OpenAI o1: Testing on Complex Business Problems and Logic

In this video, Samer's discusses the unexpected release of OpenAI's new model, OpenAI o1. Unlike the excitement surrounding GPT-5, OpenAI o1's announcement came with mixed reactions. Instead of redoing existing tests, Samer focuses on testing the model on complex business problems in supply chain, supply chain finance, and procurement. He provides a detailed exploration of how OpenAI o1 tackles these problems and evaluates the model's solutions.

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⏰ Chapters:

00:00 Introduction and OpenAI o1 announcement
02:26 Overview of OpenAI's claims about o1
04:45 Testing o1 with complex business problems
05:20 Supply chain crisis problem
09:13 Analysis of o1's response to supply chain problem
14:33 Supply chain finance problem
19:23 Analysis of o1's response to finance problem
23:19 Procurement contracts problem
27:55 Analysis of o1's response to procurement problem
30:55 Hypothetical AI uprising scenario
33:12 "Chicken or egg" philosophical question
36:13 Conclusion and final thoughts on OpenAI o1

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#GiveMeTheMic #OpenAI #AIModel #BusinessSolutions #SupplyChain #Procurement

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FileName: GMTM172

[andromeda]

Thank you very much for your insightful contribution. I can see you are quite well-versed in this field.

However, as you know, this is merely the first stage, o1, correct? This means, on the one hand, we can expect improvements. These improvements will likely occur in cycles, approximately every six to twelve months. On the other hand, we still haven't reached AGI, artificial general intelligence. What we have with this O-model, if I may put it that way, is certainly a step in the right direction.

The current goal is to elevate it to a human level through scaling and various techniques. But we are not yet at a fully human level. Once we reach that, we would have AGI, true general artificial intelligence. Within a year, however, we will likely see above-average answers to such questions from the model.

What you are expecting, and indeed what most people are anticipating, is a kind of superintelligence-level response. But the system is not there yet. Naturally, it would require access to far more data, particularly in this area. Eventually, though, it will in very near future deliver astonishing results, much like AlphaGo did with move 37.

Move 37 in AlphaGo’s historic match against Lee Sedol represents a profound moment not just in the world of artificial intelligence, but for humanity's understanding of intelligence itself.

In this game, AlphaGo—a machine—played a move that was so unconventional, so unexpected, that even the grandmaster Lee Sedol, one of the world's greatest Go players, was taken aback. Experts initially thought the move was a mistake, as it defied traditional human logic and strategy. But, as the game progressed, it became clear that this move was not only valid but brilliant, leading to AlphaGo's victory.

For humanity, Move 37 symbolizes the potential of AI to transcend human intuition and knowledge. It demonstrated that machines could think in ways fundamentally different from us, exploring possibilities that the human mind might overlook or deem improbable.

[hypersonicmonkeybrains]

I have no idea how it works, but from a layman's perspective from what i've heard i think what its doing is using prompts behind the scenes that are designed specifically to tackle complex problems like 'chain of thought' 'agents' and several others, its like its working through a flow chart, trying these techniques and keeping track of the result to see if it conforms to the answer demanded by the prompt" finally after all these behind the scenes prompts it will output its final answer.

[MyWatermelonz]

So, the issue is that this is still an LLM. So if you throw in a prompt that is just a question out of a business textbook with all the business jargon/terminology, it's gonna still throw out the typical MBA answer.

o1 isn't perfect as you've seen, but like other models prompting is just as important. I find better results with a shorter and more concise prompt with bullet points on what it needs to do/figure out and then tell it to think as if you are like a genius CEO. This helps the CoT use certain words in its thinking process that are higher level and keeps it on track with the more concise bullet points without all the jargon.

[humphuk]

I guess I am like many - its impressive that it knows who killed Aunt Agatha - but does it bring value in the business world over the current models? I guess I may be looking in the wrong places - as I find little testing in this space apart from Samer .... and the likes of Ethan Mollick. I guess I just need to try.... I have seen much on the need to prompt these models differently to the GPT series .... more learning to do. Thanks Samer for putting this out there

[amdenis]

Great vid! I wouldn't say out of nowhere, as we were talking about it for months now, as an incremental release before October's next gen full release of Strawberry.

[Ztedits_br]

OpenAI's latest model, known as 01, introduces a feature called Chain of Thought (CoT), which allows the AI to think through problems more effectively. It's likely built on something like GPT-4.5 (raw), and they've trained it to reflect on its own reasoning during test-time instead of just relying on pre-training and fine-tuning. This means the model can adapt and improve its thinking on the fly, using patterns learned from users. While we don’t know the full details of their "Strawberry" architecture, it's said that they use reinforcement learning to reward the best reasoning processes. With enough computing power, this model can do some pretty impressive things, and according to Terence Tao, its ability to handle complex math has really improved. but its not AGI and lacks alot regarding some usecases...

[ToolmakerOneNewsletter]

You might want to do some research before you make your next "test" video. It might help you align your purpose with your tests as they relate to the stated strengths of the model. Your comments about SORA and voice also show you have not been keeping up with news on these topics (studio contract talks, red team testing, etc.).

[the_proffesional]

Tidak mungkin kamu kembarannya Misha Charoudin?

[sunofson]

don't know, i was expecting something impressive