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Showing posts with label manufacturing industry. Show all posts
Robotics
AI technology AI tools Cyber Security Generative AI generative AI tools Job Automation Job Security Llama 3 Llama 4 manufacturing industry Robotics

Foxconn’s Chairman Warns AI and Robotics Will Replace Low-End Manufacturing Jobs

 

Foxconn chairman Young Liu has issued a stark warning about the future of low-end manufacturing jobs, suggesting that generative AI and robotics will eventually eliminate many of these roles. Speaking at the Computex conference in Taiwan, Liu emphasized that this transformation is not just technological but geopolitical, urging world leaders to prepare for the sweeping changes ahead. 

According to Liu, wealthy nations have historically relied on two methods to keep manufacturing costs down: encouraging immigration to bring in lower-wage workers and outsourcing production to countries with lower GDP. However, he argued that both strategies are reaching their limits. With fewer low-GDP countries to outsource to and increasing resistance to immigration in many parts of the world, Liu believes that generative AI and robotics will be the next major solution to bridge this gap. He cited Foxconn’s own experience as proof of this shift. 

After integrating generative AI into its production processes, the company discovered that AI alone could handle up to 80% of the work involved in setting up new manufacturing runs—often faster than human workers. While human input is still required to complete the job, the combination of AI and skilled labor significantly improves efficiency. As a result, Foxconn’s human experts are now able to focus on more complex challenges rather than repetitive tasks. Liu also announced the development of a proprietary AI model named “FoxBrain,” tailored specifically for manufacturing. 

Built using Meta’s Llama 3 and 4 models and trained on Foxconn’s internal data, this tool aims to automate workflows and enhance factory operations. The company plans to open-source FoxBrain and deploy it across all its facilities, continuously improving the model with real-time performance feedback. Another innovation Liu highlighted was Foxconn’s use of Nvidia’s Omniverse to create digital twins of future factories. These AI-operated virtual factories are used to test and optimize layouts before construction begins, drastically improving design efficiency and effectiveness. 

In addition to manufacturing, Foxconn is eyeing the electric vehicle sector. Liu revealed the company is working on a reference design for EVs, a model that partners can customize—much like Foxconn’s strategy with PC manufacturers. He claimed this approach could reduce product development workloads by up to 80%, enhancing time-to-market and cutting costs. 

Liu closed his keynote by encouraging industry leaders to monitor these developments closely, as the rise of AI-driven automation could reshape the global labor landscape faster than anticipated.
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Manufacturing Organization
Cyber Awareness Cyber Security Cybersecurity Strategy Data protection data security manufacturing industry Manufacturing Organization

Building Cyber Resilience in Manufacturing: Key Strategies for Success

 

In today's digital landscape, manufacturers face increasing cyber threats that can disrupt operations and compromise sensitive data. Building a culture of cyber resilience is essential to safeguard against these risks. Here are three key strategies manufacturers can implement to enhance their cyber resilience. 

First, manufacturers must prioritize cybersecurity training and awareness across all levels of their organization. Employees should be educated about the latest cyber threats, phishing scams, and best practices for data protection. Regular training sessions, workshops, and simulations can help reinforce the importance of cybersecurity and ensure that all staff members are equipped to recognize and respond to potential threats. By fostering a knowledgeable workforce, manufacturers can significantly reduce the likelihood of successful cyberattacks. Training should be continuous and evolving to keep pace with the rapidly changing cyber threat landscape. Manufacturers can incorporate real-world scenarios and case studies into their training programs to provide employees with practical experience in identifying and mitigating threats. 

Second, adopting robust security measures is crucial for building cyber resilience. Manufacturers should implement multi-layered security protocols, including firewalls, intrusion detection systems, and encryption technologies. Regularly updating software and hardware, conducting vulnerability assessments, and implementing strong access controls can further protect against cyber threats. Additionally, integrating advanced threat detection and response solutions can help identify and mitigate risks in real-time, ensuring a proactive approach to cybersecurity. It is also vital to develop and maintain a comprehensive incident response plan that outlines specific steps to be taken in the event of a cyberattack. 
This plan should include roles and responsibilities, communication protocols, and procedures for containing and mitigating damage. Regular drills and simulations should be conducted to ensure that the incident response plan is effective and that employees are familiar with their roles during an actual event.  

Third, creating a collaborative security culture involves encouraging open communication and cooperation among all departments within the organization. Manufacturers should establish clear protocols for reporting and responding to security incidents, ensuring that employees feel comfortable sharing information about potential threats without fear of reprisal. By promoting a team-oriented approach to cybersecurity, manufacturers can leverage the collective expertise of their workforce to identify vulnerabilities and develop effective mitigation strategies. Fostering collaboration also means engaging with external partners, industry groups, and government agencies to share threat intelligence and best practices. 

By participating in these networks, manufacturers can stay informed about emerging threats and leverage collective knowledge to enhance their security posture. Moreover, manufacturers should invest in the latest cybersecurity technologies to protect their systems. This includes implementing AI-powered threat detection systems that can identify and respond to anomalies more quickly than traditional methods. Manufacturers should also consider employing cybersecurity experts or consulting firms to audit their systems regularly and provide recommendations for improvement. 

Finally, fostering a culture of cyber resilience involves leadership commitment from the top down. Executives and managers must prioritize cybersecurity and allocate sufficient resources to protect the organization. This includes not only financial investment but also dedicating time and effort to understand cybersecurity challenges and support initiatives aimed at strengthening defenses.
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Technology
Cyber Threats Data collection Data Risk manufacturing industry online data risks Technology

Data Collection: What are Some ‘Unlikable’ Traits in This Growing Trend?


One of the consequences of the pandemic in the many B2B2C manufacturers was the changes in interactions with their clients. Numerous manufacturing brands in consumer packaged goods (CPG), fashion, equipment, etc. understood the advantages of implementing a direct-to-consumer approach even when the retail shops that would ordinarily distribute their products were shut down.

Due to their business model, which involved selling their goods via resellers, these businesses have typically had little contact with the final consumer. However, several manufacturers smartly constructed digital experiences to interact with, sell to, and gather data from their customers directly as a result of resellers being closed or operating at reduced capacity.

Data that was previously gathered and owned by resellers or intermediaries was suddenly made directly available to manufacturers for them to profit from and learn from. This opened up new revenue streams by charging other organizations for their data, using it to cross- or upsell products, or making the customer experience less complicated.

With all likable traits of data collection, there however exists certain risks that comes with it. These risks not only include data hack, malware or data theft but also exploitation of the collected data that may lead to a brand wreckage or even legal challenges to an organization.

In order to minimize the damaging consequence, organizations are advised to develop a proactive ethical framework rather than any reactive measure, in order to govern the use of technology and data. These principles create a foundation of security and respect for clients, reducing consumer harm.

Moreover, with the evolution of cyber threats, the previously admired strategies are now outdated. There is no longer a secure border or barrier. Through the use of security-in-depth techniques like encrypted communications, segregated areas, granular authentication and authorization, and sophisticated intrusion detection systems, system design should enable risk management and security enforcement across the whole architecture.

Lastly, the manufacturers are also urged to reconsider their views on data in order to effectively address privacy. Particularly, they ought to give top priority to well-considered governance systems that allow for informed choice-making with regard to data collection, access, and utilization. Manufacturers could guarantee that data is treated properly and ethically by designating data owners. For enterprises, having a solid governance framework is important for safeguarding user data and privacy.

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