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Why the Edge is Key to Unlocking IoT’s Full Potential – ReadWrite

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Paul Butterworth


To IoT’s great benefit, edge computing is about to take the spotlight. Consider that each day billions of devices connected to the Internet of Things come online. As they do, they generate mountains of information. One estimate predicts the amount of data will soar to 79.4 zettabyes within five years. Imagine storing 80 zettabytes on DVDs. All those DVDs would circle the Earth more than 100 times.

In other words, a whole lot of data.

Indeed, thanks to the IoT, a dramatic shift is underway. More enterprise-generated data is being created and processed outside of traditional, centralized data centers and clouds. And unless we make a course correction, the forecasts could come unglued. We must make better use of edge computing to deal more effectively with this ocean of data,

Network Latency

If we do this right, our infrastructure should be able to handle this data flow in a way that maximizes efficiency and security. The system would let organizations benefit from instantaneous response times. It would allow them to use the new data at their disposal to make smarter decisions and — most importantly — make them in real-time.

That’s not what we have nowadays.

In fact, when IoT devices ship their data back to the cloud for processing, transmissions are both slow and expensive. Too few devices are taking advantage of the edge.

Traffic Jam: The Cloud

Instead, many route data to the cloud. In that case, you’re going to encounter network latency measuring around 25 milliseconds. And that’s in best-case scenarios. Often, the lag time is a lot worse.  If you have to feed data through a server network and the cloud to get anything done, that’s going to take a long time and a ton of bandwidth.

An IP network can’t guarantee delivery in any particular time frame. Minutes might pass before you realize that something has gone wrong. At that point, you’re at the mercy of the system.

Data Hoarding 

Until now, technologists have approached Big Data from the perspective that the collection and storage of tons of it is a good thing. No surprise, given how the cloud computing model is very oriented toward large data sets.

The default behavior is to want to keep all that data. But think about how you collect and store all that information. There is simply too much data to push it all around the cloud. So why not work at the edge instead?

Cameras Drive Tons of Data – Not All of Which We Need

Consider, for example, what happens to the imagery collected by the millions of cameras in public and private. What happens once that data winds up in transit? In many – and perhaps most – instances, we don’t need to store those images in the cloud.

Let’s say that you measure ambient temperature settings that produce a reading once a second. The temperature reading in a house or office doesn’t usually change on a second-by-second basis. So why keep it?  And why spend all the money to move it somewhere else?

Obviously, there are cases where it will be practical and valuable to store massive amounts of data. A manufacturer might want to retain all the data it collects to tune plant processes. But in the majority of instances where organizations collect tons of data, they actually need very little of it. And that’s where the edge comes in handy.

Use the Edge to Avoid Costly Cloud Bills

The edge also can save you tons of money. We used to work with a company that collected consumption data for power management sites and office buildings. They kept all that data in the cloud. That worked well until they got a bill for hundreds of thousands of dollars from Amazon.

Edge computing and the broader concept of distributed architecture offers a far better solution.

Edge Helps IoT Flourish in the era of Big Data

Some people treat the edge as if it were a foreign, mystical environment. It’s not.

Think of the edge as a commodity compute resource. Better yet, it is located relatively close to the IoT and its devices. Its usefulness is precisely due to its being a “commodity” resource rather than some specialized compute resource. That most likely takes the form of a resource that supports containerized applications. These hide the specific details of the edge environment.

The Edge Environment and Its Benefits

In that sort of edge environment, we can easily imagine a distributed systems architecture where some parts of the system are deployed to the edge. At the edge, they can provide real-time, local data analysis.

Systems architects can dynamically decide which components of the system should run at the edge. Other components would remain deployed in regional or centralized processing locations. By configuring the system dynamically, the system is optimized for execution in edge environments with different topologies.

With this kind of edge environment, we can expect lower latencies. We also achieve better security and privacy with local processing.

Some of this is already getting done now on a one-off basis. But it hasn’t yet been systematized. That means organizations must figure this out on their own by assuming the role of a systems integrator. Instead, they must embrace the edge and help make IoT hum.

Politics

Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Politics

Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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Politics

UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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