This week, multimodality. Is this a new frontier in Cognitive AI?
Welcome to The Digital Eye, your weekly roundup of the latest technology news.
Our team of experts have scoured the internet for the most exciting and informative articles so that you can stay up-to-date on all things digital, data, blockchain, AI & analytics.
We hope you find this information valuable and would appreciate your help in sharing it with others who may also be interested.
Article by @TDataScience & @prukalpa
5 Trends Driving the New World of Metadata in 2022
These trends have converged to create a storm around a new, modern idea of metadata.
“Last year, we hit some major landmarks in the world of metadata. Gartner scrapped its Magic Quadrant for Metadata Management, companies started asking for third-generation data catalogues, and modern metadata companies (like mine!) launched and raised some serious VC money.
All of this actually prompted me to add metadata as one of my six key data ideas for this year.
But why is metadata such a hot topic in the data world now? What’s behind all of this hype?”
For years, writers, scientists and entrepreneurs have shown us visions of our future relationships with computers and robots.
These vary from the devastation of autonomous robots annihilating us to the marvels of superhuman enhancement in robot suits. While the Terminator and Iron Man concepts push those ideas to the extreme, they highlight a clear choice in our use of technology.
Article by @InsuranceInside
InsurTech Incited appoints Holman as board advisor
UK-based Insurtech Incited has appointed Martyn Holman as an advisor to the board, starting imminently.
“Holman brings considerable leadership experience from past positions including group commercial director at Markerstudy Group and CEO at broker Brightside. He was also previously a director at Marsh.
Incited CEO and founder Nick Turner said: “Martyn has an incredible level of expertise and experience, and we’re excited to have him on our advisory board.
“His appointment, together with the recent bolstering of our leadership team, is testament to our commitment to provide the finest data science platform to our brokers and insurers to help them advance.”
Article by @kdnuggets
How to Successfully Deploy Data Science Projects
This guide will provide detailed insight into the steps you can take to manage your data science projects successfully.
“Creating a data science project requires a combination of strategy and skills. Developing the project is only the initial step, as developers must take meticulous measures to ensure a successful deployment.
Most developers struggle to run the data science model in production successfully. In fact,87% of data science projects never make it to deployment. A poll by KDnuggets also confirmed that around 80% of projects stall before deploying.
Considering this, you need to make sure you take the right approach to deploy your data science model that carries out effective data analysis for business intelligence. This guide will provide detailed insight into the steps you can take to successfully manage your data science projects.”
This post discusses three critical types of XAI: interpretable AI, transparent AI, and interactable AI. During my time in AI, I’ve found more practicality out of these three than any others. In this post, I give an overview and example of each.
Artificial Intelligence (AI) surrounds many aspects of our lives.
We interact with many applications that AI has influenced in our day-to-day lives. There’s a chance an AI recommended this medium article for you to read about AI. It’s powerful, and there is no denying the impact these intelligent algorithms have on our society. But, for every success, it seems like there are twice as many failures by misuse or misunderstanding of how an algorithm was working.
Article by @TDataScience
Written in collaboration with Vasudev Lal and the Cognitive AI team at Intel Labs.
“An exciting frontier in Cognitive AI involves building systems that can integrate multiple modalities and synthesize the meaning of language, images, video, audio and structured knowledge sources such as relation graphs.
Adaptive applications like conversational AI; video and image search using language; autonomous robots and drones; and AI multimodal assistants will require systems that can interact with the world using all available modalities and respond appropriately within specific contexts. In this blog, we will introduce the concept of multimodal learning along with some of its main use cases, and discuss the progress made at Intel Labs towards creating of robust multimodal reasoning systems.”