Technological Convertibles?

Sascha Kratky, our Senior SW Engineer, just returned from the Mathematica User Conference. After his summary in a short workshop, I feel a bit dizzy. So many advances from tying things together which have been designed and implemented in a unified way. Things are not reused in the traditional way, they are built on-top-of-themselves and provide the capabilities of, what I would call convertibles.

For my uni software plus , developers and business developers, it is difficult to keeping the pace with Wolfram's achievements in an innovative spirals that accelerates. New possible platforms, solutions, uses and users are just emerging from a fast growing technology base that is convertible.

Mathematica does not only develop in depth but it approaches a universality stage that is unprecedented in technical computing. It drives WolframAlpha widely accessible but with the API you can use WA from your desktop application.

It is close to 20 years that we have selected Mathematica as our platform for creating a new kind of business.

We have recently released mlf 2 and we will ship UnRisk 4 from tomorrow, and after a week UnRisk FACTORY 2, all grid-enabled, task-automating, multi-method, multi-language, multi-front-end. With Mathematica 7 as platform.

And shhh we are exited about what comes next.

My Programs Ask

In my History of Future topic, I have tried to make evident that my mathematics-related business life was challenged by fundamental technology developments, most now realized in Mathematica that drives the computational part of WolframAlpha the computational knowledge engine.

Not so surprisingly there is an iPhone App .

But the innovative spiral gets another drift by the Wolfram announcements of the Wolfram Alpha Web Service API , giving access to the WolframAlpha platform.

To me this means that programs can ask WolframAlpha and integrate own results into the WA result styles.

Like courseware for Go to School but not Into School or creating kind of EveryWare in any field of computational applications.

It is fantastic. Our senior software engineer Sascha Kratky will get more insight from tomorrow on, at the International Mathematica User Conference 2009.

As Stephen Wolfram says in his blog, A Big Week for WolframAlpha .

The 7 Deadly Sins

In WIRED, Sep-09, they presented an infographics example by mapping sins created by plotting per-capita-statistics onto the US map. Greed by income spreads, Envy by thefts, Wrath by violent crime, Sloth, Gluttony, Lust, Pride also on single factor stats (no sorry, Pride as overlay of the other). A nice try, but a simplification that I find poor (to say the most polite ...).

In quantitative finance, we would be lucky to be able to model greed and fear, important factors for high leveraging deal spaces and finally bubble building? But their interdependence has its dynamic in a kind of co-evolution. And greed might be good in some cases (reasonable risk taking)? And it is absolute. But envy is bad, because it is relative (to your"neighbour"). Too much envy in finance?

However, the analysis of such "irrational", "behavioral" factors might become more important. But if, we need to put all our best efforts to analyse them in multi-variant parameter spaces and apply multi-method systems, like mlf on Mathematica .

And I think, Stephen Wolfram's NKS !

Unrest before a new UnRisk ....

I have pre-announced UnRisk PRICING ENGINE version 4 in UnRisk Insight, titled Unrest . Testresults suggest the ralease in about 2 weeks. And we will release UnRisk FACTORY version 2 within a few days after UnRisk 4.

My Unrest comes from my responsibility to do the create awareness actions right. The new releases contain so many new features, but I want to avoid the eager-seller trap ...

In addition to many new features UnRisk 4 and UnRisk FACTORY 2 are full Mathematica 7 versions.

They use its new built-in parallelism, built-in integration tools and also its fantastic documentation framework for in-product and on-the web documentation.

But let me come back to testing.

Our FACTORY combines a grid-enabled PRICING ENGINE with a data base, a web connection layer and comprehensive UnRisk services realized in Java.

Each user-session (automated by scripts) creates a log document in form of a Mathematica 7 notebook that contains each single system-action, automatically. This notebook is re-fed into the PRICING ENGINE and allows us for comprehensive automated test cycles for interactive sessions and batch processes.

The same mechanism enables us to perform unexpected short support cycles.

Having selected Mathematica pays back manifold. UnRisk 4 will be the 16th major release in 7 years. And I need to recognize that excitement and unrest come as twins.

Predicting The Present

Weather forecasting is a field where advanced modeling is fruit of challenging research from model physics (thermo- and fluid dynamics, ..) to atmospheric chemistry. Advanced numerical schemes and sw architectures allowing HPC and the management of massive data are applied. The approach is multi-strategy and multi-methods. The quality-at-time-in-advance of the forecast is related to the resolution of information.

For many applications highly precise weather predictions are important. Take the energy efficient control of (large) buildings. Focussing on such applications one needs a kind of embedded calibration system which takes the sensor information of the buildings and the coarser weather models and refine them by turning historical informations into precise local predictions. For the next hours.

Blue Sky Weather Analytics, an Austrian specialist for local weather-related products, has developed such a high-precision short term predictor based on our machine learning framework .

Go To School - But Not Into School

It was a beautiful, sunny late-summer weekend. With a few scattered clouds. I enjoyed it, reading about various things on my terrace.

Buildings in the neighbourhood, even being invariant in their facades, looked individual with unexpected contrasts, in the sun. I took a book on complexity-or-minimalism in architecture ....

and then some articles on complexity-or-minimalism of financial modelling, .... In the crisis, we have learned about many things in the laboratory of reality of financial markets. Shall we continue to believe in the Efficient Market Hypothesis, or change to more evolutionary modeling, simulating the behaviour of market participants?

How many further experiments in the laboratory of reality do we need?

And I refreshed my little knowledge in explorative and constructive learning. Thinking of obtaining computational power, Mathematica and comprehensive courseware from the cloud and use it for the construction of individual knowledge. Life-long.

How long will it take to de-monopolize education from location (school), person (teacher) and content (syllabus)? Forever?

How many cheeses?

I looked into the program of Mathematica User Cónference 2009 and when reading Wine-and-Cheese Reception I thought: "how many cheeses will people know in different territories in average?" In some, probably 7? I think, I know approx. 100, preferably French, Italian, English, Spanish, Swiss .... with very local ones like Ami-du-Chambertin, Castelmagno, Oxford Blue, Cabrales, Sbrinz, ..

Then I typed into Wolfram Alpha "cheese", knowing this is asking for static info and not computational knowledge. But yes, I got a list of more general cheese types (40?). Not bad, I thought and then "Roquefort", "Limburger", "Gruyere", ... returning useful info, like nutrition facts, nutrients compared to other food, calories, vitamins, ... Wow.