It’s fair to say that this past year we’ve been up, down and all around. Literally overnight lives changed drastically and for the first time we were living through the kind of global pandemic that we’d only read about in history books. I think we can all agree that we’re living in unprecedented times. That said, despite the extremely low lows of 2020 there were also some silver linings. With international lockdown and increasing work from home orders, many families were reunited, pollution rates steadily dwindled, digitization peaked, the season of innovation flourished.. and hey we were also graced with free balcony concerts from across the globe!
The initial euphoria over AL/ML seems to have died down in the M&E industry. Our research shows that many M&E players have run AI initiatives with different vendors but have not achieved anything substantial enough to solve their business problems. Though the demo was impressive, the project hit a wall at the Proof of Concept (PoC) stage because the AI solution did not work for their content! When the cycle was repeated with multiple vendors, they concluded that AI models are not available or mature enough to solve specific M&E business challenges.
Artificial Intelligence (AI) and Machine Learning (ML) are technologies that enterprises across industries have been keenly experimenting with to explore the utility they can bring. Is there AI adoption within the M&E industry? Enterprises are seeking automation and can AI be the solution? Have we cracked the AI code or do we have miles to go? If automation is a goal, it should be a priority even at the current times.
axle ai is showing how its radically simple browser interface lets your distributed teams search and manage Qumulo scale-out volumes with real-time updates
Today, the media landscape encompasses thousands of modes of communicating information at lightning speeds — from the smartphone to the smartwatch, to interactive adverts on streets and in cities. There are, in fact, so many outlets to disperse information that businesses, companies, and corporations are struggling to stay present with the ever-changing information technologies.
Human Decision Making: When Do We Use Confidence Levels?Confidence levels can be used anytime one is estimating or predicting something. Examples include: business, engineering, medicine, technology…or just day-to-day life. As humans we use confidence levels regularly. Whether you decide to dodge an aisle at the grocery store because you thought you saw your chatty neighbor, or using evidence and intuition to convict a suspected criminal during jury duty, your mind is in a constant state of perceiving its surroundings. It makes decisions based on those perceptions via an inherent estimate of confidence.
The Multimodal Approach: Explained “Our intuition tells us that our senses are separate streams of information. We see with our eyes, hear with our ears, feel with our skin, smell with our nose, taste with our tongue. In actuality, though, the brain uses the imperfect information from each sense to generate a virtual reality that we call consciousness. It’s our brain’s best guess as to what’s out there in the world. But that best guess isn’t always right.” - Dr. David Ludden Ph.D.
AI promises immediate benefits to media workflows, but do you have the right playbook? The exponential growth of content to be acquired, managed, produced and monetized remains a challenge in an industry where demanding audiences constantly crave fresh and customized content. Artificial Intelligence has broken into this scene promising great results. Enabling process automation, deep data analysis, contextual insights and smart recommendations thanks to combinations of cognitives services. But not all is rosy...