Marc Andreessen on the atomization of AI

Most AGI focused ventures are not even in the U.S. A prominent one is in China. Another is in Europe. The ones in the U.S are privately funded beyond the big names. Furthermore, where is the U.S's equivalent of : https://www.humanbrainproject.eu/ ?

Where are the seasoned software engineers in the ranks at these highly funded silicon valley Ai companies? I typically see a roster of 'big names' and PhDs... Whereas, I look at the companies specifically pursuing AGI and I see a whole range of individuals.. PHD neuroscience, Senior game developer, Robotics Engineer, Senior firmware developer, Guy from down the hall who can code circles around silicon valley's most decorated engineer, etc etc.

Look at the Geohot story, that's the kind of individual and company who ushers in a new paradigm ....

If the solution requires you to 'think different', how do you expect to achieve it by padding your company with a bunch of individuals who are all centered on the same techniques from academia?

Thankfully we live in an age in which the most important research to developing fundamental things like Ai is 'time'. If you have an internet connection and a reasonably decent computer, you have enough resources to create AGi.

If you passionately care about seeing your idea through, save up money, move to a cheaper location, wire your computer to the internet, and get to work.

Once you've proven your vision, who can deny you then? Slam it on the boardroom table, disrupt present day business models, and be the next tech giant.

Offer them a PhD

I think the short answer is, you don't. Between Google, OpenAI, Facebook, Baidu, Microsoft, IBM, and every other startup that is putting "deep learning" in their pitch deck to see what happens, there's enough money being pumped into the area. 90% of the results of that money being spent will be made available to everyone in the world for free. IE, if you're investing for competitive advantage, you will lose. If you're not already on one of those teams or studying the subject, I don't see any opportunity for at least a year, maybe 2.

To be clear, I'm talking about opportunities around starting a new company. If your business is consulting or you're working as an engineer for an existing company, there are many applications for deep learning, but none that stand on their own.

In 2 years, content generation will be a big thing. Like pandora with purely algorithmically generated music, or games with assets that create themselves in a way far superior to what we see in the current generation of "procedural generation". The big cos will have very good versions of Siri, but no startup is going to be able to touch that near term.

It will take much more than a "clever idea" to overcome the reliance on data of the current AI state of the art- that is to say, machine learning.

If you think about it, machine learning algorithms are essentially clever search procedures for some optimum in a heap of data (that's optimisation algorithms, so about 90% of the field). You can always get smarter in the way you search, but unless you search far enough what you find won't generalise very well to unseen data. And if "unseen data" is the real world, you need immense amounts of data to get anywhere- hence, the reliance on big data.

What we need is much more than a clever idea: it's a paradigm shift. There's probably some sort of way to make a system that can learn from very few examples and at a very short time, like we do ourselves. Machine learning is certainly not that way. We need to find another way.

I'm not sure startups with clever ideas have a very good chance to just stumble on such an other way while looking for a way to do "Facebook with deep learning".