Category Archives: Academically speaking

Neural networks – explained

As mentioned here a few times, I teach an executive course called Analytics for strategic management, as well as a short program (three days) called Decisions from Data: Driving an Organization on Analytics. We have just finished the first version of both of these courses, and it has been a very enjoyable experience. The students (in both courses) have been interested and keen to learn, bringing relevant and interesting problems to the table, and we have managed do what it said on the tin (I think) – make them better consumers of analytics, capable of having a conversation with the analytics team, employing the right vocabulary and being able to ask more intelligent questions.

Of course, programs of this type does not allow you do dive deep into how things work, though we have been able to demonstrate MySQL, Python and DataRobot, and also give the students an understanding of how rapidly these things are evolving. We have talked about deep learning, for instance, but not how it works.

But that is easy to fix – almost everything about machine learning is available on Youtube and in other web channels, once you are into a little bit of the language. For instance, to understand how deep learning works, you can check out a series of videos from Grant Sanderson, who produces very good educational videos on the web site 3 blue one brown.

(There are follow-up videos: Chapter 2, Chapter 3, and Chapter 3 (formal calculus appendix). This Youtube channel has a lot of other math-related videos, too, including a great explanation of how Bitcoin works, which I’ll have to get into at some points, since I keep being asked why I don’t invest in Bitcoin all the time.)

Of course, you have to be rather interested to dive into this, and it certainly is not required read for an executive who only wants to be able to talk intelligently to the analytics team. But it is important (and a bit reassuring) to note the mechanisms employed: Breaking a very complex problem up into smaller problems, breaking those up into even smaller problems. solving the small problems by programming, then stepping back up. For those of you with high school math: It really isn’t that complicated. Just complicated in layers.

And it is good to know that all this advanced AI stuff really is rather basic math. Just applied in an increasingly complex way, really fast.


A tour de Fry of technology evolution

There are many things to say about Stephen Fry, but enough is to show this video, filmed at Nokia Bell Labs, explaining, amongst other things, the origin of microchips, the power of exponential growth, the adventure and consequences of performance and functionality evolution. I am beginning to think that “the apogee, the acme, the summit of human intelligence” might actually be Stephen himself:

(Of course, the most impressive feat is his easy banter on hard questions after the talk itself. Quotes like: “[and] who is to program any kind of moral [into computers ]… If [the computer] dives into the data lake and learns to swim, which is essentially what machine learning is, it’s just diving in and learning to swim, it may pick up some very unpleasant sewage.”)

Big Data and analytics – briefly

DFDDODData and data analytics is becoming more and more important for companies and organizations. Are you wondering what data and data science might do for your company? Welcome to a three-day ESP (Executive Short Program) called Decisions from Data: Driving an Organization with Analytics. It will take place at BI Norwegian Business School from December 5-7 this year. The short course is an offshoot from our very popular executive programs Analytics for Strategic Management, which are fully booked. (Check this list (Norwegian) for a sense of what those students are doing.)

Decisions from Data is aimed at managers who are curious about Big Data and data science and wants an introduction and an overview, without having to take a full course. We will talk about and show various forms of data analysis, discuss the most important obstacles to becoming a data driven organization and how to deal with data scientists, and, of course, give lots of examples of how to compete with analytics. The course will not be tech heavy, but we will look at and touch a few tools, just to get an idea of what we are asking those data scientists to do.

The whole thing will be in English, because, well, the (in my humble opinion) best people we have on this (Chandler Johnson og Alessandra Luzzi) are from the USA and Italy, respectively. As for myself, I tag along as best I can…

Welcome to the data revolution – it start’s here!

After Moore: Landauer

Very interesting blog by the very readable Ted: Is computing in reverse the next big thing?

As Moore’s law continues, it will reach certain physical limitations, such as electrons behaving less dependently the thinner the conduits become (think individual electrons instead of a more predictable stream. Another (they are linked, I suspect) is Landauer’s principle, which dictates that there is a certain lower limit on how much power that is necessary to flip a bit, and that forms a hard stop in terms of how much you can lower power consumption (and with it, heat dissipation.) (See Denning, P. J. and T. G. Lewis (2016). “Exponential laws of computing growth.” Communications of the ACM 60(1): 54-65, for an excellent discussion of Moore’s law and its remaining life.)

Turns out computing capability as a function of electric power consumption might be the next big obstacle (or at least measurement.) The BitCoin miners certainly know that.

Reverse, computing, which Ted writes about, is essentially computing where the power can be reversed, recreating the initial state. While difficult technically, it certainly would reduce power consumption to almost nothing.

To learn how, read the article. Recommended!

Made my day!

digøkskjermI just got the message that the new bachelor program Informatikk: Digital Økonomi og Ledelse (Informatics: Digital Economics and Management) is now the most sought-after study program in Norway, with 19 applicants per available place (514 first-priority applicants for 27 available places).

Since I have taken the initiative to this program and developed it with colleagues at the University of Oslo (where I have an adjunct position, this definitely made my day. Week, actually.

Just sayin’…

Notes from ACM Webinar on blockchain (etc.)

The Next Radical Internet Transformation: How Blockchain Technology is Transforming Business, Governments, Computing, and Security Models

Speaker: Mark Mueller-Eberstein, CEO & Founder at Adgetec Corporation, Professor at Rutgers University, Senior Research Fellow at QIIR

Moderator: Toufi Saliba, CEO, PrivacyShell and Chair of the ACM PB Conference Committee

Warning: These are notes taken live. Errors and omissions will occur. No responsibility whatsoever.

  • intro: old enough to remember the discussions in the early 90s about how the internet would change mail services – completely forgetting shopping, entertainment and others
  • Blockchain solves the problem of transferring value between Internet users without a third party
  • goes beyond the financial industry, can handle any kind of transaction
  • most of the world has access to a mobile phone, only about 20% has access to the banking system
  • Blockchain is the banking industry’s Uber movement
  • Blockchain much wider than Bitcoin, will facilitate new business models.
  • Blockchain transfers rather than copies digital assets, making sure there is only one instance of it.
    • settlement process: no clearing houses or central exchanges
    • peer-to-peer transfers, validation by network
  • Example: WeChat taking over payments in China, no link to banks
  • many commercial or government services are basically “databases” that are centrally managed, with one central point of failure
  • Blockchain allows a distributed ledger, information put in cannot be changed
    • Estonia thinking about a Blockchain in case of hacking or occupation
  • public (open), private and government blockchainsxx1
  • allows new services to existing customers, lots of inefficiencies up for grabs
    • estate records, voting, domain control, escrow, etc…
    • iPayYou allows use of Bitcoin
    • Walt Disney looking at Blockchain (DragonChain) for internal transfers, also use it for tracking supply chain to their cruise ships. Opensourced it.
  • 80% of Bitcoin mining done in China
  • regulation comes with a cost
  • Shenzhen want to be Blockchain Tech capital
  • 6-level security model, developed by William Mougayar (goes through it in detail: transaction, account, programming, distributed organizations, network (51% attacks, perhaps as low as 30%, smaller blockchains more vulnerable), governance)
  • Ethereum blockchain focusing on smart contracts: Hard forked in 2016, DAO issue where somebody hacked DAO code to siphon off money, hacking the program using the blockchain (not the blockchain),
  • credit card transaction can take up to 30 days, with disputes and everthing, Blockchain is almost instant
  • How “real” is blockchain technology
    • Goldman-Sachs invested $500m+
    • 15% of top global banks intend to roll out full-scale, commercial blockchain
    • etc.
  • what is holding it back?
    • difficult to use, understand, buy in; perception of risk and legality
    • difficult to see value for the individual
  • questions:
    • what are the incentives and adoption models?
      • different philosophies: computing power must be made available in the network: industrial mining vs. BitTorrent model, the amount of computing provided will be important, if we can find a model where just a little bit from every mobile phone is required
    • what are the hard costs of Blockchain?
      • you can google the costs. There are other approaches being developed, will post some links
    • can Blockchain be compromized by a virus?
      • theoretically, yes. Bitcoin is 10 years without, open source means verification (change is happening slowly because of code inspection)
      • comes back to incentive and governance model
  • and that was that…recording will be at in a few days.

Case teaching in Vienna

quantI have been asked to give a keynote speech at a conference on case teaching in Vienna, at the The University of Applied Sciences BFI. This is quite an honor, and I am very much looking forward to it.

Should you happen to want to be in Vienna and focus on case teaching on May 19 – well, I hope to see you there!