In past few years, business process automation vendors have been tasked by business verticals to challenges which caused these vendors to innovate around automation, integration with virtualization and ease of deployment & customization at challenging costs. This improved the way these businesses cater to their customers, and thus raising the bar for time and cost to market. As a result of these changes, traditional businesses are seeking to transform too in order to not only stay alive but thrive. Disruptive technologies are causing increased and intelligent digital footprints for enterprises, enabling them innovative ways to impart value to customers. IPA (a set of RPA, BPM and AI tools) has emerged from the application boundaries of back office to facilitate enterprises convert into efficient and adaptive operating selves and deliver seamless experiences for customers and employees.

Following two action-packed days of workshops, conferences, paper presentations, and tech talks, Machine Learning Developers Summit 2023 concluded by awarding 40 dynamic data scientists with the 40 Under 40 Data Scientists award. Aakash is a seasoned analytics leader with 15 years experience and has been instrumental in driving data and insight-led transformations. Over his career, he has worked closely with biz functions to drive revenue and achieve aggressive market growth by leveraging more than 50 analytical approaches. He also has experience in launching AI and tech-based solutions like Omni Channel Attribution, Customer Segmentation, Customer-360, Supply Chain Efficiency, Workforce Management and more at telecom, media, FMCG, retail, and ecommerce industries. Abhilash Surendran is assistant vice president, analytics, and data science at Merkle, leading the analytics practise for their high-tech portfolio. He comes with 15 years of experience in advanced analytics, data science, data visualisation and consulting.

In the last decade, advanced approaches to the analysis and exploitation of large amounts of heterogeneous data ("big data") have gained tremendous attention, particularly on the part of corporate decision-makers but also from academic researchers [1, 2, 3]. The term "advanced analytics" generally refers to various methods beyond traditional multivariate statistics, mainly from the field of machine learning (ML), that leverage big data to drive decisions and actions (e.g., in organizations) [4, 5, 1, 6]. While researchers started to emphasize the suitability of these approaches mostly for (i) the design of innovative artifacts (e.g., decision support or process automation systems) and (ii) the induction of knowledge from quantitative studies [7, 1, 8, 9], companies increasingly deploy analytics applications in order to exploit their promising business potential [4, 6]. Several research articles show that such applications--especially those driven by modern ML algorithms--may considerably improve efficiency and/or effectiveness in important business areas, such as predictive maintenance, financial fraud detection, capacity planning, and product recommendation [10, 11, 12, 13, 14, 15, 16, 17]. The average return on investment of modern data analytics applications in a business context is estimated at an almost inconceivable rate of 1,301% [18].

Having just wrapped up a successful ODSC Europe, we're now turning our attention to ODSC West 2022 and we couldn't be more excited to announce our first group of speakers. These innovators and experts have helped shape the fields of data science and AI into what we have today, and will continue to do so in the years to come. You can find a full list of our currently confirmed ODSC West speakers here, and a sneak peek of just a few of them (and their session topics) below. In recent years, the fields of NLP, robotics, and computer vision, among others, have seen significant advancement thanks to Self-supervised and Unsupervised learning techniques. This session will provide hands-on examples of how you can apply large language models and transformers to zero-shot and few-shot learning in NLP applications.

Analytics encompasses many skills and disciplines. Identifying the problem, choosing the modeling approach, selecting the correct features to model, and evaluating the result are at the heart of analytics. The tendency, however, is to focus primarily on the technology rather than the process. Join us for a problem-focused, applied experience where you learn to apply the analytics process to produce meaningful and valuable insights.

We're getting Prabakaran Chandran on board to lead an interactive DataHour session with us. He has been working with Mu Sigma, a prestigious company as a Data and Decision Scientist that specializes in problem-solving, since 2019. He is skilled in SQL, Python, R, Advanced Analytics, and Statistics. In the fields of computer vision, natural language processing, and deep learning, he worked with a team of two people to develop AI-based solutions for Fortune 500 companies. He will be explaining Causal Inference and demonstrate how it may be applied to a specific use case in Python.

Global audit, consulting, risk management, and financial advisory services provider Deloitte has partnered with the Indian Institute of Technology (IIT) Roorkee to offer its students fellowships in artificial intelligence (AI) and advanced analytics. This new strategic partnership between the two institutions will considerably help IIT Roorkee students gain a better industry experience through work-study programs. The artificial intelligence and machine learning (ML) immersion fellowship programs are specifically developed to build the future generation workforce. Prof. Ajit K. Chaturvedi, Director, IIT Roorkee, said, "The coming together of IIT Roorkee and Deloitte will create new opportunities for both of us. In fact, this partnership has the potential to strengthen the AI roadmap of India."

Artificial intelligence (AI) adoption has been largely accepted in the legal community, as many have realized the value of technology that can detect relevant content and produce better outcomes. Incorporating AI into document review workflows or using insights to inform case strategy is transformative and drives better results. From government requests to civil litigation and internal investigations, high profile and fast-moving matters require efficient processes. Deploying technology strategically will help teams to identity key documents and themes early in the case and manage the assessment and review of data efficiently. The continued evolution of AI tools, such as the ability to detect conduct and behavior through sentiment analysis and pattern processing, will further assist with investigatory compliance but can also be used proactively.

Lawyers were quick to refute the possibility that machine learning and classification of documents could potentially offer a defensible solution …

It's a frustrating problem, given that it's so easy to solve. Those who embrace modern technology are already optimizing their inventory with advanced analytics, entirely preventing these massive amounts of overstock. So, if a retailer is wondering why consumers and investors are pulling away, it's because they are still using a traditional approach in a modern world. Whether it's fast fashion or high-end brands, at the end of the day, the goal of a business is to maximize shareholder value. As such, retailers can't afford to risk losing sales because they ran out of stock.