programming

9 Tech YouTube channels to follow

Discover nine tech-focused YouTube channels covering topics such as programming, machine learning, cybersecurity, blockchain and Web3.

Learning tech via YouTube channels can be a great way to supplement traditional learning methods, as it provides a more interactive and engaging experience. Many YouTube channels dedicated to tech provide in-depth tutorials and explanations of complex concepts in a way that is easy to understand, making it accessible to learners of all skill levels.

Additionally, YouTube channels often provide access to industry experts, giving learners the opportunity to learn from individuals with real-world experience and knowledge. For instance, Cointelegraph’s YouTube channel provides news, interviews and analysis on the latest developments in the cryptocurrency and blockchain industries. The channel’s content is well-produced and features engaging visuals, making it an accessible and entertaining way to learn about these topics.

Here are nine other YouTube channels to follow and learn beyond cryptocurrencies.

Ivan on Tech 

Ivan on Tech is a popular YouTube channel focused on blockchain technology, cryptocurrencies and decentralized applications (DApps). The channel is hosted by Ivan Liljeqvist, a software developer and blockchain expert.

Liljeqvist offers educational material on his YouTube channel on a range of subjects relating to blockchain technology, such as crypto trading, the creation of smart contracts, decentralized finance (DeFi) and more. Also, he offers updates on the most recent events and trends in the sector.

Liljeqvist also maintains an online school called Ivan on Tech Academy in addition to his YouTube channel. This school includes classes on blockchain development, cryptocurrency trading and other relevant subjects.

Andreas Antonopoulos

Andreas Antonopoulos’ YouTube channel is an invaluable resource for anyone seeking in-depth knowledge and insights into Bitcoin (BTC) and cryptocurrencies, featuring a wealth of informative talks, interviews and Q&A sessions.

Antonopoulos is a renowned advocate, speaker and author in the field of Bitcoin and cryptocurrencies. He is widely regarded as a leading expert on blockchain technology and has written several books on the subject, including Mastering Bitcoin and The Internet of Money.

He is renowned for his fervent defense of decentralized systems and his capacity to concisely and clearly convey difficult ideas. Since the beginning of cryptocurrencies and blockchain technology, Antonopoulos has been a vocal proponent of their development and use.

Crypto Daily 

Crypto Daily is a popular YouTube channel dedicated to providing daily news, analysis and commentary on the world of cryptocurrencies. With over 500,000 subscribers, the channel covers a broad range of topics, from the latest developments in cryptocurrencies to initial coin offerings and blockchain technology.

James, the host of the channel, makes his insights interesting for both inexperienced and seasoned crypto aficionados by combining wit, humor and intellect in his delivery. The channel also offers interviews with industry leaders, product reviews and educational content, making it a well-rounded resource for anybody interested in the world of cryptocurrency.

Cybersecurity Ventures 

Cybersecurity Ventures is a YouTube channel focused on providing educational content on cybersecurity, cybercrime and cyberwarfare. The channel offers in-depth analyses of new trends and technology, news updates on the most recent cyber threats and assaults, and interviews with top industry experts.

The channel, which has over 20,000 members, offers guidance and best practices for people and businesses wishing to safeguard themselves against online risks, making it a useful tool for both inexperienced and seasoned cybersecurity professionals.

Related: Top 10 most famous computer programmers of all time

Machine Learning Mastery

Machine Learning Mastery also has a YouTube channel that complements its website by providing video tutorials on machine learning topics. The channel, which is hosted by Jason Brownlee, provides a range of content, including lessons, interviews with business leaders, and discussions of the most recent developments and difficulties in the field of machine learning.

The videos are well-made and very educational, covering everything from the fundamentals of machine learning to more complex subjects, such as neural networks and computer vision. The channel, which complements the substantial materials already offered on the Machine Learning Masters website, has a growing subscriber base and is a great resource for anybody wishing to learn about machine learning in a visual format.

Two Minute Papers 

Two Minute Papers is a popular YouTube channel that summarizes and explains complex research papers in the fields of artificial intelligence, machine learning and computer graphics in two minutes or less. 

The channel, hosted by Károly Zsolnai-Fehér, provides an easy way to stay up-to-date on the most recent developments and discoveries in these areas. The professionally made videos include simple visual explanations and can help viewers understand even the most challenging studies.

In order to personalize the information, Two Minute Papers also includes interviews with researchers and subject-matter experts. Two Minute Papers, a popular and useful resource for people interested in cutting-edge research and advancements in AI and related subjects, has more than 1.5 million subscribers.

 Web3 Foundation

The Web3 Foundation is a nonprofit organization dedicated to supporting and building the decentralized web, also known as Web3. Its YouTube channel provides educational content and updates on the latest developments in Web3 technology, including blockchain, distributed systems and peer-to-peer networks.

Related: What are peer-to-peer (P2P) blockchain networks, and how do they work?

The channel offers talks by prominent authorities in the field, including programmers, researchers and businesspeople, as well as discussions and interviews on subjects pertaining to Web3 technology. Also, it provides updates on the progress of the Polkadot network, an open-source platform for constructing interoperable blockchain networks. Overall, the Web3 Foundation YouTube channel is a great resource for anyone interested in the decentralized web’s future because it has over 20,000 followers.

Dapp University 

Dapp University’s YouTube channel complements its educational platform by providing video tutorials on blockchain development, smart contracts and decentralized application (DApp) development. Hosted by developer and entrepreneur Gregory McCubbin, the channel features clear and concise explanations of complex topics in blockchain technology, making it accessible to beginners and experts alike.

The videos cover a wide range of topics, including Ethereum, Solidity and other blockchain tools and technologies. With over 300,000 subscribers, the Dapp University YouTube channel is a valuable resource for individuals looking to learn how to develop decentralized applications on the blockchain.

Tech With Tim

Tech With Tim is a popular YouTube channel dedicated to teaching programming and computer science concepts to beginners and intermediate learners. The channel offers tutorials on a range of programming languages, including Python, Java and C++, as well as web development, game development and machine learning.

It is hosted by Tim Ruscica, a software engineer and seasoned tutor. The well-produced videos have straightforward explanations and examples of programming topics, making them understandable to a variety of students. Tech With Tim is a great resource for anybody wishing to learn programming and computer science skills, with more than 800,000 members.

OpenBazaar marketplace says it’s set to ‘grow again from the ashes’

After shutting down in 2020 due to financial issues and poor user growth, the decentralized marketplace appears set to rise again.

The decentralized marketplace OpenBazaar appears set for a comeback after it was shut down over two years ago, according to a number of social media and GitHub updates.

A GitHub repository on the collaborative software development site shows progress as recent as April 12 on building a new version of the marketplace which was shut down in 2020.

Brian Hoffman, the former project lead at OpenBazaar and CEO of OB1 — the for-profit company which developed its software — tweeted on April 9 of the progress made on a “new” version of the marketplace saying it is “getting more interesting by the day.”

In the replies, Hoffman was asked how the marketplace would be different this timegiven that due to financial issues and poor user growth, OpenBazaar was forced to shut down.

Hoffman replied speaking of “freedom of exploration” and inferred that outside influence had contributed to its initial downfall.

The first hints that OpenBazaar would be launching a comeback came in a tweet from Hoffman on March 28, where he linked OpenBazaar’s GitHub page that showed he’d been working on a new version of the marketplace in the programming language Rust.

Just hours later OpenBazaar’s official account also posted a Tweet, which said “it is now time to grow again from the ashes,” and that “work has begun.”

Adding to the evidence that the marketplace appears likely to relaunch, the OpenBazaar website currently bears the message “openbazaar 3.0 – coming soon.”

Related: 5 programming languages to learn for AI development

After the exchange had shut down in 2020, Hoffman tweeted that a future iteration of OpenBazaar would require more independence from OB1, but provided no more information about how this might work.

OpenBazaar has been hailed as the decentralized eBay alternative and was first launched back in 2014. It allowed users to interact directly with each other to make transactions using Bitcoin (BTC).

The marketplace initially had the name “DarkMarket,” but changed it to OpenBazaar following community input in an attempt to improve its public image.

Cointelegraph contacted Hoffman and OpenBazaar for comment but did not immediately receive a response.

Hodler’s Digest, April 2-8: BTC white paper hidden on macOS, Binance loses AUS license and DOGE news

OpenBazaar marketplace says it’s set to ‘grow again from the ashes’

After shutting down in 2020 due to financial issues and poor user growth, the decentralized marketplace appears set to rise again.

The decentralized marketplace OpenBazaar appears set for a comeback after it was shut down over two years ago, according to a number of social media and GitHub updates.

A GitHub repository on the collaborative software development site shows progress as recent as April 12 on building a new version of the marketplace, which was shut down in 2020.

Brian Hoffman, the former project lead at OpenBazaar and CEO of OB1 — the for-profit company that developed its software — tweeted on April 9 of the progress made on a “new” version of the marketplace, saying it is “getting more interesting by the day.”

In the replies, Hoffman was asked how the marketplace would be different this time, given that OpenBazaar was previously forced to shut down due to financial issues and poor user growth.

Hoffman replied speaking of “freedom of exploration” and inferred that outside influence had contributed to its initial downfall.

The first hints that OpenBazaar would be launching a comeback came in a tweet from Hoffman on March 28, where he linked OpenBazaar’s GitHub page that showed he’d been working on a new version of the marketplace using the programming language Rust.

Just hours later OpenBazaar’s official account also posted a tweet saying that “it is now time to grow again from the ashes,” and that “work has begun.”

Adding to the evidence that the marketplace appears likely to relaunch, the OpenBazaar website currently bears the message “openbazaar 3.0 – coming soon.”

Related: 5 programming languages to learn for AI development

After the exchange had shut down in 2020, Hoffman tweeted that a future iteration of OpenBazaar would require more independence from OB1, but provided no more information about how this might work.

Hailed as a decentralized eBay alternative, OpenBazaar was first launched back in 2014. It allowed users to interact directly with each other to make transactions using Bitcoin (BTC).

The marketplace initially had the name “DarkMarket,” but changed it to OpenBazaar following community input in an attempt to improve its public image.

Cointelegraph contacted Hoffman and OpenBazaar for comment but did not immediately receive a response.

Hodler’s Digest, April 2-8: BTC white paper hidden on macOS, Binance loses AUS license and DOGE news

How to solve coding problems using ChatGPT?

ChatGPT, the AI language model, can assist in breaking down complex coding problems and finding efficient solutions.

Here’s how one can use ChatGPT’s abilities to solve coding problems:

  • Identify the problem: The first step is to identify the problem that you need to solve. Once you have identified the problem, you can start thinking about how to solve it.
  • Break the problem down: The next step is to break the problem down into smaller, more manageable pieces. This will help developers or programmers understand the problem better and make it easier to solve.
  • Research: Once you have broken the problem down, you may need to do some research to find out how to solve each part of the problem. So, you can use ChatGPT to search for information about coding algorithms, concepts and programming languages.
  • Create a plan: Once developers or programmers have researched the problem, they can create a plan to solve it.
  • Write the code: With a plan in place, you can start writing the code to solve the problem. And you can use ChatGPT to generate code snippets, check syntax and help debug the code.
  • Test and debug: Once you have written the code, they should test it to make sure it works as expected. In case of any errors, ChatGPT can help them debug the code.
  • Refine and optimize: After developers or programmers have tested their code, they may need to refine and optimize it to make it faster or more efficient, for which they can use ChatGPT.

Here are some examples of coding problems that you could solve using ChatGPT.

What kind of coding problems can be solved using ChatGPT?

Various problems that can be solved using ChatGPT are discussed below:

Syntax error

Syntax errors occur when the code violates the rules of the programming language. For example, forgetting to close a parenthesis or quotation mark can result in a syntax error. The following code shows an example of a syntax error:

This code produces a syntax error because the quotation mark is not closed. To solve this error, you can add the missing quotation mark and closing parenthasis as shown below:

Type error

Type errors occur when you try to perform an operation on a value that is not of the correct type. For example, trying to add a string to an integer can result in a type error. The following code shows an example of a type error:

This code produces a type error because you cannot add a string to an integer. To solve this error, you can convert the string to an integer using the int() function as shown below:

Name error

A name error occurs when the interpreter or compiler cannot find a definition for a particular name (variable, function, class, etc.) that is being used in the code.

This can happen for a variety of reasons, including the name is misspelled or incorrectly capitalized, the name has not been defined yet or has been removed from the code, or the name is defined in a different scope or module than where it is being used. The following code shows an example of a name error:

This code produces a name error because x has not been defined. To solve this error, you can define x and assign a value to it as shown below:

Index error

Index errors occur when you try to access an element of a list or array that does not exist. The following code shows an example of an index error:

This code produces an index error because “my_list” only has three elements, and you are trying to access the fourth element (which does not exist). To solve this error, you can access one of the existing elements of the list as shown below:

Reference error

A reference error occurs due to a variable or function not being declared. The solution is to declare the variable or function before referencing it. For example, let’s say we have the following code that causes a reference error because the variable “myVariable” has not been declared:

To fix this, we need to declare the variable before referencing it:

Top 10 most famous computer programmers of all time

Computer programming has made the impossible possible. Read about the top 10 computer programmers to date.

For computer programs and mobile applications, programmers must develop code. In order to keep things working properly, they are also involved in maintaining, debugging and troubleshooting software and systems.

Here is a brief overview of the top 10 most famous computer programmers of all time.

Alan Turing

Alan Turing was a British mathematician and computer scientist who contributed significantly to the growth of artificial intelligence, cryptography and computer science. He helped decipher the Enigma code during World War II and introduced the idea of the Turing Machine, a theoretical representation of a computer.

Turing also contributed to the creation of the Manchester Baby, the first stored-program computer and the basis for contemporary computing. He is widely regarded as the father of theoretical computer science and artificial intelligence.

Ada Lovelace

Many people consider Ada Lovelace, an English mathematician and writer, to be the first ever computer programmer. She understood the creative potential of computing and realized that computers could do more than just crunch numbers, creating the first published algorithm designed to be processed by a machine.

Lovelace has motivated countless generations of women to work in the fields of science and technology and is honored today for her contributions to the history of computing.

Bill Gates

Bill Gates is a software developer, businessman and philanthropist most well known for founding Microsoft, the world’s largest personal computer software company. He was crucial to the development of the PC and transformed the computer software market.

Under his direction, Microsoft created several successful lines of software, including the well-known Windows operating system, which eventually overtook other PC platforms. In addition, Gates founded the Bill and Melinda Gates Foundation to help improve global health and education.

Steve Jobs

Steve Jobs co-founded Apple and played a crucial role in developing the Macintosh, iPod, iPhone, and iPad. With his ground-breaking innovations and striking design aesthetics, he changed the PC, music and mobile phone sectors as well as popularized the graphical user interface. Jobs was a dynamic, forward-thinking leader who encouraged and motivated his team to develop and introduce successful products.

Jobs’ technical know-how and love for design and marketing contributed to Apple’s success as one of the world’s most cutting-edge and prosperous technological businesses. Numerous people acknowledge his influence on technology, and his legacy continues to motivate future generations of entrepreneurs and tech enthusiasts.

Linus Torvalds

Linus Torvalds developed the Linux operating system, which is frequently found running servers, supercomputers and mobile devices. He began Linux as a side project, but it has since expanded into an extensive global development collaboration.

In addition, he is the principal architect of the Linux kernel, the foundational element of the Linux operating system. Torvalds has won numerous honors for his contributions to the open-source software movement, and Linux has grown to be one of the most significant, well-known software projects in history.

Mark Zuckerberg

Mark Zuckerberg co-founded Facebook, one of the world’s most widely used social networking sites. He played a crucial role in building its infrastructure and turning the startup into a multibillion-dollar corporation now known as Meta. He has been instrumental in connecting people across the world through the platform, enabling them to share information, news and personal experiences.

Meta is currently working on several projects and initiatives to make its vision of the metaverse a reality, including the Meta Quest (formally Oculus Quest) virtual reality headsets, Horizon Worlds and Meta Horizon. In addition to Meta, Zuckerberg has worked on charitable projects, including the Chan Zuckerberg Initiative, which aims to advance human potential and promote equal opportunity.

Related: What is metaverse in blockchain? A beginner’s guide on an internet-enabled virtual world

Guido van Rossum

Computer programmer Guido van Rossum created the Python programming language in 1989. In addition to being the language’s original implementer, he actively participated in its growth and made numerous significant contributions to its functionality, community of users and design.

In July 2018, he left his post as the Python community’s “benevolent dictator for life” (BDFL).

Bjarne Stroustrup

Early in the 1980s, Danish computer scientist and professor Bjarne Stroustrup developed the C++ programming language. C++, one of the most popular programming languages in the world, was created by him to add object-oriented capabilities to the C language.

Stroustrup has made numerous key contributions to the design and features of the C++ language and is still actively involved in its development and progress.

Tim Berners-Lee

British computer scientist Tim Berners-Lee is widely recognized as the creator of the World Wide Web. In the early 1990s, he created the first web browser and server software and expanded on the idea of hypertext, which made it possible to create connected documents and the modern web.

Berners-Lee, who currently serves as the president of the World Wide Web Consortium — the leading international standards body for the Web — has been a significant proponent of the open Web and continues to work on its advancement and accessibility.

Related: What is Web 3.0: A beginner’s guide to the decentralized internet of the future

Dennis Ritchie

American computer scientist Dennis Ritchie was instrumental in creating the Unix operating system and the C programming language. While working at Bell Labs in the late 1960s and early 1970s, he co-created Unix, and his contributions to the development of the C programming language helped make it one of the world’s most widely used programming languages.

Ritchie is widely considered a pioneer of modern computing, and his work has had a significant impact on the computer science industry.

How to improve your coding skills using ChatGPT

ChatGPT can generate code snippets and solutions to coding problems quickly and efficiently. Here’s how.

As a language model, ChatGPT is primarily used for natural language processing tasks such as text generation and language understanding. While it can be used to generate code samples, it’s not designed to help improve coding skills. However, here are a few ways ChatGPT can be used to help improve coding skills.

Practice explaining coding concepts

Use ChatGPT to explain coding concepts and algorithms to help solidify one’s understanding of them. This can also help users identify areas where they may need to study further.

For instance, when using ChatGPT to practice explaining coding concepts, one can input a prompt that describes a specific coding concept or algorithm, such as “Explain how a hash table works” or “How does the quicksort algorithm work?”

ChatGPT will then generate a response that explains the concept in a clear and concise manner, using natural language. This can help users understand the concept better by hearing it explained in different ways and also help them identify areas where they may need to do further study.

One can also use this approach to practice explaining coding concepts to others, which can be an important skill for technical communication and teaching. By reviewing the output generated by ChatGPT, users can identify areas where they might need to improve their explanations and practice different ways to present the information.

Generate code snippets

ChatGPT can be used to generate code snippets based on certain inputs. This can be useful as a starting point for one’s coding projects or to help understand how a certain function or algorithm works.

To use ChatGPT for this purpose, users can input a prompt that describes the code snippet they want to generate, such as “generate a Python function to reverse a string” or “generate JavaScript code for a simple calculator.”

Related: 10 ways blockchain developers can use ChatGPT

ChatGPT will then generate a code snippet based on the input prompt, and the output will be coherent and functional code that one can use as a reference or starting point for their project. However, keep in mind that the code generated by ChatGPT may require some modifications and debugging to fit one’s specific use case or project requirements. Additionally, users should always review and test the code before using it in a production environment.

Research and learning

ChatGPT can be used for coding research and learning by inputting prompts that ask for information on a specific technology or programming language. For example, one can input a prompt like “What are the key features of Python 3.0?” or “What are the best practices for writing efficient JavaScript code?”

ChatGPT will then generate a response that summarizes the key concepts and information users need to know about the topic, which they can use as a starting point for their research and learning. Additionally, they can use the generated output as a reference, while they are learning the new technology or language.

Related: How to learn Web3 development for beginners

Nonetheless, while ChatGPT can provide a good starting point, it’s not a substitute for hands-on practice and in-depth learning. It’s essential to supplement the information provided by ChatGPT with additional resources and practice.

Practice coding challenges

By entering prompts that outline a challenge or problem that users desire to tackle, ChatGPT can be used to practice coding problems. For example, one can input a prompt like “Write a function that finds the second largest element in an array” or “Create a script that takes a string and returns the number of vowels in it.” ChatGPT will then generate a response that includes a code snippet that solves the problem or challenge.

One can then use the generated code as a reference and try to implement the solution on their own, comparing their code with the generated one. This can help users practice their coding skills and improve their understanding of specific concepts or algorithms. Additionally, users can modify the generated code to fit their specific needs or to add more complexity to the problem.

It is critical to note that while ChatGPT can generate functional code, it’s not a substitute for hands-on practice and learning. Reviewing the generated code and trying to implement the solution on their own will help users solidify their understanding of the concepts and algorithms used. Additionally, users should always test and debug the code before using it in a production environment.

Collaborate with other developers

ChatGPT can be used to collaborate with other developers by inputting prompts that describe a specific coding problem or challenge and then sharing the generated response with other developers for review and feedback. For example, one can input a prompt like “I am having trouble with this function; can you help me optimize it?” along with the code snippet and share it with other developers. They can then use the generated response to provide feedback and suggestions on how to improve the code.

ChatGPT can also be used to generate detailed explanations of the code, which can be helpful when working on a team or trying to understand the code written by others. Additionally, ChatGPT can be used to generate comments and documentation for the code, which can make it easier for other developers to understand and maintain the codebase.

Programming languages prevent mainstream DeFi

Asset-oriented programming makes fundamental functions native to the programming language. DeFi needs more of that to improve security.

Decentralized finance (DeFi) is growing fast. Total value locked, a measure of money managed by DeFi protocols, has grown from $10 billion to a little more than $40 billion over the last two years after peaking at $180 billion.

Total value locked in DeFi as of Nov. 2022. Source: DefiLlama

The elephant in the room? More than $10 billion was lost to hacks and exploits in 2021 alone. Feeding that elephant: Today’s smart contract programming languages fail to provide adequate features to create and manage assets — also known as “tokens.” For DeFi to become mainstream, programming languages must provide asset-oriented features to make DeFi smart contract development more secure and intuitive.

Current DeFi programming languages have no concept of assets

Solutions that could help reduce DeFi’s perennial hacks include auditing code. To an extent, audits work. Of the 10 largest DeFi hacks in history (give or take), nine of the projects weren’t audited. But throwing more resources at the problem is like putting more engines in a car with square wheels: it can go a bit faster, but there is a fundamental problem at play.

The problem: Programming languages used for DeFi today, such as Solidity, have no concept of what an asset is. Assets such as tokens and nonfungible tokens (NFTs) exist only as a variable (numbers that can change) in a smart contract such as with Ethereum’s ERC-20. The protections and validations that define how the variable should behave, e.g., that it shouldn’t be spent twice, it shouldn’t be drained by an unauthorized user, that transfers should always balance and net to zero — all need to be implemented by the developer from scratch, for every single smart contract.

Related: Developers could have prevented crypto’s 2022 hacks if they took basic security measures

As smart contracts get more complex, so too are the required protections and validations. People are human. Mistakes happen. Bugs happen. Money gets lost.

A case in point: Compound, one of the most blue-chip of DeFi protocols, was exploited to the tune of $80 million in September 2021. Why? The smart contract contained a “>” instead of a “>=.”

The knock-on effect

For smart contracts to interact with one another, such as a user swapping a token with a different one, messages are sent to each of the smart contracts to update their list of internal variables.

The result is a complex balancing act. Ensuring that all interactions with the smart contract are handled correctly falls entirely on the DeFi developer. Since there are no innate guardrails built into Solidity and the Ethereum Virtual Machine (EVM), DeFi developers must design and implement all the required protections and validations themselves.

Related: Developers need to stop crypto hackers or face regulation in 2023

So DeFi developers spend nearly all their time making sure their code is secure. And double-checking it — and triple checking it — to the extent that some developers report that they spend up to 90% of their time on validations and testing and only 10% of their time building features and functionality.

With the majority of developer time spent battling unsecure code, compounded with a shortage of developers, how has DeFi grown so quickly? Apparently, there is demand for self-sovereign, permissionless and automated forms of programmable money, despite the challenges and risks of providing it today. Now, imagine how much innovation could be unleashed if DeFi developers could focus their productivity on features and not failures. The kind of innovation that might allow a fledgling $46 billion industry to disrupt an industry as large as, well, the $468 trillion of global finance.

Total assets of global financial institutions from 2002 to 2020. Source: Statista

Innovation and safety

The key to DeFi being both innovative and safe stems from the same source: Give developers an easy way to create and interact with assets and make assets and their intuitive behavior a native feature. Any asset created should always behave predictably and in line with common sense financial principles.

In the asset-oriented programming paradigm, creating an asset is as easy as calling a native function. The platform knows what an asset is: .initial_supply_fungible(1000) creates a fungible token with a fixed supply of 1000 (beyond supply, many more token configuration options are available as well) while functions such as .take and .put take tokens from somewhere and put them elsewhere.

Instead of developers writing complex logic instructing smart contracts to update lists of variables with all the error-checking that entails, in asset-oriented programming, operations that anyone would intuitively expect as fundamental to DeFi are native functions of the language. Tokens can’t be lost or drained because asset-oriented programming guarantees they can’t.

This is how you get both innovation and safety in DeFi. And this is how you change the perception of the mainstream public from one where DeFi is the wild west to one where DeFi is where you have to put your savings, as otherwise, you’re losing out.

Ben Far is head of partnerships at RDX Works, the core developer of the Radix protocol. Prior to RDX Works, he held managerial positions at PwC and Deloitte, where he served clients on matters relating to the governance, audit, risk management and regulation of financial technology. He holds a bachelor of arts in geography and economics and a master’s degree in mapping software and analytics from the University of Leeds.

The author, who disclosed his identity to Cointelegraph, used a pseudonym for this article. This article is for general information purposes and is not intended to be and should not be taken as legal or investment advice. The views, thoughts, and opinions expressed here are the author’s alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.

DEX accidentally hits kill switch on mainnet, locking 660,000 USDC inside

The deployment of a program upgrade went terribly wrong as a fateful “Solana program close” command stopped OptiFi’s platform indefinitely.

A decentralized cryptocurrency (D options exchange cut its own life short after unwittingly executing a command that closed its mainnet program and made it irrecoverable.

OptiFi informed users that its platform had come to an unceremonious end after its development team tried to update its code on Monday. According to the decentralized exchange, the program incident also locked up some 660,000 USD Coin (USDC) on-chain.

OptiFi has pledged to compensate user funds lost by the error, while a large bulk of the locked-up USDC was reportedly vested by one of its team members. The company has also urged other developers working on the Solana blockchain to be wary of the ramifications of the “Solana program close” command.

In a Medium post, the platform unpacked the series of events that led to the sudden closure of its mainnet. It began with an attempt to deploy an update to its Solana program code.

The deployment took longer than usual due to what the team described as bad network status, and the command was canceled. However, a buffer address was created that received SOL the team wanted to recover.

Related: Aave community proposes to temporarily suspend ETH lending before the Merge

In the past, the team managed to recover SOL from buffer accounts without using memory phrases by closing the program. The approach initially looked to have worked after executing the command, as the team recovered the SOL, allowing them to attempt to deploy the program a second time.

An error message was returned indicating that the program had been closed and could not be redeployed unless a new program ID was used. Discussions with a Solana core developer confirmed the team’s fears that it would not be able to redeploy the program with its previous ID.

“Here it turned out that we didn’t really understand the impact and risk of this closing program command line. ‘solana program close’ is actually for closing the program permanently and sending the SOL tokens in the buffer account used by the program back to the recipient wallet.”

The OptiFi team has called for the Solana development community to explore two-step confirmation when running the “Solana program close” function and caution users of the results of using the command.