Some of the latest developments in AI that are shaping the industry:
The FTC has introduced new rules banning fake reviews, including those generated by AI.
Google is broadening its AI Overviews feature in search and will now include citations.
Anthropic launched a new feature, Prompt Caching, designed to improve speed and reduce API costs.
Snapchat has introduced new AI-powered tools for advertisers, including a feature that generates ad copy.
SAG-AFTRA partnered with AI voice startup Narrativ to allow actors to create and monetize digital replicas of their voices for audio ads.
Meta has replaced its Crowdtangle tool with the Meta Content Library, despite concerns about the timing before the upcoming election.
Hubspot added a new “AI search grader” to help brands assess their visibility in AI-driven search results.
XAI released Grok 2, which now features image generation for X. The update follows a letter several secretaries of state sent to X owner Elon Musk asking him to address the spread of election misinformation on the platform.
A new survey by Digitas and Vox explores the relationship between AI and creativity.
The startup BattlegroundAI has expanded beta access for political advertisers aiming to create AI-generated content for local elections.
Experts in the Automotive Industry Asia
You need one, but don`t want to hire one permanently?
The global auto industry is undergoing a revolution, significantly driven by the rapid advancement of Chinese automakers. These companies dominate electric motor production and excel in integrating high-efficiency systems and digital features into vehicles. Chinese EVs, like Tesla, focus on innovative digital components, including autonomous driving, virtual reality, and multiple high-resolution dashboard screens. The term “digital bling” captures this trend.
Chinese automakers are ahead in the EV supply chain, emphasizing software and new features over hardware. For example, JiYue offers a saloon controlled by voice commands and touch screens, while Nio provides augmented reality glasses and advanced autonomous driving systems. Electronics and digital technology now constitute over 40% of a vehicle’s cost, projected to reach 45% by 2030.
Xiaomi’s entry into the EV market, with its SU7 model, showcases rapid innovation, competing with Tesla’s Model 3 by offering advanced autonomy and a lower price. Xiaomi’s success stems from fast-follower techniques and leveraging China’s dynamic supply chain. Tesla’s “gigacasting” process for manufacturing is also being adopted and innovated by Chinese companies like Nio and XPeng.
Chinese EV makers benefit from strategic partnerships with Western firms and government policies that foster technological development. These collaborations enhance local market understanding and technological advancements, positioning China as a leader in the global EV market. Source: itif.org
Experts in the Automotive Industry Asia
You need one, but don`t want to hire one permanently?
The winds of technological change are blowing stronger than ever in the world of supply chain transformation. It’s becoming increasingly clear that purpose-built intelligent applications are shaping the future of supply chain technology, particularly in the area of supply chain data management.
Over the past three years, purpose-built intelligent applications have gathered numerous insights, serving as the glue that addresses specific issues by integrating disparate systems like ERP, EAM, and P2P. Crucially, by eliminating the necessity for impeccably organized MRO data, intelligent “systems of routine” facilitate optimization and foster collaboration among internal teams and external suppliers.
This trend of data integration repeats a bit of a significant phase in the ERP industry during the late 1990s. At that time, well-funded “middleware” companies such as Active Software, BEA Systems, and WebLogic drove the eBusiness movement, revolutionizing enterprise application and service-oriented architecture (SOA) by acting as central brokers, combining data from various applications and data types into a unified system.
In the modern supply chain landscape, new software engines powered by GenAI, deep learning, and natural language processing (NLP) have the capacity to handle significantly larger datasets compared to earlier machine learning iterations. These advanced applications can analyze complex variables, including MRO inventory and spending data, far quicker. They can help build data connections between different ERP software platforms, enabling efficient management of day-to-day operations and procurement needs.
By removing the prerequisite of “clean” data, these intelligent “systems of routine” empower enterprise manufacturers to use their existing MRO data, accelerating value creation. Consequently, this will help drive the generation of demand signals and enhances optimization across supplier networks.
How can Purpose-Built Technology Benefit Supply Chain Sustainability Data Management?
The expectation for companies to embrace sustainability has evolved from a mere preference to a societal imperative. This paradigm shift necessitates businesses to realign their operations accordingly, with particular emphasis on supply chain management.
Navigating this transition poses several challenges for organizations, including the integration of diverse data sources and the complexity of multi-tiered supply networks. Maintaining data accuracy, integrity, and accessibility further compounds these challenges.
While businesses often turn to their existing technological infrastructure to address these issues, they soon realize its limitations in managing the intricacies of sustainability data effectively.
Purpose-built technology solutions offer a tailored approach to address these challenges, facilitating improved processes, security, and efficiency. These solutions enable businesses to:
Utilize versatile data collection methods adaptable to different technological capabilities and input preferences of suppliers.
Implement consistent and recurring data collection processes to minimize information gaps and reinforce procedural standards.
Provide user-friendly interfaces for external stakeholders, simplifying the adoption process and enhancing collaboration.
Automate calculations and unit conversions to ensure accuracy and streamline reporting procedures.
Enhance assurance facilitation and auditing efficiency by improving data consistency and collaboration.
Offer comprehensive data visualization and reporting functionalities to identify trends and opportunities across the supply chain.
Resilience and Agility
Purpose-built solutions serve as a vital tool that enrich and standardize procurement and operations data across systems.
Ensuring that all parties are working from the same trusted and consistent data source eliminates the need for costly traditional data cleansing.
This is critical because the more business is automated, the more we rely on the data that drives it all. Mistakes may arise in MRO inventory if data is incomplete or if your team enters MRO material information under different names.
If you’re a manufacturer with indirect and MRO inventory, you know how bad or incomplete MRO data can lead to inventory discrepancies that result in material overages or critical shortages.
The way to get around that is in purpose-built intelligent AI applications.
Companies need to adapt quickly with greater visibility and traceability to manage risk.
The future of the supply chain lies in technological advancement. It’s time for your organization to enhance your existing technology stack with purpose-built intelligent solutions to drive better outcomes in your supply chain operations.
For more information, please contact:
Karlheinz ZUERL – CEO of GTEC (German Technology & Engineering Cooperation)
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