OpenAI is fighting lawsuits from artists, writers, and publishers who allege it inappropriately used their work to train the algorithms behind ChatGPT and other AI systems. On Tuesday the company announced a tool apparently designed to appease creatives and rights holders, by granting them some control over how OpenAI uses their work. The company says it will launch a tool in 2025 called Media Manager that allows content creators to opt out their work from the company's AI development. In a blog post, OpenAI described the tool as a way to allow "creators and content owners to tell us what they own" and specify "how they want their works to be included or excluded from machine learning research and training." OpenAI said that it is working with "creators, content owners, and regulators" to develop the tool and intends it to "set an industry standard."

Generative language models produce highly abstractive outputs by design, in contrast to extractive responses in search engines. Given this characteristic of LLMs and the resulting implications for content Licensing & Attribution, we propose the the so-called Extractive-Abstractive axis for benchmarking generative models and highlight the need for developing corresponding metrics, datasets and annotation guidelines. We limit our discussion to the text modality.

Sen. Marsha Blackburn, R-Tenn., shares her takeaways from Tuesday's AI hearing with OpenAI CEO Sam Altman. She also reveals what next steps she and her colleagues are prepared to take to protect consumer data amid the AI boom. EXCLUSIVE: Nashville musicians are increasingly worried about complications with artificial intelligence's growing sophistication that could threaten their livelihood, Sen. Marsha Blackburn, R-Tenn., warned this week. "We met with the Nashville Technology Council a couple of weeks ago, and we have talked with so many of the musicians. They're concerned that using AI, they will do a copycat of their voice and take the lyrics of their song, which you can get on ChatGPT," Blackburn told Fox News Digital during an interview in her Senate office.

Netflix's Korean drama "Squid Game" was one of the most-watched dubbed series of all time, proving the massive potential for foreign-language programming to become a hit in overseas markets. Now, a startup called Deepdub is capitalizing on the growing demand for localized content by automating parts of the dubbing process using AI technology. With its end-to-end platform, Deepdub can decrease the time it takes to complete a dubbing project, allowing content owners and studios to have results in weeks instead of months. What's more, it does this by using just a few minutes of the actors' voices -- so the dubbed version sounds more like the original. The Tel Aviv startup has now closed on $20 million in Series A funding for its efforts, led by New York-based investment firm Insight Partners.

If 2020 was a banner year for any business, that would undoubtedly be OTT. The global lockdown induced an unprecedented surge in OTT viewership resulting in a meteoric growth of subscribers, revenue, and investments into content creation/acquisition. While the heightened interest has been primarily Covid-led, it's improbable the patronage will subside once the pandemic ends. Audience habits around content consumption have changed forever. OTT businesses struggled to find content to retain the newly acquired and hungry for content eyeballs, with the slowdown of traditional film and show production due to social distancing and lockdown.

Amagi, which deals in cloud-based technology for media processing, has announced the launch of Tornado, a machine learning-based content preparation service that enables TV networks and content owners to scale their operations, accelerate broadcast workflows, generate new revenues and reduce operational costs. Tornado is a first-of-its-kind, cloud-based machine learning-augmented content preparation suite that tackles content preparation challenges head-on. Amagi Tornado is conceptualised as a suite of machine learning-based content preparation services that dynamically evolves as machines learn more about each segment of a video asset as they process higher volumes of content. Tornado can cater to the unique preparation needs of TV networks, content owners, vMVPD platforms, and digital-first networks with the company planning to continually expand the suite functionality and capabilities to optimise the entire broadcast workflow. Factory-scale VOD segment creation: Linear broadcast model is highly reliant on sophisticated processing of video for ad break points identification, credits, color bars and blacks.

Amagi, a global leader in cloud-based technology for media processing, today announced the launch of TORNADO, a machine learning-based content preparation service that enables TV networks and content owners to scale their operations, accelerate broadcast workflows, generate new revenues and reduce operational costs. Compared to traditional manual content preparation, Amagi TORNADO is nearly six times more efficient, allowing broadcasters free up capital and streamline workflows. Over the last three years, the broadcast industry has had to evolve significantly due to a rise in multi-screen content consumption, demands for "here and now" content and a shift in how consumers are viewing content as more consumers move from cable to OTT services. In such an evolving scenario, TV networks, content owners, and digital-first networks are creatively trying to grab a piece of the action by trying new mediums and delivery methods to provide better experiences to consumers while streamlining costs and operations. However, despite these efforts, content preparation continues to require pain-staking hours of manual work and massive overhead costs.

One of the most interesting trends we've seen in 2017 is the spread of artificial intelligence into areas like marketing and security. Is this set to continue into next year, and are there new fields where AI is set to make a significant impact? Here are the views of some industry experts. AI isn't yet ready to go mainstream, but more businesses will be laying the ground work to use it in future, says Couchbase SVP of engineering and CTO Ravi Mayuram. "Today AI is more of a trendy buzzword than practical reality, and it's difficult to execute because AI is only as good as its data. While data integrity still varies within the enterprise, true implementation of AI is still a concept that will not come to fruition for a few years. However, we've seen early stages of machine learning applications in verticals such as advertising and retail. In the years ahead, we'll see more industries, including industrial IoT, digital health and digital finance, begin taking advantage of machine learning within applications to provide more meaningful user experiences. Throughout this transformation, the database will play an instrumental role by accommodating rapidly-changing data at scale while keeping big data sets reliable and secure."

Future Decoded is a conference for customers and partners of the tech giant which was held in London over two days at the start of this month. Discussions about the potential of artificial intelligence (AI) were much in evidence. Microsoft's approach to AI is as a service delivered from its Azure cloud delivered through a network of large scale data centres and smaller edge based technologies. Also on the agenda was Microsoft's Quantum Computing software programme development which uses what is known as Topological Qubits code, described as "a robust type of quantum bit that Microsoft believes will serve as the basis for a scalable, general purpose quantum computer system." Microsoft plans to release Quantum Computing developer code before then end of the year.

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