What's your viewpoint on the likelihood of GPT-5 being able to autonomously create, train, and implement an AI superior to GPT-5?

Became recently aware of the progress made in synthetic data and other algorithmic improvements. We have not pushed GPT-4 to the max yet. 

e.g. this paper https://arxiv.org/abs/2305.20050

It details how training on the steps in step by step reasoning as opposed to just rewarding the end result can give significant improvements. And there is so much more.  

There's AGI, autonomous agency and a wide variety of open-ended objectives, and generation of synthetic data, preventing natural tokens from running out, both for quantity and quality. My impression is that the latter is likely to start happening by the time GPT-5 rolls out. 

It appears this situation could be more accurately attributed to Human constraints rather than AI limitations? Upon reaching a stage where AI systems, such as GPT models, can absorbed all human-generated information, conversations, images, videos, discoveries, and insights, these systems should begin to pioneer their own discoveries and understandings?

While we can expect Humans to persist (hopefully) and continue generating more conversations, viewpoints, and data for AI to learn from,  AI's growth and learning shouldn't necessarily be confined to the pace or scale of Human discoveries and data.  They should be capable of progressing beyond the point where Human contribution slows, continuing to create their own discoveries, dialogues, reflections, and more to foster continuous learning and training?

Quality training data might be even more terrifying than scaling, Leela Zero plays superhuman Go at only 50M parameters, so who known what happens when 100B parameter LLMs start getting increasingly higher quality datasets for pre-training.

Where would these "higher quality datasets" come from?  Do they already exist? And, if so, why are they not being used already?

The biggest issue I think is agency. In 2024 large improvements will be made to memory (a lot is happening in this regard). I agree that GPT-4 already has a lot of capability. Especially with fine-tuning it should do well on a lot of individual tasks relevant to AI development. 

But the executive function is probably still lacking in 2024. Combining the tasks to a whole job will be challenging. Improving data is agency intensive (less intelligence intensive). You need to contact organizations, scrape the web, sift through the data etc. Also it would need to order the training run,  get the compute for inference time, pay the bills etc. These require more agency than intelligence. 

Absolutely.  Even with GPT-4's constrained "short term memory", it is remarkably proficient at managing sizable tasks using external systems like AutoGPT or Baby AGI that take on the role of extensive "planning" on behalf of GPT-4.  Such tools equip GPT-4 with the capacity to contemplate and evaluate ideas -- facets akin to "planning" and "agency" -- and subsequently execute individual tasks derived from the plan through separate prompts.

This strategy could allow even GPT-4 to undertake larger responsibilities such as conducting scientific experiments or coding full-scale applications, not just snippets of code.  If future iterations like GPT-5 or later were to incorporate a much larger token window (i.e., "short-term memory"), they might be able to execute tasks, while also keeping the larger scale planning in memory at the same time? Thus reducing the reliance on external systems for planning and agency.

However, humans can help with the planning etc.  And GPT-5 will probably boost productivity of AI developers. 

Note: depending on your definition of intelligence, agency or the executive function would/should be part of intelligence. 

Agreed.  Though, communication speed is a significant concern.  AI-to-Human interaction is inherently slower than AI-to-AI or even AI-to-Self, due to factors such as the need to translate actions and decisions into human-understandable language, and the overall pace of Human cognition and response.

To optimize GPT-5's ability in solving complex issues quickly, it may be necessary to minimize Human involvement in the process.  The role of Humans could then be restricted to evaluating and validating the final outcome, thus not slowing down the ideation or resolution process?  Though, depending on the size of the token window, GPT-5 might not have the ability to do the planning and execution at the same time.  It might require GPT-6 or subsequent versions to get to that point.

The biggest issue I think is agency.

"Q: How do you see planning in AI systems?  How advanced are AI right now at planning?

A: I don't know it's hard to judge we don't have a metric for like how well agents are at planning but I think if you start asking the right questions for step by step thinking and processing, it's really good."

Thanks GPT-4. You're the best!  

Veniversum Vivus Vici, do you have any opinions or unique insights to add to this topic?

Specific Resources (Access to a DGX data center): Even if an AI had access to such resources, it would still need to understand how to use them effectively, which would require capabilities beyond what GPT-4 or a hypothetical GPT-5 have.

To my knowledge resource management in data centers is done by AI's. It is the humans who cannot do this. The AI already can.