Techniques, unique software, systems, models & tools

No one but no one has access to the range of the most advance targeting, optimising and modelling techniques in the industry. Many of these techniques are academically reviewed by peers & are published in academic journals. However, the guts and the further development to our applied systems are unique to us. No one else in the world has the technology and systems which we have at our disposable, No one is even an order of magnitude close to us.

Others talk of what algorithms can achieve. We were actually part of that process. We go back to Control Data Corporation computers (CDC 7600/6600/6400s 60 bit machines which gave us 120 bits word length in Fortran IV) joint with Northwestern University running on the University of London’s computer centre in Guildford Street where some of our team members were classified as trouble makers for hogging extreme amounts of what was then one of the most powerful computers in the world - working on Chess 4.0 to 4.7.

For a time in the 1970s and 1980s it was unclear whether any chess program would ever be able to defeat the expertise of top humans. In 1968, International Master David Levy made a famous bet that no chess computer would be able to beat him within ten years. He won his bet in 1978 by beating Chess 4.7 (our program playing on the most powerful computer at the time), but acknowledged then that it would not be long before he would be surpassed. In 1989, Levy was defeated by IMB’s Deep Thought in an exhibition match. Deep Thought had many of the algorithms first developed in Chess 4.7. Deep Thought metamorphosed into IBM’s Deep Blue which did go on to beat Levy and indeed Garry Kasparov (who initially defeated Deep Thought). The basic technology was built on advanced predictive modeling and learning algorithms. We actually helped to invent and worked on Chess 4.7. Those same systems are also present in current world-class chess programs such as Junior, Fritz, Naum, Crafty, Rebel and the world leading chess engine Rybka (rated at 3232 Elo).

This landmark event showed that by combining computing power, with advanced statistical modeling and pre-programmed expertise, a machine could not just solve complex problems, but also out think and beat competitors in head on competition. It could recall history, and make judgments. It could learn. This paved the way for computing & artificial intelligence into industry, to solve complex problems like, financial modeling – of which among our team members is someone who has published extensively on modelling.

Other major systems written include complex modeling (with artificial intelligence) for many of the surviving major car manufacturers, intelligent financial modelling, airline reservations systems, banking systems, credit card processing systems, bank unification and inter-bank transactions (worldwide), GPS (mobile phone systems). These were undertaken as part of the European Commission’s Race and Esprit programs and amounted to around $500 million.

Today, AFS has built on those same technologies and principles to create a suite of systems (not a single system) to help with our bid management and optimization. A set of systems that examines and utilizes the mathematical and data demands placed on marketers, in analyzing and managing large complex search campaigns, and continually improving your profitability and/or targets in what in an increasingly competitive environment on the net.

These are some of the technique we use combined into an integrated network of hierarchical solutions: