#AI Text Converter To Human Form UK

[cudekai]

AI Text Converter To Human Form UK

Cudek AI is a powerful text conversion tool that utilizes artificial intelligence to convert text into human-readable form. This advanced technology has been specifically designed for users in the UK, providing accurate and efficient conversion results. For more information, please visit https://www.cudekai.com/convert-ai-text-to-human

[blockgeni]

New AI pop stars

Pop stars often inhabit otherworldly personas. Artists such as David Bowie and Lady Gaga made their mark on culture by becoming almost transcendent, mystical figures. But their success has also been down to their humanity; their ability to shock, surprise and sing about things we identify with or aspire to. Experiments in artificial intelligence are now assembling an artist that’s truly alien: the AI pop star. Could a non-­human entertainer enchant and enthral a human audience? Could we become devoted fans of a bunch of algorithms? The most fully formed example currently is Auxuman, a collective of five AI personas created by London artist Ash Koosha. Yona, Mony, Gemini, Hexe and Zoya released their first album back in September, with a follow-up two months later. They each have their own musical style that’s computer-generated rather than composed. On the song Crossfire,Mony sings of spending days “shooting pixels off the screen”, and how he “lost my friends in the crossfire”. The sound is synthesised, beguiling, opaque. https://youtu.be/gT2D5_CTzb4 The aim of the project was to build virtual entertainers that could “satisfy our endless thirst for entertainment”, but producing a cultural facsimile of pop music is far from easy. Lyrics, voice, melody, sound and image have to dovetail together in a way that appeals to huge numbers of people. Humans find this notoriously difficult to achieve; millions have tried and failed. And Auxuman hasn’t hit the big-time (yet). AI certainly has its work cut out. Given the recent advances in the quality of computer-­generated text, lyrics should, at least in theory, present the least problem. Neural networks can mine text data to produce strings of words that have rhyme, alliteration and rhythm. Koosha told website Digital Trends the Auxuman lyric engine was trained on articles, poems and conversations from online. “Expression on each song comes from stories we have told, ideas we have generated and opinions we have shared,” he said. A budding AI pop star would need to be able to convert those words into song. While most of us can sing impromptu tunes to ourselves in an instinctive way, AI has no such instinct. The initial inspiration for a song’s subject – unless it’s randomised – also has to come from a human. Last week, US researcher Li Yang Ku unveiled his “Home-made Rap Machine”, a web-based engine trained on 180,000 rhymes by classic MCs. You feed in a line, it supplies a rejoinder, which was described by Li as “entertaining, but with limited success”. When prompted with “I think I got coronavirus” it replied: “Put me on my head like a vinyl”. Questionable. A smartphone app called Alysia also claims to be able to automate lyric writing, but only for certain topics (including Love, Sadness, Joy, Girls and Boys) and the onus is on you to organise and edit the generated lines. A budding AI pop star would need to be able to convert those words into song. While most of us can sing impromptu tunes to ourselves in an instinctive way, AI has no such instinct. In December, scientists at Amazon’s research centre in Cambridge, UK, used a Google-designed algorithm to analyse language and combine it with notes into a sung melody. Human listeners then marked the results for “naturalness”; it scored 59 per cent on average. Not bad. But its actual voice – the singing, if you like – still involves synthesis with a sound determined by a human being. Then there’s the song’s arrangement, combining melody and harmony in a way that’s pleasing to the ear. AI was first used to generate a musical composition back in 1957, a string quartet (“Illiac Suite”) composed by a vacuum tube computer at the University of Illinois. The results were pleasant, but clumsy. Fast forward 60 years, and a Sony research laboratory was using AI to compose a Beatles-style song called Daddy’s Car. Again, it felt like an impersonation of pop music rather than pop music itself. AI has managed to distinguish itself, however, in the field of muzak, which doesn’t demand our attention. An AI project called Boomy has made hundreds of thousands of ambient soundscapes that quietly move around simple musical shapes. But that’s something very different to achieving pop stardom.

Experimental musicians such as Holly Herndon use AI to push compositions in new directions. Getty. AI is undoubtedly useful for facilitating and developing ideas. Experimental musicians such as Holly Herndon use AI to push compositions in new directions and challenge musicians to move out of their comfort zone. At the other end of the scale, AI provides engines for people who’d love to write music but need help doing so. An app called Amadeus Code bills itself as an “AI powered songwriting assistant”, generating melodies in a number of styles. In December, Amazon unveiled DeepComposer, “the world’s first musical keyboard powered by generative AI”, which fleshes out melodies with accompaniments. Other services offer something similar without a keyboard, including the iOS app HumTap, and OpenAI’s MuseNet, which generates music for up to 10 instruments in more than a dozen genres. It is possible for AI to generate a song from an idea. But it needs plenty of helping hands along the way. But what about the physical embodiment of an AI popstar? Modern audiences are certainly willing to be entertained by non-human entities, whether it’s the cartoons that represent the band Gorillaz, or modern day virtual entertainers such as Instagram’s Lil Miquela. But AI doesn’t choose the way it presents itself; humans do. The look of Auxuman’s five personas were not the result of a flash of computer-generated inspiration; they’re designed to look like pop stars. Across every creative aspect of pop music, AI is only currently able to facilitate or augment the stylistic choices of the humans behind it. That may yet result in something culturally significant, according to Stephen Phillips of Australian AI firm Popgun. He believes that AI will help younger kids create their own pop personas that connect with other kids of the same age. “Once they have the tools to make music that sounds great, they’ll make music for each other, and it’ll sound incredibly genuine to them,” he said in a recent interview. For many years now, it’s been relatively easy to get a computer to make music that sounds vaguely acceptable to the ear. We appreciate it for being clever. But it’s far harder for it to make music that we appreciate for its artistic merit and want to revisit. “Music is a complex, highly structured sequential data modality,” researchers at AI company DeepMind noted in a 2018 paper. For now, AI music is less about computers entertaining us, and more about marketing. The AI pop star is merely a puppet. Some, of course, may argue that this is what human pop stars have been all along. This article has been published from a wire agency feed without modifications to the text. Only the headline has been changed. #Popstars#DavidBowie#LadyGaga#transcendent#mysticalfigures#algorithms#AI#ML#humanaudience#Auxuman#Yona#Mony#Gemini#Hexe#Zoya#shootingpixels#virtualentertainers#Lyrics#voice#melody#sound#image#HomemadeRapMachine#webbasedengine#Humanlisteners#synthesis#musicalcomposition#Daddy’sCar#popmusic#Boomy#ambientsoundscapes#musicalshapes#popstardom#DeepComposer#deepmind#datamodality#AIpopstar#AImusic#news#blockgeni Source link Read the full article

[localbizlift]

Facebook’s human-AI blend for audio transcription is now facing privacy scrutiny in Europe

Facebook’s lead privacy regulator in Europe is now asking the company for detailed information about the operation of a voice-to-text feature in Facebook’s Messenger app and how it complies with EU law.

Yesterday Bloomberg reported that Facebook uses human contractors to transcribe app users’ audio messages — yet its privacy policy makes no clear mention of the fact that actual people might listen to your recordings.

A page on Facebook’s help center also includes a “note” saying “Voice to Text uses machine learning” — but does not say the feature is also powered by people working for Facebook listening in.

A spokesperson for Irish Data Protection Commission told us: “Further to our ongoing engagement with Google, Apple and Microsoft in relation to the processing of personal data in the context of the manual transcription of audio recordings, we are now seeking detailed information from Facebook on the processing in question and how Facebook believes that such processing of data is compliant with their GDPR obligations.”

Bloomberg’s report follows similar revelations about AI assistant technologies offered by other tech giants, including Apple, Amazon, Google and Microsoft — which have also attracted attention from European privacy regulators in recent weeks.

What this tells us is that the hype around AI voice assistants is still glossing over a far less high tech backend. Even as lashings of machine learning marketing guff have been used to cloak the ‘mechanical turk’ components (i.e. humans) required for the tech to live up to the claims.

This is a very old story indeed. To wit: A full decade ago, a UK startup called Spinvox, which had claimed to have advanced voice recognition technology for converting voicemails to text messages, was reported to be leaning very heavily on call centers in South Africa and the Philippines… staffed by, yep, actual humans.

Returning to present day ‘cutting-edge’ tech, following Bloomberg’s report Facebook said it suspended human transcriptions earlier this month — joining Apple and Google in halting manual reviews of audio snippets for their respective voice AIs. (Amazon has since added an opt out to the Alexa app’s settings.)

We asked Facebook where in the Messenger app it had been informing users that human contractors might be used to transcribe their voice chats/audio messages; and how it collected Messenger users’ consent to this form of data processing — prior to suspending human reviews.

The company did not respond to our questions. Instead a spokesperson provided us with the following statement: “Much like Apple and Google, we paused human review of audio more than a week ago.”

Facebook also described the audio snippets that it sent to contractors as masked and de-identified; said they were only collected when users had opted in to transcription on Messenger; and were only used for improving the transcription performance of the AI.

It also reiterated a long-standing rebuttal by the company to user concerns about general eavesdropping by Facebook, saying it never listens to people’s microphones without device permission nor without explicit activation by users.

How Facebook gathers permission to process data is a key question, though.

The company has recently, for example, used a manipulative consent flow in order to nudge users in Europe to switch on facial recognition technology — rolling back its previous stance, adopted in response to earlier regulatory intervention, of switching the tech off across the bloc.

So a lot rests on how exactly Facebook has described the data processing at any point it is asking users to consent to their voice messages being reviewed by humans (assuming it’s relying on consent as its legal basis for processing this data).

Bundling consent into general T&Cs for using the product is also unlikely to be compliant under EU privacy law, given that the bloc’s General Data Protection Regulation requires consent to be purpose limited, as well as fully informed and freely given.

If Facebook is relying on legitimate interests to process Messenger users’ audio snippets in order to enhance its AI’s performance it would need to balance its own interests against any risk to people’s privacy.

Voice AIs are especially problematic in this respect because audio recordings may capture the personal data of non-users too — given that people in the vicinity of a device (or indeed a person on the other end of the phone line who’s leaving you a message) could have their personal data captured without ever having had the chance to consent to Facebook contractors getting to hear it.

Leaks of Google Assistant snippets to the Belgian press recently highlighted both the sensitive nature of recordings and the risk of reidentification posed by such recordings — with journalists able to identify some of the people in the recordings.

Multiple press reports have also suggested contractors employed by tech giants are routinely overhearing intimate details captured via a range of products that include the ability to record audio and stream this personal data to the cloud for processing.

Apple suspends Siri response grading in response to privacy concerns

Google ordered to halt human review of voice AI recordings over privacy risks

Amazon’s lead EU data regulator is asking questions about Alexa privacy

[pmsocialmedia]

Facebook’s human-AI blend for audio transcription is now facing privacy scrutiny in Europe

Facebook’s lead privacy regulator in Europe is now asking the company for detailed information about the operation of a voice-to-text feature in Facebook’s Messenger app and how it complies with EU law.

Yesterday Bloomberg reported that Facebook uses human contractors to transcribe app users’ audio messages — yet its privacy policy makes no clear mention of the fact that actual people might listen to your recordings.

A page on Facebook’s help center also includes a “note” saying “Voice to Text uses machine learning” — but does not say the feature is also powered by people working for Facebook listening in.

A spokesperson for Irish Data Protection Commission told us: “Further to our ongoing engagement with Google, Apple and Microsoft in relation to the processing of personal data in the context of the manual transcription of audio recordings, we are now seeking detailed information from Facebook on the processing in question and how Facebook believes that such processing of data is compliant with their GDPR obligations.”

Bloomberg’s report follows similar revelations about AI assistant technologies offered by other tech giants, including Apple, Amazon, Google and Microsoft — which have also attracted attention from European privacy regulators in recent weeks.

What this tells us is that the hype around AI voice assistants is still glossing over a far less high tech backend. Even as lashings of machine learning marketing guff have been used to cloak the ‘mechanical turk’ components (i.e. humans) required for the tech to live up to the claims.

This is a very old story indeed. To wit: A full decade ago, a UK startup called Spinvox, which had claimed to have advanced voice recognition technology for converting voicemails to text messages, was reported to be leaning very heavily on call centers in South Africa and the Philippines… staffed by, yep, actual humans.

Returning to present day ‘cutting-edge’ tech, following Bloomberg’s report Facebook said it suspended human transcriptions earlier this month — joining Apple and Google in halting manual reviews of audio snippets for their respective voice AIs. (Amazon has since added an opt out to the Alexa app’s settings.)

We asked Facebook where in the Messenger app it had been informing users that human contractors might be used to transcribe their voice chats/audio messages; and how it collected Messenger users’ consent to this form of data processing — prior to suspending human reviews.

The company did not respond to our questions. Instead a spokesperson provided us with the following statement: “Much like Apple and Google, we paused human review of audio more than a week ago.”

Facebook also described the audio snippets that it sent to contractors as masked and de-identified; said they were only collected when users had opted in to transcription on Messenger; and were only used for improving the transcription performance of the AI.

It also reiterated a long-standing rebuttal by the company to user concerns about general eavesdropping by Facebook, saying it never listens to people’s microphones without device permission nor without explicit activation by users.

How Facebook gathers permission to process data is a key question, though.

The company has recently, for example, used a manipulative consent flow in order to nudge users in Europe to switch on facial recognition technology — rolling back its previous stance, adopted in response to earlier regulatory intervention, of switching the tech off across the bloc.

So a lot rests on how exactly Facebook has described the data processing at any point it is asking users to consent to their voice messages being reviewed by humans (assuming it’s relying on consent as its legal basis for processing this data).

Bundling consent into general T&Cs for using the product is also unlikely to be compliant under EU privacy law, given that the bloc’s General Data Protection Regulation requires consent to be purpose limited, as well as fully informed and freely given.

If Facebook is relying on legitimate interests to process Messenger users’ audio snippets in order to enhance its AI’s performance it would need to balance its own interests against any risk to people’s privacy.

Voice AIs are especially problematic in this respect because audio recordings may capture the personal data of non-users too — given that people in the vicinity of a device (or indeed a person on the other end of the phone line who’s leaving you a message) could have their personal data captured without ever having had the chance to consent to Facebook contractors getting to hear it.

Leaks of Google Assistant snippets to the Belgian press recently highlighted both the sensitive nature of recordings and the risk of reidentification posed by such recordings — with journalists able to identify some of the people in the recordings.

Multiple press reports have also suggested contractors employed by tech giants are routinely overhearing intimate details captured via a range of products that include the ability to record audio and stream this personal data to the cloud for processing.

Apple suspends Siri response grading in response to privacy concerns

Google ordered to halt human review of voice AI recordings over privacy risks

Amazon’s lead EU data regulator is asking questions about Alexa privacy

via Social – TechCrunch https://ift.tt/2MZ55c5

[workfromhom]

Facebook’s human-AI blend for audio transcription is now facing privacy scrutiny in Europe

Facebook’s lead privacy regulator in Europe is now asking the company for detailed information about the operation of a voice-to-text feature in Facebook’s Messenger app and how it complies with EU law.

Yesterday Bloomberg reported that Facebook uses human contractors to transcribe app users’ audio messages — yet its privacy policy makes no clear mention of the fact that actual people might listen to your recordings.

A page on Facebook’s help center also includes a “note” saying “Voice to Text uses machine learning” — but does not say the feature is also powered by people working for Facebook listening in.

A spokesperson for Irish Data Protection Commission told us: “Further to our ongoing engagement with Google, Apple and Microsoft in relation to the processing of personal data in the context of the manual transcription of audio recordings, we are now seeking detailed information from Facebook on the processing in question and how Facebook believes that such processing of data is compliant with their GDPR obligations.”

Bloomberg’s report follows similar revelations about AI assistant technologies offered by other tech giants, including Apple, Amazon, Google and Microsoft — which have also attracted attention from European privacy regulators in recent weeks.

What this tells us is that the hype around AI voice assistants is still glossing over a far less high tech backend. Even as lashings of machine learning marketing guff have been used to cloak the ‘mechanical turk’ components (i.e. humans) required for the tech to live up to the claims.

This is a very old story indeed. To wit: A full decade ago, a UK startup called Spinvox, which had claimed to have advanced voice recognition technology for converting voicemails to text messages, was reported to be leaning very heavily on call centers in South Africa and the Philippines… staffed by, yep, actual humans.

Returning to present day ‘cutting-edge’ tech, following Bloomberg’s report Facebook said it suspended human transcriptions earlier this month — joining Apple and Google in halting manual reviews of audio snippets for their respective voice AIs. (Amazon has since added an opt out to the Alexa app’s settings.)

We asked Facebook where in the Messenger app it had been informing users that human contractors might be used to transcribe their voice chats/audio messages; and how it collected Messenger users’ consent to this form of data processing — prior to suspending human reviews.

The company did not respond to our questions. Instead a spokesperson provided us with the following statement: “Much like Apple and Google, we paused human review of audio more than a week ago.”

Facebook also described the audio snippets that it sent to contractors as masked and de-identified; said they were only collected when users had opted in to transcription on Messenger; and were only used for improving the transcription performance of the AI.

It also reiterated a long-standing rebuttal by the company to user concerns about general eavesdropping by Facebook, saying it never listens to people’s microphones without device permission nor without explicit activation by users.

How Facebook gathers permission to process data is a key question, though.

The company has recently, for example, used a manipulative consent flow in order to nudge users in Europe to switch on facial recognition technology — rolling back its previous stance, adopted in response to earlier regulatory intervention, of switching the tech off across the bloc.

So a lot rests on how exactly Facebook has described the data processing at any point it is asking users to consent to their voice messages being reviewed by humans (assuming it’s relying on consent as its legal basis for processing this data).

Bundling consent into general T&Cs for using the product is also unlikely to be compliant under EU privacy law, given that the bloc’s General Data Protection Regulation requires consent to be purpose limited, as well as fully informed and freely given.

If Facebook is relying on legitimate interests to process Messenger users’ audio snippets in order to enhance its AI’s performance it would need to balance its own interests against any risk to people’s privacy.

Voice AIs are especially problematic in this respect because audio recordings may capture the personal data of non-users too — given that people in the vicinity of a device (or indeed a person on the other end of the phone line who’s leaving you a message) could have their personal data captured without ever having had the chance to consent to Facebook contractors getting to hear it.

Leaks of Google Assistant snippets to the Belgian press recently highlighted both the sensitive nature of recordings and the risk of reidentification posed by such recordings — with journalists able to identify some of the people in the recordings.

Multiple press reports have also suggested contractors employed by tech giants are routinely overhearing intimate details captured via a range of products that include the ability to record audio and stream this personal data to the cloud for processing.

Apple suspends Siri response grading in response to privacy concerns

Google ordered to halt human review of voice AI recordings over privacy risks

Amazon’s lead EU data regulator is asking questions about Alexa privacy

from Facebook – TechCrunch https://ift.tt/2MZ55c5 via IFTTT

[un-enfant-immature]

Facebook’s human-AI blend for audio transcription is now facing privacy scrutiny in Europe

Facebook’s lead privacy regulator in Europe is now asking the company for detailed information about the operation of a voice-to-text feature in Facebook’s Messenger app and how it complies with EU law.

Yesterday Bloomberg reported that Facebook uses human contractors to transcribe app users’ audio messages — yet its privacy policy makes no clear mention of the fact that actual people might listen to your recordings.

A page on Facebook’s help center also includes a “note” saying “Voice to Text uses machine learning” — but does not say the feature is also powered by people working for Facebook listening in.

A spokesperson for Irish Data Protection Commission told us: “Further to our ongoing engagement with Google, Apple and Microsoft in relation to the processing of personal data in the context of the manual transcription of audio recordings, we are now seeking detailed information from Facebook on the processing in question and how Facebook believes that such processing of data is compliant with their GDPR obligations.”

Bloomberg’s report follows similar revelations about AI assistant technologies offered by other tech giants, including Apple, Amazon, Google and Microsoft — which have also attracted attention from European privacy regulators in recent weeks.

What this tells us is that the hype around AI voice assistants is still glossing over a far less high tech backend. Even as lashings of machine learning marketing guff have been used to cloak the ‘mechanical turk’ components (i.e. humans) required for the tech to live up to the claims.

This is a very old story indeed. To wit: A full decade ago, a UK startup called Spinvox, which had claimed to have advanced voice recognition technology for converting voicemails to text messages, was reported to be leaning very heavily on call centers in South Africa and the Philippines… staffed by, yep, actual humans.

Returning to present day ‘cutting-edge’ tech, following Bloomberg’s report Facebook said it suspended human transcriptions earlier this month — joining Apple and Google in halting manual reviews of audio snippets for their respective voice AIs. (Amazon has since added an opt out to the Alexa app’s settings.)

We asked Facebook where in the Messenger app it had been informing users that human contractors might be used to transcribe their voice chats/audio messages; and how it collected Messenger users’ consent to this form of data processing — prior to suspending human reviews.

The company did not respond to our questions. Instead a spokesperson provided us with the following statement: “Much like Apple and Google, we paused human review of audio more than a week ago.”

Facebook also described the audio snippets that it sent to contractors as masked and de-identified; said they were only collected when users had opted in to transcription on Messenger; and were only used for improving the transcription performance of the AI.

It also reiterated a long-standing rebuttal by the company to user concerns about general eavesdropping by Facebook, saying it never listens to people’s microphones without device permission nor without explicit activation by users.

How Facebook gathers permission to process data is a key question, though.

The company has recently, for example, used a manipulative consent flow in order to nudge users in Europe to switch on facial recognition technology — rolling back its previous stance, adopted in response to earlier regulatory intervention, of switching the tech off across the bloc.

So a lot rests on how exactly Facebook has described the data processing at any point it is asking users to consent to their voice messages being reviewed by humans (assuming it’s relying on consent as its legal basis for processing this data).

Bundling consent into general T&Cs for using the product is also unlikely to be compliant under EU privacy law, given that the bloc’s General Data Protection Regulation requires consent to be purpose limited, as well as fully informed and freely given.

If Facebook is relying on legitimate interests to process Messenger users’ audio snippets in order to enhance its AI’s performance it would need to balance its own interests against any risk to people’s privacy.

Voice AIs are especially problematic in this respect because audio recordings may capture the personal data of non-users too — given that people in the vicinity of a device (or indeed a person on the other end of the phone line who’s leaving you a message) could have their personal data captured without ever having had the chance to consent to Facebook contractors getting to hear it.

Leaks of Google Assistant snippets to the Belgian press recently highlighted both the sensitive nature of recordings and the risk of reidentification posed by such recordings — with journalists able to identify some of the people in the recordings.

Multiple press reports have also suggested contractors employed by tech giants are routinely overhearing intimate details captured via a range of products that include the ability to record audio and stream this personal data to the cloud for processing.

Apple suspends Siri response grading in response to privacy concerns

Google ordered to halt human review of voice AI recordings over privacy risks

Amazon’s lead EU data regulator is asking questions about Alexa privacy

[sheminecrafts]

Facebook’s human-AI blend for audio transcription is now facing privacy scrutiny in Europe

Facebook’s lead privacy regulator in Europe is now asking the company for detailed information about the operation of a voice-to-text feature in Facebook’s Messenger app and how it complies with EU law.

Yesterday Bloomberg reported that Facebook uses human contractors to transcribe app users’ audio messages — yet its privacy policy makes no clear mention of the fact that actual people might listen to your recordings.

A page on Facebook’s help center also includes a “note” saying “Voice to Text uses machine learning” — but does not say the feature is also powered by people working for Facebook listening in.

A spokesperson for Irish Data Protection Commission told us: “Further to our ongoing engagement with Google, Apple and Microsoft in relation to the processing of personal data in the context of the manual transcription of audio recordings, we are now seeking detailed information from Facebook on the processing in question and how Facebook believes that such processing of data is compliant with their GDPR obligations.”

Bloomberg’s report follows similar revelations about AI assistant technologies offered by other tech giants, including Apple, Amazon, Google and Microsoft — which have also attracted attention from European privacy regulators in recent weeks.

What this tells us is that the hype around AI voice assistants is still glossing over a far less high tech backend. Even as lashings of machine learning marketing guff have been used to cloak the ‘mechanical turk’ components (i.e. humans) required for the tech to live up to the claims.

This is a very old story indeed. To wit: A full decade ago, a UK startup called Spinvox, which had claimed to have advanced voice recognition technology for converting voicemails to text messages, was reported to be leaning very heavily on call centers in South Africa and the Philippines… staffed by, yep, actual humans.

Returning to present day ‘cutting-edge’ tech, following Bloomberg’s report Facebook said it suspended human transcriptions earlier this month — joining Apple and Google in halting manual reviews of audio snippets for their respective voice AIs. (Amazon has since added an opt out to the Alexa app’s settings.)

We asked Facebook where in the Messenger app it had been informing users that human contractors might be used to transcribe their voice chats/audio messages; and how it collected Messenger users’ consent to this form of data processing — prior to suspending human reviews.

The company did not respond to our questions. Instead a spokesperson provided us with the following statement: “Much like Apple and Google, we paused human review of audio more than a week ago.”

Facebook also described the audio snippets that it sent to contractors as masked and de-identified; said they were only collected when users had opted in to transcription on Messenger; and were only used for improving the transcription performance of the AI.

It also reiterated a long-standing rebuttal by the company to user concerns about general eavesdropping by Facebook, saying it never listens to people’s microphones without device permission nor without explicit activation by users.

How Facebook gathers permission to process data is a key question, though.

The company has recently, for example, used a manipulative consent flow in order to nudge users in Europe to switch on facial recognition technology — rolling back its previous stance, adopted in response to earlier regulatory intervention, of switching the tech off across the bloc.

So a lot rests on how exactly Facebook has described the data processing at any point it is asking users to consent to their voice messages being reviewed by humans (assuming it’s relying on consent as its legal basis for processing this data).

Bundling consent into general T&Cs for using the product is also unlikely to be compliant under EU privacy law, given that the bloc’s General Data Protection Regulation requires consent to be purpose limited, as well as fully informed and freely given.

If Facebook is relying on legitimate interests to process Messenger users’ audio snippets in order to enhance its AI’s performance it would need to balance its own interests against any risk to people’s privacy.

Voice AIs are especially problematic in this respect because audio recordings may capture the personal data of non-users too — given that people in the vicinity of a device (or indeed a person on the other end of the phone line who’s leaving you a message) could have their personal data captured without ever having had the chance to consent to Facebook contractors getting to hear it.

Leaks of Google Assistant snippets to the Belgian press recently highlighted both the sensitive nature of recordings and the risk of reidentification posed by such recordings — with journalists able to identify some of the people in the recordings.

Multiple press reports have also suggested contractors employed by tech giants are routinely overhearing intimate details captured via a range of products that include the ability to record audio and stream this personal data to the cloud for processing.

Apple suspends Siri response grading in response to privacy concerns

Google ordered to halt human review of voice AI recordings over privacy risks

Amazon’s lead EU data regulator is asking questions about Alexa privacy

from iraidajzsmmwtv https://ift.tt/2MZ55c5 via IFTTT

[endenogatai]

Facebook’s human-AI blend for audio transcription is now facing privacy scrutiny in Europe

Facebook’s lead privacy regulator in Europe is now asking the company for detailed information about the operation of a voice-to-text feature in Facebook’s Messenger app and how it complies with EU law.

Yesterday Bloomberg reported that Facebook uses human contractors to transcribe app users’ audio messages — yet its privacy policy makes no clear mention of the fact that actual people might listen to your recordings.

A page on Facebook’s help center also includes a “note” saying “Voice to Text uses machine learning” — but does not say the feature is also powered by people working for Facebook listening in.

A spokesperson for Irish Data Protection Commission told us: “Further to our ongoing engagement with Google, Apple and Microsoft in relation to the processing of personal data in the context of the manual transcription of audio recordings, we are now seeking detailed information from Facebook on the processing in question and how Facebook believes that such processing of data is compliant with their GDPR obligations.”

Bloomberg’s report follows similar revelations about AI assistant technologies offered by other tech giants, including Apple, Amazon, Google and Microsoft — which have also attracted attention from European privacy regulators in recent weeks.

What this tells us is that the hype around AI voice assistants is still glossing over a far less high tech backend. Even as lashings of machine learning marketing guff have been used to cloak the ‘mechanical turk’ components (i.e. humans) required for the tech to live up to the claims.

This is a very old story indeed. To wit: A full decade ago, a UK startup called Spinvox, which had claimed to have advanced voice recognition technology for converting voicemails to text messages, was reported to be leaning very heavily on call centers in South Africa and the Philippines… staffed by, yep, actual humans.

Returning to present day ‘cutting-edge’ tech, following Bloomberg’s report Facebook said it suspended human transcriptions earlier this month — joining Apple and Google in halting manual reviews of audio snippets for their respective voice AIs. (Amazon has since added an opt out to the Alexa app’s settings.)

We asked Facebook where in the Messenger app it had been informing users that human contractors might be used to transcribe their voice chats/audio messages; and how it collected Messenger users’ consent to this form of data processing — prior to suspending human reviews.

The company did not respond to our questions. Instead a spokesperson provided us with the following statement: “Much like Apple and Google, we paused human review of audio more than a week ago.”

Facebook also described the audio snippets that it sent to contractors as masked and de-identified; said they were only collected when users had opted in to transcription on Messenger; and were only used for improving the transcription performance of the AI.

It also reiterated a long-standing rebuttal by the company to user concerns about general eavesdropping by Facebook, saying it never listens to people’s microphones without device permission nor without explicit activation by users.

How Facebook gathers permission to process data is a key question, though.

The company has recently, for example, used a manipulative consent flow in order to nudge users in Europe to switch on facial recognition technology — rolling back its previous stance, adopted in response to earlier regulatory intervention, of switching the tech off across the bloc.

So a lot rests on how exactly Facebook has described the data processing at any point it is asking users to consent to their voice messages being reviewed by humans (assuming it’s relying on consent as its legal basis for processing this data).

Bundling consent into general T&Cs for using the product is also unlikely to be compliant under EU privacy law, given that the bloc’s General Data Protection Regulation requires consent to be purpose limited, as well as fully informed and freely given.

If Facebook is relying on legitimate interests to process Messenger users’ audio snippets in order to enhance its AI’s performance it would need to balance its own interests against any risk to people’s privacy.

Voice AIs are especially problematic in this respect because audio recordings may capture the personal data of non-users too — given that people in the vicinity of a device (or indeed a person on the other end of the phone line who’s leaving you a message) could have their personal data captured without ever having had the chance to consent to Facebook contractors getting to hear it.

Leaks of Google Assistant snippets to the Belgian press recently highlighted both the sensitive nature of recordings and the risk of reidentification posed by such recordings — with journalists able to identify some of the people in the recordings.

Multiple press reports have also suggested contractors employed by tech giants are routinely overhearing intimate details captured via a range of products that include the ability to record audio and stream this personal data to the cloud for processing.

Apple suspends Siri response grading in response to privacy concerns

Google ordered to halt human review of voice AI recordings over privacy risks

Amazon’s lead EU data regulator is asking questions about Alexa privacy

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[technicalsolutions88]

Facebook’s lead privacy regulator in Europe is now asking the company for detailed information about the operation of a voice-to-text feature in Facebook’s Messenger app and how it complies with EU law.

Yesterday Bloomberg reported that Facebook uses human contractors to transcribe app users’ audio messages — yet its privacy policy makes no clear mention of the fact that actual people might listen to your recordings.

A page on Facebook’s help center also includes a “note” saying “Voice to Text uses machine learning” — but does not say the feature is also powered by people working for Facebook listening in.

A spokesperson for Irish Data Protection Commission told us: “Further to our ongoing engagement with Google, Apple and Microsoft in relation to the processing of personal data in the context of the manual transcription of audio recordings, we are now seeking detailed information from Facebook on the processing in question and how Facebook believes that such processing of data is compliant with their GDPR obligations.”

Bloomberg’s report follows similar revelations about AI assistant technologies offered by other tech giants, including Apple, Amazon, Google and Microsoft — which have also attracted attention from European privacy regulators in recent weeks.

What this tells us is that the hype around AI voice assistants is still glossing over a far less high tech backend. Even as lashings of machine learning marketing guff have been used to cloak the ‘mechanical turk’ components (i.e. humans) required for the tech to live up to the claims.

This is a very old story indeed. To wit: A full decade ago, a UK startup called Spinvox, which had claimed to have advanced voice recognition technology for converting voicemails to text messages, was reported to be leaning very heavily on call centers in South Africa and the Philippines… staffed by, yep, actual humans.

Returning to present day ‘cutting-edge’ tech, following Bloomberg’s report Facebook said it suspended human transcriptions earlier this month — joining Apple and Google in halting manual reviews of audio snippets for their respective voice AIs. (Amazon has since added an opt out to the Alexa app’s settings.)

We asked Facebook where in the Messenger app it had been informing users that human contractors might be used to transcribe their voice chats/audio messages; and how it collected Messenger users’ consent to this form of data processing — prior to suspending human reviews.

The company did not respond to our questions. Instead a spokesperson provided us with the following statement: “Much like Apple and Google, we paused human review of audio more than a week ago.”

Facebook also described the audio snippets that it sent to contractors as masked and de-identified; said they were only collected when users had opted in to transcription on Messenger; and were only used for improving the transcription performance of the AI.

It also reiterated a long-standing rebuttal by the company to user concerns about general eavesdropping by Facebook, saying it never listens to people’s microphones without device permission nor without explicit activation by users.

How Facebook gathers permission to process data is a key question, though.

The company has recently, for example, used a manipulative consent flow in order to nudge users in Europe to switch on facial recognition technology — rolling back its previous stance, adopted in response to earlier regulatory intervention, of switching the tech off across the bloc.

So a lot rests on how exactly Facebook has described the data processing at any point it is asking users to consent to their voice messages being reviewed by humans (assuming it’s relying on consent as its legal basis for processing this data).

Bundling consent into general T&Cs for using the product is also unlikely to be compliant under EU privacy law, given that the bloc’s General Data Protection Regulation requires consent to be purpose limited, as well as fully informed and freely given.

If Facebook is relying on legitimate interests to process Messenger users’ audio snippets in order to enhance its AI’s performance it would need to balance its own interests against any risk to people’s privacy.

Voice AIs are especially problematic in this respect because audio recordings may capture the personal data of non-users too — given that people in the vicinity of a device (or indeed a person on the other end of the phone line who’s leaving you a message) could have their personal data captured without ever having had the chance to consent to Facebook contractors getting to hear it.

Leaks of Google Assistant snippets to the Belgian press recently highlighted both the sensitive nature of recordings and the risk of reidentification posed by such recordings — with journalists able to identify some of the people in the recordings.

Multiple press reports have also suggested contractors employed by tech giants are routinely overhearing intimate details captured via a range of products that include the ability to record audio and stream this personal data to the cloud for processing.

Apple suspends Siri response grading in response to privacy concerns

Google ordered to halt human review of voice AI recordings over privacy risks

Amazon’s lead EU data regulator is asking questions about Alexa privacy

from Social – TechCrunch https://ift.tt/2MZ55c5 Original Content From: https://techcrunch.com

[royal-red-asks]

10 Mind Numbing Facts About SEO 2019

Good SEARCH ENGINE OPTIMIZATION articles increase a website's SEARCH ENGINE OPTIMIZATION traffic because articles are listed online. Register and raise some sort of free donation for SEO London, uk every time you shop on the internet. Local SEO - Optimize that localized content on your web site to properly leverage local alerts, online reviews and business entries. Learn more about content material optimization for SEO here. Along with paid-search it offers a very focused audience, visitors referred by SEARCH ENGINE OPTIMIZATION will only visit your web site if they are seeking particular home elevators your products or even related content. From keyword padding to link buying, the SEARCH ENGINE OPTIMISATION landscape has seen numerous black-hat tricks — and Google constantly catches on. Chris Gregory, founder plus managing partner at Jacksonville dependent firm, DAGMAR Marketing, predicts that will AI and machine learning might have a big impact upon SEO in 2019 and SEOs who aren't technical will become left in the dust. Some SEO specialists also advise that anchor textual content should be varied as a lot of pages linking to one web page using the same anchor textual content may look suspicious to look motors. SEO trickery such because keyword ‘stuffing' in irrelevant written content simply won't cut it within the current day, with Google's algorithm taking over 200 aspects to ensure that it's ranks provide results with valid plus authoritative sites, it is next to on impossible to perform anything additional than work with the look for engines to make sure best quality SEO results. From a SEARCH ENGINE OPTIMIZATION perspective, the principal keyword need to be at the beginning adopted by the other relevant key phrases. On this web page you'll find a list associated with 21 SEO insanely tactical strategies that you can use in order to boost your engine rankings. 26% of respondents state email is the digital advertising channel using the greatest positive influence on revenue; SEO is 2nd (17%), followed by paid lookup (15%), social media (5%), plus online display advertising (5%). Along with an increased focus on consumer experience, Google has challenged the particular SEO community to pay even more attention to the entire expertise of a website and just how the content interacts with customers, rather than just the simple elements that most optimize towards. While that will certainly not get solved in 2018, we require integrate the SEO group alongside other marketing, both compensated and owned initiatives. For example, several businesses miss the mark along with SEO and images, and nevertheless rank well. Thankfully, you can find your very own broken links on site using the particular myriad of Tools available. Ask any SEO services company and they will tell a person that whenever a page is definitely searched, the major search motors spiders search it through hyperlinks. Effective SEO aims to boost lookup engine position, user visits, come back visits, and to improve transformation rates, which reflect the figures of visitors who take preferred actions on the site. Wise SEARCH ENGINE OPTIMIZATION activities transform your rankings in the particular search engine results page (SERP). This is the best goal for ecommerce SEO, plus the traffic those links will certainly bring through will convert with a very high rate.

SEO is really the shortened phrase for search motor optimization. I believe SEO within 2019 will largely be such as SEO in 2018, with the particular exception of some big” Search engines update that wipes out sufficient websites to make people think the algorithms have grown significantly smarter. SEARCH ENGINE OPTIMIZATION works by optimizing a home page's pages, conducting keyword research, plus earning inbound links. The business offers excellent SEO packages that will help rank the clients' site within top three pages associated with search engine pages. That can make SEO an ideal lead era tool, because when searchers stick to links back to your web site, you have the chance in order to convert them to leads, plus later make sales. Whenever asked to point out ideas that are unique towards the particular web, most people will arrive up with two main types: SEO and social media. How many links do a person need for good off-page SEARCH ENGINE OPTIMIZATION? If you are carrying out a professional SEO audit to get a actual business, you are going in order to have to think like the Google Search Quality Rater And also a Google search engineer to supply real long-term value to the client. 44. Give your own social media profiles an SEARCH ENGINE OPTIMIZATION boost. 10% of our experts believe that will there's likely to be the lot of focus on cellular in 2019, as older SEOs realize optimizing for desktop is usually pointless. White hat SEO is not really just about following guidelines, yet is about ensuring that the particular content google search indexes and consequently ranks will be the same content the user will see.

You will become introduced to the foundational components of how search engines such as google work, how the SEARCH ENGINE OPTIMIZATION landscape is promoting and exactly what you can expect in the particular future. The SISTRIX Toolbox consists associated with six modules 1) SEO, 2) Universal, 3) Links, 4) Advertisements, 5) Social and 6) Optimizer. Low-quality content can severely impact the achievements of SEO, within 2018. When your own SEO starts building strong environment, competitors can start maligning your own SEO backlinks. ” With content marketing spend anticipated to reach $300 billion by 2019, this statistic is worrisome. Now the electronic marketing companies know how in order to use AI for SEO, plus in coming years AI will certainly dominate in developing the SEARCH ENGINE OPTIMIZATION strategies of the digital advertising companies. Ray Cheselka, AdWords and SEARCH ENGINE OPTIMIZATION Manager at webFEAT Complete, the design and SEO agency, states that in 2019 search intention will continue to become even more important. Expert writers of SEO articles may take the time to study the particular industry or specific niche market market. 2 tools to help with regional SEO are BrightLocal (for rankings) and MozLocal (for local research optimization). Concerning on-page SEO best practices, I usually link out to other quality appropriate pages on other websites exactly where possible and where a human being would find it valuable. It includes a well known Regular Table of SEO Success Factors”, a 9-chapter guide to SEARCH ENGINE OPTIMIZATION basics, and links to several from the site's most useful blog posts. This guide is definitely made to describe all places of SEO—from seeking the terms plus phrases (keywords) that generate visitors to your website, to producing your blog friendly to search motors, to building links and advertising the unique associated with your own site. With out SEO, a website can become invisible to search engines. On-page SEO refers to be able to every strategy, technique, and application you utilize within your web site to optimize your web webpages and content for search search engines like google. Today, the quality of arriving links is evaluated higher as compared to their quantity and may add your SEO efforts. Research engine optimization (SEO) tools assist companies position themselves to obtain a favorable ranking in internet search engine results. The particular second biggest SEO trend within 2019 will be voice research. Jooxie is long past mobile search plus voice-search being a ‘trend' : they are the full upon normal now, outdoing desktop research in both volume and SEO-favorability. Rather compared to marketing at people, you require to make it possible with regard to them to find you whenever they want you, and gowns where SEO is available within. Prior To going BlowFish SEO full Time, Robert Headed very successful internet incoming marketing campaigns for Bella Sante Day Spa's of Boston plus Red Door Spas increasing their own yearly Gift Card Sales simply by over 400% and increasing client appointments over 300%. In 2019 and over and above, the majority of the on the internet searches will be in the particular form of conversation, and since a result, the online entrepreneurs will give more importance in order to artificial intelligence keywords for marketing of the web content. The Technical Audit Checklist Produced For Human Beings — Within this post by Distilled, a person will find a link in order to a Google sheet that offers an technical SEO audit register and links to resources upon how to complete each checkbox. Then each time the term SEO appears on your web site, it's automatically changed into the link you specified. Keyword Analysis for SEO: The Definitive Guideline — This comprehensive guide simply by Brian Dean teaches you the number of strategies for getting keywords and determining intent intended for your target market. On-page and off-page SEO function together to improve your lookup engine rankings in complementary style; however, SEOs generally advise obtaining your on-page SEO ducks within a row before focusing as well much on off-page SEO. Within 2019, web-based businesses will follow more voice-to-text technology to boost engagement and search activity. There are many SEO web sites suggesting that they can supply a service to make the website LSI friendly, or satisfy ‘LSI requirements'. The particular art of web SEO is situated in focusing on how individuals search for things and knowing what type of results Search engines wants to (or will) screen to its users. Social press SEO would encourage your present customers to come back whilst helping you develop authority with regard to potential ones. He is an expert in SEO, Content Marketing, plus Pinterest Marketing. An SEARCH ENGINE OPTIMIZATION expert plays a huge function in helping companies build their own businesses and attract new clients through website traffic. We all desired to look at a massive group that included businesses of just about all sizes and in all sectors so we could really observe how SEO traffic increased whenever the only common denominator was incorporating reviews to their site. In reality, this is section of the SEO technique we have used to continuously grow our organic traffic throughout the last 12 months right here at SnapApp: #3. Mobile will certainly account for 72% of ALL OF US digital ad spend by 2019. This workshop is definitely designed to help business proprietors implement Digital Marketing techniques with regard to their business including social mass media, organic SEO as well since paid channels. The Beginner's Guide in order to SEO continues to be go through over 3 million times plus offers comprehensive information you require to get on the road to professional quality Search Motor Optimization, or SEO. Whether it's using web analytics for carrying out research or even conversion tools that monitor plus report the usage of essential keywords, SEO agencies know just how and where you can obtain the information they need in order to save time furthermore decrease your in-house price. Generally there is probably no more simple strategy for SEO than the particular integration of internal links in to your site - it will be an easy way to enhance traffic to individual pages, SEARCH ENGINE OPTIMIZATION Consult says. SEO SERVICES Right now there are a number of SEARCH ENGINE OPTIMIZATION services which can help enhance the organic search engine search positions of a website. Keyword studies about obtaining those terms so that a person can use them properly within content optimization and SEO within general. Just as content by yourself isn't enough to guarantee SEARCH ENGINE OPTIMIZATION success, SEO alone isn't good enough to ensure that people can find and engage with your own articles. While intense SEO may involve complex site restructuring along with a firm (or consultant) that will specializes in this area, right now there are a few simple actions you can take yourself in order to improve your search engine ranking. 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Even though certain techniques of SEO articles remain the same, like not really compromising on quality; there are usually definitely techniques which have progressed from the past and a person should find out whether your own SEO articles writing services are usually very well aware of that will or not. SEO service suppliers are specialized in increasing the particular traffic to your site simply by increasing your position in the particular search engine ranking positions. Entice international people to your internet sites with these SEO tips. The top challenges within organic SEO are link developing (easy-to-get links no more have got much value) and keyword analysis (the low-hanging fruit is lengthy gone). For illustration, the phrase ‘SEO tips' is furthermore included inside the less competing phrase ‘SEO tips 2019', which usually is searched for too.

PeepCon (which stands for The Someones Conference”) seeks to teach doable SEO and digital marketing training. See how Matthew had taken a website from zero in order to one million visits in much less than a year, using the mix of blogging, content marketing and advertising, and SEO. Solid being familiar with of the keywords, questions, and even phrases your ideal customers employ to find your products and even services is critical to successful SEO. 34. Applying SEO practices (such keyword optimization) to social media marketing raises discoverability when users search sociable platforms like Facebook and Youtube . com. Onsite SEARCH ENGINE OPTIMIZATION Guide — If you the particular actual link, you will notice a opt-in button where a person can download the Onsite SEARCH ENGINE OPTIMIZATION Guide. ” Matt Diggity will a lot of testing upon his own sites, and this guideline reflects what on page strategies are working best for your pet. One important aspect associated with taking care of SEO will be identifying issues that are harming search engine ranking positions plus reducing the traffic you obtain through SERPs. User-generated content like reviews assist SEO through SMO, because this often comes in the type of social shares, likes, or even commenting, or common threads such as hashtags that point back in the direction of a brand. Local SEARCH ENGINE OPTIMIZATION services offer a very focused online marketing approach, (it's not really like dropping off brochures upon front-porch steps or paying for a good ad in a local newspapers that could or may not really be seen by a probable client that is actually fascinated in your products or services).

Head associated with Marketing at @impressiontalk specialising within user-centred SEO, PAGE RANK, content marketing and digital technique. Primary is definitely on inbound marketing, including almost everything from SEO to social press. However, a good agency providing SEO services is usually all about being proactive in order to keep up-to-date with the most recent search engine news and adjustments in SEO techniques. Video marketing provides new opportunities to drive even more visitors your site and enhance its SEO status. Research Engine Optimisation (SEO) in 2018 is really a technical, deductive and creative process to enhance the visibility associated with the website in search motors. Off-page SEO pertains to the actions taken exterior of your own personal website that can easily help boost your search powerplant rankings. Mainly because Blog9T of this insufficient visibility this can be hard to create a sound business case with regard to SEO, even though it will be strikingly obvious of the advantages to most companies of the particular number one position on Search engines. This particular is a time-honored SEO exercise called broken link building. Definitely engaging in reputation management, content material management and SEO (Search Motor Optimization) can give even the particular smallest business a chance in order to compete globally. Whether you are already adding SEO into your online marketing and advertising mix or not, you may ask yourself how aCO site stacks up against acom. With recent Google adjustments, failure to look after cellular SEO could result in research invisibility, and mobile's bringing various other changes you'll need to end up being ready for.

[loginworksoftware-blog]

Data processing technologies are developing as rapidly as data collection is advancing, that is, at a continually accelerating rate. There’s a whole lot of technology that is breaking ground and offering new solutions in this exciting field.

Let’s take a look at what some of the latest cutting-edge technologies are for data processing systems.

DISTRIBUTED SYSTEMS ARCHITECTURE

Big data sets common in data processing today have limitations on computational power. The technology needed to deal with this is called distributed systems architecture.

MPP – Massive parallel processing, and Hadoop are two key technologies that are leading the industry in distributed systems architecture. Both feature the “shared nothing” technology that ensures autonomous operation.

The key difference between the two is that MPP is proprietary and rather costly to implement, while Hadoop is open source and can be integrated from very small, low cost applications, to very very large ones. While Hadoop is more recent than MPP, and allows flexibility and scalability, MPP remains slightly quicker.

MPP systems are provided by Teradata, Netezza, Vertica, and Greenplum. Oracle and Microsoft also have their own MPP systems.

Hadoop is a software project by Apache, containing a collection of software utilities that provide huge storage and processing power. Hadoop uses MapReduce to process large non-structured data sets, as the name implies, by a map function, and a reduce function within Hadoop. Many platforms can be built on top of the Hadoop framework. Non-proprietary applications available for use on Hadoop continue to develop in number and complexity.

QUERY OPTIMIZATION

Part of leading technology for data processing in a relational database is query optimization design. Query optimization is an automated process that attempts to provide the best possible answers based on a range of possible query plans. A query plan is a set of rules that a relational database uses to search data for the required parameters. Query optimization can effectively determine which searches are valid, and which will be most accurate, efficient, and timely.

Query hints may be built into query optimization, for example, a query on a GPS database might be selected for the fastest or the quickest route. A simplified example of query optimization is to imagine a query for the number of a certain car make and model, where the database could search all makes then all models, just all models, since the model subset automatically includes make. Query optimization would choose the latter.

NON-RELATIONAL DATABASES – NO-SQL

With the explosion of Big-Data, has come two more players in data processing technology, non structured and dark data.

Traditional databases have relational structure, usually called relational data base management systems (RDBMS), and are primarily built on SQL – structured query language, which is why non-relationship databases are coined No-SQL.

A Non-relational, No-SQL database can store and access un-structured data easily using a common data format called JSON documents, and can import JSON, CSV, and TSV formats.

A JSON, Javascript Object Notation is a lightweight data-interchange format, simple yet very powerful, since stored data need not be structured. The ability to store and access this non-structured data is what makes non-relational databases such important technology for data analytics systems. As a draw back, since they are non relational, the query itself has to draw a relation, so working with a non-relational database requires more skill.

Popular No-SQL databases used in data processing are MongoDB, Arango DB, Apache Ignite, and Cassandra.

DATA VIRTUALIZATION

Data storage and retrieval can sometimes deteriorate data due to the format that is required by the storage or retrieval. Unlike the traditional ETL (extract, transform, load) data method, in data virtualization the data remains where it is, a viewer accesses it in real time, from it’s existing location, solving the problem of format losses. An abstraction layer between viewer and source means that the data can be used without extraction and transformation.

A simplified example of data virtualization we can all identify with is the technology that drives images on social media. When you view an image on most social media platforms, normally you’re viewing it temporarily in real time on your mobile device or computer, but it exists in reality on the server of whichever social media you’re on. The file format is not relevant, nor do you need software related to the format to view it. The image is only converted into real data if it’s downloaded or via a screenshot, but the data is searchable and viewable without ever opening the file itself because of data virtualization.

STREAM PROCESSING AND STREAM ANALYTICS

Stream processing provides the capability for performing actions and analyzing events on real-time data. To do this stream processing makes use of a series of continuous queries. Stream processing allows data information to be processed before it lands in a database, which makes it incredibly powerful.

A good example to explain the process of live stream data analytics is the correlation of GPS data or driver mobile data with user locations. Uber’s apps have used this with great success to revolutionize private transport. Many bank applications also use stream processing to immediately alert users of suspicious activity.

Striim, IBM Infosphere, SQLStream, and Apache Spark are examples of common streaming database applications.

DATA MINING AND SCRAPING

Data mining and scraping technology is improving the content that data-processing systems have available in the data capture phase. Data mining in it’s simplest form essentially takes very large sets of data and extracts smaller more useful sets. Data mining software automizes the fundamental data processing function of finding patterns in large data sets, to create smaller subsets which match search query criteria. Web search is essentially a form of data mining we all use, taking the catalogue of websites and extracting only those that match search terms. Data mining may be applied to any type of data, text, audio, video, images. Data mining can be incredibly useful in finding information a company doesn’t currently have from large unstructured data sources.

Scraping is similar to mining, but where mining analyzes data for patterns, scraping collects data matching certain parameters.

MACHINE LEARNING AND AI

Data processing is a key field for advances in machine learning and AI. Data preparation involves cleaning and transforming the data for us. It often takes around 60 to 80% of the whole data processing time, with as little as 20% for analytics and presentation. The preparation of data is largely repetitive and time consuming, so it is a perfect area for implementation of the latest technology in machine learning. Processing large amounts of data, especially when complex text based data like searching contracts, reports, articles, machine learning is a one of the latest technological advancements that will improve the industry. Machine learning can match phrases in a range of documents based on connections that previously only humans could do. We think of AI and machine learning as way out there, but we actually interact with it every day on platforms like Google search. Haven’t you noticed how it seems to know more and more what you might be thinking, with scary accuracy? It’s a simple concept yet, currently one of the most extensive examples of machine learning data processing in everyday use. Machine learning is also growing steadily in user interaction devices on the web. Automated answers to users questions, along with databasing questions and responses for improved machine learning, helps organizations better serve their customers.

AI and machine intelligence is advancing faster than we can train people to work with it. An unbelievable 2 jobs are available for every AI graduate in the UK.

DATA COMPRESSION

Compression is driving data processing, with larger and larger data sets, any reduction in data sizes will improve experiences. Storage space and processing times can be reduced significantly with better compressions techniques, this in turn significantly reduces costs and improves performance. Facebook has released their latest compression tool Z standard on an open source platform. While previous storage compression devices had around 9 levels, Z standard has 22 levels. Data compression will help improve our storage and processing capacities.

SELF-DRIVING DATABASE MANAGEMENT SYSTEMS

The last and most significant technology in data processing systems is the self-driving database management system. A self-driving database can be run without user intervention, and totally managed by the user. Leading this technological advancement is Oracle’s Autonomous Database. Oracle’s founder claims it will revolutionize data management, since there is no need to apply patches, complete manual back-ups, or tune, it’s capable of total automation. Peleton is a good example of a leading open source autonomous database solution.

For data processing, it’s important to stay ahead of the trends. Check out some of the ideas we’ve discussed here to find out more about where your data processing systems can evolve.

[cudekai]

AI Text Converter To Human Form

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