IBM snaps up i2 for £309m
The big Cambridge sell-off continues, this time with computer giant IBM paying a reported £309m for i2 at Fulbourn.
The company’s software helps police and the military around the world to analyse security information and evidence.
The i2 sale is not quite the same as last month’s $10bn sale of Autonomy to HP as i2 had already been sold to Californian private equity company Silver Lake Sumeru.
Eight of the 10 largest companies in the world use i2’s technology which analyses data for crime and fraud prevention intelligence, as do 12 of the top 20 retail banks globally.
Robert Griffin, chief executive of i2, said: “i2’s existing clients will be at home with IBM, a company known for its ability to help organisations make the most of their data assets.”
At its HQ on Capital Park and around the world, i2 has 350 employees and more than 4,500 customers.
Wednesday, 7 September 2011
Cambridge Business News | Cambridgeshire Local Business & Corporate News | IBM snaps up i2 for £309m
Become an interpreter
To become a conference interpreter you need to know languages, in particular your own language. You will need a university degree (in any subject) and also a post graduate degree in conference interpreting.
These pages are about how and what to study in order to prepare to apply for a job as an interpreter with the EU institutions. You will also find links to useful learning resources and some information about living in Brussels.
If you still have questions, do please get in touch with us. See the Contact page below for details.
In Conversation: Brian Aldiss | The Idler - London UK - Date: Tuesday 6 September. Time: 6.30pm for 7pm. Place: The Idler Academy, 81 Westbourne Park Road, London W2 5QH
In Conversation: Brian Aldiss
The great Brian Aldiss and actor Sir Timothy Ackroyd start our “In Conversation” series with a three-way symposium about life, art and everything with Melli Bond (“arbritrary and irrelevant,” The Guardian). Come and spend an evening in the company of one of our finest and most distinguished writers.
Brian W. Aldiss was born in Norfolk in mangel-wurzel territory. Fortunately these vegetables had very little influence on his creativity. Nothing did. Soon Aldiss was reading Dickens and Zola. Zola was known as the French Dickens, while Dickens was known as the English Dickens.
Brian Aldiss
Aldiss began writing one midnight and there remains a dark side to his writing, popularly known as the backside. He narrowly missed World War One, but got lucky with World War 2, when he was sent by popular acclaim far away to the East to become acquainted withy the Japanese. He remained for four years out East, in the safety and comfort of the British army. This long stay accounts for much of his behaviour when back in England.
To silly to become a journalist, too sensible to become a politician, he combined both roles and became a contemporary writer. The irregular hours suited his irregular habits.
Aldiss has had a long career with several cats and children; both cats and children have been good for him, if not he for them. It must be admitted that he is still having this career. Many of his books were widely read — indeed, the fatter you were, the more widely you read.
He has written about thirty novels at the last count, and none at the first count. Most of his novels are deflections — or reflections, as we like to say — on the world today and tomorrow. One example is The Cretan Treat which, owing to a publisher’s misprint, is known as The Cretan Teat. But he has always kept abreast of the times.
He is currently writing a novel entitled The Old Family Canvas, at least until he can think of a more dreary title.
The Bodleian Library are about to launch a collection of articles and reflections entitled An Exile On Planet Earth on the suspecting public.
Date: Tuesday 6 September.
Time: 6.30pm for 7pm.
Place: The Idler Academy, 81 Westbourne Park Road, London W2 5QH. BOOK HERE.
Price: £30 or £25 concessions. Includes free wine and nibbles.
Date: Tuesday 6 September.
Time: 6.30pm for 7pm.
Place: The Idler Academy, 81 Westbourne Park Road, London W2 5QH
Tuesday, 6 September 2011
Pensioner jailed for growing cannabis (From Falmouth Packet)
Pensioner jailed for growing cannabis
8:26am Tuesday 6th September 2011
A 67-year-old man has been jailed for 18 months after police found £30,000 worth of cannabis growing in his house.
Brian Roissetter's home in Brea, Camborne was raided by police on February 9.
They found cannabis plants being grown in four areas, and that the electricity supply had been diverted from the cottage to run the sophisticated production units, prosecutor Philip Lee told Truro Crown Court on Friday.
Officers found 526 plants in various stages of growth, and the potential yield of skunk cannabis from 96 well grown, healthy plants was estimated to be worth £30,000 on the streets. It was estimated about £2,000 worth of electricity had been diverted.
"Even on the basis of selling to people who want to use it as a medicine this was a commercial operation," declared Judge Christopher Elwen.
Roissetter, who had pleaded guilty earlier to producing the drug and abstracting electricity, was jailed for 18 months.
Read these News stories
- Pride in Porthleven tidy-up planned
- Bus and 4x4 crash on road to Constantine
- Passengers to benefit from new ticketing technology
- MP urges colleagues to vote against health bill
- Fireworks to light up beach
- High winds and heavy rain to sweep county
- Engine is now full steam ahead
- Dredging will help restore china clay quarries
- Police hunt for missing teen
- Bodyboarders rescued after drama in the dark
Read this!
Bus and 4x4 crash on road to Constantine
Traffic was delayed slightly on the Constantine to Falmouth road this morning after a crash involving a bus and a 4x4.
Passengers to benefit from new ticketing technology
Bus passengers in Cornwall are set to benefit from a £1.2 million investment into new ticketing technology for the county.
Pride in Porthleven tidy-up planned
Volunteers from Pride in Porthleven are planning to meet and tidy up more parts of the port on Sunday, September 11 at 11am.
Pensioner jailed for growing cannabis
A 67-year-old man has been jailed for 18 months after police found £30,000 worth of cannabis growing in his house.
MP urges colleagues to vote against health bill
Helston and West Cornwall MP Andrew George has said he will vote against the government's controversial Health Bill this week as concerns rise that it will see the privatisation of the NHS.
Monday, 5 September 2011
Women for Schapelle: Schapelle Corby - The World Donates to End Australian Government Corruption
Friday, August 26, 2011
Schapelle Corby - The World Donates to End Australian Government Corruption
Via this page, and I've now added that link to the top of every blog post. The bizarre, corrupt World of the Australian Government is about to be headlined around World . . . Schapelle's massive Global support can no longer be ignored, as it translates into direct action in her homeland. Her book is still selling everywhere, a doco is still doing the rounds in many countries - and even more massive exposure is JUST ABOUT TO BE RELEASED. Damning new information that's never seen the light of day until now, though what's already known is fatally damaging . . .. . . ministers who don't have a clue why the footage from thousands of CCTV cameras ended up in the trash can (as well as crucial X-ray imagery), will have their naked butts on public view. Ditto . . .. . . a national police force that refuses to arrest and charge criminal baggage handlers, who imported 200 kilos of cocaine into Australia, using innocent passengers as unwitting drug mules - and then lies through its teeth.. . . a national airline that employs career criminals, and openly says their background is "Irrelevant.". . . a federal transport minister who completely ignores key aviation security issues, ditto the Office of Transport Security.. . . a Commonwealth Director of Public Prosecutions who rewards dangerous criminals with hundreds of thousands of dollars, ditto the New South Wales Crime Commission.. . . a Police Integrity Commission that spits in the face of justice and common sense, ditto the Australian Commission for Law Enforcement Integrity.. . . a country that allows the human rights of its citizens to be trashed by a foreign power without a whimper, as violent terrorists and sickening murderers get off with a slap on the wrist.. . . an incestuous and corrupt national media that burns witches for corporate profit, as it lies and abuses.
BBC News - Dale Farm: Essex Travellers' eviction dates set - 19th September 2011
5 September 2011 Last updated at 10:20Dale Farm: Essex Travellers' eviction dates set
Travellers are set to be evicted from the site later this month
The eviction of travellers from the UK's largest illegal site will take place during the week commencing 19 September, the BBC has learned.
About 400 people face eviction from Dale Farm, at Crays Hill, Essex, by Basildon Council.
The deadline for them to leave the illegal site passed last Wednesday.
A United Nations committee has called on the government to suspend the eviction but the council said it would be going ahead.
Families are to be evicted from 400 illegal pitches, built at the site without planning permission.
The UN's Committee on the Elimination of Racial Discrimination said the eviction would disproportionately affect family life and create hardship.
It called on the government to suspend it "until culturally appropriate accommodation is identified and provided".
But the Department for Communities and Local Government said the council was within its rights to press ahead with the eviction.
Supporters of the Travellers have established a protest camp, called Camp Constant, at the site and have pledged to help the Travellers resist eviction through non-violent means.
Sunday, 4 September 2011
Pickles Plans a Pogrom - Eric Pickles is planning to demolish, destroy, and devastate half of Dale Farm, on Oak Lane, Crays Hill, near Billericay.
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        1. 'Essex travellers facing eviction threaten Big Fat Gypsy War on the authorities', 13 March 2011, Daily Mail, posted on www.dailymail.co.uk 2. 'Travellers face bank holiday crackdown', 13 April 2011, Evening Standard 3. 'Not evicting gypsies will set "very bad precedent" ', 10 March 2011, This is Total Essex, Essex Chronicle 4. James Heartfield, 'Dale Farm rebellion against eco-elitism', 26 January 2009, Spiked Online, posted here 5. Patrick Barkham, 'Dale Farm Travellers eviction: the battle of Basildon', 25 March 2011, The Guardian 6. Eric Pickles, speech to the 'Home Builders Federation "One Year On" Conference', London, 31 March 2011 7. Andrew Levy, 'Travellers build a £12,000 hall at illegal camp - with taxpayers' cash, and without planning permission', 1 May 2008, Daily Mail 8. Joshua Farrington, 'Basildon: Council votes for eviction despite travellers' protests', 16 March 2011, This is Total Essex, Essex Chronicle 9. Tony Ball, quoted by Patrick Barkham, 'Dale Farm Travellers eviction: the battle of Basildon', 25 March 2011, The Guardian 10. 'Basildon Council votes to evict Dale Farm', 16 March 2011, Travellers' Times 11. Rosa Prince, 'Eric Pickles: gipsies could take advantage of Royal Wedding bank holiday to set up illegal camps', 13 April 2011, The Telegraph 12. Eric Pickles, quoted by Rosa Prince, 'Eric Pickles: gipsies could take advantage of Royal Wedding bank holiday to set up illegal camps', 13 April 2011, The Telegraph 13. Eric Pickles, 'It’s the local economy, stupid', 30 July 2010, Conservative Home Blog 14. Candy Sheridan, quoted by Patrick Barkham, 'Dale Farm Travellers eviction: the battle of Basildon', 25 March 2011, The Guardian 15. Rachel Stevenson, 'Dale Farm Travellers: 'We won't just get up and leave', 27 July 2010, The Guardian 16. Grattan Puxon, open letter to Eric Pickles, Secretary of State for Communities and Local Government, 'UN calls for halt to UK Gypsy Evictions', 22 July 2010, Lolo Diklo |       | Pickles Plans a PogromPogróm is a word with Yiddish origin, and is a Russian word meaning “to wreak havoc, to demolish violently, to destroy, or to devastate a town". Eric Pickles is planning to demolish, destroy, and devastate half of Dale Farm, on Oak Lane, Crays Hill, near Billericay. Situated to the North of the now established "plotlands" around the post-war New Town of Basildon in Essex, Dale Farm is home to around 1000 people. It is not a farm. It is a 5 hectare former scrapyard off the A127, outside the M25, owned by the Gypsies and Travellers themselves. They have built their own chalet homes in around 100 plots, large enough to include caravan pitches for their families and friends. The problem they have is that the Local Authority has changed it's attitude to letting Gypsies and Travellers stay to make something of this redundant Brownfield site. Today the Local Authority is mostly against the residents of Dale Farm. But it was not always so in this part of Essex with a long history of "plotlands". In the 1960s there were fewer than 10 plots on Oak Lane. Over time the Local Authority, Basildon Council, granted planning permission for around 40 additional plots. Then attitudes hardened in 2000. The Local Authority decided that the Dale Farm plots could not be added to, and that having allowed earlier building on the scrapyard was a mistake. Residents faced opposition to new building on their own land, and the 50 or so homes that were built in the twenty-first century were never going to be granted planning permission by the Local Authority that now wished none of them were there. Half the homes are legal. The other half have had to be built on land the residents legally own, but which the Local Authority now sees as "Green Belt". The Gypsies and Travellers face a Local Authority that, despite Basildon's history of "plotlands", has nastily turned against them. For more information see http://dalefarm.wordpress.com
On Google Earth look for the rectangle of family housing built in poor quality Green Belt land at Dale Farm, Oak Lane, Crays Hill, Billericay, Essex, CM11 2YJ. The Dale Farm Gypsies and Travellers have shown how people can meet their own housing needs, if only the Local Authority will give them planning permission. Now Basildon Council is planning to spend £8.0 million in demolishing their homes, plus the cost of policing the action. The Daily Mail claimed that Essex Police has asked the Home Office for £10.0 million to cover that policing cost. (1) What kind of crazy planning tyranny is it when people - just like you and I - are prevented from planning and building a field of family houses for themselves? Faced with a challenge to 1947 legislation the planning system is acting desperately in forcing the demolition of the Dale Farm homes. The Coalition government has pledged up to £1.2 million to help Basildon Council clear the Gypsies and Travellers away. (2) Basildon Council had asked the department for Communities and Local Government for £3.0 million to help fund an eviction. (3) It's not the money, but the bigger principle that bothers Eric Pickles, who is now going further. He promises that the CLG will be consulting on new planning guidelines intended to strengthen the hand of Local Authorities in dealing with "unauthorised developments". Dale Farm may be unauthorised, but it is the Local Authority, the CLG, and ultimately Eric Pickles as Secretary of State, who refuse to grant planning approval. If planning approval was likely this conflict would not exist, and 1000 people would be left in peace. Pickles is determined to clear the Gypsies and Travellers away. He told the Evening Standard that '... we are giving councils the power and discretion to protect the environment and help rebuild community relations'. (2) What he means, of course, is that he sees no place in the local community for Gypsies and Travellers. He is blaming them for any strained local relationships when all they want is to be left alone. He appeals to green ideologues, when the Green Belt that engulfs Dale Farm is waste land. James Heartfield made that point on Spiked! in 2009, when the Dale Farm residents were, once again, unable to overcome the planning legal system. The Dale Farm residents face eco-elitism: 'The law that the Basildon Council is upholding is the law that protects the so-called "Green Belt", which is supposed to stop our towns and cities from sprawling over the unspoilt countryside. Sheridan and his fellow travellers have not taken anyone else’s land; they have built their own homes on their own land. But they are being punished because they have sinned against the sacred cow that is the English Countryside.' (4) Even Pickles will probably admit that vast swathes of the Green Belt, and particularly in Essex, is poor quality, but like New Labour before him, he will not let it be used to live in, and particularly not by working people. He sees an opportunity to get the "law abiding" working people of Basildon to turn on the hard working and independent Gypsies and Travellers for breaking the stupid planning law, and challenging the very idea of an ecology in need of his protection. So Pickles is now going deeper into the green prejudice that people are sprawling over the countryside, and need to be contained. At Dale Farm he is tapping into the prejudice amongst environmentalists that large families are a problem. Many Gypsies and Travellers like to have large families, and look after each other, but their sociable culture is evidently at odds with the anti-human idea amongst greens that population growth is threatening the planet. The anti-human prejudice is common to environmentalists, but is being directed by Pickles as he pushes the planning system towards a legal presumption in favour of "sustainable development". Pickles is saying that Gypsies and Travellers building homes represents the unsustainable development his National Planning Policy Frameworkaims to stop. Large families flouting the planning law, and building on the Green Belt in ways that government defines as unsustainable are unacceptable to Pickles. He encourages the local community to organise to move them on, and to use the police to forcibly clear their homes from their own land. Pickles plans a pogrom against Gypsies and Travellers in 2011. As even The Guardian recognised, anticipating "The Battle of Basildon", Pickles '... is fast turning his personal track record of vehement opposition to unauthorised Traveller sites into government policy'. (5) Pogróm originally meant attacks on Jews in the Russian Empire. The first was anti-Jewish rioting in Odessa in 1821. The term "pogrom" gained common use with anti-Jewish riots across the Ukraine and southern Russia between 1881 and 1884, after Narodnaya Volyaterrorists assassinated Tsar Alexander II in St. Petersburg. The "People's Will" anarchists were responsible, but the reaction to the assassination took the form of anti-semitic attacks, lootings, evictions, and expulsions. The perpetrators were organized locally, often with government and police encouragement. Between 1903 and 1906 there were further pogroms, while the 1917 Bolshevik Revolution was widely denounced as a Jewish conspiracy. The British "Khaki" General Election after the First World War returned David Lloyd George as Prime Minister in December 1918, and Winston Churchill became War Minister and Air Secretary. No strangers to anti-semitism, and fearing a spread of mutinous internationalism throughout Europe, they sent the British Expeditionary Forces to help the Tsarist "White" Russians attack the Bolsheviks in the Soviet Union. Nationalists and the Tsarist Army, backed by Expeditionary Forces from Britain, France, and the United States of America, engaged in pogroms in Ukraine, Poland, Belarus, Romania, and Western Russia, killing tens of thousands of Jews between 1918 and 1920. Pogroms continued in Romania to 1921. Anti-semitism went systematically with racism against Gypsies across Europe between the wars, and did not end with the massacre of the Gypsy Camp at Auschwitz-Birkenau on 2 August 1944.
'Look at the alternatives. If a council turns a blind eye to law-breaking what moral right do we have to enforce against anybody else who breaches planning laws? Green belt is there for a reason. It is to stop urban sprawl'. (9) If the Dale Farm residents win, the denial of the Right to Build can be challenged by many more people around Britain than there are Gypsies and Travellers. Planners would need to win support for something positive to be built by freeholders, having lost the power to say "No". Basildon Council Leader Tony Ball defended the eviction plan on 15 March 2011 in a television interview, posted on www.bbc.co.uk.
'Travellers have been known in the past to take advantage of bank holidays to launch “land grabs,” setting up home on land which they do not have authorisation to camp on, and applying for retrospective planning permission once the council offices reopen... Councils are also being allowed to resist retrospective planning applications submitted by gipsies and other home builders, and give more rights to enforce removal notice against those who act illegally'. (11) This eco-anxiety is getting to the truth of the matter. Pickles is blaming Gypsies and Travellers for their independence, but is really worried about "other home builders" who might break the planning law on their own land. 'It’s time for fair play in the planning system', he said, '... standing up for those who play by the rules and tougher action for those who abuse and play the system'. (12) Gypsies and Travellers know the planning system is not fair. It is stacked against them, and if they try to do anything to solve their own housing predicament the planning system will be used by "the wider community" to demolish, destroy, and devastate their homes. Locals who are not Gypsies and Travellers are asking "Why don’t we all start building extra houses, if they can get away with it?" As James Heartfield has observed, '... people usually mean it rhetorically. But actually, it is the right question, just put the wrong way around'. (4) If many more people broke the planning law, and argued to be free to build on their own land as a point of principle, Britain would not have a housing shortage. If Pickles persisted with evictions he would be exposed for his intolerance of Gypsies and Travellers, which in this impending pogrom is hard not to see as an expression of racism. It seems clear that eco-elitism can very easily slip into racism, and the ambition of "Localism" seems reduced to mobilising parochial hatreds. Talking up "Localism", Pickles told the Conservative Home blog readers that '... it’s up to you. Be as ambitious as you can. Be as radical as you like. Be as bold as you want. I’m not going to stand in anyone’s way'. (13) Pickles doesn't mean Gypsies and Travellers. He will do more than stand in their way, and is whipping up racism against Gypsies and Travellers. Not everyone in Basildon will support what he is doing, but the problem is that locally, and nationally, the disparate working people who support the Gypsies and Travellers are not yet sufficiently organised to effectively stop Pickles. That need not remain a political weakness. Pickles will obstruct everyone challenging the 1947 planning law, but he will be viscious against Gypsies and Travellers. He wants "the wider community" to be involved in discussions in determining the number of traveller sites to be provided. (11) Gypsies and Travellers should be free to live on their own land without this sort of government backed locally perpetrated "community" discipline. Don't be fooled by all the talk from this Coalition about "Big Society" or ending the "dependency culture".
The Dale Farm Gypsies and Travellers are clearly being singled out for having the strength to demonstrate their desire for independence. In fact it is Pickles and his burdensome planning law that wants to keep them in a state of dependency. As James Heartfield argued in 2008, we should all applaud and follow the example of Britain's Gypsies and Travellers:
 Britain should be pushing for a universal freedom to build, not forced demolitions, targeted against the few. Don't be fooled by the awesome mendacity of Eric Pickles. He's got it in for Gypsies and Travellers, and they threaten his planning system. For Pickles this is a long run battle.
Every planning initiative from this government and from the last one is in tatters. Pickles has no plan to build housing, only punish Gypsies and Travellers who refuse to wait around for the planning system to allow house building. They won't go easily, and they should be supported. (15) The CLG looks to be about to demolish more homes built by Gypsies and Travellers than they have managed to deliver through the entire failed Eco-Towns programme. The CLG should be ashamed of their record, and of what Pickles is doing in the name of the planning system.
Grattan Puxon representing the Dale Farm Residents Association wrote an open letter to Pickles on the http://lolodiklo.blogspot.com, an organization dedicated to raising awareness about the history, culture and true lives of Romani people. Puxon told Pickles that '... forced eviction is always an ugly action but when it’s being taken against ninety families of one community and those families belong to a ethnic minority, then there must be cause for concern, alarm and shame'. (16) But Pickles is shameless. He says he is acting for the environment and the community of Basildon. In reality he is acting on his own prejudices from within a Coalition government sustained in power by Liberal Democrats. It is time to stand in the way of Eric Pickles as he plans a pogrom in 2011 Ian Abley 13.04.2011 and updated 16.04.2011  | |
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The Surprising Winner of HP's Autonomy Buyout: EMC - The Motley Fool
This article is part of our Rising Star Portfolios series. Let there be no doubt: I'm a shameless EMC (NYSE: EMC ) bull. I've pounded the table over and over telling investors their shares are a steal. There's simply no better way to get cheap exposure to the trend around massive data growth and complexity. So, maybe it's my rose-tinted glasses talking, but when I saw Hewlett-Packard (NYSE: HPQ ) was shelling out a whopping $10 billion for big data specialist Autonomy, I thought one thing: Good for EMC. It's not what you think However, what's less understood is the niche Autonomy fills in the data world. Judging by the fact that Autonomy's website crashed shortly after news broke that HP was close to buying the company, I'd guess a fair amount of traders were furiously Googling what the heck Autonomy actually does. Here's the key idea: while Autonomy might describe itself behind the hard-to-decipher description as "the leader in meaning based computing & enterprise search," it's largely a play on the growth of unstructured data. As Autonomy says in the company's "Introduction to Autonomy" section: Previously computers could only process information if it was organised in rows and columns, or "structured" The amount of unstructured information such as email, instant messaging and video is growing exponentially so that it now exceeds structured data 4:1 This is the biggest change in the IT industry to date because it is the first major change to the information rather than the technology A buyout you should be watching ... At the time, many believed that EMC had overpaid for Isilon. Seeing as how Isilon only had $175 million in trailing revenues, the 13 times sales multiple looked extremely rich. However, we've now seen HP pay 11 times sales for a company in the same field. Further, I'd argue that EMC can give its acquisition a much stronger distribution, meaning that there's more upside to Isilon being bought by a large company relative to Autonomy. In an odd way, HP's willingness to pay up so steeply for Autonomy validates EMC's decision to shell out a high price for Isilon last year. Bottom line Investors also fled high-end storage after NetApp's (Nasdaq: NTAP ) tepid quarter, but I think that's a mistake. While IT spending could drop in the short-run, advanced data storage is an absolutely critical expenditure for most large IT organizations. EMC's acquisition of Isilon is just another example of the complex problems that top-tier storage companies like NetApp and EMC are tackling. So even if IT budgets get cut for months -- or even years -- in the long run, these are two advanced companies that offer a breadth of solutions that are not only unparalleled by their rivals, but are essential in modern business. I might sound like a broken record, but my suggestion is to get in on the cheap while you can. To follow my technology commentary and buys in my real money portfolio, make sure to follow me on Twitter. Otherwise, the best way to keep up with all EMC analysis is adding the company to our free My Watchlist feature that gives you up-to-date news on all your favorite companies.http://www.fool.com/investing/general/2011/08/31/the-surprising-winner-of-hps-autonomy-buyout-emc.aspx
The Surprising Winner of HP's Autonomy Buyout: EMC
August 31, 2011 | Comments (5)
And my bullishness on EMC following HP's acquisition isn't for the reasons you might expect. The obvious implication is that Autonomy's specialty is making sense of huge amounts of data. Likewise, as the storage leader, EMC profits through the need to store all this data being created.
Likewise, EMC recently made a big push into the growing field of unstructured data. While Autonomy allows analysis of the data, EMC acquired a special architecture that's ideally suited to storing the data being created when it purchased Isilon last year. Here's what I had to say about the deal in an earlier article on the subject:EMC has been extremely adept at filling product holes with timely acquisitions. Last fall, I was able to visit scale-out storage specialist Isilon's headquarters and talk to the company about its ambitions in the storage market. I came away very impressed; their solution for storing "unstructured data" made complete sense, especially with more and more data moving toward unstructured forms like videos or power point presentations. However, I was unsure of their ability to sell their product to stodgy IT firms that might be unfamiliar with a new, seemingly revolutionary kind of storage. However, EMC eventually bought Isilon. While the deal might have struck some as overpaying, I see Isilon as a key storage centerpiece that can create outsized opportunities for EMC as the storage industry continues morphing. Whereas Hewlett-Packard and Dell(Nasdaq: DELL ) had to engage in a wild bidding war over 3Par in large part because they had underinvested in storage research and development, EMC is filling logical holes in its portfolio that should leave the company primed to continue growing strongly across the next half-decade. EMC can immediately put its world-class sales force to work selling Isilon products, and the deal should only expand the company's leadership in storage.
Investors have started cautiously looking back to the broader storage sector, with heavily beaten down Micron (Nasdaq: MU ) and SanDisk (Nasdaq: SNDK ) seeing recent gains after a brutal beginning to August. Companies peddling more commoditized storage like flash memory modules naturally bear the brunt when fears of a steep demand decline in the semiconductor industry rear their ugly head.
Saturday, 3 September 2011
Nuance - Dragon Go! In Action - Nuance Dragon Go! Just Say it. Get it. And Go! One App Access for Everything Across the Mobile Web
Dragon Go! is a revolutionary new mobile application that hears what you say and delivers the results you want within seconds! How’s this possible? Dragon Go! features a smart natural language understanding functionality that knows what you want simply by how you say it!
And it will deliver you directly to the best mobile sites on the Web offering what you want– such as Fandango for movie showtimes and trailers, Accuweather.com for local weather updates, Pandora® internet radio, and Yelp for local reviews, recommendations and more! You can also share your Dragon Go! results via an easy-to-use pop-up toolbar featuring link share options across email, text messages, Facebook and Twitter.
Featuring the dynamic Dragon Carousel™, Dragon Go! not only delivers you to the best mobile web site featuring what you want, it also delivers complementary results that enable you to slide the carousel from side-to-side to compare information across the most relevant sites for your Dragon Go! request.
For example:
You say….
“Cowboys & Aliens showtimes” – Dragon Go! delivers you directly to Fandango featuring movie trailers, showtimes and ticket purchasing for your local theaters. The Dragon CarouselTM also enables you to see what people are saying about the movie on Twitter and flick over to Wikipedia to learn more about the graphic novel the movie is based on.You say….
“What’s the weather like”? – Dragon Go! takes you to AccuWeather.com delivering your local weather results. And the Dragon Carousel enables you to compare weather results across The Weather Channel and Weather UndergroundAnd that’s not all! In a place where it’s not convenient to speak? You can also type your Dragon Go! requests for the same fast, accurate results!
Dragon Go! – Control Your Personal Universe with No Boundaries
- Smart! Say it your way, Dragon Go! understands
- Innovative Dragon Carousel™ takes you directly to the mobile web site you want
- No endless blue link options – go direct to the best mobile web sites
- Speak it or type it. Dragon Go! delivers the same accurate results fast!
- Compare results across similar web sites with just the flick of your finger
- No boundaries: shop, request music, find local dining reviews, buy tickets and more
- Sharing is easy – pop-up toolbar enables link share across email, text and social media
Learn More
Speech Analytics: Speech Recognition Leaps Forward - Is it a revolution?
Wednesday, August 31, 2011
Speech Recognition Leaps Forward - Is it a revolution?
Please comment if you experience this technology and if you indeed view it as a revolution.Thx, OferSpeech Recognition Leaps ForwardBy Janie ChangAugust 29, 2011 12:01 AM PTDuring Interspeech 2011, the 12th annual Conference of the International Speech Communication Association being held in Florence, Italy, from Aug. 28 to 31, researchers from Microsoft Research will present work that dramatically improves the potential of real-time, speaker-independent, automatic speech recognition.
Dong Yu, researcher at Microsoft Research Redmond, and Frank Seide, senior researcher and research manager with Microsoft Research Asia, have been spearheading this work, and their teams have collaborated on what has developed into a research breakthrough in the use of artificial neural networks for large-vocabulary speech recognition.
The Holy Grail of Speech Recognition
Commercially available speech-recognition technology is behind applications such as voice-to-text software and automated phone services. Accuracy is paramount, and voice-to-text typically achieves this by having the user “train” the software during setup and by adapting more closely to the user’s speech patterns over time. Automated voice services that interact with multiple speakers do not allow for speaker training because they must be usable instantly by any user. To cope with the lower accuracy, they either handle only a small vocabulary or strongly restrict the words or patterns that users can say.
The ultimate goal of automatic speech recognition is to deliver out-of-the-box, speaker-independent speech-recognition services—a system that does not require user training to perform well for all users under all conditions.
“This goal has increased importance in a mobile world,” Yu says, “where voice is an essential interface mode for smartphones and other mobile devices. Although personal mobile devices would be ideal for learning their user’s voices, users will continue to use speech only if the initial experience, which is before the user-specific models can even be built, is good.”
Speaker-independent speech recognition also addresses other scenarios where it’s not possible to adapt a speech-recognition system to individual speakers—call centers, for example, where callers are unknown and speak only for a few seconds, or web services for speech-to-speech translation, where users would have privacy concerns over stored speech samples.
Renewed Interest in Neural Networks
Artificial neural networks (ANNs), mathematical models of the low-level circuits in the human brain, have been a familiar concept since the 1950s. The notion of using ANNs to improve speech-recognition performance has been around since the 1980s, and a model known as the ANN-Hidden Markov Model (ANN-HMM) showed promise for large-vocabulary speech recognition. Why then, are commercial speech-recognition solutions not using ANNs?
“It all came down to performance,” Yu explains. “After the invention of discriminative training, which refines the model and improves accuracy, the conventional, context-dependent Gaussian mixture model HMMs (CD-GMM-HMMs) outperformed ANN models when it came to large-vocabulary speech recognition.”
Yu and members of the Speech group at Microsoft Research Redmond became interested in ANNs when recent progress in building more complex “deep” neural networks (DNNs) began to show promise at achieving state-of-the-art performance for automatic speech-recognition tasks. In June 2010, intern George Dahl, from the University of Toronto, joined the team, and researchers began investigating how DNNs could be used to improve large-vocabulary speech recognition.
“George brought a lot of insight on how DNNs work,” Yu says, “as well as strong experience in training DNNs, which is one of the key components in this system.”
A speech recognizer is essentially a model of fragments of sounds of speech. An example of such sounds are “phonemes,” the roughly 30 or so pronunciation symbols used in a dictionary. State-of-the-art speech recognizers use shorter fragments, numbering in the thousands, called “senones.”
Earlier work on DNNs had used phonemes. The research took a leap forward when Yu, after discussions with principal researcher Li Deng and Alex Acero, principal researcher and manager of the Speech group, proposed modeling the thousands of senones, much smaller acoustic-model building blocks, directly with DNNs. The resulting paper, Context-Dependent Pre-trained Deep Neural Networks for Large Vocabulary Speech Recognition by Dahl, Yu, Deng, and Acero, describes the first hybrid context-dependent DNN-HMM (CD-DNN-HMM) model applied successfully to large-vocabulary speech-recognition problems.
“Others have tried context-dependent ANN models,” Yu observes, “using different architectural approaches that did not perform as well. It was an amazing moment when we suddenly saw a big jump in accuracy when working on voice-based Internet search. We realized that by modeling senones directly using DNNs, we had managed to outperform state-of-the-art conventional CD-GMM-HMM large-vocabulary speech-recognition systems by a relative error reduction of more than 16 percent. This is extremely significant when you consider that speech recognition has been an active research area for more than five decades.”
The team also accelerated the experiments by using general-purpose graphics-processing units to train and decode speech. The computation for neural networks is similar in structure to 3-D graphics as used in popular computer games, and modern graphics cards can process almost 500 such computations simultaneously. Harnessing this computational power for neural networks contributed to the feasibility of the architectural model.
In October 2010, when Yu presented the paper to an internal Microsoft Research Asia audience, he spoke about the challenges of scalability and finding ways to parallelize training as the next steps toward developing a more powerful acoustic model for large-vocabulary speech recognition. Seide was excited by the research and joined the project, bringing with him experience in large-vocabulary speech recognition, system development, and benchmark setups.
Benchmarking on a Neural Network
“It has been commonly assumed that hundreds or thousands of senones were just too many to be accurately modeled or trained in a neural network,” Seide says. “Yet Yu and his colleagues proved that doing so is not only feasible, but works very well with notably improved accuracy. Now, it was time to show that the exact same CD-DNN-HMM could be scaled up effectively in terms of training-data size.”
The new project applied CD-DNN-HMM models to speech-to-text transcription and was tested against Switchboard, a highly challenging phone-call transcription benchmark recognized by the speech-recognition research community.
First, the team had to migrate the DNN training tool to support a larger training data set. Then, with help from Gang Li, research software-development engineer at Microsoft Research Asia, they applied the new model and tool to the Switchboard benchmark with more than 300 hours of speech-training data. To support that much data, the researchers built giant ANNs, one of which contains more than 66 million inter-neural connections, the largest ever created for speech recognition.
The subsequent benchmarks achieved an astonishing word-error rate of 18.5 percent, a 33-percent relative improvement compared with results obtained by a state-of-the-art conventional system.
“When we began running the Switchboard benchmark,” Seide recalls, “we were hoping to achieve results similar to those observed in the voice-search task, between 16- and 20-percent relative gains. The training process, which takes about 20 days of computation, emits a new, slightly more refined model every few hours. I impatiently tested the latest model every few hours. You can’t imagine the excitement when it went way beyond the expected 20 percent, kept getting better and better, and finally settled at a gain of more than 30 percent. Historically, there have been very few individual technologies in speech recognition that have led to improvements of this magnitude.”
The resulting paper, titled Conversational Speech Transcription Using Context-Dependent Deep Neural Networks by Seide, Li, and Yu, is scheduled for presentation on Aug. 29. The work already has attracted considerable attention from the research community, and the team hopes that taking the paper to the conference will ignite a new line of research that will help advance the state of the art for DNNs in large-vocabulary speech recognition.
Bringing the Future Closer
With a novel way of using artificial neural networks for speaker-independent speech recognition, and with results a third more accurate than what conventional systems can deliver, Yu, Seide, and their teams have brought fluent speech-to-speech applications much closer to reality. This innovation simplifies speech processing and delivers high accuracy in real time for large-vocabulary speech-recognition tasks.
“This work is still in the research stages, with more challenges ahead, most notably scalability when dealing with tens of thousands of hours of training data. Our results represent just a beginning to exciting future developments in this field,” Seide says. “Our goal is to open possibilities for new and fluent voice-based services that were impossible before. We believe this research will be used for services that change how we work and live. Imagine applications such as live speech-to-speech translation of natural, fluent conversations, audio indexing, or conversational, natural language interactions with computers.”
Speech Recognition Leaps Forward - Microsoft Research
Speech Recognition Leaps ForwardBy Janie ChangAugust 29, 2011 12:01 AM PTDuring Interspeech 2011, the 12th annual Conference of the International Speech Communication Association being held in Florence, Italy, from Aug. 28 to 31, researchers from Microsoft Research will present work that dramatically improves the potential of real-time, speaker-independent, automatic speech recognition.
Dong Yu, researcher at Microsoft Research Redmond, and Frank Seide, senior researcher and research manager with Microsoft Research Asia, have been spearheading this work, and their teams have collaborated on what has developed into a research breakthrough in the use of artificial neural networks for large-vocabulary speech recognition.
The Holy Grail of Speech Recognition
Commercially available speech-recognition technology is behind applications such as voice-to-text software and automated phone services. Accuracy is paramount, and voice-to-text typically achieves this by having the user “train” the software during setup and by adapting more closely to the user’s speech patterns over time. Automated voice services that interact with multiple speakers do not allow for speaker training because they must be usable instantly by any user. To cope with the lower accuracy, they either handle only a small vocabulary or strongly restrict the words or patterns that users can say.
The ultimate goal of automatic speech recognition is to deliver out-of-the-box, speaker-independent speech-recognition services—a system that does not require user training to perform well for all users under all conditions.
Dong Yu“This goal has increased importance in a mobile world,” Yu says, “where voice is an essential interface mode for smartphones and other mobile devices. Although personal mobile devices would be ideal for learning their user’s voices, users will continue to use speech only if the initial experience, which is before the user-specific models can even be built, is good.”
Speaker-independent speech recognition also addresses other scenarios where it’s not possible to adapt a speech-recognition system to individual speakers—call centers, for example, where callers are unknown and speak only for a few seconds, or web services for speech-to-speech translation, where users would have privacy concerns over stored speech samples.
Renewed Interest in Neural Networks
Artificial neural networks (ANNs), mathematical models of the low-level circuits in the human brain, have been a familiar concept since the 1950s. The notion of using ANNs to improve speech-recognition performance has been around since the 1980s, and a model known as the ANN-Hidden Markov Model (ANN-HMM) showed promise for large-vocabulary speech recognition. Why then, are commercial speech-recognition solutions not using ANNs?
“It all came down to performance,” Yu explains. “After the invention of discriminative training, which refines the model and improves accuracy, the conventional, context-dependent Gaussian mixture model HMMs (CD-GMM-HMMs) outperformed ANN models when it came to large-vocabulary speech recognition.”
Yu and members of the Speech group at Microsoft Research Redmond became interested in ANNs when recent progress in building more complex “deep” neural networks (DNNs) began to show promise at achieving state-of-the-art performance for automatic speech-recognition tasks. In June 2010, intern George Dahl, from the University of Toronto, joined the team, and researchers began investigating how DNNs could be used to improve large-vocabulary speech recognition.
“George brought a lot of insight on how DNNs work,” Yu says, “as well as strong experience in training DNNs, which is one of the key components in this system.”
A speech recognizer is essentially a model of fragments of sounds of speech. An example of such sounds are “phonemes,” the roughly 30 or so pronunciation symbols used in a dictionary. State-of-the-art speech recognizers use shorter fragments, numbering in the thousands, called “senones.”
Earlier work on DNNs had used phonemes. The research took a leap forward when Yu, after discussions with principal researcher Li Deng and Alex Acero, principal researcher and manager of the Speech group, proposed modeling the thousands of senones, much smaller acoustic-model building blocks, directly with DNNs. The resulting paper, Context-Dependent Pre-trained Deep Neural Networks for Large Vocabulary Speech Recognition by Dahl, Yu, Deng, and Acero, describes the first hybrid context-dependent DNN-HMM (CD-DNN-HMM) model applied successfully to large-vocabulary speech-recognition problems.
“Others have tried context-dependent ANN models,” Yu observes, “using different architectural approaches that did not perform as well. It was an amazing moment when we suddenly saw a big jump in accuracy when working on voice-based Internet search. We realized that by modeling senones directly using DNNs, we had managed to outperform state-of-the-art conventional CD-GMM-HMM large-vocabulary speech-recognition systems by a relative error reduction of more than 16 percent. This is extremely significant when you consider that speech recognition has been an active research area for more than five decades.”
The team also accelerated the experiments by using general-purpose graphics-processing units to train and decode speech. The computation for neural networks is similar in structure to 3-D graphics as used in popular computer games, and modern graphics cards can process almost 500 such computations simultaneously. Harnessing this computational power for neural networks contributed to the feasibility of the architectural model.
In October 2010, when Yu presented the paper to an internal Microsoft Research Asia audience, he spoke about the challenges of scalability and finding ways to parallelize training as the next steps toward developing a more powerful acoustic model for large-vocabulary speech recognition. Seide was excited by the research and joined the project, bringing with him experience in large-vocabulary speech recognition, system development, and benchmark setups.
Benchmarking on a Neural Network
“It has been commonly assumed that hundreds or thousands of senones were just too many to be accurately modeled or trained in a neural network,” Seide says. “Yet Yu and his colleagues proved that doing so is not only feasible, but works very well with notably improved accuracy. Now, it was time to show that the exact same CD-DNN-HMM could be scaled up effectively in terms of training-data size.”
The new project applied CD-DNN-HMM models to speech-to-text transcription and was tested against Switchboard, a highly challenging phone-call transcription benchmark recognized by the speech-recognition research community.
First, the team had to migrate the DNN training tool to support a larger training data set. Then, with help from Gang Li, research software-development engineer at Microsoft Research Asia, they applied the new model and tool to the Switchboard benchmark with more than 300 hours of speech-training data. To support that much data, the researchers built giant ANNs, one of which contains more than 66 million inter-neural connections, the largest ever created for speech recognition.
The subsequent benchmarks achieved an astonishing word-error rate of 18.5 percent, a 33-percent relative improvement compared with results obtained by a state-of-the-art conventional system.
Frank Seide“When we began running the Switchboard benchmark,” Seide recalls, “we were hoping to achieve results similar to those observed in the voice-search task, between 16- and 20-percent relative gains. The training process, which takes about 20 days of computation, emits a new, slightly more refined model every few hours. I impatiently tested the latest model every few hours. You can’t imagine the excitement when it went way beyond the expected 20 percent, kept getting better and better, and finally settled at a gain of more than 30 percent. Historically, there have been very few individual technologies in speech recognition that have led to improvements of this magnitude.”
The resulting paper, titled Conversational Speech Transcription Using Context-Dependent Deep Neural Networks by Seide, Li, and Yu, is scheduled for presentation on Aug. 29. The work already has attracted considerable attention from the research community, and the team hopes that taking the paper to the conference will ignite a new line of research that will help advance the state of the art for DNNs in large-vocabulary speech recognition.
Bringing the Future Closer
With a novel way of using artificial neural networks for speaker-independent speech recognition, and with results a third more accurate than what conventional systems can deliver, Yu, Seide, and their teams have brought fluent speech-to-speech applications much closer to reality. This innovation simplifies speech processing and delivers high accuracy in real time for large-vocabulary speech-recognition tasks.
“This work is still in the research stages, with more challenges ahead, most notably scalability when dealing with tens of thousands of hours of training data. Our results represent just a beginning to exciting future developments in this field,” Seide says. “Our goal is to open possibilities for new and fluent voice-based services that were impossible before. We believe this research will be used for services that change how we work and live. Imagine applications such as live speech-to-speech translation of natural, fluent conversations, audio indexing, or conversational, natural language interactions with computers.”
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