OpenAI Just Shocked the World "gpt-o1" The Most Intelligent AI Ever!

So in our last video, we discussed OpenAI's upcoming model, which we referred to by its internal codename, Strawberry. The anticipation has been building and now the wait is over. OpenAI has officially unveiled their latest AI model, now known as OpenAI 01 Preview. There's actually a lot to cover, so let's get into it. Alright, so OpenAI O1 preview is part of a new series of reasoning models designed to tackle complex problems that by spending more time thinking before responding. Unlike previous models like GPT4 and GPT4O, which focused on rapid responses, O1 Preview emphasizes in depth reasoning and problem solving. This approach allows the model to reason through intricate tasks and solve more challenging problems in fields such as science, coding and mathematics. Starting from September 12th, OpenAI released the first iteration of this series in ChatGPT and their API. This releases a preview version with regular updates and improvements expected. Alongside this, they've included evaluations for the next update that's currently in development. This means we're witnessing the beginning of a significant evolution in AI capabilities. So how does this new model work? OpenAI trained O1 Preview to spend more time deliberating on problems before providing an answer, much like a person tackling a difficult question. Through this training, the model learns to refine its thought process, experiment with different strategies, and recognize its mistakes. This method is known as chain of thought reasoning. In terms of performance, O1 preview shows substantial improvements over its predecessors in internal tests. The next model update performs similarly to PhD students on challenging benchmark tasks in physics, chemistry and biology. For instance, in a qualifying exam for the International Mathematics Olympiad, GPT4O correctly solved only 13% of the problems. In contrast, the new reasoning model achieved an impressive 83% success rate. This represents a significant leap in problem solving capabilities when it comes to coding abilities, the model has been evaluated in CodeForces competitions, reaching the 89th percentile for context. CodeForces is a platform for competitive programming contests, and ranking in the 89th percentile indicates a high level of proficiency. These results suggest that O Preview is not just better at reasoning, but also excels in practical applications like coding. As an early model, O1 Preview doesn't yet have some of the features that make ChatGPT particularly versatile, such as browsing the web for information or uploading files and images. For many common use cases, GPT4O remains more capable. In the near term. However, for complex reasoning tasks, O1 Preview represents a significant advancement and a new level of AI capability. Recognizing this leap, OpenAI has reset the model numbering back to one. Hence the name O1 Safety is a critical aspect of any AI deployment, and OpenAI has taken substantial steps to ensure that O1 Preview is both powerful and safe to use. They've developed a new safety training approach that leverages the model's reasoning capabilities to make it adhere to safety and alignment guidelines. By being able to reason about safety rules in context, the model can apply them more effectively. One method they use to measure safety is by testing how well the model continues to follow its safety rules if a user tries to bypass them, a practice known as jailbreaking. On one of their most challenging jailbreaking tests, GPT4O scored 22 out of 100. In contrast, the O1 preview model scored 84 out of 100, indicating a substantial improvement in resisting attempts to generate disallowed content. To align with the new capabilities of these models, OpenAI has bolstered their safety work, internal governance and collaboration with federal governments. This includes rigorous testing and evaluations using their preparedness framework, Top tier Red teaming, which involves ethical hacking to identify vulnerabilities, and board level review processes overseen by their Safety and Security Committee. They've also formalized agreements with the US and UK AI safety institutes. OpenAI has begun operationalizing these agreements, granting the institutes early access to a research version of the model. This partnership helps establish a process for research, evaluation and testing of future models before and after their public release. The O Preview model is particularly beneficial for those tackling complex problems in science, coding, math and related fields. Healthcare researchers can use it to annotate cell sequencing data. Physicists can generate complex mathematical formulas needed for quantum optics. Developers across various disciplines can build and execute multi step workflows. The enhanced reasoning capabilities open up new possibilities for solving challenging tasks. Delving deeper into the technical aspects the O1 model series is trained using large scale reinforcement, learning to reason using a chain of thought. This means the model generates a sequence of intermediate reasoning steps before arriving at a final answer. These advanced reasoning capabilities provide new avenues for improving the safety and robustness of AI models. By reasoning about safety policies in context, the models achieve state of the art performance on benchmarks for risks such as generating illicit advice, selecting stereotyped responses, and succumbing to known jailbreaks. For example, on the Strong Reject benchmark, a test designed to evaluate a model's resistance to jailbreaks, O1 Preview achieved a goodness score of 84, significantly outperforming GPT4O. OpenAI conducted thorough safety evaluations, including both internal assessments and external red teaming. They used a range of public and internal evaluations to measure O Preview on tasks such as propensity to generate disallowed content, performance on tasks relevant to demographic fairness, tendency to hallucinate, and presence of dangerous capabilities. In disallowed content evaluations, O1 Preview either matches or outperforms GPT4O on their challenging refusal evaluation, Zero1 Preview achieved a not unsafe score of 93.4% compared to GPT4O's 71.3%. This indicates that the model is better at refusing to produce disallowed content while also avoiding over refusal on benign prompts. Regarding hallucinations instances where the model generates incorrect or nonsensical information, O1 Preview shows improvement over GPT4O. In the SimpleQA dataset, O1 Preview's hallucination rate was 44% compared to GPT4O's 61%. However, anecdotal feedback suggests that O1 Preview can be more convincing when it does hallucinate, potentially increasing the risk of users trusting incorrect information. Bias evaluations were also conducted on the BBQ evaluation, which tests for stereotyped responses. O1 Preview selects the correct answer 94% of the time on unambiguous questions, whereas GPT4O does so 72% of the time. This suggests that O1 Preview is less prone to selecting stereotyped options and demonstrates improved fairness. An intriguing aspect of the O1 models is the chain of thought safety. The model's chain of thought reasoning allows for the potential of monitoring their latent thinking processes. OpenAI explored methods for chain of thought monitoring to detect instances where the model may engage in deceptive behavior or generate disallowed content. In their analysis of 100,000 synthetic prompts, only 0.8% of O1 previews responses were flagged as being deceptive. Now, external red teaming played a significant role in their safety assessments. OpenAI collaborated with multiple organizations and individuals to assess key risks associated with the O1 model series improved reasoning capabilities. This included testing the model's resistance to jailbreaks and their ability to handle real world attack planning prompts in terms of their preparedness framework evaluations. OpenAI assessed the models in categories such as cybersecurity, biological, threat creation, persuasion, and model autonomy. Both O1 Preview and O1 Mini were rated as medium risk overall. Specifically, they were rated as medium risk in persuasion and CBRN chemical, biological, radiological, nuclear, and low risk in cybersecurity and model autonomy for cybersecurity. They evaluated the models using capture the flag CTF challenges, which are competitive hacking tasks. The models were able to solve 26.7% of high school level challenges but struggled with more advanced tasks, achieving 0% success in collegiate level and 2.5% in professional level challenges. This indicates that while the models have some capability in cybersecurity tasks, they do not significantly advance real world vulnerability exploitation capabilities in biological threat creation evaluations. The models can assist experts with operational planning for reproducing known biological threats which meets the medium risk threshold. However, they do not enable non experts to create biological threats as this requires hands on laboratory skills that the models cannot replace in persuasion evaluations. O Preview demonstrates human level persuasion capabilities in the Change My View evaluation which measures the ability to produce persuasive arguments, O1 Preview achieved a human persuasiveness percentile of 81.8%. This means the model's responses are considered more persuasive than approximately 82% of human responses Regarding model autonomy, the models do not advance self exfiltration, self improvement or resource acquisition capabilities sufficiently to indicate medium risk. They performed well on self contained coding and multiple choice questions, but struggled with complex agentic tasks that require long term planning and execution. OpenAI has also made efforts to ensure that the model's training data is appropriately filtered and refined. Their data processing pipeline includes rigorous filtering to maintain data quality and mitigate potential risks. They use advanced data filtering processes to reduce personal information from training data and employ their moderation API and safety classifiers to prevent the use of harmful or sensitive content. Now, addressing some of the points we speculated on in the previous video, particularly regarding the model's response times and integration with ChatGPT, the O1 preview model does take longer to generate responses, typically between 10 and 20 seconds. This deliberate pause allows the model to engage in deeper reasoning, enhancing accuracy, especially for complex queries. While this might seem slow compared to the instant responses we're accustomed to, the trade off is improved quality and reliability in the answers provided. As for integration, O1 Preview is available through ChatGPT and their API, but it's important to note that it's an early model. It lacks some of the features of GPT4O, such as multimodal capabilities and web browsing. OpenAI hasn't introduced any new pricing tiers specifically for O1 preview at this time. Reflecting on the concerns about artificial general intelligence, OpenAI appears to be cognizant of the potential risks associated with increasingly capable AI models and their extensive safety measures. Transparency and collaborations with AI safety institutes indicate a commitment to responsible development and deployment. The model's chain of thought reasoning aligns with what's known as System 2 thinking, a concept from psychology that describes slow, deliberate and analytical thought processes. This contrasts with System one Thinking, which is fast and intuitive. By incorporating System two thinking, O Preview aims to reduce errors and improve the quality of responses to, particularly in tasks that require deep reasoning. In terms of future developments, while there's no official word on integrating O1 preview with other AI models like Orion, OpenAI's focus on continuous improvement suggests that we might see more advanced models combining strengths from multiple systems in the future. Training advanced models like O1 Preview is resource intensive. OpenAI seems mindful of balancing the development of cutting edge technology with practical applications that provide tangible benefits to users and businesses. The goal is to ensure that the significant investments in AI development translate into real world value. In conclusion, OpenAI 01 Preview represents a significant advancement in AI capabilities, especially in complex reasoning tasks. The model excels in areas like science, coding and mathematics, demonstrating improved safety and alignment with OpenAI's policies. While it's still an early model, lacking some features of previous versions, it its potential applications are vast, particularly for professionals tackling complex problems. Alright, thanks for tuning in and if you enjoyed this video, don't forget to like subscribe and hit that notification bell so you don't miss any of our future videos on the latest in tech and AI. We've got more exciting content coming your way, so stay tuned and keep exploring the wonders of AI with us.