Would you let an AI make decisions for you? With all the buzz about AI and calls for its regulation (apparently AI will kill us all some day), I’ve been thinking about under what circumstances we might delegate decision making in certain areas to machines (call it AI). That’s not as crazy as it sounds, because mankind has been doing that for years already.
Archive for the ‘Artificial Intelligence (AI)’ Category
Deferring Decisions to AI
Wednesday, February 14th, 2018Machine Learning Newsticker
Saturday, April 2nd, 2016Shameless plug: I’ve fixed my scripts and my Machine Learning Newsticker (that reaches back to February 2005) is back in business. RSS Link Expect periodic updates on ML and AI related news items.
Starcraft AI competition
Friday, November 13th, 2009UCSC is holding a Starcraft AI competition. I wish I had the time to participate… Starcraft is one of my all time favorite games, and writing a better AI for a real-time strategy game is certainly interesting and challenging.
Famous bugs in AI game engine caught on tape
Saturday, May 2nd, 2009Found this on aigamedev and some of them are really hilarious: AI game bugs caught on tape
Automation of Science
Sunday, April 5th, 2009Two interesting articles in Science: The Automation of Science is about a robotic system that autonomously generated functional genomic hypotheses about a yeast. The second article, Distilling Free-Form Natural Laws from Experimental Data, is about a system learning from physics experiments and deriving a hypothesis from the data (this is along the lines of the general idea I’ve written about in the past). Cool stuff.
ISC on the Future of Anti-Virus Protection
Friday, August 1st, 2008An article on the Internet Storm Center discusses wether Anti-Virus software in the current state is a dead end. In my opinion it has been dead for quite a while now. Apart from the absolutely un-usable state that anti-virus software is in, I think it’s protecting the wrong things. Most attacks (trojans, spyware) nowadays come through web-browser exploits and maybe instant-messenger (see reports on ISC). So instead of scanning incoming emails, how about a behavior blocker for the web-browser and the instant messenger? There are a couple of freeware programs (e.g. IEController [German]) out there that successfully put Internet Explorer, etc. into a sandbox; whatever Javascript exploit – known or unknown – the browser won’t be able to execute arbitrary files or write outside its cache-directory. Why is there nothing like that in the commercial AV packages?
However, a few possibilities suggested in the article might be worth exploring. For example, they suggest Bayesian heuristics to identify threats. Using machine learning techniques might be a direction worth exploring. IBM AntiVirus (maybe not the current version anymore) has been using Neural Networks with 4Byte sequences (n-grams) for bootsector virus detection.
A couple things to keep in mind, though:
- Quality of the classifier (detection rate) should be measured with Area-under-ROC-Curve (AUC), not error-rate like most people tend to do in Spam-Filter comparisons. The base-rate of the “non-virus” class is pretty high; I have over 10.000 executables/libraries on my windows machine. All (most?) of them non-malicious.
- The tricky part with that is the feature extraction. While sequences of bytes or strings extracted from a binary might be a good start, advanced features like call-graphs or imported API-calls should be used as well. This is pretty tricky and time-consuming, especially when it has to be done for different types of executables (Windows scripts, x86-EXE files, .Net files etc.). De-obfuscation techniques, just like in the signature based scanners, will probably be necessary before the features can be extracted.
- Behavior blocking and sandboxes are probably easier, a better short-term fix, and more pro-active. This has been my experience with email-based attacks as well back in the Mydoom days when a special mime-type auto-executed an attachment in Outlook. Interestingly there are only two programs out there that sanitize emails (check mime-types, headers, rename executable attachments etc.) at the gateway-level – a much better pro-active approach than simply detecting known threats. The first is Mimedefang, a sendmail plugin. The other is impsec, based on procmail. CU Boulder was using impsec to help keep student’s machines clean (there were scalability issues with the procmail solution, though).
The cloud obscuring the scientific method
Saturday, July 12th, 2008“All models are wrong, and increasingly you can succeed without them” — George Box
“Sometimes…” — Me
In a Wired article about the Peta-byte age of data processing the author claimed that given the enormous amounts of data and the patterns found by data mining we are less and less dependent on scientific theory. This has been strongly disputed (see Why the cloud cannot obscure the Scientific Method) as the author simply ignores the fact that all the patterns that were found are not necessarily exploitable – finding a group of genes that interact is a first step, but won’t cure cancer. However, in machine translation or placing advertising online one can succeed with little to no domain knowledge. That is, once somebody comes up with the right features to use (see Choosing the right features for Data Mining).
What would be interesting to develop, however, is a “meta-learning” algorithm that can abstract from simpler models and learn e.g. a differential equation. For example, lets take data from several hundred Physics experiments about heat-distribution conducted on different surfaces etc. We can probably learn a regression model for one particular experiment which could predict how the heat will distribute given the parameters of the experiment (material, surface etc.). The meta-learning algorithm would then look at these models and somehow come up with the heat-equation. That would be something…
Artificial Addition (Overcoming BIAS)
Friday, November 23rd, 2007I found the following article interesting: http://www.overcomingbias.com/2007/11/artificial-addi.html
What Machine Learning Papers to read …
Friday, July 13th, 2007Laura just pointed me to this system, best described as:
I have a routine problem that sometimes paper titles are not enough to tell me what papers to read in recent conferences, and I often do not have time to read abstracts fully. This collection of scripts is designed to help alleviate the problem. Essentially, what it will do is compare what papers you like to cite with what new papers are citing. High overlap means the paper is probably relevant to you. Sure there are counter-examples, but overall I have found it useful (eg., it has suggested papers to me that are interesting that I would otherwise have missed). Of course, you should also read through titles since that is a somewhat orthogonal source of information.
http://www.cs.utah.edu/~hal/WhatToSee/
I have the same problem. And wow… I will have a lot to read this weekend.
Interesting Experimental Captchas
Monday, June 11th, 2007Captchas are these little word-puzzles in images that web-sites use to keep spammers and bots out. They are everywhere and even the New York Times had an article about Captchas recently. It turns out it’s a nice exercise in applying some machine learning to break these things (with lots of image manipulation to clean up the images). Since spam-bots are becoming smarter, people are switching to new kinds of Captchas. My favorites (using images) so far are Kittenauth and a 3D-rendered word-captcha.