Herself’s Artificial Intelligence

Human Computer Interfaces
Game Theory
Probabilistic Graphical Models
Computer Science 101
Software as a Service
Machine Learning
Natural Language Processing
Cryptography
Design and Analysis of Algorithms I
and
Lean Launchpad
Technology Entrepreneurship

I can’t recommend these classes enough. I’ve taken the iPhone Development, Intro to Artificial Intelligence, Intro to Databases, and Machine Learning classes.

It’s my thought that the future of education will not be 4 year degrees on site, but life long learning at home.

If you need to brush up on some math first try Khan Academy, Wolfram Math World.

Malware is in the eye of the beholder

Computer scientists predict that a new generation of malware will mine social networks for people’s private patterns of behaviour

It’s not hard top find frightening examples of malware which steals personal information, sometimes for the purpose of making it public and at other times for profit. Details such as names, addresses and emails are hugely valuable for companies wanting to market their wares.

But there is another class of information associated with networks that is potentially much more valuable: the pattern of links between individuals and their behaviour in the network–how often they email or call each other, how information spreads between them and so on.

Why is this more valuable? An email address associated with an individual who is at the hub of a vibrant social network is clearly more valuable to a marketing company than an email address at the edge of the network. Patterns of contact can also reveal how people are linked, whether in a relationship for example, whether they are students or executives or whether they prefer celebrity gossip to tech news.

This information would allow a determined attacker to build a remarkably detailed picture of the lifestyle of any individual, a picture that would be far more useful than the basic demographic information that marketeers use today which consists of little more than sex, age and social grouping.

We’ll almost certainly have to deal with this one sooner or later. source

Stealing Reality

It’s not just the malware, it’s also your future employer:

However, the pre-crime concept is coming very soon to the world of Human Resources (HR) and employee management.

A Santa Barbara, Calif., startup called Social Intelligence data-mines the social networks to help companies decide if they really want to hire you.

While background checks, which mainly look for a criminal record, and even credit checks have become more common, Social Intelligence is the first company that I’m aware of that systematically trolls social networks for evidence of bad character.

Using automation software that slogs through Facebook, Twitter, Flickr, YouTube, LinkedIn, blogs, and “thousands of other sources,” the company develops a report on the “real you” — not the carefully crafted you in your resume. The service is called Social Intelligence Hiring. The company promises a 48-hour turn-around. source

Social Intelligence

New FOIA Documents Reveal DHS Social Media Monitoring During Obama Inauguration

The Emerging Web of Social Machines

With the advent of smartphone technology, it has become possible to conceive of entirely new classes of applications. Social swarming, in which users armed with smartphones are directed by a central director to report on events in the physical world, has several real-world applications: search and rescue, coordinated fire-fighting, and the DARPA balloon hunt challenge. In this paper, we focus on the following problem: how does the director optimize the selection of reporters to deliver credible corroborating information about an event. We first propose a model, based on common intuitions of believability, about the credibility of information. We then cast the problem posed above as a discrete optimization problem, and introduce optimal centralized solutions and an approximate solution amenable to decentralized implementation whose performance is about 20% off on average from the optimal (on real-world datasets derived from Google News) while being 3 orders of magnitude more computationally efficient. More interesting, a time-averaged version of the problem is amenable to a novel stochastic utility optimization formulation, and can be solved optimally, while in some cases yielding decentralized solutions. To our knowledge, we are the first to propose and explore the problem of extracting credible information from a network of smartphones. source

paper ( pdf )

More information:
Thruthy, Indiana U webpage to test the truthiness of something using datamining
Fast Company story on Truthy