Improve Efficiency by Double Digits – Leveraging Artificial Intelligence and Machine Learning
Download as PPTX, PDF1 like388 views
John Motz, CTO of Graymeta, discusses leveraging AI and machine learning to improve efficiency in media and entertainment by addressing challenges like geographic constraints and compliance in distribution. He notes that by 2019, 80% of global internet traffic will be video, emphasizing the need for smarter cloud services and the commoditization of technology to reduce costs. The document highlights the growth potential of the voice recognition market and improvements in machine translation productivity, although it acknowledges that translation accuracy remains a challenge.
Improve Efficiency by Double Digits – Leveraging Artificial Intelligence and Machine Learning
- 2. John Motz Chief Technology Officer, GrayMeta Improve Efficiency by Double Digits – Leveraging Artificial Intelligence and Machine Learning
- 3. Creation, Distribution & Consumption are all changing By 2019, 80% of global Internet consumption will be video content Source: By 2019, 80% of the World's Internet Traffic Will Be Video http://tubularinsights.com/2019-internet-video-traffic/#ixzz4bcZTaGxV ©TubularInsights.com, All Rights Reserved
- 4. Data now becoming more available Things have changed… with more change to come Distracted Bored Leave Expensive Geographic Constraints Siloed Can be Expensive Geographic Constraints Human CapitalFacilities Lots of data and history on this – good and bad Scales well Cost improves over time Cloud Services Gets smarter over time Companies are building platforms to ensure there is commoditization and scale Result: Decreased costs Machine Learning Cognitive / AI
- 5. Accelerating the opportunity at GrayMeta Media & Entertainment Compliance Distribution ( IFE ) Distribution (New Markets) Distribution (Regulatory) Search, Recommendation, Discovery EPG, Apps New Tech – Bots Ad Platforms and Revenue Generation
- 7. What happens when you use cloud translation technology instead of highly trained people?
- 8. Watson’s latest feat of 94.1 percent accuracy is fairly impressive — though it should be noted, it’s still well below the 98.5 percent accuracy rate required by many captioning companies. A recent study, Global and China Speech Recognition Industry Report 2015-2020, projected the global intelligent voice market will grow from $6.21 billion in 2015 to $19.2 billion in 2020. In China alone, voice recognition is expected to be a nearly $3.8 billion market within four years. – David Ward thejrc.com Date: Nov 2016 It isn’t perfect, but is getting better everyday
- 9. Machine Translation for Subtitling: Large-Scale Evaluation, Jan 5, 2016 Productivity “Taking the average productivity for each translation pair, and considering all machine translated files, filtered and unfiltered, the gain in productivity reached 38.2%.” And “Measures of productivity gain/loss were also positive, with an overall increase of nearly 40% in terms of subtitles per minute.” Accuracy “Overall pretty good. Simple sentences were usually perfect, but the machine has problems when the sentence is complicated.” And “Generally speaking, it was only in very rare instances that the level of translation generated was such that it needed little or no editing at all. Frequently, it was just easier to get rid of everything and start from scratch.” Perfection isn’t required to realize benefit
- 10. What are the opportunities? Time Cost Quality Control
Editor's Notes
- #4: We have seen in 2016 and early signs already show 2017 wont be any different You can be a creator, seller, buyers, channel, broadcaster, OTT or a Youtube channel Creation, Distribution, Consumption of data and content is continuing to be in the rise / incline More sellers and creators, its not all about theatrical release, short form is huge and growing Buyers are growing How good is good ? The amount of time it is taking for content prep and compliance – be it airline, new int. markets – technology needs to be able to reduce this, even it is going to impact some of the existing services offerings or rate card line items Sellers working direct with buyers ( IMF as an example ) – less transcode rev. Technology Providers now able to offer the services. Microsoft Azure media Services, S2T Buyers building platforms to control costs and quality and technology used MAM, DAMS – newer ones on the market – Vidispine, Levels Beyond and more…. Built for the cloud vs yes we are in the cloud There will be predators and there will be protectors … seen it in film scanning, seen it in new packages like UV, DPP, IMF
- #5: Things have changed for sure
- #7: There are the incumbents just like every industry, protecting existing market share, customers and revenue Then there are the predators looking for some of the existing market share or to create new market share There will be new platforms and systems and providers in the market place in the next 12-18 months.. There have been some great new entrants or great new technology in this space in recent years… Sfera did some great things early with the Cloud and AWS changing how things were done so much so seems many providers used them.. Now they are part of Deluxe – kudos to Morgan Fumi and team .. Zoo Digital is also another great one that at every NAB or IBC they have new versions of software, they want to push the envelope.. Maybe the future providers are the platforms doing it for themselves.. As long as there is the high dependency on human capital to get this work done then anyone can have a crack at it … these people tend to be free to work for whomever.. Maybe the future is every resource doing captioning etc has their own ID that goes with their content and the future is a open marketplace where jobs are issued and bid on.. So in 2018 who will have the control on how this work gets done? Will it be the same as it is now.. ??
- #8: To finish on a light note hopefully, we spent time looking at example of where this technology might not be ready for all use cases. Came across this .. Not that service providers in the room use public internet services to translate but look what can happen if you just keep feeding the machine
- #9: There are plenty or articles, blogs and opinions out there Data points seems to becoming more frequent Improvements are gaining velocity Body text: The latest on speech recognition - By David Ward http://thejcr.com/2016/11/29/the-latest-on-speech-recognition/
- #10: Some of you in this room were part of the EU paper – our review of it and we also asked many people to read and give their view is – not ready for prime time don’t stop everything you have already done But its moving at such a pace in the right direction. You just need to decide when you are going to start using or working with this technology and to what extend. Its also ok to sit and wait Body text: http://www.lrec-conf.org/proceedings/lrec2014/pdf/463_Paper.pdf
- #11: What are we looking to do leveraging Cloud and Machine Learning services How can we use technology to connect data easier Reduce time, cost Sustain Quality or Improve Quality Give more control ( when it is wanted ) Context set – while a number of our team come from the M&E space, much of our focus is outside of M&E also. WHAT WE HAVE LOOKED AT We have looked outside M&E at some industries that are bigger in spend but also are facing huge growth in video and content – this data type is pretty new for them unlike M&E Law Enforcement, Public Safety, Govt and Healthcare, Fin Tech Some of the initial areas we are looking at and testing with companies in the M&E space – Content Creators or Buyers / Service Providers Compliance – object, word, content – safety = saves time, and cost tied to failed checked with broadcasters, Leverage the speech to text – to improve search and rec engines and ad insertion for digital properties .. We are seeing interest to look at this tech for lower tier content not movies but talking head shows and news What we are doing – How We are working with a range of technologies some our own IP, ( open sourced ) and platforms which can leverage technology around ML,DL, Cognitive and AI to start – in sometimes very small ways to make a dent in some of these 4 key areas There seems to be a good amount of conversation around S2T and then translation and language detection.. What is interesting is there are large companies out there working on things tied to the M&E but aren’t in the usual top 5-6 localization vendors