[YeGoblynQueenne]

>> AGI is computable on present day hardware if one has enough knowledge on how to correctly structure it. (...) Hardware reached capability in recent years.

How could you possibly know anything regarding whether this is true or not, given that we know nothing about AGI?

Also, may I ask what you mean by "AGI Developer"?

[simonh]

I’ve seen this claimed before. I think it’s based on an estimation of the computational sophistication of the human brain. Not what’s required to perfectly simulate a brain as such, much of the activity in brain cells is likely metabolic and not tied to their relevant behaviour, but what’s required to replicate the brain’s cognitive activity.

We may know little to nothing about AGI, but we do have one very common example of GI abundantly available to use as a point of reference.

I’m not sure what estimation the poster is using though, or how likely it might be to be accurate.

[s1dechnl]

You are correct. You don't need to do a whole brain simulation to achieve AGI. Instead, you need to understand an incredible amount about its processes, design, and overall nature. At which point, you need to translate this into the computational domain. A lot can be 'left on the table' so to speak. The fundamental problem arises with how deep your understanding is so as to know which parts you can leave on the table and which parts you can't. As far as then putting this into a functional computational system, you would need an extensive knowledge in this domain as well so as to know how to structure the software to best exploit the hardware. Lots of prototypes, performance testing, scaling, etc until you have a sound 'feel' of what you can expect and where things and you need to go. That being said.. Yes, I can run my stack on a consumer grade CPU/GPU. I have designs for hardware architectures that don't quite exist yet but all of that can be emulated in software. Latency is the only consequence of current hardware which can be trimmed with effort. Latency when too high can be abstracted with time scaled simulation. So, there is absolutely no blocker in hardware for developing AGI and yes it can be done on affordable consumer hardware .. If GPUs don't continue to be resigned to ponzi schemes and RAM prices come back to earth. That being said, if I need to, and if things don't change down the road, I'd be more than happy to spin my own hardware to keep costs in order.

[s1dechnl]

Sure. I am Jovan Williams from : http://www.monad.ai. I know its true because I am sitting in front of working aspects that I have been researching and developing full time for approximately 4 years. Some years ago, I was operating a full stack on a 4-core Intel processor. While resources were pegged, it only contributed to increased latency which is why I created my own simulation layer to continue my proofing work. I utilized various software to create a simulated virtual environment w/ time scaling and continued w/ my work.

I charted out some ways hardware had to evolve over the years. So far its beating my estimates. I conducted a simple upgrade to my hardware a year ago and saw various latency figures cut in half which is exactly what I estimated. The industry continues to push hardware towards capabilities that will only increase performance.

So yes.. Currently, I can run my stack in real-time on an 8-core consumer grade computer. I have already proofed it beating human response times in various tests by 100%. This is before any specific optimizations. Structure matters [Software] and I have other unspecified hardware in the loop. I intended on applying to Ycombinator in march, but will extend this out a bit. I'll be going more public with proofed functionality and capability. Just making my rounds in various communities/mediums as I have been doing for some time to correct the record and get a gauge of people's sentiments.

[YeGoblynQueenne]

Hi Jovan. Thanks for being open about your background and good luck with your endeavour.

It's perhaps not my place to offer any sort of advise, but it might be a good idea to be a little conservative with your terminology ("AGI") on forums like HN. The wrong response may well hurt much more than your HN karma, especially if you're looking for funding.

[s1dechnl]

I'm self funded. I have been for a number of years and throughout the crucial stages of my work. I chose this route to ensure the integrity of my work.

While I have always remained truthful which indeed has consequence, I am becoming my open as it does not (at this stage). I know exactly who frequents this board, who will likely be able to read my comments here and other places where I have openly attributed my name. I also am aware of what can be mined to unmask me in other places. I know exactly what the potential consequences are.

If funding is withheld from me because I state inconvenient truths, I don't desire it from such entities. Capital is plentiful in the world. Powerful ideas and manifestations are not.

I speak more openly because I see a world increasingly at war with itself because truth and intelligence have sit at the back of the bus whereas disinformation/manipulation/profit for profit sake sit at the front. I don't want to birth something as powerful as AGI into such a world. I don't want to be funded/influenced by someone who holds contrary views... which is why I've operated from my own capital base up until now.

How open and frank I am relates to the stage of my work. Take that as you will. For some, the bane meme comes to mind. Were going to enter into the intelligence age on new terms not via carry over terms dictated by careless capital. If a particular capital entity wants to be on board for the incredible financial upside such a technology maintains, they'll necessarily have to get on board and get comfortable with the ideas that I have outlined.

It isn't a hard pill to swallow. It's centered on truth and genuine progress of mankind : Intelligence embodied in a truer form. It currently functions on consumer grade hardware. You can also take that as you will.

Thank you for the advice ^_^. However, I know exactly how the 'game' is played.

[petermcneeley]

Computational power and memory estimates could be made based on existing knowledge of the human brain. The one big assumption being that the neuron is the source for human intelligence.

[YeGoblynQueenne]

An even bigger assumption is that intelligence in computers will require the same amount of computational power that it requires in humans. The AI we have so far is completely different than human intelligence (e.g. machine learning requires vast amounts of data; human learning can learn from single examples, etc). Computers themselves have completely different abilities than humans. Intelligence on the human brain is just not a very good model for intelligence on the computer.

[yonkshi]

I agree a true general AI will probably be fairly different on computer than human. Although I want to mention that humans can learn from one example is mostly because we already have a large a priori from our life experience. We spend years learning how to talk, communicate, write and read. Through which we have built very structured symbolic logic system, which is _learnt_.

A example of this would be mathematics. If a person is never taught mathematics, she/he are only limited to basic math operations. It would take the person years of learning and practice in order to comprehend a mathematical literature. Once we have a symbolic logic network built for a certain aspect of our life, we can rapidly retrieve information based on previous logical patterns, thus allowing us to learn from one example.

[s1dechnl]

Both of you are correct. One need only have understanding. You must maintain a yet to be discovered understanding of the human equivalent and have a depth of understanding in computational systems. While the understanding is non-trivial, the translation effort from one domain to the other isn't much effort. Computing resource capability scales with $$. I decided to do something unorthodox and start with limited computational resources. It drives the innovative spirit ^_-. If your processor is to 'slow', you can simply create a simulated abstraction of time and go from there. Computational power doesn't bog down/limit the effort, one's own understanding of the problem space/domains does.