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Siemens recently announced an expansion of its Industrial Assistant, introducing an advanced maintenance solution based on generative AI. This tool, called "Siemens Industrial Assistant," aims to help customers leverage generative AI across the entire value chain, from design and planning to engineering, operations, and service. The assistant notably supports engineering teams in generating Programmable Logic Controller (PLC) code in their native languages. This process is estimated to increase SCL code generation speed by 60%, while simultaneously reducing errors and lowering reliance on specialized expertise. This innovation...

The global application of Artificial Intelligence (AI) in the real estate market is rapidly expanding, projected to reach $180.345 billion by 2030, with a compound annual growth rate of 35%. This market's rapid growth is driven by advancements in machine learning, predictive analytics, and the increasing demand for automation in property management. Key players in this market include Zillow Group, Compass, Redfin Corporation, and Reonomy, leveraging AI-powered tools to enhance customer experience.

H2O.ai recently announced the launch of its new multi-agent platform h2oGPTe, which combines generative and predictive AI models to provide businesses with more consistent responses. Sri Ambati, founder and CEO of H2O.ai, stated that a major demand from enterprises for AI agents is to maintain response consistency. The h2oGPTe platform utilizes H2O.ai's proprietary models Mississippi and Danube, while also allowing access to other models.

At the main forum of the 2024 Inclusion Bund Conference, Michael Jordan emphasized three key points missing from the current discussions on artificial intelligence: collectivity, uncertainty, and incentive mechanisms. He pointed out that AI systems need to form collaborative collectives and introduce an economic perspective on incentives to build collaborative systems. He noted that AI performs inadequately when facing uncertainty and that humanity's ability to cope with uncertainty through collective collaboration is worth emulating. To enhance the collective collaboration capability of AI systems, Michael Jordan suggested constructing a 'three-layer data market' model.

PepsiCo's Chief Operating Officer Greg Lyon recently stated that the changes the company has experienced in the past three years are greater than in the previous 31 years he has worked there. This shift is largely driven by a significant change in consumer shopping habits, particularly after the pandemic, with people increasingly leaning towards online purchases of food and beverages.

Recently, General Motors (GM) announced the suspension of production for the Cruise Origin autonomous taxi. According to a report by The New York Times, GM has decided to shift its focus to the already in-use Chevrolet Bolt EV, with a modified version set to be launched next year.Image source: Generated by AI, image licensed through Midjourney Regarding this decision, GM CEO Mary Barra stated in a letter to shareholders that the design of the Cruise Origin led to "regulatory uncertainty." The ve

In this era of rapid advancement in artificial intelligence, how machines understand and "see" the world has remained a hot topic of research among scientists. Recently, a study published in the journal Nature Machine Intelligence has unveiled a novel approach—utilizing visual predictive coding to autonomously construct cognitive maps. This breakthrough is not only significant in the field of AI but also deepens our understanding of how machines simulate human visual perception. Within the brai

Siemens has introduced generative AI capabilities in its Senseye predictive maintenance service, enabling a transition to prescriptive maintenance. The new features make predictive maintenance more intuitive and efficient through a conversational interface, helping users gain deeper insights into machines and systems. Generative AI, combined with machine learning and human insights, enhances service levels, supports digital transformation, and optimizes resources to increase productivity. The new features streamline decision-making processes, making them faster and more efficient, assisting customers in addressing skill shortages and achieving critical milestones.

Michael Jordan believes that current large models still need to improve in quantifying uncertainty and providing measures of certainty in predictions. Large models also lack a healthy economic incentive structure to trace and reward those who provide answers. Michael Jordan had two epiphanies in his career, one in statistics and the other in microeconomics, which influenced his expectations for large models. He believes that solving social problems requires considering issues from a systemic and collective perspective, not just enhancing individual models. Governments and foundations should not only support large corporations.

According to an EY survey, global CEOs are confused by the uncertainty surrounding generative AI. CEOs in the U.S. face pressure to deploy generative AI, but the uncertainty surrounding the technology puts them in a 'dilemma'. CEOs recognize the need to act swiftly regarding generative AI, but an equal proportion express that the uncertainty of the technology 'hinders' them.