O'Really?

October 23, 2014

Two big challenges facing the technology & digital industries (IMHO)

Digital Turing

Alan Turing Binary code, Shoreditch High Street, London by Chris Beckett on Flickr (CC-BY-NC-ND license)

Over at democracy corner, Manchester Digital is interviewing all of its elected council members. Somehow, I got volunteered to be first interviewee. Here’s my two pence on one of the questions asked: “What do you think is biggest challenge we face as an industry?” (with some extra links)

  • Firstly, coding and “computational thinking” [1], needs to be understood as something that isn’t just for developers, geeks, coders, techies, boffins or “whizz kids” – as the Manchester Evening News likes to call them. Computational thinking, the ability to understand problems and provide innovative solutions in software and hardware, is a fundamental skill that everyone can learn, starting in primary school. As well as being fun to learn and practice, it is a crucial skill in a wide range of organisations in digital and beyond. Thankfully, the new computing curriculum in UK schools has recognised and addressed this, but it remains to be seen what the long-term impact of the changes in primary & secondary education will be on employers.
  • Secondly, as an industry, both the digital and technology sectors are seriously hindered by gender imbalance. If only 10-20% of employees are female, then large numbers of talented people are being excluded from the sector – bad news for everyone.

Is that reasonable –  or have I missed the point? Are there more pressing issues facing the technology sector? Either way, you can read the rest of the interview at manchesterdigital.com/democracy-corner which will be supplemented with more interviews of council members every week over the next few months.

References

  1. Wing, J. (2008). Computational thinking and thinking about computing Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 366 (1881), 3717-3725 DOI: 10.1098/rsta.2008.0118

August 3, 2012

June 15, 2012

Alan Turing Centenary Conference, 22nd-25th June 2012

Alan Turing by Michael Dales

The Alan Turing statue at Bletchley Park. Creative commons licensed picture via Michael Dales on Flickr

Next weekend, a bunch of very distinguished computer scientists will rock up at the magnificent Manchester Town Hall for the Turing Centenary Conference in order to analyse the development of Computer ScienceArtificial Intelligence and Alan Turing’s legacy [1].

There’s an impressive and stellar speaker line-up including:

Tickets are not cheap at £450 for four days, but you can sign up for free public lectures by Jack Copeland on Turing: Pioneer of the Information Age and Roger Penrose on the problem of modelling a mathematical mind. Alternatively, if you can lend some time, the conference organisers are looking for volunteers to help out in return for a free conference pass. Contact Vicki Chamberlin for details if you’re interested.

References

  1. Chouard, T. (2012). Turing at 100: Legacy of a universal mind Nature, 482 (7386), 455-455 DOI: 10.1038/482455a see also nature.com/turing

July 25, 2006

AAAI’06: Highlights and conclusions

The AAAI conference finished last Thursday, here are some highlights and papers that might be worth reading if you are interested in building and / or using a more “intelligent” (and possibly semantic) web in bioinformatics.

Here are the papers or talks I enjoyed the most and hope you might also find them useful or inspiring.

  1. Unifying Logical and Statistical AI talk given by Pedro Domingos.

    Intelligent agents must be able to handle the complexity and uncertainty of the real world. Logical AI (of which the semantic web is an example) has focused mainly on the former, and statistical AI (e.g. machine learning) on the latter. The two approaches can be united, with significant benefits, some of which are demonstrated by the Alchemy system

  2. Developing an intelligent personal assistant: The CALO (Cognitive Agent at that Learns and Organises) project talk given by Karen Myers.

    CALO is a desktop assistant that learns what you do in the lab / office. Sounds spooky, but involves some interesting technology and fascinating research questions.

  3. Bookmark hierarchies and collaborative recommendation by Ben Markines, Lubomira Stoilova and Filippo Menczer.

    Describes an open-source, academically-oriented social bookmarking site where you can donate your bookmarks to science at givealink

  4. Social network-based Trust in Prioritised Default Logic by Yarden Katz and Jennifer Golbeck.

    Who and how can you trust on the Web?

  5. Google vs Berners-Lee was a memorable debate. According to Jim Hendler, Tim and Peter are reconciling their differences now

Not particularly webby, but…

…entertaining nonetheless.

  1. Stephen Muggletons talk on Computational Biology and Chemical Turing Machines, went down well but unfortunately I was stuck in a parallel track, experiencing “death by ontology”.
  2. Bruce Buchanan gave a talk What Do We Know About Knowledge. A roller-coaster ride through the last 2000+ years of human attempts to understand what knowledge is, how to represent it and why it is powerful
  3. Winning the DARPA Grand Challenge with an AI Robot called Stanley talk given by Sebastian Thrun, amazing presentation on a driving a robotic car through the desert over rough terrain. However, it doesn’t take too much imagination to think of horrific applications of this. Next year they will try to drive it from San Francisco to Los Angeles on a public freeway, and Stanley hasn’t even passed its driving test yet!

Turing’s dream

Appropriately, the conference which was subtitled Celebrating 50 years of AI finished with two talks by Lenhart K. Schubert and Stuart M. Shieber about the Turing test. The first discussed Turing’s dream and the Knowledge Challenge, the second talk asked Does the Turing Test Demonstrate Intelligence or Not? Now I’m back in Manchester, where Turing once worked, I can’t help wondering, what would Alan make of the current state of AI and the semantic web? I think there are several possibilities, he could be thinking:

  • EITHER: Fifty odd years later, they’re not still wasting time working on that Turing test are they?!
  • OR: He is smugly satisifed that he devised a test, that no machine has passed, and perhaps never will, but has provided us with a satisfactory operational definition of “intelligence” ;
  • …AND What the hell is the “Semantic Web”?

We will never know what Alan Turing would make of todays efforts to make a more intelligent web. However, that won’t stop me speculating that he would be impressed by the current uses of computers (intelligent or otherwise) to drive robots through the desert, perform all sort of computations on proteins and to search for information on this massive distributed global knowledge-base we call the “Web”. Not bad for 50 years of work, here’s to the next 50…

References

  1. Alan Turing (1950) Computing Machinery and Intelligence: The Turing TestMind 59(236):433-460
  2. Stephen H. Muggleton (2006) Exceeding human limits: The Chemical Turing MachineNature 440:409-410
  3. Stephen H. Muggleton (2006) Towards Chemical Universal Turing Machines in Proceedings on the 21st National Conference on Artificial Intelligence
  4. Picture credit: Image from Steve Jurvetson
  5. This post was originally published on nodalpoint with comments

May 5, 2006

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