Skill Leap AI - New ChatGPT 4.5 is Here - The Good, The Bad and The UGLY
GPT 4.5, recently released by OpenAI, is available in a $200/month plan and will soon be accessible in other plans. It is not a reasoning model, which limits its performance in benchmarks compared to models like O1 or Deeps R1. However, it excels in emotional intelligence and writing tasks, making it suitable for tasks requiring empathy and human-like interaction. The model has a broader knowledge base and a lower hallucination rate (37% vs. 61%) than its predecessors. Despite these improvements, it struggles with speed and accuracy in some cases, such as providing incorrect information during a cost comparison test. The model's pricing for API usage is also considered impractical for developers due to high costs. While GPT 4.5 shows potential in specific areas, it does not significantly outperform GPT 4 in technical writing or document analysis tasks. Users are advised to wait for GPT 5, which promises to integrate reasoning capabilities and improve speed, eliminating the need to choose between different models for various tasks.
Key Points:
- GPT 4.5 is not a reasoning model, limiting its benchmark performance.
- It excels in emotional intelligence and writing tasks, suitable for empathetic interactions.
- The model has a broader knowledge base and lower hallucination rate than predecessors.
- API pricing is high, making it impractical for developers.
- Users are advised to wait for GPT 5 for integrated reasoning and improved speed.
Details:
1. 🔍 Exploring GPT 4.5: Initial Impressions
- OpenAI released GPT 4.5, and initial testing was conducted over nearly a full day.
- The focus of the initial exploration was to assess the capabilities and improvements over previous versions.
- Specific features tested included natural language processing efficiency, response accuracy, and adaptability across different contexts.
- Initial findings suggest improved response times and more nuanced understanding in complex queries compared to previous versions.
2. 🤔 Access and Availability of GPT 4.5
- The introduction of the clae 3.7 model highlights advancements over the previous chat GPT model, focusing on performance improvements.
- The comparison reveals specific areas of enhancement, such as processing speed and accuracy, which are critical metrics for model evaluation.
- The clae 3.7 model demonstrates a reduction in response time by 20% and an increase in accuracy by 15%, providing tangible improvements over its predecessor.
- These enhancements suggest a strategic focus on refining user experience and operational efficiency in AI models.
- The availability of GPT 4.5 and its integration with existing systems is aimed at maximizing accessibility and leveraging advanced features.
3. 🌀 Overwhelmed by Choices: The Model Landscape
- GPT 4.5 is currently in research preview and only available in the $200/month plan.
- Advised against upgrading solely for access as it will be available in the Plus and Teams plans next week.
- Education and Enterprise plans will receive access the following week.
- GPT 4.5 represents a significant advancement in AI capabilities, promising improved performance and more efficient processes.
- Access to GPT 4.5 is strategically staggered to manage demand and ensure stability across different user bases.
- Users are encouraged to evaluate their current needs and potential benefits of GPT 4.5 before making subscription changes.
4. 🚀 Future Prospects: The Promise of GPT-5
- GPT-5 aims to revolutionize AI model selection by integrating multiple model types into one, eliminating the need for choosing different models for various tasks.
- The 'model picker' feature will facilitate seamless transitions between models optimized for reasoning, writing, speed, and scheduling tasks, significantly enhancing user experience.
- This integration is expected to streamline workflows and improve efficiency by allowing users to leverage a single model for diverse applications, reducing the complexity and time involved in model selection.
5. 📉 Limitations: Not a Reasoning Model
- Open AI acknowledges that while this model is the largest and best for chat, it is not designed as a reasoning model.
- The model's inability to perform complex reasoning tasks means users should be cautious when applying it to scenarios requiring deep logical understanding.
- For instance, tasks that involve multi-step problem-solving or require understanding nuanced human emotions might not be suitable for this model.
- The lack of reasoning capability could impact the effectiveness of the model in fields that require analytical thinking and decision-making.
- Users should consider complementing it with other tools or methods when reasoning is crucial.
6. 📊 Testing Q&A Accuracy and Hallucination Rates
- The AI model demonstrates superior performance in Q&A accuracy, scoring higher than GPT 40 and other reasoning models, indicating a broader knowledge base.
- The Q&A accuracy rate of the AI model stands at 62%, highlighting its effectiveness in providing correct answers.
- The hallucination rate is measured at 37%, which is lower than other models, suggesting better reliability in information generation.
- Testing methodology involved benchmarking against industry standards, ensuring the accuracy rate reflects real-world application scenarios.
- The lower hallucination rate implies a reduced likelihood of generating incorrect or misleading information.
- These metrics suggest the AI model's enhanced capability in understanding and accurately responding to queries, making it a viable option for applications requiring high precision.
7. 🤗 Emotional Intelligence: Does GPT 4.5 Deliver?
- GPT 4.5 demonstrates a high level of emotional intelligence, particularly excelling in tasks that require human-like empathy and conversational skills.
- A performance metric of 61% indicates its effectiveness in delivering emotional responses that are comparable to human interactions, outperforming the 37% benchmark of earlier models.
- The model is rigorously tested for hallucinations to ensure the accuracy and reliability of its empathetic interactions, making it trustworthy for specific applications.
- In practice, GPT 4.5 is being used in customer service to provide personalized and empathetic responses, significantly improving customer satisfaction and engagement metrics.
- For example, a case study showed a 20% increase in customer satisfaction scores when using GPT 4.5 in automated support systems compared to previous AI models.
8. 💲 Cost Analysis: API Pricing Concerns
- The cost of using GPT 4.5 for API development is $75 per million tokens, which is significantly higher compared to GPT 40, priced at $25 per million tokens. This considerable cost difference is crucial for developers considering API usage for automation and other applications.
- Developers need to weigh these costs against their budget constraints, particularly when scaling applications that require high token usage.
- An unspecified model is priced at 15 cents, but the context and comparative benefits of this model remain unclear without further details.
- Understanding the pricing structure and its potential impact on project budgets can guide developers in choosing the most cost-effective API solution.
- Businesses must consider these pricing differences in their strategic planning to avoid unexpected expenses in their development projects.
9. 🔍 Hallucination Test: Fact-Checking Capabilities
- The initial pricing of $150 for developers using AI was considered unreasonable, suggesting a potential market misalignment. Accurate pricing is crucial for strategic planning and market entry.
- Early attempts at fact-checking resulted in incorrect data, such as using 4.5 instead of 150, which underscores the need for improved accuracy in AI systems. This inaccuracy can lead to significant strategic missteps in development cycles.
- The initially provided source was not accessible, casting doubts on the reliability and verification process of AI outputs. Reliable sourcing is essential for trust in AI-driven insights.
- Upon re-evaluation, correct information was obtained from verified sources like OpenAI and Anthropic, demonstrating that AI needs robust mechanisms for sourcing and validity checks to ensure factual accuracy.
- AI errors, such as inaccurately reporting costs as half the actual amount, can drastically affect app development budgets and strategic decisions. Ensuring data accuracy in AI systems is critical to avoid costly mistakes.
10. ✍️ Writing and Emotional Tone: Empathy in Communication
- A test introduced a fictional mango variety, 'orange cream,' and the AI responded with detailed, yet fabricated, information, illustrating AI's potential to produce misinformation.
- The AI's response consistency, regardless of search capability, underscores the risk of plausible but unverified content generation.
- Highlights the critical need for systems to verify AI outputs, especially where factual accuracy is essential.
- The findings emphasize the challenge for developers to prevent AI from spreading misinformation and the importance for users to critically evaluate AI-generated content.
11. 📝 Technical Writing: Practical Tips and Comparisons
- The presenter emphasizes transparency by not cherry-picking results, showcasing the outcomes of the first attempt with models.
- Search results using certain models, such as ChatGPT 4.5, can still be inaccurate or fabricated, as demonstrated by examples like the 'orange cream' query.
- When tasked with creating a sincere message for a sensitive situation (laying off half a team), the model demonstrated strong emotional intelligence and effective communication skills.
- Subtle improvements in model versions, such as from 4.0 to 4.5, can affect output quality, particularly in areas like emotional tone and empathy.
12. 💡 Idea Generation: Business Innovation with AI
12.1. AI Writing and Suggestions Evaluation
12.2. Innovative AI Business Ideas
13. 🔍 Document Analysis: Red Flags and Recommendations
13.1. AI Tools for SMEs
13.2. Comprehensive Business Planning
13.3. Document Analysis Capabilities
14. ⚡ Speed and Efficiency: Comparing Performance
- GPT-45 is significantly slower than its predecessor GPT-40, which negatively impacts user experience due to increased wait times. Speed is crucial for user satisfaction, especially in applications requiring quick interactions.
- The speed issue in GPT-45 is notable because it is not classified as a reasoning model, which typically requires more processing time for accuracy. Users expect non-reasoning models to be faster; hence, the lag is unexpectedly problematic.
- Alternative models like Gemini Flash and Claud are highlighted for their faster response times and efficiency compared to GPT-45, offering shorter and more concise answers, which enhances user experience.
- Despite GPT-45's comprehensive responses, the speed and efficiency of competing models make them more attractive for users needing quick results, underscoring the importance of balancing detail with speed.
- The anticipation for future models like GPT-50 is high, with expectations for improved speed and a default reasoning capability that could simplify user choices by combining the best of both worlds—speed and detailed reasoning.