Google have just released a new systems programming language called “go“. The syntax has a vaguely 80’s C style to it, which is hardly surprising, given that Rob Pike and Ken Thompson are listed among the designers of the language.
I’d be interested to hear if anybody has used go to do anything useful?
Ironically, the kinda lame name that they chose for the language will likely make it difficult to google for useful webpages on it.
Fergus Burns reports that IBM have announced the final 5 shortlisted companies for the IBM SmartCamp.
Of the five companies listed, one (HeyStacks) is a spin-out from the SFI-funded CSET CLARITY, founded by Prof. Barry Smyth, and another (TreeMetrics) is a Cork-based SME that is working in collaboration with the SFI-funded Cork Constraint Computation Centre (4C) based in UCC.
Good luck to both HeyStacks and TreeMetrics.
As a general rule, I’m not a huge fan of keynote, invited talks – in my experience, they tend to be dry, hastily prepared and badly delivered.
Chris Horn has posted the text from an invited talk he delivered at a COMREG event yesterday on his blog, and this talk (at least in its written form) defies my stereotype. Well researched, thought provoking, and as he says himself, a little provocative.
There’s a nice article in today’s Irish Times website on the SFI-funded CLARITY CSET.
Researchers in DCU have developed a robot fish called WANDA – hard to resist a corny movie reference, I guess. WANDA stands for "Wireless Aquatic Navigator for Detection and Analysis".
Check out the article on the IT website.
DERI, the SFI-funded CSET in semantic web technology, has announced the launch of Sig.ma, which they describe as giving live aggregation of semantic web data. Sig.ma is based on another piece of DERI technology – Sindice, the semantic web search engine.
To quote from their post:
In Sig.ma, elements such as large scale semantic web indexing, logic reasoning, data aggregation heuristics, pragmatic ontology alignments and, last but not least, user interaction and refinement, all play together to provide entity descriptions which become live, embeddable data mash ups.
I haven’t had an opportunity to play around with Sig.ma yet, but it looks interesting, and I plan on doing so.
The report of An Bord Snip Nua was published by Government yesterday. The two volumes can be downloaded from the Department of Finance website.
The following is an extract from Volume I of the report (Section 2.4, pp 22-23) as it pertains to Science, Technology and Innovation (STI). It is provided verbatim, and with no commentary:
2.4 Science, technology & innovation (STI)
The Group observes that over the period 2000 to 2007, there was a threefold increase in ‘Government Budget Outlays & Appropriations for Research and Development’ (GBOARD). Analysis of trends in spending and policy in this area gives rise to a number of specific issues of concern to the Group, as outlined below.
- Real returns on investment
Although spending on STI is promoted as a key element of enterprise and education policy, the scale and nature of any ultimate economic impacts arising cannot be known with confidence at the outset. The Group considers that any further STI investment must yield clear economic returns. The evidence adduced to date for the impact of State STI investment on actual economic activity has not been compelling.
- Output of PhDs
In the absence of a clear business need for the doubling of PhDs currently being funded, the Group is concerned that graduates will be underemployed or forced to emigrate. Indeed some empirical evidence suggests that 20% of new doctorate holders find employment overseas, and of those who remain in Ireland, most find employment in the public rather than the private sector.
- Rationalisation of funding structures
Funding of STI is dispersed through a large proliferation of supports and many target the same or similar activities. The Group considers that there is significant scope for the rationalisation of supports and a reduction in the large administrative overheads in the system.
Regarding the multiplicity of bodies involved in the formulation and implementation of science policy, the Group considers that streamlining the policy framework for STI will improve coordination across research agendas, bring greater efficiency to STI expenditure and maximise the potential for the commercialisation of sectoral research output in particular.
- Reducing dependence on Exchequer funding
Exchequer funding (as distinct from business funding, philanthropy etc.) has grown as a proportion of gross expenditure on R&D in recent years. This suggests some displacement of private funding by public funding and this trend should be halted.
Taken together, these considerations have led the Group to the view that the policy and funding mechanisms for STI should be radically rationalised and streamlined into a single stream of funding, and that the level of Exchequer funding for STI activities can and should be better-focused and made less costly to achieve given goals. The Group proposes an initial reduction of just over €100m, or 15% of the 2009 allocation, in the overall level of spending on STI, and the incidence of these savings across particular spending areas, as set out in the table below, is reflected in each of the Detailed Papers.
Recently, I’ve been playing a little with the Twitter REST API, and with Sinatra, the new Ruby web framework that all the cool kids are into.
On the back of said playing, I’ve just released a pre-alpha (if there is such a thing) version of SemanticTweet.
Basically, SemanticTweet is a simple web service that generates a FOAF RDF document for you from your list of Twitter friends and followers. It does this using the Twitter REST API. This service uses public Twitter data only, and so doesn’t need your Twitter username or password.
FOAF, which stands for friend-of-a-friend, if you’re unfamiliar with it, is a semantic web representation of your list of friends. It’s typically represented in a semantic web format known as RDF: resource description framework. To give you an idea of what a FOAF document looks like, here’s my one, as generated by SemanticTweet.
One of the benefits of this approach is that it ensures that you don’t have to build and maintain your FOAF file by hand (or using a service like FOAF-a-matic), which is a real pain. This service will dynamically generate the FOAF file each time its queried. The second big benefit is that it turns your friends’ Twitter pages into dereferenceable URIs, which means that a semantic web browser or search engine can traverse from link-to-link, just like a standard web page, and all without having to explicitly call the Twitter API.
One way you can use this service/document is by embedding it in your blog/website. Just add a line to the <head> section of your template which reads:
<link rel="meta"
type="application/rdf+xml"
title="FOAF"
href="http://semantictweet.com/your-twitter-screen-name" />
This approach is what Tim Berners-Lee refers to as Linked Data. Check out his excellent talk at TED to get a better idea of this movement.
There’s plenty more to do, and plenty of ways in which Twitter data can be presented in a semantic webby way, to allow more interesting documents to be produced, so watch this space.
So run, don’t walk, over to semantictweet.com, and check it out. You too can have that FOAF document you’ve always wanted but were afraid to ask for. Let me know if you have any comments or observations.
You can follow developments on blog.semantictweet.com and @semantictweet.
Over the past few years, Google have been moving more and more into the machine translation (MT) space – see, for example, their language tools page, which allows you to translate an arbitrary webpage, or a snippet of text from one language to another.
Google’s approach to machine translation is what’s called statistical machine translation (SMT). Essentially, they take the millions of human translated webpages that their search engine has already indexed, and align them – that is, they match sentences in one language (let’s say English) with their counterpart sentences in the second language (let’s say Spanish).
By doing this process across millions and millions of webpage they can build up pretty robust statistical methods of guessing a particular phrase’s correct translation.
This approach had been proposed relatively early on in the development of machine translation – as far back as the 1940’s or early ’50’s, indeed, but until recently, it could not compete with the other major school of thought in the area: rule-based machine translation. Google’s innovation, of course, was that because of their enormous web index they could bring several orders of magnitude more data (translated web pages) to the party than any other previous approach to SMT. In so doing, they showed that an abundance of data can lead to a significant improvement in the quality of the resulting translation.
Why is all of this relevant now? For two reasons: firstly, SFI is funding the Centre for Next Generation Localisation CSET (one of the grants in my portfolio), part of whose work includes machine translation. Second, by way of TechCrunch, I learned of the newly released Google Translator Toolkit. This toolkit is designed to work with the existing Google translation system, but also to allow human translators to add or correct the translations as they see fit.
Of course, there are many professional software tools to support human translation of software packages, websites, documents, etc., but the new Google Translator Toolkit appears to be aimed more at crowd-sourced translations. This is the latest development in website localisation (in particular), led by companies such as Facebook, where the casual (as opposed to professional) translator can translate some of the content of a site into another language. Indeed, crowd-sourced translation is also one of the areas of particular interest to CNGL.
This is a very hot area, and with the release of this toolkit, looks likely to get hotter. It’ll be interesting to see what impact this has, on the translation research community, the amateur/enthusiast translator, and indeed, also the professional translation business.
There’s no mention of the new Apple iPhone 3G S on the O2’s iPhone page yet. Let’s see how long it will take for the 3G S to make it to these shores.
Hopefully, O2 will fully support the new tethering option in the next rev of the iPhone OS.
The Enterprise Ireland Silicon Valley blog has a post on why Ireland rocks for telecoms innovation. Number 5 is:
Irish universities are active in telecoms research. A number have linked with industry to develop novel products. For example, UCC are working on encryption techniques; Maynooth are working on wireless Antenna control.
There are a bunch of world class research centres in Ireland investigating different aspects of networks and telecommunictaions, including:
Another reason I would add to the list is ComReg, the Commission for Communications Regulation. While ComReg regularly comes in for criticism from the Irish blogging community for not pushing hard enough to get broadband rollout, it does deserve credit for its enlightened view over allocation of spectrum for telecoms research. Because we’re an island, Ireland is an ideal test-bed for research and development of wireless technologies which can be tested and developed without polluting the spectrum of our neighbours.