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SMNYC 2024: Streaming Learning Center's Jan Ozer Talks AI, Codecs, and Patent Pools

At Streaming Media NYC 2024, Tim Siglin, Founding Executive Director, Help Me Stream Research Foundation, and Contributing Editor, Streaming Media, interviews Jan Ozer, Owner, Streaming Learning Center. Ozer discusses how the Streaming Learning Center has expanded into a platform offering courses on streaming-related topics to help technical people in the industry become familiar with terms, technologies, best practices, and tools. He also talks about machine learning, the shift towards Neural Programming Units (NPUs), and the legal and financial implications of choosing a codec due to potential patent infringements.

What is the Streaming Learning Center?

Siglin asks Ozer to describe the Streaming Learning Center and what it does.

Ozer says that Streaming Learning Center is a blog he started around 13 years ago that contained articles about compression, codecs, and encoding. Then, about five years ago, it began to offer courses in streaming-related topics. “It just helps technical people coming into the industry get familiar with all the terms and technologies and best practices and tools that they need to use to become conversant and effective in their roles, either on the user side or on the builder side,” he says. “So those are my two targets.”

What is the impact of AI on codecs?

Siglin says, “From a builder standpoint, obviously, quite a bit has changed in the last couple of years. For instance, machine learning, which some people call AI, has become more popular, at least from a buzzword standpoint. What's your take on that?”

Ozer says that while machine learning and AI have exploded into the public consciousness since ChatGPT came out, companies that have been in the business for a while, such as Harmonic and Vizioner, have been writing about and using machine learning in their codecs since as early as 2016. “So I think it has been a big part of codec development for a while, primarily in content adaptive technology,” he says. “So the ability to gauge a technology and estimate what bitrate would be necessary to encode it effectively and then [to] only use that bit rate.”

Siglin asks, “So how has it progressed from that 2016 timeframe to now?”

“It’s hard for me to say,” Ozer replies. “The one thing I discovered is that it's impossible to separate the efficiency delivered by AI from the efficiency delivered by other techniques. So everybody's going to say machine learning, or AI, or generative in their spec sheets, but you're never going to be able to tell, is it 5%? Is it 10%? I spoke at a panel on NAB, and I told people to ignore when they see an encoder with AI. If you're evaluating it, evaluate it like any other encoder and gauge its overall effectiveness, not what contribution AI has overall.”

Siglin says, “We've got workflows that have machine learning, but are we seeing a similar scenario where new codecs will say, ‘Look, we've got AI, therefore we're better, or is it strictly AI and the workflow?”

“The whole thing that stops codec deployment is the decode side,” Ozer says. “And there's a huge preference for hardware decode in mobile. There's a necessity for hardware decode in the living room, where all premium content is really targeted. So that's where all the money goes. And it's very challenging to change traditional codecs in a way that makes them incompatible with those decoders. There's a company called Deep Render, and they're building their codec to be decoded on NPUs (Neural Programming Units). And those have been shipping in edge devices since 2015 or 2016. It's interesting because those are general purpose devices, and you can use them for any machine learning, any type of AI on [the] unwinding that you need. It feels like the move is going to be toward them, as opposed to codec-specific silicon. It may be that VVC or even HEVC could be the last dedicated silicon decode-based codec, and we could be moving towards NPUs. A big part of the recent Apple announcement with the M4 chip was 18 TOPS or 36 TOPS NPU unit on the chip. And that can more than handle decode for any of the new codecs that are coming out that are AI-based.”

The legal and financial implications of 2024 codec patent pools

Siglin asks, “Where do we stand in the patent pool space at this point? On the encoding side especially.”

“We are at a huge inflection point,” Ozer says. “Avanti came out with Avanti video pool that is charging royalties based on content. So it's not encoder, it's not decoder, it's encoded bitstreams. There was a recent case in Germany, Broadcom versus Netflix, where the court found Netflix violated Broadcom's patents because they, not encoded, not decoded, but transmitted HEVC encoded Bitstreams within Germany, which is content. So it's content royalties. There's a suit in California where Nokia is suing Amazon for H.264 and H.265 bitstreams, not where they're encoded, not where they decode. And so we've got three or four sources of law that are going to say if you're encoding in a specific format, you're liable to the patent owners for some fee as yet undetermined. So, I think if you look at codec adoption in 2024, I could be the only person who cares about this. Everybody I speak to is either unaware of it or doesn't think it's going to be significant. But I really think before I adopted codecs in 2003, back then you needed to be a codec expert to choose a new one. And even in 2013, or 2018, or 2019, you needed to be a codec expert. Now you need to be a legal expert, a chief financial officer, because you've got to evaluate all these pools and all these lawsuits, and it helps if you know a little bit about encoding.”

Siglin says, “So to the extent that we've mastered encoding as an industry, what we've not mastered is the financial implications of how we choose to encode and the potential legal ramifications.”

“Exactly,” Ozer says.

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