Sunday, October 1, 2017

Parasitic computing

I just stumbled upon a new concept: Parasitic computing

It grabbed my attention because some days ago we were discussing similar issue in our team – the fact that the gradual meta-learning architecture may invent experts that act like parasites on other experts, etc.

Parasitic computing is programming technique where a program in normal authorized interactions with another program manages to get the other program to perform computations of a complex nature. It is, in a sense, a security exploit in that the program implementing the parasitic computing has no authority to consume resources made available to the other program.
It was first proposed by Albert-Laszlo Barabasi, Vincent W. Freeh, Hawoong Jeong & Jay B. Brockman from University of Notre Dame, Indiana, USA, in 2001.
The example given by the original paper was two computers communicating over the Internet, under disguise of a standard communications session. The first computer is attempting to solve a large and extremely difficult 3-SAT problem; it has decomposed the original 3-SAT problem in a considerable number of smaller problems. Each of these smaller problems is then encoded as a relation between a checksum and a packet such that whether the checksum is accurate or not is also the answer to that smaller problem. The packet/checksum is then sent to another computer. This computer will, as part of receiving the packet and deciding whether it is valid and well-formed, create a checksum of the packet and see whether it is identical to the provided checksum. If the checksum is invalid, it will then request a new packet from the original computer. The original computer now knows the answer to that smaller problem based on the second computer's response, and can transmit a fresh packet embodying a different sub-problem. Eventually, all the sub-problems will be answered and the final answer easily calculated.
And then there's parasitic computing implemented as a virtual machine :-)
This Diploma Thesis of the University of Applied Sciences in Bern (Switzerland) does extend that concept into a fully programmable virtual machine that is capable of solving any known problem in classic computer science.
http://www.szene.ch/parasit/index.html
Why am I writing about this? Because I think that these are good examples of behavior that may/will emerge in every recursively self-improving AI architecture.
It's important to anticipate these issues and prepare for them - e.g. by implementing immune system experts, or creating learning tasks (curriculum) that teach some kind of immune system reactions, etc.

What is an expert? A very loose definition would be: expert is a program (policy, skill, heuristic, etc) that solves some general or specialized problem in external or internal environment. General AI architecture would be a network of these experts.

Thank you for reading!


Marek Rosa

CEO, Founder, Keen Software House
CEO, Founder, GoodAI

For more news:


General AI Challenge: www.general-ai-challenge.org

AI Roadmap Institute: www.roadmapinstitute.org
GoodAI: www.goodai.com
Space Engineers: www.spaceengineersgame.com
Medieval Engineers: www.medievalengineers.com

Personal bio:


Marek Rosa is the CEO and CTO of GoodAI, a general artificial intelligence R&D company, and the CEO and founder of Keen Software House, an independent game development studio best known for their best-seller Space Engineers (2mil+ copies sold). Both companies are based in Prague, Czech Republic. 

Marek has been interested in artificial intelligence since childhood. Marek started his career as a programmer but later transitioned to a leadership role. After the success of the Keen Software House titles, Marek was able to personally fund GoodAI, his new general AI research company building human-level artificial intelligence, with $10mil. 

GoodAI started in January 2014 and has grown to an international team of 20 researchers.

Saturday, September 30, 2017

Results and Evaluation for Gradual Learning Round of the General AI Challenge


SUMMARY:
  • We have finished the first round of the General AI Challenge focusing on gradual learning
  • There were no winners but we awarded $7000 of prizes to reward the top four efforts
  • We will continue the gradual learning round in 2018 and are launching Round 2: Race Avoidance in November 2017


We have reached a big milestone having completed the first Gradual Learning round of the General AI Challenge. Firstly, I would like to say a huge thank you to everyone involved in the round: all participants, our jury and advisors, our 15 main partners (see below) and everyone who helped.

GoodAI launched the General AI Challenge in February 2017, with the aim of using citizen science to tackle crucial research problems in human-level AI development.

The first round of the Challenge asked participants to create AI agents capable of gradual learning (building new knowledge on top of previously learned skills and reapplying existing skills to learn how to solve new problems more efficiently), one of the keys to solving general AI.

We had over 500 people from 56 countries registered for the 1st round of the General AI Challenge from February till August 2017, and we received 13 submissions competing for the main, quantitative prize (“best gradually learning AI agent”) and for the qualitative (“best idea”) prize.

To compete for quantitative prize, AI agents had to pass an evaluation curriculum of tasks, that we designed specifically to test the gradual learning capability. Since none of the submitted AI agents were able to solve the entire evaluation curriculum, and the jury concluded that more work is required to demonstrate future potential of submitted designs, the jury chose no winner.

However, to encourage further work on gradual learning and to reward the participants for their considerable efforts, we decided to split the 2nd prize in “best idea” category ($7000) among the four finalists. Four shortlisted solutions were closely comparable, but the finalist who received most points from the judges was also awarded a GEFORCE GTX 1080 GPU - the special prize from our Challenge partner NVIDIA.


I was particularly impressed at the diversity on display and the determination of our participants. The top four awarded finalists, as chosen by our jury, are:


Dan Barry: A former NASA astronaut and a veteran of three space flights, four spacewalks and two trips to the International Space Station. He retired from NASA in 2005 and started his own company, Denbar Robotics, that focuses on smart robots and artificial intelligence interfaces, concentrating on assistive devices for people with disabilities. In 2011 he co-founded Fellow Robots, a company that provides robots for retail settings. He has ten patents, over 50 articles in scientific journals and has served on two scientific journal editorial boards.


Andrés del Campo Novales: AI hobbyist passionate about the idea of a general AI. He is a Software Engineer with 15 years of professional experience. He has been working for Microsoft in Denmark for the last 11 years in business applications. Andrés studied computer science & engineering at Córdoba and Málaga. He created a chatbot that could learn conversation patterns, context and numerical systems.
Andreas Ipp: Andreas Ipp works as a research fellow at the TU Wien where he obtained his habilitation in the field of theoretical physics. His current research is focused on simulating the production of the quark-gluon plasma in heavy ion colliders like the LHC in CERN. After obtaining his PhD, he had postdoctoral fellow positions in Italy and at the Max Planck Institute in Germany. Since his return to TU Wien, he is involved in teaching activities, including lecturing on quantum electrodynamics. Apart from his scientific achievements, he founded the choir of the TU Wien a few years ago, which successfully participates at international choir competitions.

Susumu Katayama: Assistant professor at the University of Miyazaki in Japan, inventor of the MagicHaskeller inductive functional programming system. He has been working on inductive functional programming (IFP) for fifteen years. His research goal is to realize a human-level AI based on IFP.








It’s great to see our participants coming from such different walks of life and I wonder if Dan Barry has every played our Space Engineers! :-)

I was also inspired by the passion of our participants. Andrés del Campo Novales only learnt about the competition a couple of months ago. However, this didn’t stop him putting in over 150 hours during the weekend and in the evenings.

Next steps


We have listened to the feedback from participants, and eagerness of our finalists to continue their work and improve on the quantitative challenge. Therefore, we have decided we will continue the gradual learning round of the Challenge in 2018.

In the meantime you can get involved in the second round of the General AI Challenge which will launch in November 2017 and will focus on AI Race avoidance. With the increasing rate of progress made in the AI field, developers might race towards being the first to achieve general AI and might neglect either safety procedures or agreements with other stakeholders for the sake of first mover advantage. Participants will be asked to come up with a proposal of what practical steps can be taken to avoid the pitfalls of the AI race and advance the development of beneficial general AI.

Thank you for reading!

Marek Rosa
CEO, Founder, Keen Software House
CEO, CTO, GoodAI
:-)

For more news:
General AI Challenge: www.general-ai-challenge.org
AI Roadmap Institute: www.roadmapinstitute.org
Space Engineers: www.spaceengineersgame.com
Medieval Engineers: www.medievalengineers.com

Personal bio: Marek Rosa is the CEO and CTO of GoodAI, a general artificial intelligence R&D company, and the CEO and founder of Keen Software House, an independent game development studio best known for their best-seller Space Engineers (2mil+ copies sold). Both companies are based in Prague, Czech Republic. Marek has been interested in artificial intelligence since childhood. Marek started his career as a programmer but later transitioned to a leadership role. After the success of the Keen Software House titles, Marek was able to personally fund GoodAI, his new general AI research company building human-level artificial intelligence, with $10mil. GoodAI started in January 2014 and has grown to an international team of 20 researchers.









Monday, September 25, 2017

Space Engineers Skins Sale (Concluded)


SUMMARY:
  • 6 skin sets available for purchase
  • Sale starts September 25, only open for a few days
  • Store option has been requested by players
  • Rules of screenshot competition are not changing


This sale has now ended. Thank you for your feedback and we hope
you enjoy your newly acquired skins!

Hello Engineers!

Today we’re excited to announce a special limited-time sale for some select skins you’ve been asking for! Starting on Monday, September 25, you will be able to purchase six skin sets. This sale will only last for a few days, so make sure to check it out on Steam Item Store (this sale has now ended) before it’s too late!

The skins up for sale are:
  • Graffiti
  • Police
  • Prisoner
  • Skeleton
  • Digi Camo
  • Lava

We’ve had lots of requests from players asking for a way to simply purchase skins instead of spending time chasing down containers to find those elusive badger boots. In light of the ongoing screenshot competition we’ve decided to not sell all the skin sets, instead we’ve selected some of the more popular mid-tier sets for you to purchase.


If you’re only missing one or two pieces from a suit, you can buy those separately, but if you buy all eight pieces at once, you get a special bundle discount!

If you have questions about the skin system, see my blog post about skins for more info. We addressed some of the most common questions and concerns in this post when we released skins.

The rules for the screenshot competition haven’t changed, and users who have purchased skins won’t be judged any differently. We are judging the screenshots based on style, composition, and creativity, not which skin you bought. So keep sending in screenshots whether you bought your skin from the workshop or earned it the hard way. All of us at Keen love seeing the amazing creativity coming from our community, so keep it coming!


Space Engineers is still in development. Everything in the game is subject to change.

Thank you for reading!

Marek Rosa
CEO and Founder of Keen Software House
CEO, CTO of GoodAI

For more news:
Space Engineers: www.spaceengineersgame.com
Medieval Engineers: www.medievalengineers.com
General AI Challenge: www.general-ai-challenge.org
AI Roadmap Institute: www.roadmapinstitute.org
GoodAI: www.goodai.com
Keen Software House: www.keenswh.com

Personal bio:

Marek Rosa is the CEO and CTO of GoodAI, a general artificial intelligence R&D company, and the CEO and founder of Keen Software House, an independent game development studio best known for their best-seller Space Engineers (2mil+ copies sold). Both companies are based in Prague, Czech Republic.
Marek has been interested in artificial intelligence since childhood. Marek started his career as a programmer but later transitioned to a leadership role. After the success of the Keen Software House titles, Marek was able to personally fund GoodAI, his new general AI research company building human-level artificial intelligence, with $10mil.

GoodAI started in January 2014 and has grown to an international team of 20 researchers.