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How Digital Technology is Reshaping the Automobile Industry

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How Digital Technology is Reshaping the Automobile Industry

Digital transformation in the automotive industry is redefining the way vehicles are conceived, assembled, and operated.

Technology is reshaping the automobile industry from automating and speeding up the process of designing new models of cars to enabling cars to drive themselves,

From carts and carriages pulled by animals in the ancient ages to vehicles that automatically drive themselves today, the way we traverse over land has seen a massive transformation, to say the least. Cars, since their invention just about two centuries ago has gone from being an innovative marvel to a luxury, now, have become a necessity for most people. The automotive industry, pioneered by stalwarts like Ford and Benz, has seen a steady growth in the decades leading to today, but the evolution of the industry in the pre-digital era is nothing compared to the rapid transformation it is presently undergoing. The past decade has seen the pervasion of every conceivable digital technology into the process of making or driving a motor vehicle. Be it artificial intelligence, big data, the internet of things, or blockchain, every form of digital technology is converging in the automobile industry. The digital transformation in the automotive industry is poised to transform not just the way cars are driven, but also the way they are made and conceived.

Digital Transformation in the Automotive Industry

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1. Artificial Intelligence is Empowering Self Driving Cars

If you’ve been following the world of technology and automobiles in recent years, chances are you’re already aware of the inevitability of the worldwide mass adoption of self-driving cars. Self-driving cars, as the name suggests, refer to AI driven cars that do not require a human driver for operation. These cars, although not as common today as AI enthusiasts would have loved, are currently being tested on roads with real passengers. We are getting ever-closer to achieving totally self-driven with new advances like the development of vector-based navigation, which gives AI agents the ability to orient and move in physical space like humans and other animals do.

A future where the roads are exclusively filled with self-driving cars seems distant, both due to the technological hurdles that need to be crossed, and the fact that there will be people who would prefer to drive their own vehicles. Until the era of total automation of vehicles arrives, technologies like AR and IoT are being employed to enrich the experience of driving and owning cars. An ever-increasing number of IoT sensors are being included in automobile design to allow drivers to monitor vital parameters pertaining to the location and performance of the vehicle. Onboard vehicle telemetry, which has been in use for a while now, not only helps Government regulators to track the vehicle but can also enable them to force the vehicle to stop. Such systems that enable remote connectivity and data gathering are increasingly becoming common in modern cars. Vehicles have onboard sensors to track dozens of performance parameters that are relayed to the driver’s dashboard display, and in some cases even to the carmakers. The information gathered may also include driver behavior data that can be used to find patterns in drivers’ driving habits, which can not only help in adjusting vehicle parameters in real-time but also used in the future to improve vehicle features.

2. Digital Marketing & The Advent of the Internet are Helping Customers Evaluate Vehicles

Digital technology has perhaps made the greatest impact on the way customers buy, and manufacturers sell automobiles. Before the popularization of the internet and the recent progress in digital technology, customers did not have many ways to evaluate and compare their options before purchasing a new vehicle. Except for the short advertisements on television and print media, and time-consuming visits to vehicle dealerships, people did not have many ways to make an informed decision while buying new cars. With the advent of the internet and digital marketing, car buyers can now have extensive information, including opinions and reviews on vehicles to help them in making a purchase decision.

Car manufacturers have more channels to market their vehicles to customers, and especially in a more focused manner with the help of big data analytics and targeted marketing. The digital transformation in the automotive industry has brought down the barriers between manufacturers and customers, which means manufacturers can have a better understanding of the market.

A new trend in automobile distribution is the increasing use of virtual reality. Manufacturers like Audi have started using virtual reality in their dealership facilities to give potential buyers a virtual tour of their offerings. Eventually, fully immersive VR test drives may become a common thing in the automotive market.

3. Industrial Internet of Things Are Improving The Manufacturing Process

The introduction of digital technologies such as analytics and the Industrial Internet of things (IIoT) has been a major game-changer in the automotive industry. Predictive analytics has become a staple in manufacturing facilities, where it is used to monitor and maintain the health of manufacturing and assembly equipment. Predictive analytics has enabled vehicle manufacturers to cut down on breakdown times by minimizing unplanned stoppages. Continuous analysis of manufacturing processes using big data analysis is helping manufacturers to identify areas of improvements and bottlenecks in the assembly processes that were previously unnoticeable.

The advent of the internet of things has multiplied the influx of operational data that is gathered from the vehicle assembly lines, enabling further fine-tuning of the processes. Analytics is not only leading to improvements in the mechanical aspects of manufacturing but is also leading to better management of both material and human resources. The use of artificial intelligence and machine learning in the automotive industry has led to further leaps of improvement in the way cars are assembled, leading to shorter lead times, greater quality, and consequently, increased profits.

4. Artificial Intelligence Analytics is Creating New Vehicle Designs

In addition to redefining the way cars are manufactured, the digital transformation in the automotive industry has even changed the way vehicles are conceptualized. Artificial intelligence, which has already made significant inroads into the processes requiring repetitive precision, has also begun proving itself in tasks requiring creativity. Automobile makers have already started exploring the use of artificial intelligence to design cars. Car design, which used to be a completely a human process, is now slowly being ceded to intelligent systems that use a large base of knowledge and data as a reference to generate completely new car models that don’t just meet the aesthetic requirements but also the performance requirements of the mainstream public.

The use of IoT and big data is helping vehicle makers to continuously monitor their cars and the way they are being used by customers to determine what aspects of design are working and what needs to change. With increasingly flexible manufacturing systems, the time between the conception of a change in design and its execution is getting incredibly shorter. Thus, vehicle manufacturers benefiting from the digital transformation through increased design flexibility.

Although digital technology continues to be a major transformational factor in the automotive sector, the role of other developments in changing the industry, such as the exploration of new sources of energy is undeniable. However, unlike innovations in the fields of renewable energy and material science that lead to the occasional yet radical change in the transportation sector, digital transformation in the automotive industry is an ongoing process that will continuously change the way cars are driven, distributed, and designed.


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TECHNOLOGY

What’s Wrong with the Algorithms?

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What's Wrong with the Algorithms?

Social media algorithms have become a source of concern due to the spread of misinformation, echo chambers, and political polarization.

The main purpose of social media algorithms is to personalize and optimize user experience on platforms such as Facebook, Twitter, and YouTube.

Most social media algorithms sort, filter, and prioritize content based on a user’s individual preferences and behaviors. Social media algorithms have come under scrutiny in recent years for contributing to the spread of misinformation, echo chambers, and political polarization.

Facebook’s news feed algorithm has been criticized for spreading misinformation, creating echo chambers, and reinforcing political polarization. In 2016, the algorithm was found to have played a role in the spread of false information related to the U.S. Presidential election, including the promotion of fake news stories and propaganda. Facebook has since made changes to its algorithm to reduce the spread of misinformation, but concerns about bias and polarization persist.

Twitter’s trending topics algorithm has also been criticized for perpetuating bias and spreading misinformation. In 2016, it was revealed that the algorithm was prioritizing trending topics based on popularity, rather than accuracy or relevance. This led to the promotion of false and misleading information, including conspiracy theories and propaganda. Twitter has since made changes to its algorithm to reduce the spread of misinformation and improve the quality of public discourse.

YouTube’s recommendation algorithm has been criticized for spreading conspiracy theories and promoting extremist content. In 2019, it was revealed that the algorithm was recommending conspiracy theory videos related to the moon landing, 9/11, and other historical events. Additionally, the algorithm was found to be promoting extremist content, including white nationalist propaganda and hate speech. YouTube has since made changes to its algorithm to reduce the spread of misinformation and extremist content, but concerns about bias and polarization persist.

In this article, we’ll examine the problem with social media algorithms including the impact they’re having on society as well as some possible solutions.

1. Spread of Misinformation

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Source: Scientific American

One of the biggest problems with social media algorithms is their tendency to spread misinformation. This can occur when algorithms prioritize sensational or controversial content, regardless of its accuracy, in order to keep users engaged and on the platform longer. This can lead to the spread of false or misleading information, which can have serious consequences for public health, national security, and democracy.

2. Echo Chambers and Political Polarization

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Source: PEW Research Center

Another issue with social media algorithms is that they can create echo chambers and reinforce political polarization. This happens when algorithms only show users content that aligns with their existing beliefs and values, and filter out information that challenges those beliefs. As a result, users can become trapped in a self-reinforcing bubble of misinformation and propaganda, leading to a further division of society and a decline in the quality of public discourse.

3. Bias in Algorithm Design and Data Collection

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Source: Springer Link

There are also concerns about bias in the design and implementation of social media algorithms. The data used to train these algorithms is often collected from users in a biased manner, which can perpetuate existing inequalities and reinforce existing power structures. Additionally, the designers and developers of these algorithms may hold their own biases, which can be reflected in the algorithms they create. This can result in discriminatory outcomes and perpetuate social injustices.

4. Democracy in Retreat

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Source: Freedom House

Social media algorithms are vulnerable to manipulation and can spread false or misleading information, which can be used to manipulate public opinion and undermine democratic institutions. The dominance of a few large social media companies has led to a concentration of power in the hands of a small number of organizations, which can undermine the diversity and competitiveness of the marketplace of ideas, a key principle of democratic societies.

How to Improve Social Media Algorithms?

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Source: Tech Xplore

Governments and regulatory bodies have a role to play in holding technology companies accountable for the algorithms they create and their impact on society. This could involve enforcing laws and regulations to prevent the spread of misinformation and extremist content, and holding companies responsible for their algorithms’ biases.

There are several possible solutions that can be implemented to improve social media algorithms and reduce their impact on democracy. Some of these solutions include:

  • Increased transparency and accountability: Social media companies should be more transparent about their algorithms and data practices, and they should be held accountable for the impact of their algorithms on society. This can include regular audits and public reporting on algorithmic biases and their impact on society.

  • Regulation and standards: Governments can play a role in ensuring that social media algorithms are designed and operated in a way that is consistent with democratic values and principles. This can include setting standards for algorithmic transparency, accountability, and fairness, and enforcing penalties for violations of these standards.

  • Diversification of ownership: Encouraging a more diverse and competitive landscape of social media companies can reduce the concentration of power in the hands of a few dominant players and promote innovation and diversity in the marketplace of ideas.

  • User education and awareness: Social media users can be educated and empowered to make informed decisions about their usage of social media, including recognizing and avoiding disinformation and biased content.

  • Encouragement of responsible content creation: Social media companies can work to encourage the creation of high-quality and responsible content by prioritizing accurate information and rewarding creators who produce this content.

  • Collaboration between industry, government, and civil society: Addressing the challenges posed by social media algorithms will require collaboration between social media companies, governments, and civil society organizations. This collaboration can involve the sharing of data and best practices, the development of common standards and regulations, and the implementation of public education and awareness programs.

Conclusion

Social media companies have the power to censor and suppress speech, which can undermine the right to free expression and the democratic principle of an open and inclusive public discourse. It is crucial for technology companies and policymakers to address these issues and work to reduce the potential for harm from these algorithms. Social media platforms need to actively encourage and facilitate community participation in the development and improvement of their algorithms. This would involve setting up forums for discussion and collaboration, providing documentation and support for developers, and engaging with the community to address their concerns and ideas. In order to ensure that the algorithms are fair and unbiased, tech companies need to be transparent about the data they collect and use to train their algorithms. This would involve releasing the data sets used to train the algorithms, along with information about how the data was collected, what it represents, and any limitations or biases it may contain.

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Daasity builds ELT+ for Commerce on the Snowflake Data Cloud

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Cloud Computing News

Modular data platform Daasity has launched ELT+ for Commerce, Powered by Snowflake.

It is thought ELT+ for Commerce will benefit customers by enabling consumer brands selling via eCommerce, Amazon, retail, and/or wholesale to implement a full or partial data and analytics stack. 

Dan LeBlanc, Daasity co-founder and CEO, said: “Brands using Daasity and Snowflake can rapidly implement a customisable data stack that benefits from Snowflake’s dynamic workload scaling and Secure Data Sharing features.

“Additionally, customers can leverage Daasity features such as the Test Warehouse, which enables merchants to create a duplicate warehouse in one click and test code in a non-production environment. Our goal is to make brands, particularly those at the enterprise level, truly data-driven organisations.”

Building its solution on Snowflake has allowed Daasity to leverage Snowflake’s single, integrated platform to help joint customers extract, load, transform, analyse, and operationalise their data. With Daasity, brands only need one platform that includes Snowflake to manage their entire data environment.

Scott Schilling, senior director of global partner development at Snowflake, said: “Daasity’s ELT+ for Commerce, Powered by Snowflake, will offer our joint customers a way to build a single source of truth around their data, which is transformative for businesses pursuing innovation.

“As Snowflake continues to make strides in mobilising the world’s data, partners like Daasity give our customers flexibility around how they build data solutions and leverage data across the organisation.” 

Daasity enables omnichannel consumer brands to be data-driven. Built by analysts and engineers, the Daasity platform supports the varied data architecture, analytics, and reporting needs of consumer brands selling via eCommerce, Amazon, retail, and wholesale. Using Daasity, teams across the organisation get a centralised and normalised view of all their data, regardless of the tools in their tech stack and how their future data needs may change. 

ELT stands for Extract, Load, Transform, meaning customers can extract data from various sources, load the data into Snowflake, and transform the data into actions that marketers can pursue. For more information about Daasity, our 60+ integrations, and how the platform drives more profitable growth for 1600+ brands, visit us at Daasity.com.

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4 Activities that Automakers Can Digitize Now

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4 Activities that Automakers Can Digitize Now

Digital automaking is supported by technology-driven trends, consumer needs and new developments in artificial intelligence.

Manufacturing, procurement of raw materials, marketing and sales are factors involved in this change.

Digital automaking is a process that combines simulation, three-dimensional visualizations, analytics and several tool partnerships to make automotive manufacturing easier. Since the automotive industry has been undergoing a digital transformation primarily driven by intelligent mobility, it has encouraged the market to adopt new technology and software for modern vehicles. There has also been a growing need to increase industrial processes’ sustainability, environmental friendliness and adaptability. All of this has made automotive digitalization extremely important.

Automotive digitization helps to keep precise control over business operations, which is made possible using modern technologies like ML (machine learning) and AI (artificial intelligence) to improve short- and long-term performance. 

Automotive digitization has also increased the capacity to monitor each component of the supply chain while lowering costs and risks. Digital automaking can offer automotive solutions in terms of better design, time efficiency, and many other industry solutions.

4 Activities that Can Be Digitized by Automakers Now

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1. Manufacturing

Customers desire tailored goods, but they don’t want to pay more than they would for items that are mass-produced. As a result, manufacturing must be more adaptable than ever, leading to mass customization. Thus, the design, fabrication, use and maintenance of products are changing as a result of the digitalization of manufacturing. It is also changing the operations, procedures and energy footprint of supply chains and more. Digital manufacturing enables firms to provide additional options that are tailored to individual customers. Businesses can better understand supply-chain challenges, including inventory levels, delivery status and demand cycles, thanks to digital manufacturing. 

The factories of the future will move from automation to autonomy, strengthening real-time communication between equipment, physical systems, and people. These factories are referred to as smart factories. The most notable advantages of a smart factory are its shop floor connectivity, advanced robotics, flexible automation, augmented and virtual reality systems, and efficient energy management. The general manufacturing sector’s global standards are established by the automotive industry.

Over the past two decades, the automotive sector has expanded tremendously. However, the main elements that will affect whether digitalization is successfully implemented are the significance of realizing a return on investment (RoI) and the willingness of employees at both the top-most and lowest levels of an organization.

2. Supply Chain

By removing the functional barriers that divide different areas, the digitization of the supply chain is a cross-functional process that spans the entire lifecycle of a vehicle or product and involves all company divisions. It allows for an ecosystem that connects all stakeholders, from raw material and component suppliers to logistics companies, dealers and customers.

Utilizing digital technology throughout the entire supply chain allows for real-time monitoring of all supply-chain stages, be it either procurement of raw materials or finished products ready to be delivered or purchased. The evaluation and management of each event’s impacts on the supply chain can help the automation of procedures and the avoidance of potential interruption.

3. Design

Design plays a significant role in the automotive industry. By digitizing design activity, design professionals can test multiple hypotheses before proceeding with the design phase. Digitalization in the designing of products has been enabled by a digital model known as Digital Twins, which represents tangible assets in 3D. Digital twins mirror the complete car or one of its components’ appearance and behavior. With great assistance from sophisticated software, businesses can collect information about configuration, sensors, inspection data, and other details to improve the product’s design.

Automobile manufacturers are among the many industrial firms that recognize digital twins’ possibilities and the potential it has to bring in the best in the business of automobiles. The design and production processes are simplified by 3D representations, improving vehicle performance and cutting costs for the manufacturers. The twin technology is quickly rising to the top of the list of software solutions used in contemporary auto manufacturing, with applications ranging from car design to predictive maintenance to boosting sales using digitally generated models.

4. Marketing

Any marketing strategy aims to tailor the right message to the right set of audiences at the right time. A marketing campaign that appeals to a 45-year-old countryside man might not affect a 23-year-old lady residing in an urban area. Therefore, the impact of marketing combined with the effectiveness of Artificial Intelligence (AI) can be the biggest boon to any business. The automotive industry can enormously benefit in how they market their brand/product by adding the power of artificial intelligence to their current data. It can lead to a strong possibility of purchasing your products early in the sales process, possibly before customers even begin looking for their new car, which is indicated by specific online activities. 

As a result of recent advancements in third-party cookies and mobile advertising identifiers, AI can now assist brands in finding new prospects much more quickly by utilizing data to identify customers with similar characteristics and behaviors. This strategy can potentially increase your prospective customer base and give you an advantage over your competitors. You can identify high-priority targets by identifying the demographic categories that overlap. These solutions don’t require cookies and are more likely to comply with escalating privacy requirements because they rely on behaviors rather than personal data.

The automotive sector has modified its strategy and is now embracing digitization. Digital transformation in the automotive industry still has a lot of gaps to be addressed, but the trend toward digitization is a sign that the stakeholders in the automotive sector will be properly supplied with digital solutions in the coming days. With intelligent technology, and operations across the entire company and all departments, including manufacturing, supply chain, marketing, and sales, digital automaking will help the automotive industry to flourish in this digital era. An increasingly digital supply chain will also dismantle established barriers and greatly enhance communication. Undoubtedly, businesses must adopt a more significant digital transformation to be ready in this competitive automotive industry.

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