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Towards a new regulatory era for cryptos according to JP Morgan

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Luke Jose A.

In a research report published on Thursday, US investment bank JP Morgan looked into the lawsuits filed by the Securities and Exchange Commission (SEC) against Binance and Coinbase. The crackdown could create profound changes in the evolution of the crypto industry. It could indeed migrate outside the United States. Accordingly, JP Morgan is urging US lawmakers to establish a comprehensive framework governing the industry. What should we take away from this analysis?

JP Morgan and SEC logos

JP Morgan: Taking advantage of the SEC crackdown to regulate the crypto sector

Recently, the SEC filed lawsuits against Binance and Coinbase, two of the biggest cryptocurrency exchanges.

According to JP Morgan’s research report, these lawsuits are based on the fact that the SEC considers the majority of cryptocurrencies to be securities. As a result, it wants to place most companies in the sector and exchanges under its supervision, and bring them to comply with the regulatory frameworks that currently apply to other securities.

However, as Nikolaos Panigirtzoglou explains, classifying cryptocurrencies in the category of securities is not a simple legal question. It is quite ambiguous and requires further reflection. The ongoing SEC vs. Ripple case illustrates very well the lack of legal clarity on the subject.

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All of these elements lead JP Morgan to the following conclusion. American legislators must imperatively proposea comprehensive framework on how to regulate crypto-related industries and the relative responsibilities of the SEC versus the Commodity Futures Trading Commission (CFTC)“.

The Urgency of Crypto Industry Regulation

The regulator has filed lawsuits against Binance, its CEO Changpeng Zhao, and the operating company of Binance.US citing alleged violations of federal real estate securities laws. Soon after, it continued its crackdown by filing a similar lawsuit against Coinbase, Binance’s main rival.

This SEC policy disapproved by the Chamber of Commerce has the effect of encouraging players in the crypto industry to migrate outside the United States and to decentralized entities. Also, according to JP Morgan, crypto venture capital funding is likely to remain subdued going forward.

American legislators must therefore react as quickly as possible and establish a complete and precise regulatory framework. If they rule in favor of the SEC, Coinbase, Binance.US and other US exchanges would be forced to register as brokers. At the same time, most cryptocurrencies would now be treated as securities.

While putting these regulations in place can be onerous and expensive for the crypto industry, it should bring several benefits. According to the research report by JP Morgan bank, the crypto sector would become more transparent and could offer better protection to investors. Assets not to be overlooked for mass adoption!

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Luke Jose A. avatar

Luke Jose A.

A graduate of Sciences Po Toulouse and holder of a blockchain consultant certification issued by Alyra, I joined the Cointribune adventure in 2019. Convinced of the potential of the blockchain to transform many sectors of the economy, I took the commitment to raise awareness and inform the general public about this constantly evolving ecosystem. My goal is to enable everyone to better understand the blockchain and seize the opportunities it offers. I strive every day to provide an objective analysis of the news, to decipher market trends, to relay the latest technological innovations and to put into perspective the economic and societal challenges of this revolution in motion.

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Can Wasm replace containers? | InfoWorld

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Can Wasm replace containers? | InfoWorld
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If WASM+WASI existed in 2008, we wouldn’t have needed to have created Docker. That’s how important it is. WebAssembly on the server is the future of computing.

The devil is in the details. What Hykes meant to say was that if Wasm had existed back then, the need for containers like Docker wouldn’t have been as acute. Yet, that did not happen, and we live in a universe where Docker containers reign. Replacing mission-critical Linux-based containers is not a trivial act. As Hykes explains:

That tweet of mine was widely misunderstood. It was interpreted as WebAssembly is going to replace Docker containers. I did not think then that it would happen, and lo and behold, it did not happen, and in my opinion, will never happen. Now that Docker exists and is a standard, WebAssembly and WASI, as cool as they are, are very different. It’s not at all a replacement. It has a very different shape.

Most agree that WebAssembly beats containers in the browser, edge computing use cases, sandboxed plugins, and certain serverless functions. While some are more confident about the transformative potential Wasm will have, outlooks are split on Wasm as a long-term replacement for server-side containers or stateful, long-running server processes. Below, we’ll dive deeper to compare where exactly Wasm beats containers, and where it doesn’t.

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Where Wasm beats containers

Some developers see Wasm getting extensive use across applications, especially where containers are too clunky. “Wasm is just as adept in embedded IoT as it is in massive cloud infrastructure,” says Matt Butcher, co-founder and CEO of Fermyon. “Wasm is an excellent technology for serverless functions, IoT, edge computing, and plugin-style extension mechanisms,” he says.

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Breaking down digital silos | InfoWorld

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Shared goals, shared success

I run developer relations for MongoDB. My team is filled with engineers who write code and eschew marketing. Yet my team sits within the marketing org. Different companies do this differently, with some developer relations teams housed within the product or engineering groups (as we used to be at MongoDB). But in my experience, developer relations fits better within marketing precisely because few (if any) within my team would consider themselves marketers. For a company that focuses on serving developers, the last thing we want is traditional marketing. Instead, we want “marketing” to look like deep technical workshops, how-to tutorials, etc.

None of this works without being joined at the hip with more traditional marketing functions. My team knows, for example, that all their work has to support larger business goals. At the same time, these other teams (strategic marketing, field marketing, digital and growth, etc.) also know that they can count on us to support them and help inform the work they do.

This confluence of different functions isn’t a bug, it’s a feature, and it’s something that needs to happen well beyond my developer relations team and marketing. The best companies, whatever their industry, marry technology with business functions. According to Gartner VP Daniel Sanchez-Reina, “To become a digital vanguard, CIOs … need to prioritize four areas: making digital platforms easy for the workforce to build digital solutions, teaching them the interdependencies between technology and business, helping business leaders become innovation leaders at digital, and expanding digital skills beyond the IT department.” Technology, in other words, isn’t meant to sit in a silo. It needs to be central to how all areas of the business operate.

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AI accelerating API development, IBM says

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AI accelerating API development, IBM says
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IBM sees a confluence of generative artificial intelligence and APIs, with AI powering APIs in a way that improves the productivity of API teams.

AI is augmenting skills that API teams may just be starting to learn, said Rashmi Kaushik, director of product management for the integration portfolio at IBM, during a presentation at the API World conference in Santa Clara, California, on November 6. “It’s able to help them complete their API projects faster.” Also, APIs are powering AI, she added. APIs empowering AI and the rise of AI assistance are truly beneficial to API teams, Kaushik said.

Companies such as IBM have released API testing capabilities on traditional AI. But AI is not magic. It has been a technology in the making for many years now and it is here to transform the way business is done, Kaushik said. Regardless of how much AI is leveraged, users want to make sure that it is safe, responsible, and ethical, she said.

IBM offers the API Assistant for IBM API Connect, powered by the watsonx.ai integrated AI platform. It uses generative AI to help API teams accelerate API life-cycle activities for a quicker time to market, the company said. IBM API Assistant automates tasks, enabling teams to focus on higher-value work and innovation, according to IBM. API assistants are able to augment API teams, so they progress faster, Kaushik said.

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Java proposals would boost resistance to quantum computing attacks

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Both proposals warn of the threat posed to information security by advancements in the field of quantum computing. A future large-scale quantum computer could use Shor’s algorithm to compromise the security of widely deployed public-key-based algorithms. Such algorithms are used by the Java platform for activities such as digitally signing JAR (Java archive) files and establishing secure network connections. An attack could be accomplished by a quantum computer using Shor’s algorithm in hours. Cryptographers have responded to this threat by inventing quantum-resistant algorithms that cannot be defeated by Shor’s algorithm. Switching to quantum-resistant algorithms is urgent, even if large-scale quantum computers do not yet exist.

Each of the two proposals is eyed for the Standard Edition of Java, but neither is targeted for a specific version at this point. Both proposals were created August 26 and updated November 6.

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Serverless computing’s second act | InfoWorld

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Despite these issues, the hype train was at full speed. For example, a large provider took issue with me pointing out some of the shortcomings of this “new” serverless technology. Instead of addressing the problems, they called for my immediate firing due to blasphemous comments. I hit a nerve. Why was that? The cloud providers promoting serverless should have had more confidence in their technology. They knew the challenges. I was right about serverless then, right when I wrote its decline. However, I’m always willing to reevaluate my position as technology evolves. I believe in redemption.

A technological comeback

Despite its early hurdles, serverless computing has bounced back, driven by a confluence of evolving developer needs and technological advancements. Major cloud providers such as AWS, Microsoft Azure, and Google Cloud have poured substantial resources into serverless technologies to provide enhancements that address earlier criticisms.

For instance, improvements in debugging tools, better handling of cold starts, and new monitoring capabilities are now part of the serverless ecosystem. Additionally, integrating artificial intelligence and machine learning promises to expand the possibilities of serverless applications, making them seem more innovative and responsive.

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Java app security would get a boost through quantum resistance

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Java application security would be enhanced through a couple of proposals to resist quantum computing attacks, one plan involving digital signatures and the other key encapsulation.

The two proposals reside in the OpenJDK JEP (JDK Enhancement Proposal) index. One proposal, titled “Quantum-Resistant Module-Lattice-Based Digital Signature Algorithm,” calls for enhancing the security of Java applications by providing an implementation of the quantum-resistant Module-Latticed-Based Digital Signature Algorithm (ML-DSA). Digital signatures are used to detect unauthorized modifications to data and to authenticate the identity of signatories. ML-DSA is designed to be secure against future quantum computing attacks. It has been standardized by the United States National Institute of Standards and Technology (NIST) in FIPS 204.

The other proposal, “Quantum-Resistant Module-Lattice-Based Key Encapsulation Mechanism,” calls for enhancing application security by providing an implementation of the quantum-resistant Module-Lattice-Based Key Encapsulation Mechanism (ML-KEM). KEMs are used to secure symmetric keys over insecure communication channels using public key cryptography. ML-KEM is designed to be secure against future quantum computing attacks and has been standardized by NIST in FIPS 203.

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IBM: APIs getting AI boost

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IBM: APIs getting AI boost
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IBM sees a confluence of artificial intelligence and APIs, with AI powering APIs in a way that improves the productivity of API teams.

AI is augmenting skills that API teams may just be starting to learn, said Rashmi Kaushik, director of product management for the integration portfolio at IBM, during a presentation at the API World conference in Santa Clara, California, on November 6. “It’s able to help them complete their API projects faster.”  Also, APIs are powering AI, she added. AI empowering APIs and the rise of AI assistance are truly beneficial to API teams, Kaushik said.

Companies such as IBM have released API testing capabilities on traditional AI. But AI is not magic. It has been a technology in the making for many years now and it is here to transform the way business is done, Kaushik said. Regardless of how much AI is leveraged, users want to make sure that it is safe, responsible, and ethical, she said.

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GitHub Copilot learns new tricks

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GitHub Copilot learns new tricks
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You start with an existing project and the details of build tools and frameworks, along with a target Java version (for example upgrading from Java 8 to Java 21). The Copilot upgrade assistant analyses your code base and generates a list of the necessary steps to run your upgrade, presenting it as a set of GitHub issues that you can check before running the update.

Once you’re happy with the tasks, the tool takes you to a dashboard where you can watch the update process, including how Copilot rewrites code for you. You can stop and start the process at any time, drilling down into tasks for more information on just how the AI-based code is working. It’s good to have this level of transparency, as you need to be able to trust the AI, especially when it’s working on business-critical software.

As this is an agentic AI process, the service can detect errors and fix them, launching sub-agents that make changes, rebuild, and retest code. Interestingly if a fix doesn’t work, it’ll take another approach, using the shared knowledge of the Java developers whose work has been used to train the Copilot Java model. Like other GitHub Copilots, changes that work are used to fine-tune the model, reducing the risk of errors in future runs. That goes for manual updates and changes too.

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‘Package confusion’ attack against NPM used to trick developers into downloading malware

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‘Package confusion’ attack against NPM used to trick developers into downloading malware
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In other words, there is no single address, IP, or server to block. That said, there are downsides to the technique that are not mentioned by Checkmarx, including the fact that blockchain communication is slow, as well as public. The blockchains can’t be edited, or blocked easily, but they can be tracked once their use as part of malware C2 has been uncovered. 

Despite past predictions that the technique would take off, this is probably why using blockchains for C2 remains the experimental preserve of specialist malware.

Package confusion

Perhaps the more significant part of the story is that the technique is being used to target testing tools distributed via NPM, the largest open source JavaScript registry. Targeting testing tools is another way to get inside the privileged developer testing environments, and any deeper access to the CI/CD pipelines that they reveal.

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.NET vector data abstractions library now available in preview

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.NET vector data abstractions library now available in preview
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Microsoft has introduced its Microsoft.Extensions.VectorData.Abstractions library, now in preview. The library provides abstractions to help integrate vector stores into .NET applications and libraries.

The vector data abstractions library, introduced October 29, provides library authors and developers with the ability to perform create-read-update-delete (CRUD) operations and use vector and text search on vector stores.

Vector databases are important for search tasks and grounding AI responses, Microsoft said. These databases are built to store, index, and manage data represented as embedding factors. As a result, the indexing algorithms used by vector databases are optimized to retrieve data that can be used downstream in applications.

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