model excels on benchmarks such as the Aider polyglot coding benchmark, achieving a new state-of-the-art score of 79.6%, its high cost is a point of concern. The model's expense is estimated at $150 per million output tokens, marking a 15-fold increase over GPT-4o. The o4-mini offers a more cost-effective alternative, scoring 72% on the Aider benchmark while costing three times more than Gemini 2.5. However, a combination of o3 as a planner and GPT-4.1 can achieve an even higher score of 83% at 65% of the o3 cost, though this remains an expensive option.
Despite the cost concerns, the agentic nature of o3 allows it to overcome limitations associated with LLM-based searches. By actively planning and using tools iteratively, it provides coherent and complete answers, automatically performing multiple web searches to find up-to-date information. OpenAI is also experimenting with a "Deep Research Mini" tool for free ChatGPT users, powered by a version of o4-mini, aiming to democratize access to advanced AI reasoning capabilities. In related news, The Washington Post has partnered with OpenAI to integrate its journalism into ChatGPT’s search experience, ensuring that users receive summaries, quotes, and direct links to the publication's reporting.
ImgSrc: www.testingcata
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References :
- composio.dev: OpenAI o3 and o4-mini are out. They are two reasoning state-of-the-art models. They’re expensive, multimodal, and super efficient at tool use. Significantly,
- pub.towardsai.net: Pub.towardsai discusses OpenAIs agentic o3
- TestingCatalog: OpenAI Expands O3 Capabilities With Higher Limits and Task Scheduling
- venturebeat.com: OpenAI launches groundbreaking o3 and o4-mini AI models that can manipulate and reason with images, representing a major advance in visual problem-solving and tool-using artificial intelligence.
Classification:
- HashTags: #OpenAI #ReasoningModels #AIModels
- Company: OpenAI
- Target: AI Researchers, Users
- Product: GPT-4.5, ChatGPT
- Feature: Reasoning Models
- Type: AI
- Severity: Informative