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jcmarchi · 23 days

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Steve Statler, Chief Marketing Officer at Wiliot – Interview Series

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Steve Statler, Chief Marketing Officer at Wiliot – Interview Series

Steve Statler is the Chief Marketing Officer at Wiliot, author of Beacon Technologies, and the presenter of the Mister Beacon Ambient IoT podcast.

At the core of the Wiliot System are IoT Pixels, which are low-cost tags approximately the size of a postage stamp, designed for easy integration into a wide range of products. These IoT Pixels continuously gather data from their surroundings and are powered either by harvesting radio frequency energy or, in some versions, by a thin printed battery. The transmissions from IoT Pixels are secure and can be read using existing Bluetooth devices.

What are the potential benefits of integrating WiliBot into existing supply chain management systems?

Integrating WiliBot into existing supply chain management systems will allow brands and manufacturers to communicate with their products in ways that significantly improve their supply chain efficiency and sustainability.

By enabling natural-language conversations with any ambient-IoT connected product, WiliBot can be used by businesses seeking to ask questions about their ambient IoT enabled products and supply chains: How fresh is this product? How did it get to the store? Which product should I stock next, and why? What is the carbon footprint of this product? Why is it so high or low? The answers to these questions can then be integrated in real time into a businesses supply chain strategy.

How does Wiliot’s use of ambient IoT and GenAI enhance real-time data visibility in supply chains?

The combination of ambient IoT and GenAI offers a unique opportunity to enhance and apply real-time data visibility. Wiliot’s IoT Pixels are constantly collecting real-time data throughout the supply chain and even in stores.

WiliBot enhances this real-time data visibility by harnessing the power of generative AI, to make sense of the data provided. This allows companies – and eventually consumers – the ability to have conversations with the products they make, source, distribute and ultimately purchase. Breaking down complex and multitudes of data into easy to understand actionable insights.

For a GenAI model to run effectively, it requires significant data input to train it. In the past, due to the lack of large amounts of real time data, this meant supply chain GenAI models would utilize previously existing data. While this proved generally effective, supply chains shift from year to year, and last year’s data isn’t always the most accurate when predicting what businesses need in a year, month, and even day. The constant real-time data that Wiliot’s IoT Pixels and Ambient Data Platform feeds into WiliBot proves the most effective for brands looking to capitalize on the most current intelligence that’s happening in their supply chains.

In what ways can WiliBot help businesses improve sustainability and reduce waste within their supply chains?

Wilibot empowers consumers to vote with their purses and wallets based on better insights into the provenance, content and carbon footprint of one product versus another that may look identical. By capturing the dynamic carbon impact of storage, transportation at an item level and sharing that insight in real time, businesses can be empowered to manage down their carbon footprint every minute of every day. An end of year scorecard at a company level can’t do that.

Wiliot’s Ambient Data Platform, already allows companies to gain unprecedented intelligence about the sustainability about trillions of products. With the introduction of WiliBot, businesses will now be able to ask and easily break down that intelligence into real-time information about individual products.

In turn, this means companies can get real-time specifics on the sustainability of their supply chains. They can ask WiliBot questions like: why some products have a greater carbon footprint than others, what products they should stock before they expire, and how weather patterns are impacting products throughout the supply chain.

WiliBot allows companies to recognize where changes could be made to ensure sustainability and reduce waste, without waiting for the past year’s data.

How do Wiliot’s IoT Pixels work, and what makes them unique in enabling continuous, real-time data collection in supply chains without the need for batteries?

Wiliot’s IoT Pixels are low-cost tags, the size of a postage stamp, and can be seamlessly manufactured into just about any product. IoT Pixels are designed to provide insights on “everything, everywhere, all at once” – because of their small size, they can be affixed to almost any product, down to even crate-level shipments. What makes IoT Pixels unique, and what allows for them to provide continuous data collection, is that they’re powered by harvested radio frequency energy, meaning they use the radio frequencies from everyday devices that already exist in the world around us. IoT Pixels then securely transmit that data, also via existing Bluetooth devices, to the Wiliot Ambient Data Platform, where it’s available for businesses to pull from.

What are the security measures in place to ensure the privacy and integrity of data collected by IoT Pixels and processed by the Wiliot Ambient Data Platform?

The data security and governance robustness of Wiliot’s Ambient Data Platform has been certified by two leading examiners. We have achieved Systems and Organization Controls (SOC) 1 Type II and SOC 2 Type II reports, both issued by independent auditors from a leading Big 4 firm.

Additionally, we recently received its third-year recertification of its ISO 27001 and 27018 certifications by the International Organization for Standardization. Both of these certifications validate our ongoing commitment to data security, governance, and privacy.

Unlike other auto-identification technologies like QR codes and RFID, Wiliot’s implementation includes encryption backed access control to the data that relates to the content, movement and usage of products.

How does WiliBot leverage generative AI to provide actionable insights from the data generated by IoT Pixels?

The data generated by IoT Pixels is sent via Bluetooth to the Wiliot cloud once it’s finalized. From there, WiliBot can leverage the generative AI to provide actionable insights.

WiliBot’s Wiliot-developed AI, built on top of a leading Large Language Model, can identify supply chain “events” and automatically generate alerts or AI responses that allow businesses to course-correct or optimize their operations. This could mean creating an automatic alert for a business when shipments of their produce have been handled at an unsafe temperature, or when pharmaceuticals were kept in an environment too moist for them

The answers to these questions are available in the Wiliot Ambient Data platform, but haven’t always been easily accessible. With WiliBot, these actionable insights can be democratized across organizations, as opposed to requiring significant labor or integration costs.

Can WiliBot be customized to address specific industry needs, such as retail, pharmaceuticals, or food production?

Yes. Wiliot IoT Pixels can be affixed to and provide data on any product, across retail, pharmaceuticals, food production, and more, which means that WiliBot can be distinctively tailored to the needs of those industries.

The more relevant product data that is put into WiliBot, the more specific and targeted answers will be able to be. For food retailers, the priority when implementing WiliBot may be determining the effects of their supply chain’s weather patterns upon food rot and spoil; for clothing retailers, WiliBot may be more relevant in determining where product should go in the store. WiliBot is able to uniquely make sense of data based on each customer’s specific needs and to describe products, materials, supply chains, and everything connected to the internet.

How does the Wiliot Ambient Data Platform differentiate itself from traditional IoT platforms in terms of functionality and ease of integration?

The Wiliot Ambient Data Platform differentiates itself from traditional IoT platforms because of its ‘ambient’ aspect. The data drawn from the IoT Pixels into the platform are accessible all the time as opposed to requiring labor to track, scan or read it.

Wiliot also aims to set ambient IoT standards throughout the industry, which will allow for mass adoption and easy integration by the world’s largest retailers. Already, we are contributing to the 3GPPP alongside a number of large handset OEMs, and working on versions of the Ambient Data Platform that will support the Bluetooth, cellular/3GPP, and Wi-Fi/IEEE variants of ambient IoT.

What impact could WiliBot have on consumer transparency, particularly in understanding the carbon footprint and ethical sourcing of products?

Wiliot’s IoT Pixels already enable products to transmit item-level data about their carbon footprint and equip businesses with information needed to track, manage and reduce carbon emissions. WiliBot makes this even easier by allowing businesses to ask specific questions like where the or how products are sourced and their carbon footprint.

In the future, this convergence of ambient IoT and generative AI will be made available to consumers in-store and at-home through an ecosystem of mobile apps – enabling consumers themselves to speak to and converse with their products to better understand their carbon footprint, materials composition, ethical sourcing compliance, freshness and safety, and more.

This proliferation of information will allow for consumers to take their own ethical considerations into account when purchasing, and ultimately allow for an increased consumer experience without increasing employee workload or cost.

How does Wiliot ensure that the integration of ambient IoT with GenAI remains compliant with global data protection regulations?

Wiliot’s ambient IoT foundation for GenAI enables compliance to data protection regulations with accountability and access control, so that there is a clear owner of the data who has the tools to manage access to the data. Unlike other low-cost scalable radio frequency identifiers, every Wiliot tag is enabled with end-to-end encryption which prevents unauthorized access to data broadcast from a tag. Encryption starts at the chip level inside the tag and ends at the application in the cloud, which gives a single owner access to the data. With other forms of RFID, the owner isn’t clear – it could be the company that bought the RFID tag and applied it to the product, the distributor, the retailer, or the end customer. Wiliot’s approach of encrypting all the data means ownership can be transferred and data sharing can be regulated.

Thank you for the great interview, readers who wish to learn more should visit Wiliot.

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codewithdc · 1 month

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mitsde123 · 1 month

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5 AI Trends That Will Shape Digital Marketing in 2024

The landscape of digital marketing is evolving at a breakneck speed, and one of the driving forces behind this transformation is Artificial Intelligence (AI).

As we step into 2024, AI continues to revolutionize how brands connect with their audiences, optimize campaigns, and predict consumer behaviour.

Here are five AI trends that will shape digital marketing this year and how you can stay ahead of the curve with the right skills and certifications.

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nitinrajput2922 · 1 month

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How To Get A Machine Learning Certification Course Online?

For Quick Enquiry: Click Here

Introduction: Embarking on the Journey to a Machine Learning Certification Course Online

In today's tech-driven world, Machine Learning (ML) has become a game-changer. Whether it's self-driving cars, personalized recommendations, or even your phone's voice assistant, ML is behind it all. Naturally, the demand for professionals skilled in this domain is skyrocketing. For those aiming to break into this field, obtaining a certification is a crucial first step. This is where a comprehensive AI Intelligence Course in Noida can come into play, offering the knowledge and credentials needed to stand out in a competitive job market.

Finding the right online course to get certified in ML can be overwhelming. With so many options out there, how do you choose the one that suits your goals? Do you go for a short-term course or a more intensive one? And what about the credibility of the certification? These are the questions that often swirl in the minds of aspiring ML professionals. Fear not! This blog will guide you through the essential steps to getting a machine learning certification online, making sure you don't get lost in the sea of choices.

In this guide, we will explore how to select the best online Artificial Intelligence Institute In Delhi, understand the prerequisites, and ensure that you gain the right skills to excel in the ML field. If you're looking to jump-start your ML career from the comfort of your home, read on to find out how you can achieve your certification goals efficiently and effectively.

Choosing the Right Machine Learning Certification Course

1. Understanding the Different Types of Machine Learning Courses Available Online

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It's essential to assess your current skill level before enrolling in a course. If you're just starting, look for courses that offer a solid foundation in the basics of machine learning. These introductory courses typically cover essential topics such as linear regression, classification algorithms, and data preprocessing. On the other hand, if you already have some experience, you might want to consider more specialized courses that delve into advanced topics like neural networks or reinforcement learning.

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2. Evaluating Course Content, Structure, and Certification Credibility

Once you have a clear understanding of the types of courses available, the next step is to evaluate the course content, structure, and credibility of the certification. A good machine learning certification course should offer a well-rounded curriculum that covers both theoretical concepts and practical applications.

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Finding an Artificial Intelligence Institute In Delhi that offers a balance between theory and practice is key to getting the most out of your learning experience. Consider the credibility of the platform and the instructors as well. After all, you wouldn’t want to invest time and money into a course only to find out that the certification holds little weight in the industry.

3. Considering Course Duration, Flexibility, and Cost

Another crucial factor to consider when choosing an online machine learning certification course is the duration, flexibility, and cost. Depending on your current commitments, you may prefer a self-paced course that allows you to study at your own pace or a more structured program with set deadlines. Additionally, the duration of the course can vary significantly, from short-term courses lasting a few weeks to comprehensive programs that take several months to complete.

When searching for an AI Intelligence Course in Noida, make sure to choose one that fits your schedule and budget. While some courses are free, others may require a significant financial investment. It's essential to weigh the cost against the potential benefits of the certification. Remember, just like investing in quality ingredients can lead to a delicious meal, investing in the right course can lead to a successful career in machine learning.

Preparing for the Course and Maximizing Learning

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Before diving into an Artificial Intelligence Institute In Delhi, it's crucial to ensure that you meet the prerequisites. Many machine learning courses require a basic understanding of programming, particularly in languages like Python or R, as well as a solid grasp of mathematics, including linear algebra and statistics. If you're new to programming or math, consider taking introductory courses in these subjects before tackling machine learning.

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While a good Artificial Intelligence And Machine Learning Course in Noida will provide you with the necessary knowledge, it's always a good idea to supplement your learning with additional resources. Online communities, forums, and study groups can provide valuable insights and support as you progress through the course. Websites like Stack Overflow, GitHub, and Medium often have articles, tutorials, and discussions that can help you deepen your understanding of machine learning concepts.

In addition to online resources, consider reading books or watching tutorials to reinforce what you've learned. Engaging with different learning formats can help solidify your understanding and provide new perspectives on the material. Just like seasoning a dish enhances its flavor, utilizing additional resources can enrich your learning experience.

3. Gaining Practical Experience Through Projects and Challenges

One of the best ways to solidify your machine-learning knowledge is by applying it to real-world problems. Many online courses include projects as part of the curriculum, but it's also beneficial to seek out additional challenges on your own. Platforms like Kaggle and DrivenData offer competitions and datasets that allow you to test your skills and work on real-world problems.

Participating in these challenges not only helps you gain practical experience but also builds your portfolio, which can be a valuable asset when applying for jobs. If you're enrolled in an AI Intelligence Course in Noida, make sure to take full advantage of any project opportunities and seek out additional challenges to further enhance your skills.

Think of gaining practical experience as the final step in cooking a meal—you've prepared all the ingredients, followed the recipe, and now it's time to taste the finished product. By applying what you've learned to real-world problems, you'll be able to see the fruits of your labor and build the confidence needed to succeed in the field of machine learning.

Conclusion: Achieving Success with Your Machine Learning Certification Online

Embarking on the journey to obtain a machine learning certification online is an exciting and rewarding endeavor. By choosing the right course, evaluating the content, and ensuring it fits your schedule and budget, you set yourself up for success. Once enrolled, meeting the prerequisites and utilizing additional resources can further enhance your learning experience. Finally, gaining practical experience through projects and challenges will solidify your knowledge and provide a strong foundation for your future career in machine learning.

For those in India looking to get certified, enrolling in an Artificial Intelligence And Machine Learning Course in Noida is a valuable step toward becoming a skilled machine learning professional. With determination, continuous learning, and practical application, you'll be well on your way to achieving your certification goals and advancing your career in this dynamic and rapidly evolving field. So go ahead, take the plunge, and start your journey toward machine learning mastery today!