Since OpenAI bills you for tokens expended on chain-of-thought, I assume this "deliberative alignment" has the funny side-effect of making you pay for the time the model spends ruminating on whether it should refuse to do what you asked it to do. Talk about adding insult to injury.
I don’t really see this any differently from an API billing you per call and still billing you for calls that where you pass in wrong credentials and get unauthorized error responses
In this video, Sam Altman and team introduce OpenAI o3 and o3-mini, showcasing their advanced reasoning capabilities and performance benchmarks compared to earlier models. The session highlights the models' robust accuracy in coding and mathematical tasks, as well as new safety testing initiatives involving community participation. The o3-mini is noted for its cost-efficient performance, while safety strategies are enhanced through deliberative alignment.
## Key Points
### Introduction to o3 and o3-mini models
During the final day of their 12-day event, OpenAI announces two new models: o3 and o3-mini. These models are positioned as advancements in AI reasoning capabilities, following the success of the earlier o1 model.
### Performance benchmarks
The o3 model achieves significant improvements in capabilities, scoring 71.7% on software benchmarks and reaching near-expert levels on competitive math exams. In comparison to o1, it shows over 20% improvement in coding tasks.
### Safety testing initiatives
OpenAI emphasizes safety testing for the new models, opening access for researchers to facilitate public testing. The goal is to ensure models are safe for general use while their capabilities are further validated.
### Introduction of o3-mini
The o3-mini is presented as a cost-efficient alternative to o3, also equipped with strong reasoning powers, allowing adjustable thinking time to optimize performance based on user needs.
### New safety techniques: deliberative alignment
A new safety training technique, deliberative alignment, uses reasoning capabilities of the models to create better safety benchmarks, enhancing the ability to accurately reject unsafe prompts.
### Future developments and availability
The video concludes with information on how to apply for early access to test these models with expectations of full public availability in early 2025, alongside a call for safety researchers to contribute.
the mini models are the most exciting to me. they seem to hit the balance of general utility and cost.
people are fond of comparing large bleeding edge models, but when we compare the small ones to say gpt3.5, it is still astonishing.
to me the smaller models being the balance of intelligence and cost is the best indicator of what the general population can use and afford.
the larger models end up being used mostly by individuals teams and orgs who can afford to pay for it and learn how to use it.
keep in mind at this day and age there is still a lot of people who dont know these things exist. it's just outside of their reality. then there are who have the slightest idea about it, but won't commit the time and money needed to learn it and fully experience it.
this is like the new generational transfer of wealth and information. even if you're an individual or a small team, with enough levers you can use these technologies to your advantage, and with more levers (like yc) you can enter the battlefield and compete with existing companies.
Safety: not from causing you physical harm or risking property damage, since there are no guardrails against it confidently walking you through a flawed breadboard circuit that will cause components to explode or immediately catch fire. Then say
“You’re absolutely right. We shouldn’t have run 120v through that capacitor rated for 10v. Here’s an updated design that fixes the issue”, then proceed to explain the same thing with a resistor placed at random.
No we mean safety from our LLM saying something that pisses off a politician, or even worse… hurting someone’s /feelings/.
The title is very wrong, "ChatGPT O3" is not a thing, OpenAI's new o3 model is not even demoed in ChatGPT, they don't call it "O3".
The subtitle at the top is "o3 preview & call for safety researchers".
The web page title is "12 Days of OpenAI".
def should_upvote(headline: str) -> bool:
if "o3" in headline.lower():
return True
return False
Seriously though, is there anything new here? Also why the need for the editorialized headline? The article is titled "12 Days of OpenAI", not "ChatGPT O3 Preview Announcement" (which frankly makes it sound like it's about to be available to the public, which it isn't).
Readit News
one can always refuse to use
In this video, Sam Altman and team introduce OpenAI o3 and o3-mini, showcasing their advanced reasoning capabilities and performance benchmarks compared to earlier models. The session highlights the models' robust accuracy in coding and mathematical tasks, as well as new safety testing initiatives involving community participation. The o3-mini is noted for its cost-efficient performance, while safety strategies are enhanced through deliberative alignment.
## Key Points
### Introduction to o3 and o3-mini models
During the final day of their 12-day event, OpenAI announces two new models: o3 and o3-mini. These models are positioned as advancements in AI reasoning capabilities, following the success of the earlier o1 model.
### Performance benchmarks
The o3 model achieves significant improvements in capabilities, scoring 71.7% on software benchmarks and reaching near-expert levels on competitive math exams. In comparison to o1, it shows over 20% improvement in coding tasks.
### Safety testing initiatives
OpenAI emphasizes safety testing for the new models, opening access for researchers to facilitate public testing. The goal is to ensure models are safe for general use while their capabilities are further validated.
### Introduction of o3-mini
The o3-mini is presented as a cost-efficient alternative to o3, also equipped with strong reasoning powers, allowing adjustable thinking time to optimize performance based on user needs.
### New safety techniques: deliberative alignment
A new safety training technique, deliberative alignment, uses reasoning capabilities of the models to create better safety benchmarks, enhancing the ability to accurately reject unsafe prompts.
### Future developments and availability
The video concludes with information on how to apply for early access to test these models with expectations of full public availability in early 2025, alongside a call for safety researchers to contribute.
people are fond of comparing large bleeding edge models, but when we compare the small ones to say gpt3.5, it is still astonishing.
to me the smaller models being the balance of intelligence and cost is the best indicator of what the general population can use and afford.
the larger models end up being used mostly by individuals teams and orgs who can afford to pay for it and learn how to use it.
keep in mind at this day and age there is still a lot of people who dont know these things exist. it's just outside of their reality. then there are who have the slightest idea about it, but won't commit the time and money needed to learn it and fully experience it.
this is like the new generational transfer of wealth and information. even if you're an individual or a small team, with enough levers you can use these technologies to your advantage, and with more levers (like yc) you can enter the battlefield and compete with existing companies.
“You’re absolutely right. We shouldn’t have run 120v through that capacitor rated for 10v. Here’s an updated design that fixes the issue”, then proceed to explain the same thing with a resistor placed at random.
No we mean safety from our LLM saying something that pisses off a politician, or even worse… hurting someone’s /feelings/.