Investing in Artificial Intelligence | Hacker News Reader

Investing in Artificial Intelligence

techcrunch.com

47 pointsfunkyy8 comments

Hey I'm looking for hackers/engineers that want to help build Playa (http://getplaya.com/)

We're going to be the heroku for autonomous intelligent agents. If you're interested in distributed cognition, cybernetics, AI, cloud robotics, probabilistic robotics, multiagent systems, ambient computing, hit me up. I'm @dpg on Twitter or email me dan.p.gailey@gmail dot com

I basically sold everything I owned to crash in my van in Palo Alto and build this.

I'm a little confused what Playa is going to do. Heroku basically hosts code so you can upload some and have it run. Are you going to do that?

Possibly, it's still really early but I'd like to host the data (expert systems, knowledge base, talent graph, sensor data, etc, etc) and manifests for the agents. It will also provide the ability for agents to search and provision services through contracts.

Any reason for the focus on old symbolic-AI techniques? Things like expert systems have fallen out in favor of learned machine learning models. Yes, machine learning is 'popular' and 'trendy', but it also happens to work better and require less engineering effort to build and maintain than symbolic-AI systems.

Is there a market for traditional AI techniques as a service? Or maybe the wording is just throwing me off? The word 'agents' in particular is used a lot in 60's AI papers (Minsky's influence), so maybe I'm misinterpreting?

Pardon me for any confusion, I'm often reminded of this quote: "Barbarus hic ego sum, quia non intelligor illis." I'm new to all of this, but still humbly learning and building.

If modern machine learning models are better for every application, then that's most likely what we'll support. I think symbolic AI still holds some merit when thinking about how to interact with traditional physical interfaces, no? There seems to be a complement in the methods when considering a full stack thinking and acting approach, but perhaps I'm being naive.

For example, if I'm a robot in the world, it would be easy for me to access interface knowledge, and how I could interact with it to complete my task, without needing to reason what the interface does or is. This gives me a basic understanding or knowledge base. Now if there is a higher level method of thinking that produces ingenuity, and as a result a more efficient method for solving a known problem, then I assert more modern techniques can be used to adjust older symbolic representations.

I'm just imagining how an android/autonomous agent would need to operate in the real world, perhaps akin to how we might perceive and function within it, a posse ad esse.

Also I use 'agents' because I am going back through older research and it seems to fit the description of the entities involved (software, hardware, robots, devices, people). I don't see any reason for some of the vocabulary or terms to have fallen out of favor.

In a world of autonomous intelligent multi-agent systems, there is a market for knowledge representation about the world, how to complete tasks, as well as higher level thinking/reasoning functions, et cetera.

I run a robotics company and we tend to do the same, namely using agent terminology.

This does indeed not preclude new methods. SLAM is of course what everybody uses in autonomous robotics. But you also have reinforcement learning and imitation learning and a wide diversity of representations and models from DEC-POMDPs to Bayesian models to neural nets. Each time you'll need somehow to decompose into modules, units, etc. Agents represent something in the real world and are often the right term for a module that has (virtual) sensors and actuators.

Apart from that I would recommend to focus on something, so you can really excel in that part of AI.

We have chosen "understanding where an AI is located in the real world" as our main goal. I can imagine there is something similar you would like to achieve for AI.

Just my two cents! Good luck!!!

Thanks for the reply and perhaps we can work together someday!

The platform I'm currently building is just to facilitate the provisioning and correlation of third party services for emergent results.

Thanks again for the info. I'll conduct more research. Cheers. :)

The space for AI-powered venture-backed companies is really booming.

Full list of companies mentioned in the article:

Enigma - http://enigma.io/

Sift Science - https://siftscience.com/

Ravelin - https://ravelin.com/

H2O.ai - http://h2o.ai/

Seldon - http://www.seldon.io/

SigOpt - https://sigopt.com/