If you're a data scientist or you work with machine learning (ML) models, you have tools to label data, technology environments to train models, and a fundamental understanding of MLops and modelops. If you have ML models running in production, you probably use ML monitoring to identify data drift and other model risks. Data science teams use these essential ML practices and platforms to collaborate on model development, to configure infrastructure, to deploy ML models to different environments, and to maintain models at scale. Others who are seeking to increase the number of models in production, improve the quality of predictions, and reduce the costs in ML model maintenance will likely need these ML life cycle management tools, too. It's all technical jargon to leaders who want to understand the return on investment and business impact of machine learning and artificial intelligence investments and would prefer staying out of the technical and operational weeds.

The findings also reveal European executives see investing in cloud and AI as becoming central to CX strategy. Providing personalised support as part of an excellent CX is more than ever the goal for all companies. With digital channels now critically important, technology is key to remaining forefront of delivering the best CX. The results come from the third edition of the research, which surveyed 1,035 business executives across five major European markets. The survey highlights the trends and evolution in the market, which will be published across three eBooks, analysing: How AI is changing European contact centres, the Natural Language Processing (NLP) challenges in the contact centre industry, and ways contact centres can improve CX using AI.

I'm a musician and serial entrepreneur, was trained as classical pianist, and studied for a master's in music and philosophy. As a business executive, I have over 20 years of experience, leading several innovations from inception and product strategy to development and product management, to commercialization in global markets. My track record includes closing successful deals with global vendors, mobile operators, and content companies, as well as winning global awards and prizes. Across the past five years, Amit Sternberg has been driving innovation around music, health and technology. Sternberg's newest company, Rubato, is currently in its seed stage.

The World Artificial Intelligence Conference, or WAIC, will open in Shanghai tomorrow. The World Artificial Intelligence Conference, or WAIC, China's top AI event, will open on Thursday, with leading business executives participating and new tech innovations and products making debut. As the first batch of restarted exhibitions and conferences in Shanghai following the lift of the city's COVID-19 lockdown in June, the three-day WAIC 2022 will see strict pandemic prevention measures in place. As a result, many events will be held online with metaverse innovations. Scientists and business executives, including Huawei's rotating chairman Ken Hu and Qualcomm president and CEO Cristiano Amon, will attend the opening session tomorrow morning.

Artificial Intelligence (AI) and machine learning (ML) have been hot topics the last few years, and for a good reason. With AI, we can do previously impossible or costly to do things. Artificial intelligence is also benefiting businesses by automating processes, saving time and money, and improving customer experiences. But what every business leader must know about AI and ML? AI is already playing an important role in our lives, but it is just the beginning. It has the potential to change how we work, teach, live and interact with others.

All the sessions from Transform 2021 are available on-demand now. That motivational speech a coach or business executive gives you might one day soon be generated by an AI assistant alongside other bits of timely advice and insight. SportsBettingDime, in collaboration with research lab OpenAI, has been experimenting with AI in the form of a GPT-3 text editor to emulate a coach that provides both play-calling advice and motivational speeches based on the situation a team is currently facing. GPT-3 is an AI language model developed by OpenAI that employs a Transformer model to create content in any voice, style, or tone by leveraging assets freely available on the internet. The basic idea is to aggregate play calls made by other head coaches facing similar situations alongside all the best motivational speeches ever given by head coaches.

For chief data officers and data scientists, the business case for DataOps can be obvious. DataOps, correctly done, can streamline data workflows, reduce errors, and offers transparency to the entire data operations. It improves efficiency, increases data trust, and gives more time to do analysis. For business executives, such benefits are not immediately apparent. So, getting the budget to build your DataOps can run into snags -- right up until a business problem challenges your company's core value proposition. That's what happened for Screenrights.

Machine Learning is providing solutions for many existing problems in any domain. It is also helping to increase the profit in that specific domain. Machine Learning is going to play a significant role in all areas in the future. Many of us have heard that Machine Learning plays a fantastic role in business. But many of us do not know the role of machine learning in business and marketing.

Whilst UK business executives are increasingly interested in investing in AI, with over 80% thinking AI would add value now and in the future, 4 in 5 respondents recognise that there is a lack of knowledge in their organisations when it comes to understanding different AI technologies. This is a key finding from the latest research conducted by Odigo and Davies Hickman Partners with a UK sample of 205 business executives across different sectors in 2020. Odigo, a Capgemini brand formerly known as Prosodie-Capgemini, helps large organisations connect with individuals through world-class, cloud-based contact centre solutions. Its cutting-edge, proprietary technologies enable a seamless, efficient, omnichannel experience for its customers and a satisfying, engaging experience for service agents. Odigo serves more than 400,000 agents and business users globally.

Recent surveys, studies, forecasts and other quantitative assessments of the progress and impact of AI highlight the precarious nature of the future of work (long after the coronavirus pandemic ends), the continuing mixed attitudes of consumers about data privacy, and the possible resilience of this year's investments in AI. The IT department's need for AI talent has tripled between 2015 and 2019, but the number of AI jobs posted by IT is still less than half of that stemming from other business units; departments recruiting AI talent in high volumes include marketing, sales, customer service, finance, and research and development. By 2025, at least two of the top 10 global retailers will establish robot resource organizations to manage nonhuman workers; 77% of retailers plan to deploy AI by 2021, with the deployment of robotics for warehouse picking as the No. 1 use case [Gartner] By 2024, AI, virtual personal assistants, and chatbots will replace almost 69% of the manager's workload [Gartner] "Supervised machine learning doesn't live up to the hype. It isn't actual artificial intelligence akin to C-3PO, it's a sophisticated pattern-matching tool… Rather than seeing exponential improvements in the quality of AI performance (a la Moore's Law), we're instead seeing exponential increases in the cost to improve AI systems"--Stefan Seltz-Axmacher, founder, Starsky Robotics "…why are we holding our hands behind our back trying to build AI without mechanisms that infants have?"--Gary "We haven't really gone to great depth with deep learning yet. We've had a limited amount of training data so far. We've had limited structures with limited compute power. But the key point is that deep learning learns the concept, it learns the features. "…such capabilities [as "deepfake" transformation of the human face] were called image processing 15 years ago, but are routinely termed AI today.