Archive for April, 2004

April 30, 2004


Nature, 28 April 2004: An autonomous molecular computer for logical control of gene expression
“Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.”

But don’t just read the press hype about this, go the the link above, and then click on the ‘Download PDF’ link on the left to get the full original. Very exciting stuff from Shapiro’s team; same Shapiro from the ol’ Prolog days…

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April 30, 2004


Nature, 28 April 2004: An autonomous molecular computer for logical control of gene expression
“Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.”

But don’t just read the press hype about this, go the the link above, and then click on the ‘Download PDF’ link on the left to get the full original. Very exciting stuff from Shapiro’s team; same Shapiro from the ol’ Prolog days…

April 30, 2004


Nature, 28 April 2004: An autonomous molecular computer for logical control of gene expression
“Here we describe an autonomous biomolecular computer that, at least in vitro, logically analyses the levels of messenger RNA species, and in response produces a molecule capable of affecting levels of gene expression. The computer operates at a concentration of close to a trillion computers per microlitre and consists of three programmable modules: a computation module, that is, a stochastic molecular automaton; an input module, by which specific mRNA levels or point mutations regulate software molecule concentrations, and hence automaton transition probabilities; and an output module, capable of controlled release of a short single-stranded DNA molecule. This approach might be applied in vivo to biochemical sensing, genetic engineering and even medical diagnosis and treatment. As a proof of principle we programmed the computer to identify and analyse mRNA of disease-related genes associated with models of small-cell lung cancer and prostate cancer, and to produce a single-stranded DNA molecule modelled after an anticancer drug.”

But don’t just read the press hype about this, go the the link above, and then click on the ‘Download PDF’ link on the left to get the full original. Very exciting stuff from Shapiro’s team; same Shapiro from the ol’ Prolog days…

Got my GMail account… to augment my already-infinite storage…

April 30, 2004

… on the day of Google’s IPO no less… hmmmm….

I like the idea of humongous storage, no filing i.e. using fast search instead… precisely what I do anyway in my work email account…
have actually done this since about 1993, ever since Ron Baecker and Don Gentner suggested to me that effectively-infinite storage and fast searching would do away with obsolete filing techniques. Now, if anyone out there wants to do a social networking (or any other) analysis of all my emails over a ten year period, the data is all there….

And what about the privacy concerns I’ve heard raised in response to the new GMail service (targeted ads depending on email content)? Well, according to a Wired article in 1999, Sun’s Scott McNealy said in “You have zero privacy anyway.” (or, in Wired’s interpretation, and now widely but mistakenly attributed to McNealy himself): “Get over it.” Contentious, I agree, but actually not a bad operating assumption!

Semantic Web rant – automated travel agents in 1978

April 29, 2004

BBC – Radio 4: The Material World 29/04/2004: The Semantic Web: “Quentin cooper is joined by Wendy Hall professor of Computer sciences at the University of Southampton and Jim Hendler professor of Computer sciences at the University of Maryland to find out how to add meaning to mass of content on the web.”

The above page includes background info and a link to the RealAudio replay of the original 29th April programme/chat. The good news is that it’s a pretty good overview for general consumption. The bad news is that it promises mainstream Semantic Web in 10 years, but in a cavalier fashion that (earlier in the programme) mentions software agents such as Holly in Red Dwarf, which is misleading. The ubiquitous travel agent example is cited as an example, i.e. tools that, like good human travel agents, could help me cut through the morrass of data and services.

This connection reminded me that the groundbreaking automated travel agent scenario was established some 27 years ago (!!) in a paper by six of the heaviest hitters in the field:

Daniel G. Bobrow, Ronald M. Kaplan, Martin Kay, Donald A. Norman, Henry Thompson, Terry Winograd: “GUS, A Frame-Driven Dialog System.” Artificial Intelligence. 8(2): 155-173 (1977).

Now that 27 years have gone by, the travel data is all online, and is straightforwardly searchable and retrievable. But the automated travel agent still remains elusive. The data is there, the representations are there, the inference engines are there, the connectivity is there, the computing horsepower is there (in spades), but the automated travel agent still remains elusive.

I’m not going to play cynic and argue that it’s unattainable, or that it requires some mystical human intuition to be a good travel agent. On the contrary — I’m an AI person, and a Psychologist, and I’m certain that the tools are there and that the implementation has pretty much already been achieved. But I’m not a Sociologist, nor an Anthropologist, and that’s probably what was necessary to help balance that team of heavy hitters back in 1977: the usage-in-context scenarios would have set off alarm bells to someone outside of AI and Cognitive Psychology who might have said “wait a minute, folks: no one is going to USE an automated agent in the way you have envisaged.”

To make this a little more concrete, let me tell you a true story from 1978. So enamoured was I of GUS-like automated travel agent scenarios, computational linguistics, and intelligents agents, that I thought I’d test out a little scenario on a real person: a ticket agent at Waverley train station in Edinburgh, Scotland. I was travelling from The Open University in Milton Keynes up to the AI Department at the University of Edinburgh on a fairly regular basis (we were making a series of 16 TV programmes on AI with the BBC back then, for a new Open University course), and travel by train was dramatically improved if you could avoid going through London. There were some ‘unofficial’ or ‘unrecommend’ routes, that involved, if you were lucky, a 2-minute interchange at Crewe (the recommended routes required a 20-minute connection time, to be on the safe side). If your first train was more than 2 minutes late, it cost you about 2 hours!

Anyway, enough background. I needed some specific information, and I needed it badly. I formulated my question very precisely, and even wrote it down on a piece of paper so I could ask it with no ambiguity. I strolled up to the ticket window, and proudly read out my natural language version of my GUS-like query:

“What is the latest I can leave Edinburgh tomorrow morning and still arrive in Milton Keynes by 1PM?”

“Huh?”

“What is the latest I can leave Edinburgh tomorrow morning and still arrive in Milton Keynes by 1PM?”

“Sorrry, me mate, I dinna understand ye.”

“Er… sorry… I have to be in Milton Keynes tomorrow afternoon, and was just wondering if I can get there in time.”

“Ach… why didna ye sae so?”

[addendum 29th April 2004, following some useful email interchanges with KMi colleagues]
In many ways, the key for me is not having the ‘system’ actually do much for me at all, other than lay out the space of possibilities and perhaps clarify trajectories and tradeoffs for me [no surprises here: this is precisely why Meet-O-Matic doesn’t actually arrange meetings!] — toward this end, common (and clearer) representation formalisms, better interfaces, expressive systems, etc. can all contribute; what I dispute is the premise, typified by GUS and the aforementioned radio programme, that agents will actually be negotiating or deciding on my behalf.

April 29, 2004


BBC NEWS: Boy defeats bear:
“A troubled teenager who went to confront his personal demons in the Alaskan wilderness is recovering after defeating a far heavier and hairier foe. “

April 29, 2004


BBC NEWS: Boy defeats bear:
“A troubled teenager who went to confront his personal demons in the Alaskan wilderness is recovering after defeating a far heavier and hairier foe. “

April 29, 2004


BBC NEWS: Boy defeats bear:
“A troubled teenager who went to confront his personal demons in the Alaskan wilderness is recovering after defeating a far heavier and hairier foe. “

Meetomatic: Number One On Google (well, for 3-word searches)

April 27, 2004

Simple. Easy. Free. Free web tools make life easier
“Choosing mutually acceptable meeting times across a group can be a full-time job in itself! One tool I’ve found useful to help decide when to meet is the Meet-O-Matic. Meet-O-Matic allows you to define a set of possible days (or times) for a meeting, and then allows others to say which times (of the initial options) work for them. Once everyone has reported their preferred times, the Meet-O-Matic will give you the times that are best for everyone.”

Heh – just found this by chance – haven’t Google’d around for a while on meeting schedulers but guess what: try Googling these 3 words: meeting diary scheduler (or alternatively: constraint scheduler meeting, or meeting timetable scheduler, etc.)
and our humble lil’ Meetomatic, for MANY valid three-word combinations is Numero Uno! Attaining that for just ‘meeting scheduler’ is a heck of a lot harder, but Meetomatic has just been running quietly all by itself for a good few years now, with zero publicity, so this is pretty cool….

More on SNS definitions/dimensions

April 27, 2004

Judith Meskill emailed me recently to ask for some comments and a personal view on definitions of Social Networking Services, in line with the list/categories she has posted on her YASNS Meta List

So here’s what I emailed, and added as a comment to her blog entry, and am posting verbatim to my own blog below (still can’t do these three actions with just two or three mouse-clicks!):

Here’s a very quick, and to me rather obvious, answer— which may be useful for you: Given that we’re social animals, and hence social networkers by nature, SNS’s to me are about technologically-enhanced connectivity (linking people), discovery (finding people), and leverage (doing old things faster/better/cheaper or doing entirely new things). What exactly those ‘things’ are is up to the group itself or the originators of the service, but one thought I had is that the services themeselves vary along key dimensions, which we could think of as ‘necessity’ and ‘sufficiency’: for example, the social network aspect of eBay, at least its rating system and the fact that you’re dealing with people rather than a shop-front is necessary for it to work, whereas Orkut, in total contrast, pushes hard on the ‘sufficiency’ dimension (‘build it and they will come’, i.e. enabling social networking is sufficient for ‘something’ to happen, though we don’t know what right now).

Haven’t had time to try to map out other instances along these dimensions, but may provide some useful food for thought…

hope that’s useful…
cheers
-Marc