blog.andrewprendergast.com Open in urlscan Pro
2a00:1450:4001:810::2013  Public Scan

Form analysis
0 forms found in the DOM

Text Content

Your browser doesn't appear to support the HTML5 canvas element.



AP ON COMPUTERSCIENCEFUTURES

SECURING THE FUTURE OF COMPUTER SCIENCE.

Optimised for desktop first.





TUESDAY, 14 MARCH 2023


CURRENT STATE OF WEBGL / GLSL



If you are paying attention close enough, you might have noticed that in the
background of this blog is a very simple and strightforward wave simulation
using GLSL or WebGL. It has specifically been written in accordance with the
OpenGL Shading Language, Second Edition [1,2] text in mind so it is compatible
with every single WebGL implementation ever conceived, and is almost completely
decoupled from the browser. It has some intentional 'glitch' in it, which is a
reference to the analog days of Sutherland's work.

Specifically, the simulation uses a textbook implementation of GLSL, as follows:

 * GLSL 1.2
 * OpenGL ES 2.0
 * WebGL 1.0

The only coupling to the browser is the opening of a GL context, and if one
clicks on the animation in the right place, an "un-project" operation that
unwinds the Z-division takes place so that the fragment that underlies the mouse
cursor can be calculated and the scene can be rotated using a very primitive
rotation scheme which includes gimble lock (no quarternions here!). Both are
extrordinarilly simple 3D graphics operations that should not affect rendering
at all and is the absolute minimum level of coupling one might expect. In short,
it is the perfect test of the most basic of WebGL capability.

The un-project operation is written with the minimal amount of code required and
uses a little linear algebra trick to do it very efficiently. Feel free to
inspect the code to see how it's done.


CURRENT STATE

Update 26-Jun-23: After much trial and error, and testing on many many devices, I now have successfully isolated three separate WebGL bugs. Now that I have the three bugs properly isolated, I'm starting the writeup and hope to submit the following bug reports in the next week or two, as follows:

 1. Incorrect rendering of WebGL 1.0 scene in Google Chrome
 2. WebGL rendering heisenbug causes GL context to crash in Chrome after handling some N fragments
 3. WebGL rendering heisenbug causes GL context to incorrectly render scene after handling some N fragments
TBC...


The current state as at 14-March-2023 is that Chrome and other browsers are not
able to run this animation for more than 24 hours without crashing, and on the
latest versions of Chrome released early March, the animation has now slowed
down to ridiculous FPS levels. Previously the animation ran at well over 30 FPS
on most devices, but would crash after 24 hours.

This animation will quite happily run on an old iPad running Safari, however
Chrome currently seems to be struggling. The number of vertices and the the
number of sin() operations that it needs to calculate is well within the
capabilities of all modern processors, including those found in i-devices such
as phones and tablets on which one can play a typical game.


Example of correct rendering on all modern browsers including Safari on iPad


Example of incorrect rendering on Chrome 111.0.5563.111 (64-bit) as at 23-Mar-23


Brave Browser (based on Chromium) renders correctly, but is horrendously slow in
the GA branch (Beta currently works fine). I'm not sure if this is a Linux vs.
Windows issue or discrete vs. embedded GPU at this stage, will investigate
further when I have time.

NB. As at 14-March-2023, on Brave Browser 1.49.120 on Windows with a Discrete
GPU the simulation struggles to render 5 FPS, and on Brave Browser 1.50.85
(beta) on Linux with an embedded GPU it works OK, but I can point to other
vizualisation artefacts elsewhere that 1.50.85 cannot handle (but which previous
versions of Brave/Chrome could), for example, on the homepage of
vizdynamics.com, the Humanized Data Robot should gently move around the screen
with a slight parallax effect if one moves the mouse over it. Why is the
rendering engine in Chrome suddenly regressing, and why is it not using the GPU?
This wave simulation should be able to run in it's entirety on SIMD architecture
and the Humanized Data Robot used to be rendering flawlessly. What is going on?

At 30 FPS, the wave simulation requires around 75 MFLOPS of processing power. To
put that into perspective, the first Sun Microsystems SPARC Station released in
1989 was able to calculate 16.2 MIPS (similar to MFLOPS), and the SPARC Station
2 (released 1991) could calculate nearly 30 MIPS. That was over 30 years ago,
and a SPARC Station 2 machine had enough compute power that it could happily
calculate the same wave simulation at around 10-15 FPS without vizualising it,
but actually at 2-5 FPS once one implements a GPU pipeline (thank god SGI bought
out IRIS GL).

I still have my copy of the original OpenGL Programming Guide (1st edition, 6th
printing) that came with my Silicon Graphics Indy workstation. It was a curious
book, and I implemented my first OpenGL version of these wave simulations in
1996 according to it, so I'm quite familiar with what to expect. An Indy could
handle this - with a bit of careful tuning - quite well. The hardness of this
vizualisation is the tremendous number of sin() operations, and the cosine()s
used to take their derivative, so it really does test the compute power of a
graphics pipeline quite well - if the machine or the implementation isn't up to
it, these calculations will bring it to it's knees quite quickly.

Fast-forward to 2023, and a basic i7 cannot run the simulation at 30FPS! To put
things into perspective, a 2010 era Intel i7 980 XE is capable of over 100
GFLOPS (about 1000x more processing power than whats required to do 75 MFLOPS),
and that's without engaging any discrete or integrated SIMD GPU cores. Simply
put, the animation in the background of this blog should be trivial for any
computing device available today, and should run without interruption.

Lets see how well things progress through March and if things improve.


REFERENCES

[1] Rost, Randi J., and John M. Kessenich. OpenGL Shading Language. 2nd ed.
Addison-Wesley, 2006. OpenGL 2.0 + GLSL 1.10

[2] Shreiner, Dave. OpenGL Programming Guide the Official Guide to Learning
OpenGL, Version 2. 5th ed. Upper Saddle River, NJ u.a: Addison-Wesley, 2006.


Posted by Andrew (AP) Prendergast at 5:15 pm 2 comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




SATURDAY, 4 MARCH 2023


YOU ARE ALL IN A VIRTUAL



I love Urban Dictionary - watch out for my @CompSciFutures updates. Here's one I
posted today:



This is actually a commentary on attack surfaces, specifically that back in the
day, one's lead architect knew the entirety of a system's attack surface and
would secure it appropriately. Today, systems are so complex, that no single man
knows the entire intricacies of the attack surface for even just a small web
application with an accompanying mobile app. The security implications of this
are profound, hence the reason why I am writing a textbook on the topic.

Link to more Urban Dictionary posts in the footer.


Posted by Andrew (AP) Prendergast at 11:02 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




TUESDAY, 21 FEBRUARY 2023


SOFTWARE ENGINEERING MANUAL OF STYLE, 3RD EDITION



My apologies to everyone I was supposed to follow up with in January - I've been
writing a textbook. I'll get back to you late February/early March, I'm locking
down and getting this done so we can address the systemic roots of this
ridicuous cyber security problem we have all found ourselves in.

The book is called:




The Software Engineering Manual of Style, 3rd Edition
A secure by design, secure by default perspective for technical and business
stakeholders alike.



The textbook is 120 pages of expansion on a coding style guide I have maintained
for over 20 years and which I hand to every engineer I manage. The previous
version was about 25 pages, so this edition is a bit of a jump!


SECURE-BY-DESIGN, SECURE-BY-DEFAULT SOFTWARE ENGINEERING. THE HANDBOOK.

It covers the entirety of software engineering at a very high level, but has
intricate details of information security baked into it, including how and why
things should be done a certain way to avoid building insecure technology that
is vulnerable to attack. Not just tactical things, like avoiding 50% of buffer
overruns or most SQL injection attacks (and leaving the rest of the input
validation attacks unaddressed). This textbook redefines the entire process of
software engineering, from start to finish, with security in mind from page 1 to
page 120.

Safe coding and secure programming are not enough to save the world. We need to
start building technology according to a secure-by-design, secure-by-default
software engineering approach, and the world needs a good reference manual on
what that is.

This forthcoming textbook is it.


LATEST EXCERPTS


21-Feb-23 Excerpt: The Updated V-Model of Software Testing
(DOI: 10.13140/RG.2.2.23515.03368)


21-Feb-23 Excerpt: The Software Engineering Standard Model
(DOI: 10.13140/RG.2.2.23515.03368)


EDIT 22-Mar-23: Proof showing that usability testing is no longer considered
non-functional testing
(DOI: 10.13140/RG.2.2.23515.03368)


EDIT 22-Mar-23: The Pillars of Information Security, The attack surface
kill-switch riddle +
The elements of authenticity & authentication (DOI: 10.13140/RG.2.2.12609.84321)


EDIT 22-Apr-23: The revised Iterative Process of Modelling & Decision Making
(DOI: 10.13140/RG.2.2.11228.67207/1)


EDIT 18-May-23: The Lifecycle of a Vulnerability
(DOI: 10.13140/RG.2.2.23428.50561)




AUDIENCE

I'm trying to write it so it's processes and methodologies:

 * Can be baked into a firm by CXOs using strategic management principles; or
 * embraced directly by engineers and their team leaders without the CEOs shiny
   teeth and meddlesome hands getting involved.

Writing about very technical matters for both audiences is hard and time
consuming, but I think I'm getting the hang of it!


ABSTRACT FROM THE COVER PAGE

The foreword/abstract from the first page of the text reads as follows:

"The audience of this textbook is engineering based, degree qualified computer
science professionals looking to perfect their art and standardise their
methodologies and the business stakeholders that manage them. This book is not a
guide from which to learn software engineering, but rather, offers best
practices canonical guidance to existing software engineers and computer
scientists on how to exercise their expertise and training with integrity, class
and style. This text covers a vast array of topics at a very high level, from
coding & ethical standards, to machine learning, software engineering and most
importantly information security best practices.

It also provides basic MBA-level introductory material relating to business
matters, such as line, traffic & strategic management, as well as advice on how
to handle estimation, financial statements, budgeting, forecasting, cost
recovery and GRC assessments.

Should a reader find any of the topics in this text of interest, they are
encouraged to investigate them further by consulting the relevant literature.
References have been carefully curated, and specific sections are cited where
possible."

The book is looking pretty good: it is thus far what it is advertised to be.


HELPING OUT AND DONATING

The following link will take you to a LinkedIn article that I am publishing
various pre-print extracts (some are also published above).

If you are in the field of computer science or software engineering, you might
be able to help by providing some peer-review. If not, there is a link to an
Amazon booklist that you can also contribute to this piece of work by donating a
book or two.

Visit the book's homepage on LinkedIn »

And feel free just to take a look and see where we're going and what's being
done to ensure that moving forward, we stop engineering such terribly insecure
software. Any support to that end would be most appreciated.

Edited 22-Mar-23: added usability testing proof
Edited 22-Mar-23: added Pillars of Cybersecurity



Posted by Andrew (AP) Prendergast at 12:03 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




SUNDAY, 1 JANUARY 2023


VIZLAB 2.0 CLOSURE



VizDynamics is still a trading entity, but VizLab 2.0 is now closed. The lack of
attention to cybersecurity by state actors, big tech and cloud operators
globally made it impossibly difficult to continue operating an advanced computer
science lab with 6 of Melbourne's best computer scientists supporting corporate
Australia. We could have continued, but we saw this perfect storm of cyber
security coming and decided to dial down VizLab starting in 2017. Given recent
cyber disasters, it is clear we made the right decision.

State actors, cloud operators and big tech need to be careful with “vendor
backdoor” legislation such as key escrow of encryption, because this form of
'friendly fire' hides the initial attack vector and the intial point of network
contact when trying to forensically analyse and close down real attacks. Whilst
that sort of legislation is in place without apporpriate access controls, audit
controls, detective controls, cross-border controls, kill switches and
transparency reporting, it is not commercially viable for us to operate a high
powered CS lab, because all the use cases corporate Australia want us to solve
involve cloud-based PII, for example, ‘Prediction Lakes’.


A CS LAB DESIGNED FOR PAIRED PROGRAMMING

Part MIT Media lab, part CMU Autonlab, part vizualistion lab, part
paired-programming heaven: this was VizLab 2.0.


VizLab doorway with ingress & egress Sipher readers, Inner Range high frequency
monitoring & enterprise class CCTV.
A secure site in a secure site.



A BSOD in The Lab: The struggles of WebGL and 3D everywhere.
Note the 3-screen 4k workstation in the foreground designed
for paired local + remote programming.




The Lab - Part vizualisation, part data immersion. VizLab 2.0.
Note the Eames at the end of the centre aisle.



Each workstation was setup for paired programming. 6 workstations, where you
could plug in 2 keyboards, 2 mice, 2 chairs side-by-side and enough room so that
you weren't breathing on eachother with returns either side big enough for a
plethora of academic texts, client specs and all the notes you could want. With
2 HDMI cables hung from the roof linking to projectors on opposing walls that
could reach any workstation at any moment, this was an environment for working
on hard things; collaboratively, together.

Note the lack of client seating. They would have to perch on the edge of a desk
and see everything, or an Eames lounge at the end of the room and try to see
everything, or a White real leather Space Furniture couch next to a Tom Dixon
and see nothing - we took host to management teams from a plurality of ASX200s,
and the first thing that struck them — we didn't have seating for them, because
the next few hours they were going to be moving around and staring at walls,
computers, the ceiling — there simply was nowhere to sit, when a team of
computer scientists, trained in computer graphics and very deft with data
science were taking them on a journey into Data.


THE NOW: VIZLAB 3.0 – THE FUTURE: VIZLAB 4.0

AP is still around and is spending the most part of 2023 writing a textbook on
secure software engineering, and we've setup a smaller two-man VizLab 3.0 for
cyber defence research mainly around GRC assessment and computer science
education both at a secondary and a tertiary level. AP is currently doing
research in that field so we can hopefully reduce cyber-risk down to a level
that is acceptable to coprorate Australia by increasing the mathematical and
cyber-security awareness and literacy of computer science students as they enter
into university and then industry.

If we can help to create that environment, then VizLab 4.0 may materialise and
will be bigger and better, but because we dialed back our insurances (it's not
practical to be paying $25K pa while we're doing research), we aren't in a
position to provide direct consultation services at the moment. VizDynamics is
still a trading entity, and a new visualisation based Information Security brand
might be launched somewhere in 2024 based on the “Humanizing Data” vizualisation
thesis (perhaps through academia or government – we’re not sure yet). Fixes are
happening to WebGL rendering engines, and slowly cyber security awareness is
rising to the top of the agenda, so our work is slowly shifting the needing and
we’re moving in the right direction.

If you want to keep track of what AP's up to, vizit blog.andrewprendergast.com.


Posted by Andrew (AP) Prendergast at 9:11 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




SUNDAY, 4 DECEMBER 2022


THE PATH TO BUILDING STARK-TREK STARSHIPS



Posted by Andrew (AP) Prendergast at 10:30 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest

Location: San Francisco, CA, USA


SATURDAY, 5 NOVEMBER 2022


THE MIND BLOWING HARBINGER OF WIRED 1.01



Wired magazine 1.01 was published in 1993 by Nicholas Negreponte & Louis
Rosetto.

Every issue contained inside the front cover a 'Mind Grenade', and the one from
the very first issue (1.01) is -- in hindisght -- creepy. Here it is:


The 'mind grenade' from Wired 1.01, Circa March 1993.


Damn Professor Negroponte, you ring truer every day.


Posted by Andrew (AP) Prendergast at 3:19 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




FRIDAY, 21 OCTOBER 2022


RECOMMENDER SYSTEMS



Recommender systems are huge outside of Australia and USA such that most
marketing managers now consider their optimisation as important as Search Engine
Marketing (SEM). I can't believe we have totally missed the ball on this one,
and nobody on the other side of planet, from Dubai to London has bothered to
tell us!

Anwyays, here's the original seminal paper that Andreas Wiegend (ex Stanford,
market genius and inventor of Prediction Markets and The BRIC Bank, Chief
Scientist Emeritus of Amazon.com and inventor of recommender systems) directed
and promoted this paper. It's based on proper West Coast Silicon Valley AI, with
a quality discussion about a number of related techologies and market related
effects that impact recommender systems.

Enjoy!

Posted by Andrew (AP) Prendergast at 3:36 am No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




SUNDAY, 17 JULY 2022


I LOVE FOURIER DOMAIN


I've been playing with building a Swarm Intelligence simulator based on a
fourier domain discretisation to schedule the placement of drones in 3D space
and cars in 2D space. Here's a little video demo of it's basic structure in
action, on top of this is some differential equations to capture the
displacement field, then drone position coords:


LinkedIn post with a video demo of the simulator in structural mode.
You need to be logged into LinkedIn to see the post.



If you want to have a play with this class of sine wave, you might notice a simpler simulation in the background of this blog. It has a few extra features not normally seen of these types of simulation: instead of a single point being able to move along one axis (usually the Y-axis), every point in my simulation can move anywhere along the X, Y or Z axis. Take a look yourself, left-click and drag the mouse on the background (where the 3D simulation is happening) to rotate the simulation in realtime. Look below the surface to see the mesh, above it and you get a flat view. 

For best effect, try full-screen browser, remove all content and view just the background wave simulation.



Posted by Andrew (AP) Prendergast at 4:14 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




SUNDAY, 31 MARCH 2019


MY FAVOURITE VIZ OF ALL TIME




HOW GOOGLE USED VIZUALISATION TO BECOME ONE OF THE WORLDS MOST VALUABLE
COMPANIES

At VizDynamics we have done a lot of 'viz'-ualisation, so I’ve seen more than
several life-times worth of dashboards, reports, KPIs, models, metrics, insights
and all manner of presentation and interaction approaches thereof.


YET ONE VIZ HAS ALWAYS STUCK IN MY MIND.

More than a decade ago when I was post start-up exit and sitting out a
competitive-restraint clause, I entertained myself by travelling the world in
search of every significant thought leader and publication about probabilistic
reasoning that I could find. Some were very contemporary; others were most
ancient. I tried to read them all.




A much younger me @ the first Googleplex (circa 2002)


Some of this travelling included regular visits to Googleplex 1.0, back before
they floated and well before anyone knew just how much damn cash they were
making. As part of these regular visits, I came across a viz at the original
‘Plex that blew me away. It sat in a darkened hall in a room full of engineers
on a small table at the end of a row of cubicles. On this little IBM screen was
an at-the-time closely guarded viz:



The "Live Queries" vizualisation @ Googleplex 1.0


Notice the green data points on the map? They are monetised searches. Notice the
icons next to the search phrases? More “$” symbols meant better monetisation.
This was pre-NPS, but the goal was the same – link $ to :) then lay it bare for
all to see.


WHAT MAKES THIS UNASSUMING VIZ SO GOOD?

It's purpose.

Guided by Schmidt’s steady hand, Larry & Sergey (L&S) had amassed the brainpower
of 300+ world leading engineers, then unleashed them by allowing them to work
independently. They now needed a way for them to self-govern and -optimise their
continual improvements to product & revenue whilst keeping everyone aligned to
Google's users-first mantra.

The solution was straightforward: use vizualisation to bring the users into the
building for everyone to see, provide a visceral checkpoint of their mission and
progress, and do it in a humanely digestible manner.

Simple in form & embracing of Tufteism, the bottom third of the screen scrolled
through user searches as they occurred, whilst the top area was dedicated to a
simple map projection showing where the last N searches had originated from. An
impressively unpretentious viz that let the Data talk to one’s inner mind. The
pictograph in the top section was for visual and spatially aware thinkers, under
that was tabular Data for the more quantitative types. And there wasn’t a single
number or metric in sight (well not directly anyway). Three obviously
intentional design principles executed well.

More than just a Viz, this was a software solution to a plurality of
organizational problems.

To properly understand the impact, imagine yourself for a moment as a Googler,
briskly walking through the Googleplex towards your next meeting or snack or
whatever. You alter your route slightly so you can pass by a small screen on
your way through. The viz on the screen:

 * instantly and unobtrusively brought you closer to your users,
 * persistently reminded you and the rest of the (easily distracted) engineers
   to stay focused on the core product,
 * provided constant feedback on financial performance of recent product
   refinements, and
 * inspired new ideas

before you continued down the hall.


THE BEST VIZUALISATIONS HUMANISE DIFFICULT DATA IN A VISCERAL WAY

This was visual perfection because it was relevant to everyone, from L&S down to
the most junior of interns. Every pixel served a purpose, coming together into
an elegantly simple view of Google's current state. Data made so effortlessly
digestible that it spoke to one’s subconscious mind with only a passing glance.
A viz so powerful that it helped Google to become one of the world’s most
valuable companies. This was a portal into people's innermost thoughts and
desires as they were typing them into Google. All this... on one tiny little IBM
screen, at the end of a row of cubicles.


Posted by Andrew (AP) Prendergast at 1:29 am No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest

Location: Sunnyvale, Silicon Valley, CA, USA


THURSDAY, 1 JUNE 2017


ACLAND STREET – THE GRAND LADY OF STKILDA



Acland Street is the result of two years of research. As well as extended
archival and social media research, more than 150 people who had lived, worked,
and played in Acland Street were interviewed to reveal its unique social,
cultural, architectural, and economic history.

Of course we got a mention on page 133:


Note the special mention under 'The Technology', page 133. Circa 1995, published
2017.


Posted by Andrew (AP) Prendergast at 4:38 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest

Location: Acland St, Melbourne, Australia


TUESDAY, 1 SEPTEMBER 2015


CXO LEADERS SUMMIT



Posted by Andrew (AP) Prendergast at 3:02 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest

Location: Sydney NSW, Australia


THURSDAY, 30 OCTOBER 2014


INTRO TO BAYESIAN REASONING LECTURE



Here's a quick one to make the files available online from today's AI lecture at
RMIT University. Much thanks to Lawrence Cavedon for making it happen.






DOWNLOADS



Lecture Notes (PDF)





Course/grade/intelligence plate model example (Netica)





Output from sneezing diagnosis class exercise (Netica)





Burgular hidden markov model example (Netica)





Same burgular HMM in Excel (Excel)



Have fun and feel free to email me once you get your bayes-nets up and running!

Posted by Andrew (AP) Prendergast at 7:07 am No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest

Location: RMIT University, Melbourne, Australia


THURSDAY, 16 OCTOBER 2014


ACCESSING DATA WAREHOUSES WITH MDX RUNNER




It's always good to give a little something back, so each year I do some guest
lecturing on data warehousing to RMIT's CS Masters students.


We usually pull a data warehouse box out of our compute cloud for the session so
I can walk through the whole end-to-end stack from the hardware through to the
dashboards. The session is quite useful and always well received by students.








This year the delightful Jenny Zhang and I showed the students MDX Runner, an
abstraction used at VizDynamics on a daily basis to access our data warehouses.
As powerful as MDX is, it has a steep learning curve and the result sets it
returns can be bewildering to access programmatically. MDX Runner eases this
pain by abstracting out the task of building and consuming MDX queries.


Given that it has usefulness far beyond what we do at VizDynamics, I have made
arrangements for MDX Runner to be open-sourced. If you are running analysis
services or any other MDX-compatible data warehousing environment, take a look
at mdxrunner.org - you will certainly find it useful.


Do reach out with updates if you test it against any of the other BI platforms.
Hopefully over time we can start building out a nice generalised interface into
Oracle, Teradata, SAP HANA and SSAS.





Posted by Andrew (AP) Prendergast at 3:58 pm 2 comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest

Location: RMIT University, Melbourne, Australia


SATURDAY, 13 SEPTEMBER 2014


BIDDING: AXIOMS OF DIGITAL ADVERTISING + TRAFFIC VALUATION



In this post I share a formal framework for reasoning about advertising traffic
flows, is how black box optimisers work and needs to be covered before we get
into any models. If you are a marketer, then the advertising stuff will be
old-hat and if you are a data scientist then the axioms will seem almost
obvious.

What is useful is combining this advertising + science view and the interesting
conclusions about traffic valuation one can draw from it. The framework is
generalised and can be applied to a single placement or to an entire channel.


CREATIVE VS. DATA – WHO WILL WIN?

I should preface by saying my view on creative is that it is more important than
the quality of one's analysis and media buying prowess. All the data crunching
in the world is not worth a pinch if the proposition is wrong or the execution
is poor.

On the other hand, an amazing ad for a great product delivered to just the right
people at the perfect moment will set the world on fire.


PROBLEM DESCRIPTION

The digital advertising optimisation problem is well known: analyse the
performance data collected to date and find the advertising mix that allocates
the budget in such a way that maximises the expected revenue.

This can be divided into three sub-problems: assigning conversion probabilities
to each of the advertising opportunities; estimating the financial value of
advertising opportunities; and finding the Optimal Media Plan.

The most difficult of these is the assessment of conversion probabilities.
Considering only the performance of a single placement or search phrase tends to
discard large volumes of otherwise useful data (for example, the performance of
closely related keywords or placements). What is required is a technique that
makes full use of all the data in calculating these probabilities without
double-counting any information.


THE HOLY TRIUMVIRATE OF DIGITAL ADVERTISING

In most digital advertising marketplaces, forces are such that traffic with high
conversion probability will cost more than traffic with a lower conversion
probability (see Figure 1). This is because advertisers are willing to pay a
premium for better quality traffic flows while simultaneously avoiding traffic
with low conversion probability.

Digital advertising also possesses the property that the incremental cost of
traffic increases as an advertiser purchases more traffic from a publisher (see
Figure 2). For example, an advertiser might increase the spend on a particular
placement by 40%, but it is unlikely that any new deal would generate an
additional 40% increase in traffic or sales.




Figure 1: Advertiser demand causes the cost of traffic to increase with
conversion probability






Figure 2: Publishers adjust the cost of traffic upward exponentially as traffic
volume increases



To counter this effect, sophisticated marketers grow their advertising
portfolios by expanding into new sites and opportunities (by adding more
placements), rather than by paying more for the advertising they already have.
This horizontal expansion creates an optimisation problem: given a monthly
budget of $x, what allocation of advertising will generate the most sales? This
configuration then is the Optimal Media Plan.




Figure 3: The Holy Triumvirate of Digital Advertising: Cost, Volume and
Propensity




NB: There are plenty of counterexamples when this response surface is observed
in the wild. For example with Figure 2, some placements are more logarithmic
than exponential, while others are a combination of the two. A good agency
spends their days navigating and/or negotiating this so that one doesn't end up
over paying.

To solve the Optimal Media Plan problem, one needs to know three things for
every advertising opportunity: the cost of each prospective placement; the
expected volume of clicks; and the propensity of the placement to convert clicks
into sales (see Figure 3). This Holy Triumvirate of Digital Advertising (cost,
volume and propensity) is constrained along a response surface that ensures that
low cost, high propensity and high volume placements occur infrequently and
without longevity.

For the remainder of this post (and well into the future), propensity will be
considered exclusively in terms of ConversionProbability. This post will provide
a general framework for this media plan optimisation problem and explore how
ConversionProbability relates to search and display advertising.


Read more »
Posted by Andrew (AP) Prendergast at 3:13 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




SATURDAY, 22 MARCH 2014


A GRAND THESIS



Oh dear, the game is up. Our big secret is out. We should have a parade.


THE FUTURE OF MODERNITY

This year is looking like when computer scientists come out and confess that the
world is undergoing a huge technology driven revolution based on simple
probabilities. Or perhaps it's just that people have started to notice the
rather obvious impact it is making on their lives (the hype around the recent
DARPA Robotics Challenge and Christine Lagarde's entertaining lecture last month
are both marvelous example of that).

This change is to computer science what quantum mechanics was to physics: a
grand shift in thinking from an absolute and observable world to an uncertain
and far less observable one. We are leaving the digital age and entering the
probabilistic one. The main architects of this change are some very smart people
and my favorite super heroes - Daphne Koller, Sebastian Thrun, Richard
Neapolitan, Andrew Ng and Ron Howard (no not the Happy Days Ron – this one).

Behind this shift are a clique of innovators and ‘thought leaders’ with an
amazing vision of the future. Their vision is grand and they are slowly creating
the global cultural change they need to execute it. In their vision, freeways
are close to 100% occupied, all cars travel at maximum speed and the population
growth declines to a sustainable level.

This upcoming convergence of population to sustainable levels will not come from
job-stealing or killer robots, but from increased efficiency and the better
lives we will all live, id est, the kind of productivity increase that is
inversely proportional to population growth.

And then world is saved... by computer scientists.


WHAT IS IT SORT OF EXACTLY-ISH?

Classical computer science is based on very precise, finite and discrete things,
like counting pebbles, rocks and shells in an exact manner. This classical
science consists of many useful pieces such as the von-neumann architecture,
relational databases, sets, graph theory, combinatorics, determinism, greek
logic, sort + merge, and so many other well defined and expressible-in-binary
things.

What is now taking hold is a whole different class of computer-ey science,
grounded in probabilistic reasoning and with some other thing called information
theory thrown in on the sidelines. This kind of science allows us to deal in the
greyness of the world. Thus we can, say, assign happiness values to whether we
think those previously mentioned objects are in fact more pebbly, rocky or
shelly given what we know about the time of day and its effect on the lighting
of pebble-ish, rock-ish and shell-ish looking things. Those happiness values are
expressed as probabilities.

The convenience of this probability-based framework is its compact
representation of what we know, as well as its ability to quantify what we do
not(ish).

Its subjective approach is very unlike the objectivism of classical stats. In
classical stats, we are trying to uncover a pre-existing independent, unbiased
assessment. In the Bayesian or probabilistic world bias is welcomed as it
represents our existing knowledge, which we then update with real data. Whoa.







This paradigm shift is far more general than just the building of robots - it's
changing the world.


I SHALL NOW SHOW YOU THE EVIDENCE SO YOU MAY UPDATE YOUR PROBABILITIES

A testament to the power of this approach is that the market leaders in many
tech verticals already have this math at their heart. Google Search is a perfect
example - only half of their rankings are PageRank based. The rest is a big
probability model that converts your search query into a machine-readable
version of your innermost thoughts and desires (to the untrained eye it looks a
lot like magic).

If you don’t believe me, consider for a moment, how does Facebook choose what to
display in your own feed? How do laptops and phones interpret gestures? How do
handwriting, speech and facial recognition systems work? Error Correction?
Chatbots? Emotion recognition? Game AI? PhotoSynth? Data Compression?

It’s mostly all the same math. There are other ways, which are useful for some
sub-problems, but they can all ultimately be decomposed or factored into some
sort of Bayesian or Markovian graphical probability model.

Try it yourself: Pickup your iPhone right now and ask the delightful Siri if she
is probabilistic, then assign a happiness value in your mind as to whether she
is. There, you are now a Bayesian.


APAC IS MISSING OUT

Notwithstanding small pockets of knowledge, we don’t properly teach this
material in Australia, partly because it is so difficult to learn.

We are not alone here. Japan was recently struck down by this same affliction
when their robots could not help to resolve their Fukushima disaster. Their
classically trained robots cannot cope with changes to their environment that
probabilities so neatly quantify.

To give you an idea of how profound this thesis is, or how far and wide it will
eventually travel, it is currently taught by the top American universities
across many faculties. The only other mathematical discipline that has found its
way into every aspect of science, business and humanities is the Greek logic,
and that is thousands of years old.


A NEAT MATHEMATICAL MAGIC TRICK

The Probabilistic Calculus subsumes Greek Logic, Predicate Logic, Markov Chains,
Kalman Filters, Linear Models, possibly even Neural Networks; that is, because
they can all be expressed as graphical probability models. Thus logic is no
longer king. Probabilities, expected utility and value of information are the
new general purpose ‘Bayesian’ way to reason about anything, and can be applied
in a boardroom setting as effectively as in the lab.

One could build a probability model to reason about things like love, however
it's ill advised. For example, a well-trained model would be quite adept at
answering questions like “what is the probability of my enduring happiness given
a prospective partner with particular traits and habits.”

The ethical dilemma here is that a robot built on the Bayesian Thesis is not
thinking as we know it – it's just a systematic application of an ingenious
mathematical trick to create the appearance of thought. Thus for some things, it
simply is not appropriate to pretend to think deeply about a topic; one must
actually do it.


WE NEED BANDWIDTH OR WE WILL DEVOUR YOUR 4G NETWORK WHOLE

These probabilistic apps of the future (some of which already exist) will drive
bandwidth-hogging monsters (quite possibly literally) that could make full use
of low latency fibre connections.

These apps construct real-time models of their world based on vast repositories
of constantly updated knowledge stored ‘in the cloud’. The mechanics of this
requires the ability to transmit and consume live video feeds, whilst
simultaneously firing off thousands of queries against grand mid- and big-data
repositories.

For example, an app might want to assign probabilities to what that shiny thing
is over there, or if its just sensor noise, or if you should buy it, or if you
should avoid crashing into it, or if popular sentiment towards it is negative;
and, oh dear, we might want to do that thousands of times per second by querying
Flickr, Facebook and Google and and and. All at once. Whilst dancing. And
wearing a Gucci augmented reality headset, connected to my Hermes product aware
wallet.

This repetitive probability calculation is exactly what robots do, but in a
disconnected way. Imagine what is possible once they are all connected to the
cloud. And then to each other. Then consider how much bandwidth it will require!

But, more seriously, the downside of this is that our currently sufficient 4G
LTE network will very quickly be overwhelmed by these magical new apps in a
similar way to how the iPhone crushed our 3G data networks.

Given that i-Devices and robots like to move around, I don't know whether FTTH
would be worth the expense, but near-FTTH with a very high performance wireless
local loop certainly would help here. At some point we will be buying Hugo Boss
branded Occulus Rift VR headsets, and they need to plug into something a little
more substantive than what we have today.


AHH OK, WHAT DOES THIS HAVE TO DO WITH ADVERTISING?

In my previous post I said I would be covering advertising things. So here it is
if you haven't already worked it out: this same probability guff also works with
digital advertising, and astonishingly well.

There I said it, the secret is out. Time for a parade.

...some useful bits coming in the next post.


Posted by Andrew (AP) Prendergast at 12:32 am No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




FRIDAY, 21 MARCH 2014


OH HAI


Fab, I’m blogging.




A CHUMP’S GAME

A good friend of mine, whilst working at a New York hedge fund once said to me,
“online advertising is a chump’s game”.

At the time he was exploring the idea of constructing financial instruments
around the trade of user attention. His comment was coming from just how
unpredictable, heterogeneous and generally intractable the quantitative side of
advertising can be. Soon after, he quickly recoiled from the world of digital
advertising and re-ascended back into the transparent market efficiency of haute
finance; a world of looking for the next big “arb”.


WHAT I DO

I am a data scientist and I work on this problem every day.

Over the last 15 or so years I have come to find that digital advertising is, in
fact, completely the opposite of a chump's game – yes, media marketplaces are
extraordinarily opaque and highly disconnected – but with that comes
fantastically gross pricing inefficiencies exploitable in a form of advertising
arbitrage.

The Wall Street guys saw this, but never quite cracked how to exploit it.


WHAT YOU WILL FIND HERE

If you have spent more than a little time with me, then in between mountain
biking and heli-boarding at my two favorite places in the world, you will have
probably heard about or seen a probability model or two.

In the coming months I will be banging on about some of this, and in particular
sharing a few easy tricks on how advertisers can use data to gain a bit of an
advantage. With the right approach, it’s rather simple.
The concepts I will present here are already built into the black-box ad
platforms we use daily, the foundations of which are two closely related
assumptions:

 * Any flow of advertising traffic has people behind it whom possess a fixed
   amount of buying power and a more elastic willingness to exercise it.
 * As individuals we are independent thinkers, but as a swarm, we behave in
   remarkably predictable ways.

My aim is that one will find the material useful with little more than a bit of
Excel and one or two free-ish downloads. The approach is carefully principled,
elegantly simple and astonishingly effective.

Achtung! This site makes use of in-browser 3D. If your computer is struggling, then you probably need a little upgrade, a GPU or a browser change. Modern data science needs compute power, and alot of it.

The format is a mix of theory, worked examples and how-to, combined with a touch
of spreadsheet engineering. A dear friend of mine – whom has written more than a
few articles for the Economist - will be helping me edit things to keep the
technical guff to a minimum.

I am hoping along the way that a few interesting people might also compare their
own experiences and provide further feedback and refinement. If its well
received then we might scale up the complexity.

So, if digital advertising is your game then stay tuned, this will be a bit of
fun!


Posted by Andrew (AP) Prendergast at 12:02 am No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




MONDAY, 16 JULY 2007


SORTING DATA FRAMES IN R



This is a grandfathered post copied across from my old blog when I was using
MovableType (who remembers MovableType?!)

I frequently find myself having to re-order rows of a data.frame based on the
levels of an ordered factor in R.

For example, I want to take this data.frame:

       product store sales
        1       a    s1    12
        2       b    s1    24
        3       a    s2    32
        4       c    s2    12
        5       a    s3     9
        6       b    s3     2
        7       c    s3    29


And sort it so that the sales data from the stores with the most sales occur
first:

   product store sales
   3       a    s2    32
   4       c    s2    12
   5       a    s3     9
   6       b    s3     2
   7       c    s3    29
   1       a    s1    12
   2       b    s1    24


I keep forgetting the exact semantics of how its done and Google never offers
any assistance on the topic, so here is a quick post to get it down once and for
all, both for my own benefit and the greater good. First we need some data:

   productSalesByStore = data.frame(
         product = c('a', 'b', 'a', 'c', 'a', 'b', 'c'),
         store = c('s1', 's1', 's2', 's2', 's3', 's3', 's3'),
         sales = c(12, 24, 32, 12, 9, 2, 29)
      )


Now construct a sorted summary of sales by store:

   storeSalesSummary =
         aggregate(
                  productSalesByStore$sales,
                  list(store = productSalesByStore$store),
         sum)
   storeSalesSummary =
      storeSalesSummary[ 
         order(storeSalesSummary$x, decreasing=TRUE), 
         ]


storeSalesSummary should look like this:

   store  x
    2    s2 44
    3    s3 40
    1    s1 36


Use that summary data to construct an ordered factor of store names:

   storesBySales =
      ordered(
         storeSalesSummary$store,
         levels=storeSalesSummary$store
         )


storesBySales is now an ordered factor that looks like this:

      [1] s2 s3 s1
  Levels: s2 < s3 < s1


Re-construct productSalesByStore$store so that it is an ordered factor with the
same levels as storesBySales

   productSalesByStore$store =
      ordered(productSalesByStore$store, levels=storesBySales)


Note that neither the contents nor the order of productSalesByStore has changed
(yet). Just the datatype of the store column. Finally, we use the implicit
ordering of store to generate an explicit permutation of productSalesByStore so
that we can sort the rows in a stable manner:

   productSalesByStore = 
      productSalesByStore[ order(productSalesByStore$store), ]


And we are done!

Posted by Andrew (AP) Prendergast at 2:30 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




TUESDAY, 17 AUGUST 1999


PARALLEL READ/WRITE LOCKING AND MY ORACLE ADVENTURE



Back when Oracle 8i was a thing, Fibre Channel was all the rage and on the
Oracle roadmap was Oracle Parallel Database, I was called into the Oracle HQ in
Redwood City, Silicon Valley.

They'd pushed back the release of "Parallel" quarter after quarter and a couple
senior engineers caught wind that I was the guy for doing custom built memory
memory managers and I was doing big highly parallelised data structures on large
SGI platforms. I had one data structure running on 16 racks of Silicon Graphics
kit at a large data centre off highway 101 for an investment bank (aka hedge
fund), and I'd earned a reputation for being able to do parallel distributted
read/write locking of vast data structures with all CPU threads running at full
speed and without any mutex locking or blocking. So, I was summoned to Silicon
Valley "for a chat".

Oracle had this grand idea for Oracle 8i to share fibre channel LUNs between
hosts, and your federated database would sit on one LUN with multiple Oracle 8i
instances on separate machines all accessing the same database in parallel
(hence the name 'Parallel'). Oracle at the time was actively influencing the
specs of fibe channel (FCAL), but they just couldn't get it to work -- so I was
called in so they could pick my brains. The visit was fun, but I was no dummy,
and I certainly wasn't going to give up the secrets to how to build the worlds
fastest computing systems.

I found the meeting quite entertaining and it descended into an argument over
Oracle's outrageous pricing. On a multi-cpu system craylinked together with
other multi-cpu systems, why should I pay Oracle a licensing fee for every damn
CPU when we had called in Mark Gurry (the guy that wrote the book on Oracle
Performance Tuning), tuned the crap out of Oracle so that it barely used a
single CPU, maybe two under heavy load. I won the argument and secured special
pricing for Oracle moving forward (possibly not what they had intended for our
meeting - oh well, that's AP for you!)


A much more youthful looking me standing next to the Oracle lake after our
meeting


Posted by Andrew (AP) Prendergast at 11:20 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest

Location: Redwood City, Silicon Valley, CA, USA


TUESDAY, 27 JANUARY 1998


GEEKZ ON DEMAND



Geekz on Demand (G.O.D) was a HR consultancy I started back in 1997 with Richard
Taylor. At the time it was tech boom 1.0, and there was a dearth of talent that
properly knew what the Internet was and how to get things onto it.

Entre The Geekbase, and it took off like a rocket, landing us in the news quite
consistently:


Rowan and I on the cover of The Age, 27 Jan 1998.


Read more »
Posted by Andrew (AP) Prendergast at 8:02 pm No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest




THURSDAY, 18 AUGUST 1994


THE START OF THE TECH BOOM



I spent tech boom 1.0 putting as much as I could online.


PRE-TECH BOOM

Not unlike Steve Jobs, I started my tech-career with phone phreaking.

Fresh out of the AFP banging on the front door of my Brighton home in 1993 for
phone phreaking and hacking (of course, being underage, no conviction was
recorded). We were quite prolific and formed a loose nameless collective of the
absolute best of the day. We were awash with so many zero day c0dez and exploits
that we had to invent "minus days". Feared by the rest of the hacking community,
we had the ability to access any computer system or telephone network we
desired. Even Julian Assange (aka 'prof') ph3ared us. Our threat-hunting was
extrordinary, we learned how to come up with 5 new minus-days exploits in 24
hours, we'd scan 1000 telephone numbers on a bad day, and 10,000 on a good one
(basically an entire suburb). We even had a team of computer illiterate guys
that had a van and spent their evenings going through corporate rubbish bins
looking for manuals and other goodies.

Our innovations were countless, ranging from fax bombing telephone numbers (A
DOS attack directed towards a voice line/mobile), digital phreaking using
diverters and pads, hacking network switches to create conference bridges (or
'party lines' as we called them), drag-net hacking, and we even developed a code
of ethics which kept us firmly in the realm of 'explorers' and away from the
less desirable labels of 'fraudsters' or 'terrorists'.

The Black Hat Code of Ethics
 * Don't take
 * Don't break
 * Don't change
 * Don't steal (eg, credit card fraud)

The general rule was that if you broke one of those rules, then you had to put
it right before you were done with the system you had hacked into.

We weren't without oversight either. For example, a senior cryptographer from
the DSD would dial into our party line and give me and my mates a fortnightly
lecture on number theory and cryptography (which at 13 years old is something
special that lives with you the rest of your life). This went on for at least 9
months. We also had techs from Telstra watching over our activites as well,
because we were basically pen-testing (penetration testing) digital telephony.
Occasionally the techs would get in touch and give us a dressing down for some
of our activites, so we had boundaries. The DSD guy also found out what was the
latest and greatest thing in the black-hat world, so he could keep his finger
on-the-pulse. A really chilled, very Australian and very hillarious symbiotic
'free flow of information' type of relationship was shared by all us insiders.
Basically, we were a harmless bunch of Aussie bogans doing lots of hysterical
phone pranks on a global scale for the most part. For the outsiders though, we
were the pinacle of the 'Trust no-one' ethos and were scarry. Very scarry. In
the black-hat world, hax0rs would have wars and we won every single one.

We became so internationally renowned, that the second ever DEFCON was held
right here in Melbourne, and Captain Crunch (aka John Draper) flew out to meet
us.


THE GOLDEN ERA

After that little event, I decided I was done with hax0ring and phreakx0ring and
moved to the next big thing: emersing myself in what would become known as 'The
Tech Boom', being famous and doing haute-tech. It was so much more fun, and
considerably less anti-social.


Me on the cover of the Computer Age, circa early 1995.



THE NETCAFE

We were everywhere, putting anything and everything online, helping anyone and
everyone understand what this new Internet thing was. I quickly became the
poster boy for the Internet here in Melbourne, and by 1995 we had stood up
Australia's first Netcafe on Acland Street. It was a hive of activity, and
attracted everyone. I quickly caught the attention of the media, including Wired
Magazine, but they didn't have any reporters in Australia. After a couple calls,
they did the next best thing: pro sponsorship. The Wired folk didn't usually do
sponsorships, but someone at the office called Absolut Vodka and did the next
best thing, sending us a crate of 6 Absolut Vodka bottles (including whichever
one was on the back cover for that month), along with a fresh, air-freighted
current month edition of Wired Magazine, direct to The Netcafe. Back then, Wired
was the bible, but it also arrived in Australia 3 months late thanks to it being
sea-freighted.


Me sitting at a PC in the upstairs room at The Netcafe, featuring Win95 and
surrounded by Marcsta artworks
Business Review Weekly (BRW), June 1995


Chris Beaumont briefly discussing the Netcafe at an exclusive Melbourne
tech-futurist group
discussing The Netcafe and mentions moi!



An old pic circa 1996 of my first home lab. Note the Beaumont oil painting on
the wall and
the Absolut Vodka tshirt from being sponsored by Wired Magazine


The Netcafe was a special place. With support from Michael Bethune from
OzOnline, Adam from Standard Computers and of course Micrcosoft, we created a
bunch of rooms above the Deluxe cafe on Acland street that people could
experience both The Internet and Windows 95. 95 was a good operating system, it
felt like a Silicon Graphics or Sun workstation and it was fast. Everyone that
came in we showed it to, taking Melbourne from zero-knowledge about The 'Net to
being as educated as anyone in Silicon Valley. It was an amazing time.

Even Jeff Kennet humself gave me a little tiny gold badge of Victoria as an
acknowledgement of my contribution to the state.


BEAT MAGAZINE

During this period I crossed paths with Rob Furst, founder of the inky
street-press music scene publication Beat Magazine. He quickly employed me as
the e-editor, responsible for getting street press mag onto the Internet. I was
still a kid at the time, and still studying at Brighton Grammar. How I fitted
everything in I don't know, but I did. It was a great time and fun was had by
all:


List of contributors to Beat Magazine, circa 1995. Note the e-editor :)



TED NELSON

In 1996 a second luminary from Silicon Valley flew out to meet me -- Theodore
('Ted') Holm Nelson, inventor of hypertext. He heard that something amazing was
happening in Australia and he came out here to take a look for himself. We
chatted, solved a few problems then he went on his way. I still have his
business card today.


Posted by Andrew (AP) Prendergast at 1:02 am No comments:
Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest


Home








INTERESTING COMPSCIFUTURES FACTOIDS

 * PGP-Key: Here's mine, how and why you should too
 * Unix homedir snippets, Windows gems + priceless Internets artefacts (for me
   only)
 * View background wave simulation (click and drag to rotate scene)
 * delog: JSON/XML logfile deserializer - Converts unstructured CSV data to
   tabular
 * My Amazon Wish List - Feel free to donate to my cause and send me a gift!
 * ProbabilisticLogic.AI




ABOUT ME (@COMPSCIFUTURES)

Andrew (AP) Prendergast Australian (Neat Theoretical) Computer Scientist, AI
expert, cryptgrphr + Information Security Specialist.


MSc(CS), RMIT University | Cert. Advanced Cyber Security, Stanford University.

Italian, Irish, Anglican Aussie. Possibly Ashken. 🌈

To get in touch:
email me at ap@andrewprendergast.com,
contact me on LinkedIn, or try @CompSciFutures on Twitter.

If you need to open a secure channel, eg, for following up Responsible
Disclosure of Vulnerabilities, use my PGP Key (no black-hat stuff, please). View
my complete profile



COMPSCIFUTURES COPYRIGHT

(C) COPYRIGHT 1994 - 2023 Andrew Prendergast.
All Rights Reserved.

View FOSS licenses




AP ON COMPSCIFUTURES BLOG ARCHIVE

 * ▼  2023 (4)
   * ▼  March (2)
     * CURRENT STATE OF WEBGL / GLSL
     * YOU ARE ALL IN A VIRTUAL
   * ►  February (1)
   * ►  January (1)

 * ►  2022 (4)
   * ►  December (1)
   * ►  November (1)
   * ►  October (1)
   * ►  July (1)

 * ►  2019 (1)
   * ►  March (1)

 * ►  2017 (1)
   * ►  June (1)

 * ►  2015 (1)
   * ►  September (1)

 * ►  2014 (5)
   * ►  October (2)
   * ►  September (1)
   * ►  March (2)

 * ►  2007 (1)
   * ►  July (1)

 * ►  1999 (1)
   * ►  August (1)

 * ►  1998 (1)
   * ►  January (1)

 * ►  1994 (1)
   * ►  August (1)




INFOSEC RESEARCH STATEMENT OF PURPOSE

My information security research mostly fits into the strategic areas of
awareness & education, cyber defence, early warning systems, threat prevention,
risk management and GRC assessment.

I do not deal in exploits (as they are munitions), however I do occasionally
provide OSINT cyber intelligence on (highly) suspected minus-days critical
infrastructure vulnerabilities.



SOCIALS

  




Diese Website verwendet Cookies von Google, um Dienste anzubieten und Zugriffe
zu analysieren. Deine IP-Adresse und dein User-Agent werden zusammen mit
Messwerten zur Leistung und Sicherheit für Google freigegeben. So können
Nutzungsstatistiken generiert, Missbrauchsfälle erkannt und behoben und die
Qualität des Dienstes gewährleistet werden.Weitere InformationenOk