Image Recognition: Artificial Intelligence Is The Secret Sauce

Overcast MAX #4: Max Recognition

AI image recognition is one of the new-fangled terms being bandied around. So, what does it mean and what can it do for you?

In today’s media landscape, there’s a vast volume of unstructured content that organisations are trying to manage. Let’s face it, we’ve all been there: spending hours searching through content for an outstanding soundbite or a stunning shot that we know we filmed but, alas, it eludes us. 

Max Recognition

[Drum roll, please] Ladies and gentlemen, welcome Max Recognition. Not only will it save you time, it will also rescue you from frustration. 

Max Recognition uses the latest AI (artificial intelligence) and Machine Learning to identify people, objects, places, and events in videos and images. It’s like magic! Take a bow, Max!

Image recognition case studies

TV Broadcasters

Television broadcasters, by their nature, create huge amounts of content. But they are subject to strict broadcasting guidelines in relation to sensitive content. 

The traditional method of identifying such content was for people to painstakingly view hours and hours of tapes. But now, broadcasters can save hundreds if not thousands of hours a year by automating this moderation of inappropriate content using image recognition. 

Online marketplaces

An online marketplace is a website or mobile application that connects buyers and sellers. Its success depends on adeptly assessing the suitability or compatibility of those traders in order to match them up. 

For example, an influencer marketplace could use object and scene detection to segment its influencers based on what media they publish alongside their social media posts.

Benefits of Max Recognition

Automation

The great news is that you don’t have to input anything manually. That’s because your content is automatically identifiable and searchable.

Multiple use cases

Max Recognition empowers you to find what you need quickly and accurately; for example, identifying a celebrity, providing health analysis, finding sensitive data, enriching metadata or accessing events.

Big Data accessibility

We’re all creating and amassing a lot more content that is possible to consume. As a result, we’re building up archives of material. Max Recognition allows you to log and manage your archive effectively.

Get in touch

Image recognition is one of nine Overcast MAX products that facilitate easy video collaboration. If you’d like to learn more about this fantastic suite of solutions, please contact Philippe on info@overcasthq.com or click here to get in touch

Cloud Storage: How To Stop Paying Ridiculous Margins

Overcast MAX #2: Max Storage

Why use video?

The popularity of video consumption continues to explode and not just for marketing or brand building purposes. Video can also be used in-house for employee training and dissemination of information — this is even more valid in the current era of enforced remote working. 

The possibilities that video offers your business are endless: connecting with your audience through live streaming, creating interactive videos to engage your followers, explainer videos/tutorials, product demonstrations, communicating with stakeholders, promotional videos, broadcasting live events, vlogging and much more.

Size matters

Video files are large — but how big is big? 

  • 1 bit (b) = only capable of storing a single binary digit: either a 1 or 0.
  • 1 byte (B) = 8 bits … about what you need to store a single character of text. 
  • 1 kilobyte (KB) = 1,024 bytes … it takes around 10 KB to store a single page of plain text.
  • 1 megabyte (MB) = 1,024 KB … the equivalent of a 400-page book.
  • 1 gigabyte (GB) = 1,024 MB … streaming Netflix Ultra HD video uses about 7 GB per hour.
  • 1 terabyte (TB) = 1,024 GB … equivalent to 500 hours worth of movies.
  • 1 petabyte (PB) = 1,024 TB … one year of CCTV video for an average police department amounts to 1.5 PB.
  • 1 exabyte (EB) = 1,024 PB … 5 EB is equivalent to all the words ever spoken by humankind.

How To Geek

So, the more videos you create, the more storage you’ll need (although you don’t need to worry about exabytes unless you are Amazon, Google or Facebook).

Max Storage

In light of these unwieldy sizes of video files, the traditional method of handling them on premise is no longer viable. So, if you want to make your teams’ video management and collaboration much more efficient, you can either manage your workflows in the cloud or use a hybrid solution that conforms to your workflows.

Benefits of Max Storage

Cost Optimisation

As we mentioned in an earlier blog post outlining Overcast MAX, Max Storage is like a BYOB (bring your own bottle) party. BYO Storage means you keep your unique account with AWS and our software will help you to manage your content! 

Our hybrid solutions will sync with your on-premise servers: you can automatically upload your content to your account and be guaranteed secure cloud workflows.

Intelligent tiering also allows you optimise your costs based on your user actual activities, so you’ll save oodles of spondoolicks!

Metadata Enrichment

Artificial intelligence is the new sliced bread…although you can’t put chocolate spread on it! 

But you can benefit from AI functions such as Transcribe and Image Recognition to add metadata — this will ensure you can search your content quickly and accurately using time-based parameters.

Future-proofed content

Technology is changing so fast these days that it’s hard to keep up and even harder to future-proof your content. But Max Storage is on the case. We will store your originals and create proxies that can be viewed on any device. 

No problem with codecs either: your content will be available over any network.

Get in touch

If you have any questions about storage, live streaming or any of the Overcast MAX solutions, please do get in touch. Philippe would be happy to chat through your video collaboration and management needs — you can reach him on info@overcasthq.com or you can click here to contact us.

AWS To Showcase AI and ML With Overcast At IBC 2019

IBC 2019 is only a few weeks away and we are delighted to be attending as part of the Amazon Partner Network. Yes, that’s right, we’ll be on AWS booth 5.C80 from 13–17 September in Amsterdam. Click here to read an AWS blog post about the technological advances in video creation and distribution they will be showcasing.

Artificial intelligence and machine learning are changing video workflows. Two of the key innovations that we’ll be highlighting with AWS are: 

  • — Searching video clips for objects, colours, settings, events, words, sounds and facial recognition;
  • — Automating transcription and translation to generate captions, subtitles, and audio in multiple languages for live and on-demand streams.

Why not find out from our CEO Philippe Brodeur at IBC how to make video collaboration effortless? Click here to schedule a meeting.

Artificial Intelligence and Machine Learning = Faster Video Creation?

Can you really use Artificial Intelligence and Machine Learning to create video content faster?

To be honest, the more I hear and read about Artificial Intelligence and Machine Learning the more I think people are trying to pull the wool over my eyes. I honestly don’t believe most people know what they are talking about or what AI and ML actually are. So I set about setting myself a task to define them and then explain why Overcast is investing so much in them.

One of our advisors Hugh O’Byrne (a former senior IBM head of Digital Sales) started by telling me that everyone has actually got it wrong. What most people are talking about is “augmented” intelligence — i.e. they are talking about machines that can help (not replace) humans in the workplace. Machines might be able to learn and get better at doing manual tasks, but ultimately the work being done still needs a guiding human hand so it is augmented.

Understanding AI and ML

So if we keep that in mind, here is how we define AI: “Artificial Intelligence” is the science of making computers good at doing tasks that were previously done by people.

It’s pretty broad and probably covers what so many people claim as their “AI solution”. So, perhaps what is far more interesting is “Machine Learning”, which is a subset of AI and focuses on the ability of computers to use large sets of data to “learn” about a task and improve the performance of those tasks over time.

If you take these two statements for what they are, it’s actually machine learning that is far more interesting and far more powerful. AI has been talked about pretty much since the beginning of computers — but machine learning has only been possible since the introduction of large data sets that can lead to machines being “trained” or, in fact, “training themselves” according to a set of rules.

With video we are at the early stages. Up until now, very little data existed about a video that was not inputted manually. Sure, you could get technical details like length, file size, codec and things like that, but anything descriptive about the story had to be entered manually. That’s the metadata.

It’s all about business needs

Recent advances in AI and machine learning have enabled all of this to change. We can now extract a considerable amount of “descriptive” data that in turn can be used for a number of different content solutions.

A short list of what data we can extract from a video includes:

  • Voice to text
  • Image recognition
  • Scene recognition
  • Facial recognition
  • Sentiment recognition

This is just a short list of the information that can make it easier to do a number of tasks. Caption creation, search, archiving, metadata enhancement and compliance are just a number of tasks that machines are getting better at doing without the need for human intervention.

Ultimately these advances in AI and Machine Learning should help to solve problems for creatives who waste much of their time on mundane tasks like searching for content, wondering if brand guidelines are being adhered to and even putting captions with the right punctuation on their content. You know, real business needs.

The result: yes, AI and Machine Learning can help make video content faster but it takes time for the machines to learn so it is taking time for the accuracy of these solutions to be able to be deployed at scale.

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