AI in Entertainment

27 Aug 2020

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With the emergence of various innovative technologies, filmmakers are effectively saving time and money by automating their film creation process to a large extent. Filmmakers are utilizing AI in various stages of filmmaking, right from pre-production, production to the post-production stage.

Cinelytic, Los Angeles based startup, has developed AI software for filmmakers to predict the probability of a movie's success based on the casting of actors/actresses. If the filmmaker is unsure of which actor to cast for a role, he can enter their names into the program and see which actor might

Belgium based ScriptBook, has developed an AI cloud-based software Script2Screen to analyse the script and predict box office success or failure. The user can upload their screenplay on the platform which generates an AI-based assessment indicating the commercial and critical success of a project, along with insights on the storyline, target demographics, market positioning, distribution parameters etc.

Vault ML, an Israeli startup, launched an artificial intelligence platform 4CAST. It uses over 40 years of box office data, 4 lac plus movie scripts and numerous other film data to predict opening weekend box office sales. Its predictions are right 75 % of the time and thus it helps filmmakers in their business risk management.

On the other hand, 20th Century Fox has launched the AI/ML program Merlin to help review trailers before they are released. The AI program optimises the marketing and distribution efforts in order to generate wider publicity for the specific movie or web series. It predicts and recommends appealing clips and flags them as the parts of the trailer which the audience will enjoy the most.

Similarly, Microsoft has developed an AI speech translation engine Azure for dubbing Hindi movies into different languages. On this platform, Bollywood movies are dubbed with the help of AI in different languages.

Looking at the fact that there is a plethora of data available in the film ecosystem, many companies are coming up with innovative solutions where these softwares read the historical data about movie performances over the years, then cross-references it with the current information and thus helps in writing scripts, simplifying the production process, casting actors, composing music, editing movies, plan marketing and distribution and calculate the return of investment.

Credits : Akhil Handa

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Balancing control and flexibility a FinTech Startup would want to offer

FinTech startups will have a very fine line between moving from the old school way and the trust factor. Banks are now moving towards the path of digital transformations and bringing in new technologies with the intent on building leaner, faster, cheaper products than traditional banks. Brands have been created to be approachable and emotionally engaging, differing from the more traditional bank’s approach that Indian customer base is used to.
Customers does not want opaque financial institutions, rather they like customized services, more transparency, more mobility, flexible banking, lower fees and faster transactions. And now customers are spoilt with choices in the market.
But the challenge as this evolves is how you stand out, while gaining people’s trust. People have to be able to remember your name and who you are, but also trust you with their money.
1.Keep it simple and clean:
Now that it’s a new change to adapt, it should not be jargon. People need to understand clearly who you are, what you offer and why they should care. You need to be quick and simple to understand
2.Know Your Customer:
Understanding your customer, designing and delivering the value that matters most to customers is the key for the success of your product. In case of a diverse mass customer base, you can quickly get a ‘map’ of your audience’s life and world, and make sure all product decisions, features and communications are guided towards fitting in easily there.
3. Right attention to touch points: Small touches of delight you add, on top of the basics, make your experience more memorable and, thereby, more sticky. Building stickiness or virality into the design of your products and onboarding experience has more power than any amount of content marketing.
4.Nurturing partnerships:
As more technology companies spring up, covering a wide base of offers, becoming the preferred partner in your category is essential. This means cultivating a community and partnership strategy as soon as possible in your lifecycle
As the competition for banking services intensifies, FinTech startups will have to take more bold steps to set themselves apart in the market. Agile, fast, and focused execution are quintessential for success.

credits : Akhil Handa


Dear Reader,
From Amazon Alexa to Siri, Artificial Intelligence (AI) has gained serious footholds in our personal lives. However, when it comes to IT operations platforms, AI and Machine Learning technologies are still in the nascent stages.
Incidentally, the forces of digital business transformation are necessitating a change to traditional IT management techniques. Hence, advanced approach to IT-Ops, also known as AI-Ops (Artificial Intelligence for IT Operations) is being developed, which combines algorithmic and human intelligence to provide full visibility into the state and performance of the IT systems.
AI-Ops bridge three different IT disciplines - service management, performance management and automation - to accomplish its goals of continuous insights and improvements. Gartner predicts that the use of AI-Ops by large enterprises to monitor applications and infrastructure will rise from 5% in 2018 to 30% by 2023.
In this reference, SysTrack has developed AI-Ops-based platform which incorporates natural language processing (NLP) and AI-driven sentiment scoring. The integration of NLP powers an easy-to-use search function that enables the IT Team to gain holistic idea about their environment. Through integrations with AI-Ops platforms, including IBM Operations Analytics – Predictive Insights, the platform provides a detailed real-time and historical endpoint data that IT operations need to execute AIOps use cases, including proactive monitoring. The NLP engine, allows IT to type or speak questions about their environment in plain English and return suggested answers for accelerated root cause analysis.
Multiple financial institutions are also incorporating AI-Ops in their business functions. For instance, US Bank is leveraging AI-Ops to increase automation across the business lines by analyzing large, monitoring-driven data sets. With the help of AI-Ops, US Bank envisions that the query and complaint resolution will be more effective, delivering better up time and improving customer experience.
Similarly, Similarly, Barclays Bank is using AI-Ops platform through AI and machine learning to analyse end-to-end analysis of IT infrastructure based on various monitoring tools to pull together the required information in order to deliver the best user experience.
As machine-learning systems become more accurate and reliable, routine and well-understood actions can be triggered without human intervention, potentially resolving issues before users are impacted or even become aware of any problem.
Credits : Akhil Handa Manish Kulkarni

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