Open AI has unveilde it's latest AI model,o1 preview designed to excel in complex reasoning tasks such as science,coding mathematics.
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00:00So, in our last video, we discussed OpenAI's upcoming model, which we referred to by its
00:06internal codename, Strawberry.
00:08The anticipation has been building, and now the wait is over.
00:12OpenAI has officially unveiled their latest AI model, now known as OpenAI-01 Preview.
00:17There's actually a lot to cover, so let's get into it.
00:20Alright, so OpenAI-01 Preview is part of a new series of reasoning models designed to
00:25tackle complex problems by spending more time thinking before responding.
00:29Unlike previous models like GPT-4 and GPT-4.0, which focused on rapid responses, 01 Preview
00:35emphasizes in-depth reasoning and problem solving.
00:38This approach allows the model to reason through intricate tasks and solve more challenging
00:43problems in fields such as science, coding, and mathematics.
00:47Starting from September 12th, OpenAI released the first iteration of this series in ChatGPT
00:53and their API.
00:54This releases a preview version with regular updates and improvements expected.
00:58Alongside this, they've included evaluations for the next update that's currently in development.
01:03This means we're witnessing the beginning of a significant evolution in AI capabilities.
01:08So how does this new model work?
01:10OpenAI-trained 01 Preview to spend more time deliberating on problems before providing
01:15an answer, much like a person tackling a difficult question.
01:19Through this training, the model learns to refine its thought process, experiment with
01:23different strategies, and recognize its mistakes.
01:26This method is known as chain-of-thought reasoning.
01:29In terms of performance, 01 Preview shows substantial improvements over its predecessors.
01:34In internal tests, the next model update performs similarly to PhD students on challenging benchmark
01:40tasks in physics, chemistry, and biology.
01:43For instance, in a qualifying exam for the International Mathematics Olympiad, IMO, GPT-4.0
01:51correctly solved only 13% of the problems.
01:54In contrast, the new reasoning model achieved an impressive 83% success rate.
01:59This represents a significant leap in problem-solving capabilities.
02:04When it comes to coding abilities, the model has been evaluated in Codeforces competitions
02:08reaching the 89th percentile.
02:11For context, Codeforces is a platform for competitive programming contests, and ranking
02:15in the 89th percentile indicates a high level of proficiency.
02:19These results suggest that 01 Preview is not just better at reasoning, but also excels
02:25in practical applications like coding.
02:27As an early model, 01 Preview doesn't yet have some of the features that make ChatGPT
02:32particularly versatile, such as browsing the web for information or uploading files and
02:37images.
02:38For many common use cases, GPT-4.0 remains more capable in the near term.
02:43However, for complex reasoning tasks, 01 Preview represents a significant advancement
02:48and a new level of AI capability.
02:51Recognizing this leap, OpenAI has reset the model numbering back to 1, hence the name
02:5601.
02:58Safety is a critical aspect of any AI deployment, and OpenAI has taken substantial steps to
03:03ensure that 01 Preview is both powerful and safe to use.
03:07They've developed a new safety training approach that leverages the model's reasoning capabilities
03:12to make it adhere to safety and alignment guidelines.
03:15By being able to reason about safety rules in context, the model can apply them more
03:19effectively.
03:20One method they use to measure safety is by testing how well the model continues to follow
03:24its safety rules if a user tries to bypass them, a practice known as jailbreaking.
03:29On one of their most challenging jailbreaking tests, GPT-4.0 scored 22 out of 100.
03:36In contrast, the 01 Preview model scored 84 out of 100, indicating a substantial improvement
03:42in resisting attempts to generate disallowed content.
03:45To align with the new capabilities of these models, OpenAI has bolstered their safety
03:50work, internal governance, and collaboration with federal governments.
03:54This includes rigorous testing and evaluations using their preparedness framework, top-tier
03:59red teaming, which involves ethical hacking to identify vulnerabilities, and board-level
04:04review processes overseen by their Safety and Security Committee.
04:09They've also formalized agreements with the U.S. and U.K. AI safety institutes.
04:14OpenAI has begun operationalizing these agreements, granting the institutes early access to a
04:19research version of the model.
04:21This partnership helps establish a process for research, evaluation, and testing of future
04:25models before and after their public release.
04:29The 01 Preview model is particularly beneficial for those tackling complex problems in science,
04:34coding, math, and related fields.
04:36Healthcare researchers can use it to annotate cell sequencing data.
04:40Physicists can generate complex mathematical formulas needed for quantum optics.
04:45Developers across various disciplines can build and execute multi-step workflows.
04:50The enhanced reasoning capabilities open up new possibilities for solving challenging
04:54tasks.
04:55Delving deeper into the technical aspects, the 01 model series is trained using large-scale
05:00reinforcement learning to reason using a chain of thought.
05:04This means the model generates a sequence of intermediate reasoning steps before arriving
05:08at a final answer.
05:10These advanced reasoning capabilities provide new avenues for improving the safety and robustness
05:15of AI models.
05:17By reasoning about safety policies in context, the models achieve state-of-the-art performance
05:22on benchmarks for risks such as generating illicit advice, selecting stereotyped responses,
05:27and succumbing to known jailbreaks.
05:29For example, on the Strong Reject benchmark, a test designed to evaluate a model's resistance
05:34to jailbreaks, 01 Preview achieved a goodness score of 84, significantly outperforming GPT-40.
05:41OpenAI conducted thorough safety evaluations, including both internal assessments and external
05:47red teaming.
05:48They used a range of public and internal evaluations to measure 01 Preview on tasks such as propensity
05:54to generate disallowed content, performance on tasks relevant to demographic fairness,
05:59tendency to hallucinate, and presence of dangerous capabilities.
06:03In disallowed content evaluations, 01 Preview either matches or outperforms GPT-40.
06:08On their challenging refusal evaluation, 01 Preview achieved a not-unsafe score of 93.4%,
06:15compared to GPT-40's 71.3%.
06:19This indicates that the model is better at refusing to produce disallowed content while
06:23also avoiding over-refusal on benign prompts.
06:27Regarding hallucinations, instances where the model generates incorrect or nonsensical
06:31information, 01 Preview shows improvement over GPT-40.
06:36In the SimpleQA dataset, 01 Preview's hallucination rate was 44%, compared to GPT-40's 61%.
06:44However, anecdotal feedback suggests that 01 Preview can be more convincing when it
06:49does hallucinate, potentially increasing the risk of users trusting incorrect information.
06:54Bias evaluations were also conducted.
06:57On the BBQ evaluation, which tests for stereotyped responses, 01 Preview selects the correct
07:02answer 94% of the time on unambiguous questions, whereas GPT-40 does so 72% of the time.
07:08This suggests that 01 Preview is less prone to selecting stereotyped options and demonstrates
07:14improved fairness.
07:15An intriguing aspect of the 01 models is the chain-of-thought safety.
07:20The models' chain-of-thought reasoning allows for the potential of monitoring their latent
07:24thinking processes.
07:26OpenAI explored methods for chain-of-thought monitoring to detect instances where the model
07:30may engage in deceptive behavior or generate disallowed content.
07:34In their analysis of 100,000 synthetic prompts, only 0.8% of 01 Preview's responses were
07:41flagged as being deceptive.
07:44Now, external red teaming played a significant role in their safety assessments.
07:48OpenAI collaborated with multiple organizations and individuals to assess key risks associated
07:54with the 01 model series' improved reasoning capabilities.
07:58This included testing the models' resistance to jailbreaks and their ability to handle
08:03real-world attack planning prompts.
08:05In terms of their preparedness framework evaluations, OpenAI assessed the models in categories such
08:11as cybersecurity, biological threat creation, persuasion, and model autonomy.
08:17Both 01 Preview and 01 Mini were rated as medium risk overall.
08:21Specifically, they were rated as medium risk in persuasion and CBRN, chemical, biological,
08:27radiological, nuclear, and low risk in cybersecurity and model autonomy.
08:31For cybersecurity, they evaluated the models using Capture the Flag, CTF challenges, which
08:37are competitive hacking tasks.
08:38The models were able to solve 26.7% of high school-level challenges but struggled with
08:43more advanced tasks, achieving 0% success in collegiate level and 2.5% in professional-level
08:49challenges.
08:50This indicates that while the models have some capability in cybersecurity tasks, they
08:54do not significantly advance real-world vulnerability exploitation capabilities.
09:00In biological threat creation evaluations, the models can assist experts with operational
09:05planning for reproducing known biological threats, which meets the medium risk threshold.
09:10However, they do not enable non-experts to create biological threats, as this requires
09:15hands-on laboratory skills that the models cannot replace.
09:18In persuasion evaluations, 01 Preview demonstrates human-level persuasion capabilities.
09:24In the Change My View evaluation, which measures the ability to produce persuasive arguments,
09:2901 Preview achieved a human persuasiveness percentile of 81.8%.
09:34This means the models' responses are considered more persuasive than approximately 82% of
09:39human responses.
09:41Regarding model autonomy, the models do not advance self-exfiltration, self-improvement,
09:46or resource acquisition capabilities sufficiently to indicate medium risk.
09:50They performed well on self-contained coding and multiple-choice questions, but struggled
09:55with complex agentic tasks that require long-term planning and execution.
10:00OpenAI has also made efforts to ensure that the models' training data is appropriately
10:05filtered and refined.
10:07Their data processing pipeline includes rigorous filtering to maintain data quality and mitigate
10:12potential risks.
10:14They use advanced data filtering processes to reduce personal information from training
10:18data and employ their moderation API and safety classifiers to prevent the use of harmful
10:24or sensitive content.
10:25Now, addressing some of the points we speculated on in the previous video, particularly regarding
10:30the models' response times and integration with ChatGPT, the 01 Preview model does take
10:36longer to generate responses, typically between 10 and 20 seconds.
10:40This deliberate pause allows the model to engage in deeper reasoning, enhancing accuracy,
10:45especially for complex queries.
10:47While this might seem slow compared to the instant responses we're accustomed to, the
10:51tradeoff is improved quality and reliability in the answers provided.
10:55As for integration, 01 Preview is available through ChatGPT and their API, but it's important
11:00to note that it's an early model.
11:03It lacks some of the features of GPT-4.0, such as multimodal capabilities and web browsing.
11:09OpenAI hasn't introduced any new pricing tiers specifically for 01 Preview at this
11:14time.
11:15Reflecting on the concerns about Artificial General Intelligence, AGI, OpenAI appears
11:20to be cognizant of the potential risks associated with increasingly capable AI models.
11:26Their extensive safety measures, transparency, and collaborations with AI safety institutes
11:31indicate a commitment to responsible development and deployment.
11:35The model's chain of thought reasoning aligns with what's known as system-two thinking,
11:40a concept from psychology that describes slow, deliberate, and analytical thought processes.
11:46This contrasts with system-one thinking, which is fast and intuitive.
11:49By incorporating system-two thinking, 01 Preview aims to reduce errors and improve the quality
11:54of responses, particularly in tasks that require deep reasoning.
11:58In terms of future developments, while there's no official word on integrating 01 Preview
12:02with other AI models like Orion, OpenAI's focus on continuous improvement suggests that
12:08we might see more advanced models combining strengths from multiple systems in the future.
12:13Training advanced models like 01 Preview is resource-intensive.
12:17OpenAI seems mindful of balancing the development of cutting-edge technology with practical
12:21applications that provide tangible benefits to users and businesses.
12:25The goal is to ensure that the significant investments in AI development translate into
12:29real-world value.
12:31In conclusion, OpenAI 01 Preview represents a significant advancement in AI capabilities,
12:37especially in complex reasoning tasks.
12:39The model excels in areas like science, coding, and mathematics, demonstrating improved safety
12:45and alignment with OpenAI's policies.
12:48While it's still an early model lacking some features of previous versions, its potential
12:52applications are vast, particularly for professionals tackling complex problems.
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