OpenAI Testing 'o3 Alpha'

Will open source win? Because what is special about these models? Awesome. Let's talk about the new AI model by OpenAI. O3 Alpha. Yeah, I swear to God the naming scheme. Besides the naming scheme, O3 Alpha seems to be an um specialized variant of O3 which is like um really focused in in programming. And apparently from what we know so far is that it um actually outperforms Gro 3 and other models and but few days earlier we also had Kim V2 which was on on code as yeah and the thing with generally these models is like um they are growing more and more capable and with more and more context. I would really like to see in LM arena how this model will perform over the next few days. So, uh, from what I read, uh, OpenAI 03 Alpha is second on the, uh, arena. Brings me to another thing that I think is more interesting when it comes to this and I want to know what you think of. Will open source win? Because what is special about these models? Um, these are closed model most of them. Some of them are openweight and some are open sourced. And if you know the the foundational model and the the end product that we have are you know getting better and better every single time and opensource ones are also included there then to me it's like why would open AI be a winner or like why Microsoft and Google are spending so much money when while open source is keeping up base models probably not like we have Some based models have trained like tiny llama and the fine the training and finetuning tools locally become insanely good like axelottal and being able to run on very low very low requirements being really effective but the issue is these base models need so much data so much infrastructure so much it's like it's not feasible as an example there's like a right now a finished one where a model was trained decentralized with like multiple servers all over the world maybe something like that but not really because you still need like a million euros in servers. So, um these like real open source models, I'm not sure because they are still at the end of the day made by big companies. I let's say I cannot just go and make a big model. No, I I I understand that but uh they're still getting better. Yeah. Yeah, they're getting better especially the small models they get more more capable but they won't reach for the big players. There's a second category and that's fine tunes and there I could imagine yes basically that when we have a base model we can finetune it to be actually better than um an uh company release model and the big category which is in my opinion one of the mo actually important the most important category I think in regards to tooling we will win because the issue with LLM is like I wholeheartedly believe this the big issue we have with LM right now is the tooling or tooling is bad as an example the deep research which is just a chain of tool code. So let's say we're programming why do we need to uh let's say why do we need to give all the code of literally everything method if we just have met descriptions as an example and basically just like um let the LLM navigate basically a graph of a function definitions and the description what the function does. It could way easier um program applications so have like many more safeguards and easily track down bugs. We need to teach LM a fundamentally way safer and way basically a safer and more stable way to use uh tools and generally to programming and things like that and in that regard I think open source will win basically not with the not on the model side but on the tooling side. This is part of a larger conversation on my show command AI which we stream live every single week. We discuss the news and all things related to AI in the world of design and web. Catch us next week and join in the banter.