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Rethinking the Computer-Human Relationship – Solutions Review

As part of Solutions Reviews Contributed Content Seriesa collection of contributed articles written by ourenterprise tech thought leader communityVaibhav Vohra, the Chief Product and Technology Officer at Epicor, delves into the concept of rethinking the computer-human relationship in the ERP marketplace.

Computer scientists have been discussing the imminent arrival of human-centric computing for decades. It sounds great on paper but less so in practice. Yes, computers and technology have utterly transformed workplace productivity. But every day bears witness to a frustrating reality: instead of machines serving humans, its usually the other way around. Over the years, our servitude has only grown worse.

The futuristMichael L. Dertouzos, who used to run MITs Laboratory for Computer Science, wrote eloquently about this challenge, noting that all too often, it seemed as if the advanced systems we built were in charge, not us. Whether we were talking about coding languages, scripts, or firmware, machines invariably restricted how we spoke with them.

But thats not to say were condemned to imagine a future perennially beyond reach. With the advent of artificial intelligence (AI), we now have an opportunity to remake the current computing paradigm so that machines work with us in ways that are more convenient to humans. Lets see how this might unfold in the ERP world, where customers face several common challenges.

Even though ERP contains troves of information, its often a struggle to access data and systems of record. Its also not easy to get ERP systems to answer discrete questions so they can provide insights. This is a backward approach. Machines should be sending customers updates on things that really matter.

So, as we design a world around us in the shadow of AI, we can realistically think about flipping the script. We dont need to be locked into the position of supplicants having to beg the machine with questions to complete our tasks. We can reimagine a future in which machines learn how to work more effectively with people, sending us the information that matters most, knowing what we need to know, and understanding our jobs.

The industry has been making progress toward that goal. For instance, the last ten years of ERP and cloud computing have brought better data security, privacy, and scalabilityall critical to enterprises. However, that work needs to continue to empower workers further so they can make smarter decisions.

The overarching goal should be to turn the interaction into more of a real conversation rather than a one-way, screen-based diktat. That starts by equipping the people who do the actual work with better tools. And this is happening as we speak. Researchers are now developing different applications of AI to help promote these changes. With better data models and queries at their disposal, users will benefit from systems that mitigate AIs infamous tendency to hallucinate and so get their ERP to provide more accurate results. Another area of focus will be to make ERP systems searchable so that customers can deploy natural language processing.

As we build systems to engage with robots, sensors, and machines and connect to other software, the world of ERP is rapidly changing. Were now at the point where we can transform ERP. Instead of a massively complex system of records, we can think about a people-centric, easy-to-use system of insights and actions.

AI will help power this shift thanks to its ability to predict whats most important to us. Changing how we interact with machines will make systems easier to use and more useful. Whats more, well allow newly empowered workers to engage with systems through natural language to derive important signals with alerts, whether they be pricing, supply chain, or productivity trends.

Instead of focusing on tasks such as getting access to the correct data, machine, or supply chain insight (a current challenge with all ERPs), newly empowered workers will be able to focus on higher-value functionsinnovating new products, creating new business models, and redesigning processes to become more efficient. In other words, it is a tool for anyone and everyone who has an essential job to do.

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Tech Tools for the Future: Zebras, AI, and Girls in ICT Day – CSRwire.com

Published 04-19-24

Submitted by Cisco Systems, Inc.

Im excited to announce that Dr. Tanya Berger-Wolf will be joining our special Women Rock-IT broadcast to support International Girls in ICT Day, featuring women who have turned their passion for technology into rewarding and successful careers.

Dr. Tanya Berger-Wolf is the Director of theTranslational Data Analytics Instituteand a Professor of Computer Science Engineering, Electrical and Computer Engineering, as well as Evolution, Ecology, and Organismal Biology at the Ohio State University (OSU).

As a computational ecologist, Tanyas research is at the unique intersection of computer science, wildlife biology, and social sciences. She will speak on International Girls in ICT Day, hosted by Cisco Networking Academys Women Rock-IT Program. The theme for this years event is Are You AI Ready? And for those who may not be aware, AI stands for Artificial Intelligence, which is what Tanya is going to be sharing more about.

Q: What was your motivation to get into computer science, and what was your path to get there?

A: I always wanted to do math. I even declared that when I was five in front of my whole family. So I went straight for math, eventually realizing that the type of math I like is the math thats the foundation of computer science. I went on to do a theoretical computer science PhD, designing algorithms and doing proofs.

Along the way I met an ecologist who is now my husband and partner. He really charmed me with stories of industrious spiders and shy flowers and took me on nature walks to try to get me over my fear of bugs.

I intentionally switched from a very theoretical computer science PhD to designing computational methods for answering ecological questions.

A zebras friend

Q: What inspired you to focus on using AI in conservation and what keeps you motivated in the face of the ongoing extinction crisis?

A: There is both the challenge and the inspiration that keeps me going.

The way I got started in conservation was really on a bet. I was working with biologists who study social behavior of animals such as zebras. I got really curious about how they know who a zebras friend is.

After watching them take 20 minutes just to identify one individual zebra using the available technology at the time, the impatient engineer in me said that there had to be a better way of doing it.

They said, you think you can do better? And I said, yeah, you want to bet?

I literally bet my reputation on being able to identify an individual zebra from a photograph easily.

AI for conservation

The first algorithm we created was developed into an even better algorithm, which we are still curious about. But it turned out it could be very useful in conservation for things like tracking animals, counting them, and even figuring out whos a zebra or a sperm whales friend without putting collars or satellite tags on them.

We realized that we needed to build that technology in a way that non-technical people could use, without becoming AI experts in the process.

And thats how Wildbook was born. Having started creating AI technology for conservation, we realized three things:

The challenge and urgency keep me going. And most importantly, theres something meaningful that we can do with AI.

How important are digital and AI skills?

Q: How important is it for people to include digital skills in their future education and professional development plans? And why is it so important?

A: I think AI is becoming very quickly a part of pretty much everything that we use and touch. So AI literacy is becoming the basic skill that should be taught in school and everybody should have.

It is particularly important in being able to solve complex problems like biodiversity conservation. Because it is not a problem thats going to be solved by AI alone or by humans alone. The answer truly is in partnership: the human-machine partnership.

And to be able to partner well with AI, we need to know what that partner is capable of and whats the best way to have that partnership. And that means having skills that allow us to use AI, to understand AI, and even more importantly, to understand the potential of AI.

Q: What is your advice for any young women starting out in computer science?

A: Not everybody has to do computer science, but anybody who wants to, should have an opportunity to do so. And even more, everybody should have an opportunity to explore it.

Computer science is about getting machines to affect the world. For example, with a few lines of text, we can create a 3D view of the brain with an MRI machine, or understand the past through an ancient genome, or predict the path of a hurricane. This creative process of coding is exciting to me.

Accessible AI and ML learning

Q: AI/Machine learning (ML) has been a subject of academic study for more than half a century. Why was last year such a milestone for this type of technology?

A: Last year it exploded, not because of the algorithm or the math, but its about how you make that accessible.

Two things happened simultaneously. Firstly, there was a buildup of data availablewith many caveats and asterisks that were now revisiting. And secondly, modern machine learning is data hungry.

When you have the hardware to run these complex models and the data to feed it, you can start capturing the complexity of the world. But it would have been esoteric if not for this brilliant interface that allows everybody to interact with it.

And thats a huge lesson if you want to make any piece of technology useful. Its not about the technology itself, per se, its about how you make it a partner, how you really make it accessible.

Observe. Experiment.

Q: Conservation of nature often faces complex questions about the natural world. Can AI help?

A: In Henri Poincars book Science and Method, he says what we now call the scientific method consists of observation and experiment. And all that a scientist needs to do is look carefully at everything.

AI doesnt fundamentally change the scientific method. It is still observation and experiment. But just like the microscope, the telescope, or genome sequencing, it expands the types of things that scientists can look at.

The fundamental thing that ML and more broadly AI approaches do is extract complex patterns and complex relationships. So, we can not only look at more things, but we can also look carefully at the complexity of the world.

The role of public data

Q: Does publicly available data help in this quest?

A: There is a lot of publicly available data from digitized biological collections, field studies, and citizen scientists. But the most untapped data by far is from social media posts. People love taking pictures of nature, sometimes unintentionally capturing trees and grass, bugs and spiders.

Theres a lot of information already there but it is disconnected and disorganized, so were not taking advantage of it. And we need AIs help to get useful insights from all of it.

Q: Can AI help discover the undiscovered?

A: If we want to discover new things about the world, we need to take a completely different computational philosophical approach and a new design framework of algorithms.

How do we design interpretable, novelty-discovering, computational approaches that produce a testable hypothesis as an outcome?

Maybe you already have your massive species classification from an images model? Well, good for you! But were interested in using these news tools and frameworks to discover something new. A new species? A new trait? A new relationship?

This is one of my favorite quotes from Ada Lovelace, who invented the notion of programming in the 1830s:

We talk much of imagination. We talk of the imagination of poets, the imagination of artists etcetera. I am inclined to think that in general we dont know very exactly what we are talking about. It is that which penetrates into the unseen world around us, the world of science. It is that which feels and discovers what is, the real which we see not, which exists not for our senses. Those who have learned to walk on the threshold of the unknown worlds may then with the fair white wings of imagination hope to soar further into the unexplored amidst which we live.

Register now for the Women Rock-IT virtual event on April 25!

Are You AI-Ready? Unlocking natures secrets: How AI & Data save wildlife and benefit humanity

Check registration page for your local broadcast time.

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Chainlink debuts new protocol aimed at boosting cross-chain interoperability – Cointelegraph

Chainlinks Cross-Chain Interoperability Protocol (CCIP) has entered general availability with the aim of fostering more cross-chain connectivity.

The protocol lets developers permissionlessly use CCIP for cross-chain token transfers and arbitrary smart contract messaging across different blockchain networks.

Developers will also be able to send and trigger function calls on smart contracts deployed on other blockchains, making cross-chain smart contracts more interoperable.

CCIPs mainnet general availability will enable a faster and easier implementation for developers, bolstering cross-chain connectivity, according to Sergey Nazarov, co-founder of Chainlink.

In an announcement shared with Cointelegraph, Nazarov wrote:

Cross-chain bridges help users facilitate transactions between different blockchain networks. They represent some of the most significant points of vulnerability in crypto.

Chainlink is among the largest firms working on cross-chain interoperability, which is among the most pressing shortcomings of the industry since individual blockchain networks have no means to communicate with each other without interoperability solutions.

At the beginning of April, Chainlink launched Transporter, a cross-chain messaging app for bridging tokens, aiming to foster more secure cross-chain crypto transfers with a beginner-friendly app interface.

Chainlinks Transporter is underpinned by CCIP, which is the only cross-chain protocol that achieves level-5 security, according to a Chainlink spokesperson.

CCIP is available on nine blockchains, including Arbitrum, Avalanche, Base, BNB Chain, Ethereum, Kroma, Optimism, Polygon and WEMIX, with plans to integrate more networks.

CCIP aims to help financial institutions unlock the $500 trillion opportunity in tokenized assets, by offering better liquidity access for cross-chain assets, a Chainlink spokesperson told Cointelegraph:

Related: Money-hungry VCs are bad for token launches in the long term Analyst

Due to their technical complexity, cross-chain bridges represent some of the biggest points of vulnerability in todays crypto protocols.

Since 2016, over $5.85 billion worth of cryptocurrency has been stolen from decentralized finance (DeFi) protocols. Cross-chain bridges account for over 48%, or $2.83 billion, of the total value lost to exploits, according to DefiLlama data.

Ethereum co-founder Vitalik Buterin has criticized cross-chain infrastructure in the past. In a Reddit post from January 2022, Buterin shared his concerns about how 51% attacks on cross-chain bridges will become more prevalent in the future:

Related: Bitcoin outperforms Tesla stock for the first time since 2019

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AI-Powered Cryptocurrencies On The Rise But Self-Learning Smart Contracts Raise Data Protection Concerns – CCN.com

Key Takeaways

AI-powered coins are making waves in the cryptocurrency sphere, marking a revolutionary convergence of artificial intelligence and blockchain technologies. These innovative digital assets harness AI algorithms to bolster blockchain security, scalability, and functionality.

However, the rise of self-learning smart contracts alongside AI-powered crypto has raised concerns regarding data protection.

AI cryptocurrencies represent a groundbreaking fusion of AI and blockchain technologies. These digital assets leverage AI algorithms to enhance blockchain security, scalability, and functionality, distinguishing them from traditional cryptocurrencies primarily used for exchange.

The increasing popularity of AI crypto coins, exemplified by pioneers like SingularityNET (AGI), Fetch.ai (FET), and Numeraire (NMR), can be attributed to several factors. Firstly, decentralization grants users financial autonomy by operating on decentralized blockchain networks, eliminating intermediaries, and bolstering transparency and security.

Secondly, investors are attracted to cryptocurrency markets for their potential for significant returns on investment. Leading AI crypto coins and tokens, such as Cortex (CTXC) and DeepBrain Chain (DBC), demonstrate how projects leveraging AI algorithms entice investors seeking high-growth opportunities.

Lastly, cryptocurrencies borderless nature enables seamless cross-border transactions, which is ideal for global commerce and remittance. Combined with low transaction costs and efficiency, this feature appeals to individuals and businesses worldwide.

Many AI-focused companies behind AI-powered cryptocurrencies have recently developed self-learning smart contracts, sparking concerns among users regarding data protection.

These smart contracts for data privacy have broad applications across various domains and scenarios, including healthcare, finance, education, and social media. For instance, in healthcare, they empower patients to manage their medical records and monetize their data securely. In finance, they safeguard customers financial data and authenticate identities without revealing personal information. In education, they manage students academic records and validate their skills without compromising identity. Similarly, in social media, they offer users control over their data and the ability to monetize it.

However, several challenges arise with integrating AI into smart contract development. AI algorithms used in smart contract development may pose security and privacy concerns, particularly regarding access to sensitive contract and transaction data. Ensuring compliance with relevant data protection regulations, as advised by solidity.io, is crucial in this context.

Moreover, the integration of AI may raise legal and regulatory compliance issues. Developers must ensure that AI usage in smart contract development aligns with applicable laws and regulations.

Additional challenges include scalability and interoperability. The computational resources and network bandwidth required for blockchain storage and processing can impact scalability, and compatibility issues with different blockchains, platforms, or systems may hinder interoperability.

Furthermore, legal and regulatory frameworks may not universally recognize or enforce smart contracts, leading to uncertainty or disputes over data rights, obligations, or liabilities. Conflicting laws or regulations regarding data privacy across jurisdictions may further complicate compliance and validity of smart contracts, as highlighted by algorithm architect Raghuram K Ravi.

On the other hand, self-learning contracts offer a comprehensive solution to data privacy concerns through several mechanisms. Firstly, they empower data ownership and control by enabling parties to specify access permissions and conditions for data usage and modification. For instance, a smart contract can restrict data access to authorized parties or limit access duration and purpose.

Secondly, smart contracts may enhance data security by encrypting data and storing it on a decentralized network resistant to tampering or hacking. For example, data can be encrypted using a public key and only decrypted by the party possessing the corresponding private key.

Smart contracts facilitate data sharing and collaboration by establishing trustless mechanisms for data exchange, validation, and analysis. They enable secure data sharing without revealing parties identities or locations and support data analysis without exposing raw data.

Smart contracts decentralize data storage and ensure an immutable record. Their self-executing nature ensures consistent data handling, validated by blockchain consensus mechanisms. Encrypted data protection further strengthens privacy, mitigating risks associated with centralized data management. This amalgamation of features reinforces data privacy, making smart contracts an ideal solution for securing sensitive information across diverse applications.

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Cartesi to Host Community Call on May 6th – TradingView

Coindar

Cartesi will host a community call on Discord on May 6th.

CTSI Info

Cartesi (CTSI) is a blockchain project aiming to make the development and deployment of decentralized applications (DApps) more practical and scalable. It does this by enabling smart contracts to run off-chain computations in a Linux environment, which opens up the possibility to use mainstream programming languages and software, as well as access larger amounts of data more efficiently.

The fundamental piece of technology behind Cartesi is the Descartes SDK, a software development kit that provides a set of tools and services to help developers build scalable and secure DApps. With Descartes, computations can be intensive and incorporate complex business logic as they are executed off-chain in a Linux environment.

The Cartesi token (CTSI) serves multiple utility purposes within the Cartesi ecosystem. It is used as a staking mechanism in the network's Proof-of-Stake (PoS) consensus algorithm, and also as a means to pay for computational resources within the network. In addition, it's used in the network's incentive system for data availability and computation verification.

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Digital collective restores carbon market credibility through immutable smart contracts – GlobeNewswire

London, April 24, 2024 (GLOBE NEWSWIRE) -- ZERO13, the COP28 award-winning international carbon exchange, registry and aggregation hub ecosystem, part of GMEX group, is collaborating with Decarb.earth, CarbonCX and XTCC, to provide the worlds first end-to-end digitally measured, reported and verified carbon credit distribution, trading and settlement solution for renewable energy projects.

The digital climate fintech platform-as-a-service recently enabled 14,591 carbon credits, including those from GoSolr (Pty) Ltd in South Africa, to be successfully distributed, traded and settled via ZERO13 on the SECDEX Marketplace for spot carbon credits and regulated securities markets via XTCC structured products.

The high-integrity voluntary carbon credit solution maximises market value and distribution in a way which instils trust by digitally verified provenance to address the issues of greenwashing and double-counting through:

Hirander Misra, Chairman and CEO of GMEX Group and ZERO13, commented: With a multi-blockchain network-of-networks approach encompassing the diverse capabilities of our partners Decarb.earth, CarbonCX and XTCC, the ZERO13 ecosystem enables digital carbon credits, backed by smart contracts, to be officially accredited, issued, traded and settled to support the advancement of renewable energy technologies that are crucial for a sustainable future.

Marco Funk, CEO of Decarb.earth, added: There cannot be a just and swift energy transition without transparency. The carbon credit market has been fraught with controversies of low-quality credits and doubtful existence. In this context, working with ZERO13, we are absolutely delighted to offer this first of its kind fully digital end-to-end carbon credit solution for renewable energy projects. With these VCCs having now been credited, audited, verified, registered and sold, a low-carbon energy future - within time - looks ever more likely.

Dave Tims, Founder and Head of Strategy for CarbonCX Inc. said: CarbonCX is pleased to announce the completion of this first sale of digital carbon credits from African solar energy projects registered to its next-generation carbon credit platform. The sale occurred on the ZERO13 distribution platform into the SECDEX Marketplace, which is setting the global standard forefficient trading, exchange matching and real-time settlement of traditional and digital carbon credits.Working closely with ZERO13 and its industry-leading project partner, Decarb.earth, we are also settingthe standard for data recording, security and transparency related to digital carbon credits in multiple regions.

Scott Levy, Founder of XTCC, said: Decarb.earth represents a perfect example of the circularity benefits which came from investing with XTCC.By creating liquidity for the high-integrity carbon credits, Decarb.earth will also be encouraged to further their efforts to deliver impact in the social housing sector for example. Measurable community benefits are crucial to investor confidence and transparency; XTCC, ZERO13 and Decarb.earth are a unique example of how connecting to the capital markets liquidity can transform lives.

ZERO13 is an infrastructure-agnostic and cloud-native platform that ensures flexibility in deployment. Functioning as a decentralised hub, the ecosystem orchestrates workflows across multiple exchanges, participants, custodians, registries and climate fintech services. It seamlessly integrates digital monitoring, reporting and verification providers delivering real-time asset checks on carbon offset supplies and project provenance analysis. It also enables end-to-end multi-market distribution across multiple blockchains and APIs to ensure successful trading and settlement, interconnecting silos and addressing the inadequacies of the stand-alone voluntary carbon market (VCM) model.

Since its launch, ZERO13 has expanded its interoperable network of networks and grown its partnerships and customer base, bridging climate tech and climate fintech firms to over 60 participants, with continued rapid expansion and increased transaction flows through the platform and its associated network.

- ENDS -

Media Contact

GMEX Group and ZERO13Alice Ellman-Brown, The Realization Group Tel: +44 (0)7365 224804 alice.ellman-brown@therealizationgroup.com/pr@gmex-group.com

About ZERO13

ZERO13, an award winning GMEX Group (GMEX) initiative, is a market leading automated AI and blockchain-driven international carbon exchange, registry, and aggregation hub ecosystem. Accessed as a Platform as a Service (PaaS), the ZERO13 Hub offers a distributed point of entry for digital issuance, trading, and settlement of carbon credits and real-world assets such as ESG securities with an approach based on interoperability of multiple blockchains and APIs.

ZERO13 Hub connects multiple international carbon exchanges, registries, custodians, and ESG project owners for supply verification, transparent pricing, and real-time settlement. Connections are via APIs and blockchains enabled by ZERO13 Chain (Pyctor).

GMEXs Pyctor technology has been harnessed to extend ZERO13 Hubs Platform-as-a-Service (PaaS) capabilities and to power ZERO13 Chain as a multi-blockchain and multi-API interoperable network of networks. This is an effective and robust mechanism for settling various assets, optimising Delivery versus Payment (DvP) contracts through native integration for token deposits.

ZERO13 industry recognition awards include:

For further information on ZERO13, please visithttps://www.zero13.net/.

About CarbonCX

Working closely with companies deploying various technologies and activities to reduce baseline carbon emissions, CarbonCX captures, processes, aggregates and homogenizes voluntary carbon reduction efforts into standardized units recorded on the blockchain. CarbonCX technology automatically verifies, calculates and aggregates the associated carbon benefit, programmatically mints Carbon Reduction Credits in standardized allotments, and provides management tools for reporting, retiring, or listing on various emerging voluntary Carbon Credit exchanges or marketplaces.

For further information on CarbonCX, please visithttps://carboncx.io/.

About Decarb.earth

Decarb.earth is at the forefront of sustainability initiatives, driving positive change by generating carbon credits, spotlighting cleaner companies, and facilitating the transition to solar energy. With CarbonCX accreditation, Decarb.earth stands as a beacon for businesses seeking comprehensive clean energy solutions to remain competitive in a rapidly evolving market.

About XTCC

XTCC is an investment product for professional investors. XTCC includes investment products that offer a transparent, credible and sustainable avenue for investors to participate in the rapidly expanding high-integrity carbon credit market, closing the gap in the circularity ecosystem that leads to further growth and the development of new renewable energy projects. The XTCC universe includes multi-currency variants for Solar, Blue Carbon, Biomass, Biogas, Hydro, Wind and Biomethanation.

For more information, visit:http://xtcc.investmentsor contactir@xtcc.investments

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Bitcoin covenants are coming OP_CAT gets formally introduced as BIP-420 – Crypto Briefing

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The OP_CAT covenant proposal has been formally introduced as BIP-420, with the aim of enabling smart contracts, secure bridges, and on-chain trading on the Bitcoin network.

The proposal, authored by Ethan Heilman and Armin Sabouri, seeks to reintroduce the OP_CAT opcode to Bitcoin via a backward-compatible soft fork by redefining the opcode OP_SUCCESS126. This is the same opcode value used by the original OP_CAT, which was disabled by Satoshi Nakamoto in 2010 due to concerns surrounding potential vulnerabilities.

BIP-420 enables covenants on bitcoin, allowing for smart contracts, secure bridges, on-chain trading, zk proof verification and more, OP_CAT advocate and co-founder of Taproot Wizards Udi Wertheimer said.

Covenants on Bitcoin are advanced scripting features that allow for specific conditions on how bitcoins can be spent in future transactions. They could enable use cases such as creating secure vaults for reversible transactions, automated recurring payments, time-locked transfers for inheritance, and complex financial instruments like escrows and bonds.

In this sense, Bitcoin covenants currently exist as proposed mechanisms to enforce the conditions on how BTC will be transferred in the future. They serve as a set of rules that govern how a particular Bitcoin can be spent, adding an extra layer of security and functionality to the network. Bitcoin covenants operate through Bitcoins scripting language, setting forth conditions that must be met for a Bitcoin transaction to be processed.

There are different types of covenants, each with its own set of advantages and disadvantages. The most common types include:

Value-based covenants: restricts the value of the output of a transaction.

Address-based covenants: restricts the address of the output of a transaction.

Script-based covenants: restricts the script of the output of a transaction.

Bitcoin covenants could revolutionize the way we use Bitcoin today by enabling a wider range of financial products and services to be built on top of the Bitcoin network. They could make Bitcoin more versatile, allowing for more complex transactions and smart contracts.

However, the implementation of Bitcoin covenants is not without challenges. The primary risks include potential issues with fungibility, added complexity, and the introduction of new security vulnerabilities. The concept of covenants in Bitcoin has been discussed since at least 2013.

According to the proposal, the OP_CAT opcode would simplify and expand Bitcoins functionalities, making decentralized protocols more practical and supporting advanced multi-sig setups. Essentially, OP_CAT would significantly increase the power and flexibility of Bitcoin scripting, making it easier to develop more sophisticated applications directly on the Bitcoin blockchain.

Notably, the chances of an OP_CAT soft fork actually happening depends on a combination of factors that include technical capacities from the core developers, on-chain security considerations, and community consensus.

OP_CAT is not the only Bitcoin covenant proposal under discussion though. Other proposals include Check Template Verify (CTV), OP_CHECKSIGFROMSTACK (CSFS), and LNHANCE, each varying in its approach and trade-offs and at different stages of research and debate.

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Crypto Custody Firm Fireblocks Now Offers DeFi Threat Detection for Institutions – TradingView

Cryptocurrency custody specialist Fireblocks is helping institutions exploring decentralized finance (DeFi) from interacting with bad actors and falling victim to malicious attacks with new threat detection and smart contract evaluation tools.

Fireblocks dApp Protection and Transaction Simulation products, which have been in beta testing since December of last year with Galaxy and Flowdesk, are now available to check decentralized applications across over 40 blockchains via WalletConnect, Fireblocks browser extension, and MetaMask Institutional.

There has been a recent surge of interest in DeFi sometimes described as a playground for hackers thanks to a steady increase in crypto asset prices. Institutions are increasingly exploring swapping, lending, staking and bridging using popular platforms like Uniswap, Aave, Curve, 1inch and Jupiter.

Some Fireblocks customers have their own dedicated Web3 research team, but most people need to scale their operations and dont necessarily have the resources to hire cybersecurity experts who also understand DeFi and Web3, said Shahar Madar, VP of security products at Fireblocks.

The solution looks for suspicious smart contracts, phishing websites, and compromised dApps by identifying malicious patterns such as imitative URLs, harmful javascript elements, and suspicious registrars.

Weve mapped out the user journey of a DeFi and Web3 trader, Madar said in an interview. Usually, it starts when you scan with your phone and connect to a dApp and are asked to start signing transactions. We put mitigations and detection mechanisms throughout this journey. For instance, we scan the transaction, we scan the counterparty, we try to make sense of the contract, and also offer transaction simulation, essentially giving you the bottom line of what you should be expecting.

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Optimism Leads New Crypto Wave as it Tops Developer Activity Table, Thanks to Ethereum Dencun Upgrade – CCN.com

Key Takeaways

Ethereums efficiency-focused Layer-2 (L2), Optimism, is now the leading protocol by developer activity and 7-day net flows following Ethereums Dencun upgrade. This move comes less than two years after the platforms launch.

It has beaten Cardano, Polkadot, and other reputable chains that have long-dominated the market. But can Ethereums upgrades continue to boost Optimisms capabilities and vice versa?

Developer activity on Ethereums L2 scaling platform, Optimism, has pushed it to the top of the rankings according to the latest data from Santiment.

Optimism is a comparatively young product. Within a couple of years since launching its Open Mainnet, its overtaken the likes of Polkadot, Kusama, Hedera, and even Cardano. According to DeFi Llama, the number of core developers and Github commits has now begun to skyrocket, whilst total-value-locked (TVL) continues a steady and healthy climb.

The Optimism protocol was already proving itself popular among L2s, as evidenced by the 300,000+ transactions a day processed on its mainnet throughout 2023, and the spike of activity on March 2024 following Ethereums Dencun upgrade.

L2 platforms on Ethereum, which were struggling under the weight of the networks bottlenecks, received a huge boost in efficiency following the Dencun (EIP-4844) upgrade.

Among Dencuns numerous upgrades were new ways of processing transactions and handling data. These were proto-danksharding and Data Blobs.

With these in place, gas fees for L2 transactions shrunk considerably. According to Dune, the gas volumes consumed to settle/proof L2 activity on Ethereum fell off a cliff following the upgrade.

Considering Optimism is an L2 designed to help other projects scale on Ethereum, it was already markedly cheaper than other protocols. The Dencun upgrade amplified that efficiency even further, which is a huge draw for developers.

With the Bitcoin Halving and Dencun upgrade behind us, investors are beginning to feel confident in the markets once more. Notably, Optimism is also leading the charge in terms of venture capital funding having secured $89 million in a recent private token sale.

Furthermore, the latest seven-day net flow data shows that Optimism is consuming a large portion of Ethereums net flows.

If Ethereum continues to focus on increasing its efficiency, Optimism may continue to dominate L2 developer activity.

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Optimism Leads New Crypto Wave as it Tops Developer Activity Table, Thanks to Ethereum Dencun Upgrade - CCN.com

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Ethereum price data points to strong resistance at $3.5K – Cointelegraph

Ether (ETH) experienced a significant drop of 14.8% between April 13 and April 14 and has since been trading below $3,300. Each time the price of ETH tested the $3,000 level, buyers intervened, strengthening the support. However, some traders remain concerned that ETH might not reclaim $3,500 without a stronger narrative.

Analyst DeFiSurfer808 suggests that Ether's price weakness compared to Bitcoin (BTC) stems from a lack of fresh fundamentals, as the Ethereum native token lacks "some new narrative and flows."

Over the past two months, Ether underperformed Bitcoin by 16%, a trend that intensified on April 9 after Jan van Eck, the chief investment officer of VanEck investment firm, mentioned that U.S. requests for a spot Ether ETF might be rejected in May. Van Ecks comments follow a period of inaction by the U.S. SEC concerning seven pending applications for spot Ether ETFs, as reported by Cointelegraph.

Even if Ether is classified as a non-security asset, ongoing disputes between regulators and exchanges dampen investors enthusiasm for the broader Ethereum ecosystem, including layer-2 solutions, decentralized finance (DeFi), and nonfungible token (NFT) marketplaces.

On April 11, Uniswap Labs announced that it was "ready to fight" after receiving a potential enforcement notice from the U.S. Securities and Exchange Commission (SEC). Although Uniswap Labs did not disclose the precise details of the Wells notice, it asserted in a blog post that UNI was not a security and emphasized that its platform does not meet U.S. legal definitions of a securities exchange or broker.

Meanwhile, the regulatory landscape appears to be shifting. Michael Welsh and Joseph Watkins, lead SEC attorneys in the lawsuit against crypto platform DEBT Box, resigned on April 22 after a Bloomberg report revealed findings of "gross abuse" of power in the case. In March, federal Judge Robert J. Shelby penalized the SEC for making false statements and misrepresentations in its lawsuit.

Additionally, the Blockchain Association and the Crypto Freedom Alliance of Texas have initiated a lawsuit against the SEC in the Northern District of Texas. They are challenging the regulator's broad interpretation of the term "dealer" within the Securities Exchange Act of 1934, claiming that this expansion creates a vague and burdensome regulatory landscape for digital asset businesses.

Related: Ripple contests $2B SEC fine, says penalty shouldnt exceed $10M

On April 23, Ether's price rose above $3,200, supported by increased demand for Ethereum decentralized applications (DApps). According to DefiLlama, the networks smart contract deposits, measured by the total value locked (TVL), reached their highest level since July 2022 at 30.2 million ETH on April 22, marking an 8% increase from the previous month.

Highlights of Ethereum's TVL growth include innovative platforms such as EigenLayer staking solution, the decentralized exchange Uniswap, automated yield provider Pendle, and Renzo, a liquid staking application. In contrast, the Tron blockchain's TVL saw a 5% decrease in TRX (TRX) terms over the past 30 days, with its largest DeFi application, JustLend, experiencing an 11% reduction in deposits.

To understand if professional traders flipped bearish after Ethers price underperformance, one should use the ETH options 25% delta skew as a proxy. A skew metric rising above 7% indicates anticipations of a price drop, whereas a negative 7% skew typically reflects bullish sentiment.

The Ether options skew metric showed an increase between April 9 and April 18, suggesting that traders were becoming less risk-averse. However, this trend reversed on April 19 as ETH traded below $3,000. Current data reveal a balanced dynamic between call (buy) and put (sell) options, indicating a neutral market sentiment.

On-chain metrics for Ethereum and ETH derivatives demonstrate resilience, even though Ethers price has recently struggled to maintain the $3,000 support level. Nevertheless, it seems premature to anticipate a bull run surpassing $3,500, given the subdued investor enthusiasm regarding the prospects for a U.S. spot Ethereum ETF approval.

This article does not contain investment advice or recommendations. Every investment and trading move involves risk, and readers should conduct their own research when making a decision.

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