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Initial Coin Offerings (ICO) have been a popular way to fundraise projects in the crypto market, but that changed with the advent of regulations. Since then, Initial Exchange Offering (IEO) and Initial DEX Offering (IDO) have entered the market. But with the rise of blockchain games or GameFi, the latest buzz in the town is Initial Game Offering (IGO). We will look at the top 3 things you need to know about Initial Game Offerings in this article. So, without further ado, let's dive straight into it. What is IGO? Much like ICOs and IEOs, IGO is also a fundraising event for crypto gaming projects where participants get assets needed to play the game. Some IGOs also offer in-game rewards. However, it depends on a participant's investment. Simply put, that allows investors to invest in a gaming project at its early development stage. What this fundraising method does is that it lowers the barrier to entry for retail investors by enabling them to get their hands on the in-game assets and tokens before they are made available to the public. IGO is a crowdfunding approach for crypto games While the crypto game project gets the funding directly from its audience, investors get lucrative in-game assets and tokens at a considerable discount before the public sale. A significant benefit of IGOs is that it is open to all investors. The growing interest and popularity of this fundraising type have encouraged tremendous growth in the blockchain gaming space. For instance, Binance's centralized fundraising platform Binance Launchpad was the one behind the launch of the most notable gaming project Axie Infinity. A Look into Launchpads IGOs are organized through specialized platforms known as launchpad platforms. The platform you chose is crucial for the success of an IGO. This means that the platform history, success rate, amount of money raised, and time taken to achieve the funding target must be analyzed. Currently, we are at Listing.Help work with several launchpads that are hosting IGOs: 1 — GameFi was one of the first launchpads to introduce the concept of IGOs. It has four investment tiers, but only one offers guaranteed allocation. One needs a minimum of one lottery ticket, which is equivalent to 20 GAFI tokens. KABY Pool and Deathroad IGO are two popular offerings on the platform. 2 — Binance NFT is another one where IGOs grant access to exclusive in-game assets. The platform uses a subscription system to give all users an equal opportunity to participate. To ensure fairness, NFTs are allocated via public and verifiable algorithmic selection. 3 — A popular IGO launchpad Seedify Fund is governed by a DAO. As for participating in Seedify IGOs, you need between 250 and 100,000 Seedify (SFUND) tokens. The platform has nine tiers. The first one is a lottery tier, while guaranteed allocation starts from tier 2. So far, Seedify has crowdfunded Cyber Trade, Heros Chained, MetaStrike, Penguin Karts, Space, Misfits, Supernova, and other gaming projects. 4 — Enjinstarter is another popular one that has a unique approach to IGO. The ecosystem reserves 75% of IGO tokens for guaranteed allocations, which are then split into three tiers. It operates on a first-come, first-served basis, and investors can participate even with a small holding of at least 1,250 EJS tokens. Age of Tanks, Attack Wagon, Ecia, Gaia Everworld, and PathDAO, among other games, have been crowdfunded on Enjinstarter. 5 — Gamestarter, which has crowdfunded BitHotel, Crypto Fight Club, Dark Frontiers, Demole, and others, allow gaming projects to sell their NFTs or tokens to raise funds. It also has plans to expand beyond the crypto gaming space, as, in the future, Gamestarter will also support INO (Initial NFT Offering). Mechanics of IGO Buying an IGO is a chance to invest in a gaming project early. To participate in such an event, you must purchase the launchpad's native coin and lock it for a certain period of time. These tokens are locked in a pool, and based on the algorithm, the investors would receive either the project tokens or the NFTs required to play the game. In some cases, these tokens and NFTs can be traded outside of the gaming ecosystem on DEXs and NFT marketplaces. Different launchpads have different setups for an IGO, but the typical process involves: Connect your wallet to the launchpad. Select a tier that reflects the value of the investment. Identifying an IGO you want to invest in. It is also better to check whether the launchpad provides guaranteed allocation or not. To qualify for these IGOs, you can apply for Whitelist by going to relevant Launchpad's website, connecting your wallet, and staking the native token. Some platforms also require you to complete KYC. Once you have joined the pool, you can apply for the Whitelist. Raffles are another way launchpads assign assets to investors. To apply for the lottery, go to the launchpad website and ensure you're accessing the correct URL address. Connect your wallet and then join the Lottery by clicking on the button. On selecting the IGO, you'll be all set to participate in the raffle for the upcoming projects. The Crucial Ingredient: Community For an IGO to be successful, the crypto game needs to have a vibrant and strong community rooting for them. A community is usually formed and maintained via popular social media platforms such as Discord, Telegram, and Twitter. In the crypto industry, communities are instrumental in shaping how projects develop and operate. To build a thriving community, a project needs to start with potential members who identify with its envision. The project's focus needs to be on its purpose and members. Members should be involved in every step of the project and empowered through acknowledgment, feedback, and rewards. The beauty of crypto communities is that they are spread worldwide and united by the same idea and purpose. The support of a community ensures the long-term success of a project. Conclusion Crypto gaming projects are already experiencing tremendous growth and a rise in revenue. And IGO is an important part of this success. Although, GameFi help crypto adoption a lot. The recent Chainplay showed that 75% of respondents came to crypto through GameFI. And I think, as crypto goes mainstream and decentralized gaming combined with NFTs gain traction, some established blockchain games have received multimillion-dollar valuations. research The blockchain gaming industry is relatively new but fast-growing. Ultimately, with GameFi on the rise, IGOs can emerge as a viable solution for crypto gaming projects, which are already becoming a mainstay in the industry.

Top 3 Things You Need to Know About Initial Game Offerings (IGOs)

Mergers and acquisitions help drive the business world forward. Those that take place in the cybersecurity industry are no exception. Cybersecurity firm Momentum reported that M&As in cybersecurity in 2021. Around 14 mergers and acquisitions amounted to $1 billion, including deals involving Proofpoint, Avast, Mimecast, and McAfee, among others. hit a whopping $77.5 billion Another major player in the cybersecurity landscape is IBM, which recently announced plans for an upcoming acquisition. Below, learn more about IBM's acquisition of Randori, what this deal means for the future of IBM, and how it will impact the cybersecurity sector. IBM Announces Plans to Acquire Randori At this year's RSA Conference (RSAC), IBM announced plans to acquire a leading attack surface management (ASM) provider and offensive security company Randori, based in the Boston area. Randori seeks to help clients understand what external facing assets they possess, on-site or in the cloud, that attackers may see and prioritize exposures that come with the most risk. IBM acquired Randori to streamline its threat detection and improve its response solutions portfolio. Additionally, the deal is expected to bolster IBM's Hybrid Cloud Strategy, which to all types of clients, such as cost-effectiveness and more value compared to a public cloud-only approach. provides plenty of business benefits Before IBM announced this acquisition, Randori secured more than $30 million in Greenhill, Meijer and FirstBank funding. One benefit of solution is that it is a "hacker-led" company. Clients will experience an authentic cybersecurity incident during simulations. From there, Randori can assist clients in determining previously unknown exposure points that could lead to a data breach and negatively impact their business. Randori's ASM What This Means for IBM Moving Forward There's no denying that companies are grappling with an expanded attack surface. Cybercriminals are also growing to be more sophisticated — some have even __ __to launch their attacks. harnessed the power of AI One beneficial aspect of IBM's acquisition of Randori is timing. IBM recently joined hundreds of other companies and suspended business activity in Russia due to the country's recent attacks on Ukraine. IBM also in Russia in what's being called a "wind-down" of operations. The U.S. federal government also responded to Russia's attacks with punitive economic sanctions, , including banking and financial systems, oil and gas businesses, and the technology sector. began laying off employees targeting vulnerable industries As per IBM's announcement, the company plans on with the extended detection response (XDR) capabilities that come with the IBM Security QRadar. Insights from Randori's software will feed into the QRadar XDR. Security teams will gain more visibility for threat hunting, incident response and intelligent alert triage. integrating Randori's ASM software Additionally, it's expected that Randori's offensive security solution will complement X-Force Red's leading hacker lead offensive security services, another benefit rooted in IBM's acquisition. How Will the IBM Acquisition Impact the Cybersecurity Industry? Combining IBM's deep AI and threat intelligence expertise with Randori's solutions could help provide more cybersecurity solutions to clients and deliver better protection from cyber incidents. Mike Beck, global CISO at DarkTrace, says, "CISOs want solutions that prioritize cyber risks and autonomously harden their environments…businesses are in a constant state of flux and…operational risks are not static. Risk assessment and subsequent hardening must be done in real-time, which is only possible with an AI-driven approach." When companies can leverage the latest digital tools, powered by AI, machine learning, or another emerging technology, to improve their AMS, they're less likely to experience downtime or face critical data breaches lessens. It's vital to take a preventive approach to cybersecurity and managing potential attacks. Consider how beneficial it is for a company to see attacks from the cybercriminal's perspective. With the acquisition, IBM's solutions may become even more valuable to the modern company, regardless of industry. Other IBM Acquisitions Aside from the Randori deal, IBM has acquired three other companies this year. The company is looking to boost its hybrid cloud services and deliver superb AI capabilities to its clients. IBM acquired Sentaca to help them , which is expected to revolutionize the tech industry and provide more use cases for other sectors, such as health care and consumer electronics. The company also acquired Neudesec, a leading Microsoft Azure consultancy firm. prepare for the 5G era In January, IBM acquired Envizi to assist organizations with sustainability initiatives and achieve environmental goals. This specific acquisition could not be any more timely, considering how the climate crisis is a significant issue many companies and the countries they operate in are concerned about. IBM: A Juggernaut Company There's no doubt that IBM is leveraging its power and success to acquire companies and improve their goods and services. Before the Randori deal, its acquisitions were diverse. They sought to achieve unique outcomes, from the 5G tech revolution to addressing climate change. It will be interesting to see how IBM moves forward with Randori and other acquisitions in cybersecurity. It seems as though IBM is making great strides to help its clients achieve their goals, protect themselves and prepare for the world to become even more digital.

What will IBM's Acquisition of Randori Mean for Cybersecurity?

Photo by Fakurian Design on Unsplash What is an IGO? stands for IGO Initial Game Offering. It's similar to ICO – Initial Coin Offering and IDO – Initial DEX Offering. It’s a presale of tokens (available to pre-selected buyers) before they are listed on an exchange. While ICOs and IDOs can be for any type of token/project, IGOs, as the name implies, are only crypto games. The purpose of the IGO is to raise funds for the next stages of the game’s development, marketing, etc. This means investing at a very early stage and of course, this carries some risks as there’s no guarantee that the project will be completed or successful. However, the benefit of investing so early is that you’re buying the token at the lowest possible price and as a result, you can expect the value of the token to go up significantly (5x – 60x in my experience) within the first 48 hours... and potentially even more in the future. The main rule of making big gains (percentage-wise) in crypto is getting in early, before the price pumps… and you cannot get into a project any earlier than this (unless of course, you are one of the devs;). Launchpads You can find upcoming IGOs on launchpads. Launchpads are platforms designed for, well, launching new projects. They can be on different blockchains - Ethereum, BSC, Cardano, etc. Some may have games alongside other projects, while others are focused purely on games. They may have different criteria for accepting new projects and for the potential buyers to get whitelisted (being able to take part in an IGO). Also, some are likely to have more projects listed than others. There are many different launchpads but below are a few examples. Seedify Fund Game Fi Trust Pad Enjinstarter From my point of view, the four main criteria for selecting a launchpad are: 1. How frequently they launch new projects? How much it will cost me i.e. how many launchpad tokens do I have to purchase to have a guaranteed allocation in an IGO. 2. What are their criteria for a guaranteed allocation? The pool weight is your ‘slice of the pie’. It varies with each IGO (depends on how many investors are in the pool, at what tiers and how many tokens are for sale) but you can expect the bottom tier (weight 1-2) to be able to invest sometimes only around 20-30 USD in each IGO, while the top tiers might be able to invest around 3,000-5,000 USD. 3. What is the pool weight for each tier? This means that at lower tiers you certainly won’t become a millionaire anytime soon ;-). That’s the downside of pools that have a relatively low entry for guaranteed allocation – they are very attractive and have a lot of members. But as you can get 30-60x gains, you can turn for example 20 USD into 1,000 USD quite easily, which is still pretty cool  While the price of the tokens in an IGO is low, you have to remember that there’re still gas fees to consider. For example, Binance Smart Chain or Polygon have much lower fees than Ethereum. 4. Which network (blockchain) it’s using? How to Take Part in an IGO? There’s only one way - your wallet address must be on a whitelist, which is usually published a few hours or maybe a day before an IGO (for example on launchpad’s Telegram channel). There are two methods: How to get on the whitelist? Winning a spot in a lottery
. Guaranteed allocation (usually by holding a specific amount of launchpad tokens). Winning a spot in a lottery is pretty self-explanatory ;-). Sometimes the lottery is completely random, in other cases, holding a certain amount of launchpad tokens gives you higher chances of winning. For example, this is the case with Game Fi and Trust Pad. Having a guaranteed allocation is probably what most of us are interested in. It’s usually quite straightforward – you just need enough launchpad tokens in your wallet to qualify for a particular tier. The downside is that the amount is usually quite high, especially for larger allocations. How Does Guaranteed Allocation Work in Practice In this section, I will compare four launchpads (Seedify, Game Fi, Trust Pad and Enjin Starter) and the tiers they offer. Please bear in mind that over time, launchpads may change their tiers and of course the prices of their tokens will also change. Seedify Fund As you can see, you need between 250 and 100,000 SFUND tokens to participate in an IGO on and there are 9 tiers. Seedify Only Tier 1 is a lottery. From Tier 2 onwards (1,000 SFUND) you have guaranteed allocation in every IGO. SFUND token currently trades around 4.3 USD, although it was around 5.3 just a few days ago. At current prices, this means an investment of 4,300 to 430,000 USD for guaranteed allocations. It’s a lot of money but a few good IGOs can make it worthwhile. Also, the prices of many tokens went up a lot recently. I was talking about SFUND on and when the prices were between 2.9 and 3.3 USD (so it’s worth following me there;-) and during the summer market pullback you could easily get it for around 0.3 – 0.6 USD. This means that it was possible to get Tier 3 with around 1,000 USD! my YouTube channel Twitter Game Fi As you can see, has a slightly different approach – only 4 tiers and only the top one has guaranteed allocation. You need between 20 and 500 GAFI tokens, which at the current price of GAFI (68 USD) means anything between 1,360 and 34,000 USD. Game Fi Every 20 GAFI tokens give you one ‘lottery ticket’ so although tiers 1-3 are all lottery, tier 3 gives you a 20 times better chance of getting on the whitelist. Also, as it’s a lottery, the number of spots on the whitelist is known in advance so individual allocations are known upfront and higher than in the case of, for example, Seedify. Tier 1 (Rookie) of Game Fi is similar in allocation to Tier 3 of Seedify, and Tier 3 (Pro) is similar to Tier 7… but, it’s a lottery so you never know if you’ll be able to participate in an IGO. Trust Pad has 9 tiers and as you can see they’re a combination of lotteries with various weighting and guaranteed allocations. Trust Pad TPAD token currently trades around 0.46 USD (although you could get it for as little as 0.07 during the summer), so you need an investment of at least 1,380 USD to participate in the lottery or anything between 5,520 and 85,100 USD to have a guaranteed allocation. Trust Pad is not focused purely on games but there’s still a good number of IGO using it. Enjinstarter has yet another approach. 75% of the pool (the tokens which will be available in the IGO) is reserved for guaranteed allocations split between 3 tiers. Enjinstarter To participate, you have to hold between 25,000 and 500,000 EJS tokens, which at the current price of 0.13 USD amount to 3,250 – 65,000 USD. What’s different is that the remaining 25% of the pool is available to anyone who has at least 1 EJS token in their wallet. This is on the first-come, first-served basis, so it’s not the best solution but it’s nice that there are options available for those who may not necessarily be able to invest thousands into a launchpad coin. Stages of an IGO So how an IGO works in practice? This example is based on a recent launch of Bloktopia on Seedify. All upcoming IGOs are listed on Seedify’s website so you can see when the next one goes live. Private sale is for Tier 6 and above and public sale is for all other tiers. A few hours before the launch a whitelist is published on Seedify’s Telegram. If you have enough SFUND tokens in your wallet and you connected your wallet to Seedify launchpad previously, your wallet address will be on the whitelist. You can also see how much you can invest depending on your tier. These numbers will vary for every IGO. Also, make sure you have enough tokens (in this case BUSD) to purchase tokens during IGO. In the same message, there will be an information when exactly the IGO is taking place. You won’t have to rush as the window is usually 2-3 hours and your allocation is guaranteed (in this example) but you have to make sure you can access your computer in that window, otherwise, you lose your allocation. Once the IGO is live, you simply go to Seedify website and connect with your MetaMask. You will then have to authorise the transaction and pay gas. As it’s on BSC, the fees are very very low – but make sure you have some BNB in your wallet to pay for it! If not all IGO tokens sell, there will be a second phase the next day. This one is on a first-come, first-serve basis and the remaining tokens sell out in a couple of minutes max. You may need to increase your gas fee to have a chance. In that original message on Telegram, there will be also information when the token will be listed on an exchange and what is the vesting period. In the example below, you can see that you will receive 10% of your tokens once the IGO is completed, then 20% per month for the next 3 months and the remaining 30% in the final month. This also varies for each IGO. Sometimes it may be 50% once the IGO is completed and 50% after one month. The slower the release of tokens, the more stable the price as people can’t just dump them all immediately. On the day of listing the token on the exchange, you will find the following info on Telegram. Once you add this contract address manually to your MetaMask (pay attention of the network – the IGO was on BSC but this is a Polygon token so you have to add Polygon network to your MetaMask), the tokens will automatically appear in your wallet. Of course in this case, you will only receive the first 10%. The rest will be transferred after one month etc. Once the token is listed on the exchange, you can monitor the price and decide if you want to hold it or sell it. Selling Tokens In my experience, every IGO is generating profit straight away. For this IGO, I was only Tier 2 so could invest only 20.39 USD but BLOK token went up in value around 60x within the first 48 hours after listing. In other words, I could sell my 10% stake (so 2 USD worth of tokens) for 120 USD. It didn’t make me a millionaire but it’s not a bad result ;-) And I still have 90% of BLOK tokens coming in the next few months. One note – I had to make sure I have some Matic tokens on Polygon network in my MetaMask to pay for gas to sell those BLOK tokens. The fees are very small but still. Also, it’s important that these Matic tokens are on Polygon network, not Ethereum network in your wallet – some tokens can exist on different networks but you cannot just send ERC-20 (Eth) Matic to Polygon address as you’ll burn those tokens! You can use a bridge but the cost of gas makes it quite expensive. Conclusion IGOs present an amazing opportunity to make some serious gains but you have to invest a fair chunk on money in launchpad tokens. But even with much smaller investment you can still have a reliable source of modest income… at least in a bull market ;-). But the biggest opportunity (especially at higher tiers as your investment is more substantial) is the chance to get super early into gaming projects, which not only have a great potential for growth but also are a good hedge against bear market. After all, people will not stop playing games when the market crashes ;-) I hope you found this article helpful and interesting. If you’re interested in crypto tutorials and crypto market commentaries, please check out my channel and follow me on . YouTube Twitter ---- Disclaimer The content covered in this article is NOT to be considered investment advice. I’m NOT a financial adviser. These are only my own speculative opinions, ideas and theories. Do NOT trade or invest based purely upon the information presented in this article. “This article is part of The Gaming Metaverse Writing Contest hosted by HackerNoon in partnership with The Sandbox. Submit your #gaming-metaverse story today for your chance to win up to $2000.”

A Complete Guide to Initial Game Offerings (IGOs)

The Report Program Generator (or RPG for short) is a high-level programming language serves a wide array of business applications and uses. It is an IBM proprietary programming module and a vast majority of its later versions can only be accessed on IBM i- or OS/400-based systems. RPG actually has quite a long history. It was developed by the tech giant IBM in 1959 as the Report Program Generator- a tool that was developed to serve as an alternative for the punch card processing system on the IBM 1401. However, it was subsequently updated to the RPG II following the development of the IBM System/3 in the 1960s. It has since evolved into the high-level language equivalent of COBOL and PL/I. To this day, RPG is still a very popular programming language on the IBMi operating system. RPG IV (also known as ILE RPG) is the most current version of RPG and it is a tool that provides a highly enabling programming environment for AS400 RPG Programmers. When RPG was first developed, the major stronghold that it had was known as the program cycle. Every RPG program executes programs within a hypothetical loop. This loop is able to apply the same program to every file on record. At that time, there will be a comparison between each record and every line in the program. Every line has the choice to either act on the record or not, based on whether that line has an indicator turned on or off. The entire idea of level breaks and matching records is one that is unique to the RPG II language. Ever since System/38 was introduced in 1979, the majority of RPG programmers stopped making use of the cycle and rather opted for the controlling program flow which has standard looping constructs. However, IBM has also continued to provide backward compatibility for the cycle. IBM i RPG Programmers IBM iSeries programmers (or AS400 RPG Programmers, if you will) are specially trained professionals who are trained to use the RPG programming language to manipulate and solve issues. RPG programmers are usually employed by Companies to create codes that can be integrated into business operations in order to ensure a higher level of efficiency. IBM i Application Development On any particular day, an RPG programmer can work on a wide array of tasks, ranging from creating new codes to ensuring the proper maintenance of existing program codes (although existing codes might be written in versions of the RPG code that look slightly different). If you’re looking to hire an RPG Programmer, they can help you with any of the following: Analysis, designing, development and maintenance of the IBM i software written in a wide array of languages, including RPG, RPG ILE, RPG-FREE, and SQL. Following various functional specifications in order to create technical documentation and develop pseudo codes. Either create new RPG programs or strengthen existing ones. In the case of any issues, he can also troubleshoot your business processes to diagnose where the issues are. He also debugs any existing software to locate and solve issues. Implement new codes and bug fixes into the existing software. RPG has a long history… As RPG has been the most reliable language for commercial applications, many updates and versions have helped the IBM i programmers to code easily. After RPG, RPG II rolled with more updates and modifications so that it can be easily run on the smallest IBM systems of that time. These included- IBM 1130, IBM system3, system34 and system36. Later it was also used on bigger systems like system370. The most interesting aspect of RPG II is that it is a fixed format programming language, each and every code should be placed in the respective column in order to generate the right output. RPG II: Next in the line is RPG III which was developed for System38 and other bigger systems. RPGIII was more enhanced and could support new structures like IF END IF, DO loops and subroutines. It was available for the larger systems like IBM system370 with OS VS1. RPGIII: RPGIV was developed in 1994 with and has a lot of enhancements over RPGIII like: RPGIV/RPGLE: Longer field names Source level debugging Date and time support Additional data types (floating point, boolean, pointers) Free-format expressions Built in functions Case tolerance One of the great features of RPGIV is that it is ILE compliant. This means that the programmers have a vast number of functional, performance, maintenance, and productivity benefits apart from the ability to integrate multiple languages. is a free version of ILE format from IBM i V5 and from IBM i V6. RPG5 RPG6 RPG 7 is the latest version of RPG programming language and is widely used industry wide. It is a fully free format from IBM i V7. RPG7: RPG Open Access Handler A handler in any programming language is an event or function created for a certain task. RPG open access handler is an interface or method which handles the communication with the available resources and devices.  Rational open access is a way for RPG programmers to use the RPG I/O model to easily utilize the resources and devices that are not directly supported by RPG. This Open Access provides RPG’s file I/O capabilities, allowing anyone to write innovative I/O handlers to access other devices. Platforms on which RPG rolled out- As we all know the initial versions of RPG were developed for IBM systems like 1401, /360, /3, /32, /34, /36, /38 AS/400 and System i systems. Later on it was enhanced and implemented for and many more. The latest platform developed for RPG compiler is Windows .Net through the WINRPG compiler. Sperry Univac BC/7, the Digital VAX, Siemens BS2000, Univac system 80, Burroughs B700, B1700 Conclusion RPG has a long history, initially developed as a report program generator today this language is counted in one of the finest high level languages like COBOL and PL/I. Having so many versions it has created confusions sometimes but has evolved quite rapidly as compared to any other language. Many organizations which are based on IBM i rely on the latest versions of RPG ( ) to enhance and develop new solutions every now and then. Stable: RPG IV version 7

IBM’s proprietary RPG programming language: An Overview

In a sent on June 8th, IBM’s CEO Arvind Krishna made a bold statement regarding the company’s policy toward facial recognition. “IBM no longer offers general purpose IBM facial recognition or analysis software,” says Krishna. letter to congress “IBM firmly opposes and will not condone uses of any technology, including facial recognition technology offered by other vendors, for mass surveillance, racial profiling, violations of basic human rights and freedoms, or any purpose which is not consistent with our values and Principles of Trust and Transparency.” The company has halted all facial recognition development and disapproves of any technology that could lead to racial profiling. The Problem with Face Recognition The ethics of have been in question for years. However, there has been little to no movement in the enactment of official laws barring the technology. In fact, numerous law enforcement agencies actively use face recognition tech today. As an example, the has an entire section that details how they use facial recognition to catch fugitives, via a global database of images from 160 countries. face recognition technology INTERPOL website However, according to IBM, this technology may not yet be ready for use in law enforcement. “We believe now is the time to begin a national dialogue on whether and how facial recognition technology should be employed by domestic law enforcement agencies,” says Krishna. “Artificial Intelligence is a powerful tool that can help law enforcement keep citizens safe. But vendors and users of Al systems have a shared responsibility to ensure that Al is tested for bias, particularity when used in law enforcement, and that such bias testing is audited and reported.” Bias in Modern Face Recognition Algorithms In December of 2019, The National Institute of Standards and Technology (NIST) published a study which found large variations in accuracy across numerous contemporary face recognition algorithms. False Positives A false positive is when the system says that a face matches an entry in the database, when in fact they are not of the same person. The biggest glaring issue was that Oppositely, they were lowest among Eastern Europeans. The study found that “This effect is generally large, with a factor of 100 more false positives between countries.” false positive rates were much higher among those of African and Asian descent. Additionally, they found that false positives were higher in faces of women, the elderly, and young children. False Negatives A false negative is when the system says that a face does not match any entries in the database, when in fact it is in the database. This is especially dangerous at airports or border crossings. If the system checks individual faces against a criminal database, it could potentially allow dangerous individuals past a security check. The found that and lowest among Caucasians and African Americans. NIST study false negatives were highest among Asians and American Indians How Will IBM’s Boycott on Face Recognition Tech Affect the Industry? IBM has been at the forefront of machine learning development for a long time. Their natural language processing system, IBM Watson, is regarded as one of the best question-and-answer systems in the world. Aside from NLP, IBM has also done impressive work in Computer Vision with . Their advancements have garnered much respect in the AI community, and as a result their voice carries weight. Watson Visual Recognition Positive Impact of IBM’s Stance on Facial Recognition When such a large company takes a strong position on facial recognition, it is bound to make waves. In fact, IBM’s decision already seems to be causing a domino effect in the industry. Following IBM’s announcement, of their own saying they are halting sales of facial recognition technology to American police departments. Microsoft made an announcement On the other hand, other companies may take advantage of IBM halting facial recognition development.  There is now more room in the market for other companies and startups to move in. The worst case scenario is that nothing changes. Companies might continue developing face recognition algorithms to sell to law enforcement agencies, without worrying about the consequences. Final Thoughts Ideally, other developers will start investing more time and money to ensure that their algorithms are free of bias. Hopefully, more companies will take a step back to study the effects of emerging technologies before releasing them. IBM’s CEO believes that the biases that exist in modern facial recognition algorithms warrant a complete halt of their usage. They are calling on governments and vendors to ensure that their algorithms are free of bias before being implemented in vital areas of society, such as law enforcement. Many AI technologies are emerging faster than governments are able to regulate. Hopefully, IBM’s stance paves the way for other large tech companies and startups to think about ethics before advancement. Previously published on: https://lionbridge.ai/articles/why-ibm-decided-to-halt-all-facial-recognition-development/

How IBM's Stance on Face Recognition Will Affect the AI Industry

Hi there! I interned at the Industrial Design Centre, IIT Bombay under Prof. Anirudha Joshi during my second year of undergrad. There I chose to work on project titled: Chorded Keyboard. Applying to professors for a summer internship can often be a confusing and daunting task, more when you don’t have anyone to guide you through the process. The process is easy but fairly long and time-consuming. I am jotting down some points which I followed and which helped me in getting selected. The same application procedure applies to all the other academic institutions as well. Step 1: Start Early, Start Right! Mostly the Professors start receiving emails from students in the month of January which continues up till late February. The final selection of interns is done latest by March/April since usually, the internship duration is from May till July. A good first step here would be to narrow down on your research area of interest: What topics would you like to work on? What are your learning goals? How can you contribute to a Professor's ongoing research or to new research work? Next step would be to look for professors working in research areas similar to your interests. Narrow down on the ones whose projects excite you and start reaching out to them. Now the question that arises is as to What, When and How should one  reach out to a professor? Fret not the next steps will get you there! Step 2: Make your CV/Resume. I can’t stress enough on this one. After your cover letter, the only thing that is going to get you noticed and hence selected is how you present your work in a precise and concise manner in your CV. Sample Resume The hyperlink above will lead you to few actual CVs of some of the top academic students from different departments at IIT Bombay which was shared with me by a fellow senior student there. I used these as a reference while working on structuring my own CV. By looking at these you can get an idea as to what all important points you should mention in your resume and which ones to leave out! Align your previous projects and interests in such a way so that the professor you're applying to will find your profile cut fit for the role. Ideally, your CV should be a one-pager with minimal white spaces and everything should be mentioned in bullet points to reduce the word count. Tip: Make your CV using . PRO TIP: LaTeX Overleaf: Real-time Collaborative Writing and Publishing Tool I found this site super useful and handy. Since we all know that making a CV is a never-ending process that requires constant updates and iterations. On this particular site, you can use the existing templates to begin with, and then make changes to generate your own CV which you can always go back and edit. The best part is that you can share the editing link with someone else, allowing them to view and make changes to your CV in real-time. Step 3: Prepare your Cover Letter A good cover letter increases your chances of getting selected by manifolds. Since most renowned Professors have many students wanting to work under them, a good cover letter will help you in getting noticed among the lot. Since many Professors don’t have the time to go through long e-mails so try to keep the cover letter short. A word count of 150–200 would suffice. Always remember that you have to sell yourself in the best possible way as you can, also it shouldn't feel like you’re boasting. Your cover letter must not look like a copy-paste from somewhere else. I would encourage reading about the professor’s work ( why not? After all, you want to work under him!) and write your cover letter along the lines stating as to how his ongoing project interests you and how you think you can contribute to it further. Mention only selected projects and skills of yours in a line or two which you think are related to the professor’s area of interest. You can find a few sample cover letters . Here Never send your CV as an e-mail attachment. PRO TIP: Usually, the professors don’t have the time to download the CVs and it’s highly probable that once after downloading and reading he might lose the file and later forget. Instead, Upload your CV on Google Drive and get the shareable link to generate a hyperlink for CV in the mail body. Adding the link to an online portfolio site like Behance, Dribble, GitHub, LinkedIn profile, or any online platform which validates your projects and shows your online presence would help. and SHOOT that mail! Step 4: The Follow-up Once you’ve mailed the professor it’s important to wait for at least 7–10 days till you get a reply. Since most professors usually have a busy inbox you can send a reminder mail like the one I sent, shown below. After sending a reminder email, wait for few days and if the professor doesn’t reply then you can send a reminder mail again. Never email Professors of the same department and institution at the same time because it doesn’t look professional but, You can mail Professors of different institutions and departments simultaneously. TIP: Make sure that not many students from your college/course are mailing the same professor at the same time. Otherwise, chances are high that you won’t get a reply and the professor will end up marking it as spam. Step 5: Repeat! If you don’t get any reply or acceptance for a particular application (which is highly likely to happen!) email the next professor on your list, until you get a confirmation. In my case, I wanted to work under Prof. Anirudha Joshi. Hence, I never applied to any other professor rather I invested my time to align my CV and Cover Letter after going through his research work. If you would like to get in touch to talk more, please reach out to me on LinkedIn . Alternatively, you can also email your queries to contact@simranpandey.com . I send out a newsletter every month answering your questions on any topic — sign up here . Thank you so much for reading till here :) Happy learning! Previously published at https://medium.com/@simranpandey97/how-to-get-a-summer-internship-at-iits-iims-nits-or-at-foreign-universities-6772f361fc05

Applying for Research Internships at IITs, IIMs, NITs, and Foreign Universities

Today I'm pleased to interview Ajdin Imsirovic, senior developer, author and teacher of two brand new Angular courses on Learnetto - The Free Visual Guide to Getting Started with Angular and The Complete Practical Angular Course . In this interview, Ajdin shares his thoughts on Angular and frontend web development. My name is Ajdin Imsirovic. I'm a self-taught full stack web developer. I started off as a print designer, then slowly moved into digital media (web design), and finally, bit by bit, into web development. Initially, I only did HTML and CSS, then SCSS, then JavaScript, and now I'm working in several front-end languages and libraries, and with PHP and Ruby on the backend. I blog actively on and have written several . Please introduce yourself. https://www.codingexercises.com technical books I built my first web page as a table-based layout in 2001. The web was young back then, and it was a fun, novel technology to play around with (I still feel the same way today!). However, I didn't really get into full time coding till maybe 10 years later. In the meantime, I was mostly designing on the side and working in non tech-related jobs. Regardless, all that time I kept following the progress of web technologies, and every once in a while, I'd dabble a bit with mostly front-end development. Finally, in 2011 I got hired as a webmaster, then as a web developer, and it went on from there. What got you into programming? Why do you like Angular? Let's say there are several obstacles you're trying to solve as a web developer: Stay relevant and improve your skills. Use a complete framework that helps you be productive. Balance challenging tasks with familiar tasks so that you can grow and your job is not boring. I believe Angular is a right mix of several competing solutions, each one pulling in their own direction. For example, you need to stay relevant, by learning new things. So, if you know JavaScript, but don't know TypeScript, Angular will help you there since it's the default language to use. Additionally, it's a complete framework: it comes with batteries included. For example, you don't have to think about the best way to perform XHR requests, it's built-in; you just need to know how to use the features as intended. Once you do know it, each project will have a level of similarity that makes you become more productive, faster. Angular also has enough different features that there's always something new to explore and get better at - thus you're never bored. But you are still staying inside the Angular ecosystem, which is helping you master your craft. Long story short, I only have words of praise for it. How does it compare to other frontend libraries and frameworks? I've already sort of answered the question, but if you'd like a more direct comparison, here's my take on it: I don't like React since it's too flexible. It's like somebody gave you all the parts of a car, feel free to assemble it yourself. However, being curious as I am, I'm still watching React and making mini projects in it here and there, but Angular just feels like a better fit for me. It reminds me of Elm because very often it won't compile if you messed something up. For example, if you accidentally mess up your HTML templates, it will throw an error saying: Template parse errors. So it safeguards you against your own mistakes - to a point. One complaint could be that Elm catches many more errors then Angular does, because Angular's compiler is not as strict, but it's strict enough for my taste. Vue is sort of like an offshoot of Angular. It's a strong contender in my opinion; I like it, but it doesn't feel as enterprise-ready as Angular, and the market share is not as big. However, all of these answers need to be taken with a grain of salt. Lots of online comparisons of frameworks really boil down to personal preference and to what is actually used at your place of work. The best advice, in my opinion, is to try them all, then decide which one works best for you. This is a significant effort, but it's still doable. Even if you decide to try something like that, I'd say you should try Angular right after you do it in vanilla JavaScript and/or jQuery. The standardized way of doing things is my number 1 Angular feature. People say React has got more jobs and more projects online, but Angular is better when these projects become bigger. So it is sort of expected that bigger projects should/will use Angular on the frontend. It's a stretch, but this might mean that you'll have better job stability since you'd be working for enterprise clients or directly in enterprise firms. Also, standardization helps avoid things getting messy as your projects grow bigger. Additionally, standardization makes it easier to add new features, because most of the times, there are only a few suggested/expected ways of doing things in Angular. Angular is best-suited for large projects with lots of features. I've used it to build some very complex web apps that included lots of logic on the front-end. Since I'm a teacher by vocation and a self-taught web developer in practice, I'm really curious - even obsessive - about the learning process. Like any web-related technology, it is best to learn it by doing. However, it's important to not lose too much time learning the basics, because it takes time to learn Angular. My suggestion is start with and if you like it, enrol in to go in-depth while building a complete Angular application. What's your favourite thing about Angular? What kind of projects is Angular best for? What projects have you used it for? How do you recommend people start learning Angular? The Free Visual Guide to Getting Started with Angular The Complete Practical Angular Course

Interview with Ajdin Imsirovic on Angular and Frontend Web Development

The Red Hat acquisition took many by surprise — especially the price tag. Since the announcement, many experts, strategists, and employees both current and former have chimed in on various angles some suggesting this mirrors , when Lou was in charge, how keeping Red Hat’s employees happy is IBM’s new strategy, or that this is all about . IBM’s old playbook Gerstner really Kubernetes At , we have a front-row seat to what’s happening in the digital cloud, but the Red Hat acquisition is unique for many reasons. Intricately I wanted to offer another perspective by looking at the acquisition as a parallel to the rise of industrialized shipping for context on why Red Hat will be a critical part of IBM’s future. In particular, we’ll focus on the growing number of companies’ moving to multi-vendor cloud strategies and its potential for this strategy to commoditize the big cloud vendors core (compute and storage) businesses. We’ll then unpack IBM’s bet on cloud commoditization and the acquisition of Red Hat (particularly its service business) as an opportunity to own a high-margin business and maintain relevance in the face of cloud domination from AWS, Google Cloud, and Azure. I’ll also make a bunch of logistics and shipping references. I hope you like them. Shipping bits vs shipping atoms In a former career, I worked in logistics and read (would highly recommend_)_. A somewhat lengthy title that crisply sums up the roughly 400 pages. We’ll shorten the title to from here on out. Mark Levinson’s The Box : How the Shipping Container Made the World Smaller and the World Economy Bigger The Box Do you remember what life was like shipping containers? Probably not. Long story short, Amazon.com wouldn’t have been possible, international commerce was hard, and it involved lots of . before really stevedores Prior to 1956, products were shipped as , this was companies putting their goods in boxes, bags, barrels, drums, crates, and whatever else they felt like which were occasionally secured to pallets. The stevedores unpacked and packed ships all day long full of various shapes and sizes of products. break bulk cargo Sound familiar? Today, the internet as we know it is being is powered by cloud providers that act as both the transportation vehicles (the ships, trucks, and airplanes that deliver your goods via virtual machines) the makers of the break bulk cargo containers of all shapes and sizes (the niche AI, ML, and other solutions). and This is partially due to the cloud providers waging a war to capture IT dollars as businesses first moved to hybrid cloud, then the native cloud, and increasingly, a multi-cloud strategy. But as Amazon, Microsoft, and Google turned their resources towards building the vehicles and cargo cases for the cloud over the last ten years, IBM chose to sit things out, costing them billions of dollars in potential cloud revenue. IBM tried to rectify this in 2013 with the acquisition of Softlayer, but between being late to market not in a position to commit the CAPEX necessary to compete with the established Big Cloud Co’s, they needed a new plan. and Containers to the rescue? While the cloud companies have been at war for companies’ infrastructure spend, technologies like and have made substantial progress on cloud standardization by innovating with containers. Docker Kubernetes Similar to how revolutionized global trade, cloud containerization allows companies to ship (digital) products faster and cheaper by defining and enforcing a standard set of rules, streamlining the process for all parties involved. Intermodal containers Moving to the standard shipping container and away from break bulk cargo required concerted effort between entrepreneurs, private investors, governments, and ports. We’re now seeing this happen in the cloud as IT buyers move to a multi-vendor strategy, changing the way digital products are built and deployed. Just like the massive expansion of standardized shipping that changed the world, the cloud is having to reconcile itself to the benefits of standardization in the best interest of their customers by providing the fastest and cheapest solutions to deliver their product. It’s clear that the transition to standardized shipping containers radically changed international logistics and grew the total addressable market exponentially. Okay, okay, but wasn’t this an article about IBM and Red Hat? Well, over the last few years, Red Hat has been focused on for enterprises (i.e Kubernetes). Similarly to how IBM was once the layer between , containerization has the potential to deliver standardization between all of a company’s applications regardless of the underlying cloud provider or technology. in implementing open source container solutions open source technologies and the enterprise This means that with containerization, digital products can be manufactured and shipped to consumers faster and cheaper across the internet superhighway by defaulting to the easiest route — whether that’s Amazon, Azure, or Google Cloud servers that handle the “logistics”. Rather than ships with irregular cargo of all shapes and sizes, containerization empowers digital “manufactures” by no longer locking them onto certain infrastructures and allowing them to deliver products and applications across the cloud based on the optimal route for each customer. Similarly to how Walmart has dozens of shipping partners that go from production facilities on the other side of the globe to the last mile, containerization allows companies to pick the best providers for each leg of the journey with ease. Building the right kind of port If the revolution of intermodal containerization taught us anything, it’s that sometimes a necessary solution is building a whole new port. The transition to standardized containers is the reason for the death of first-generation port cities like New York, London, and San Francisco (think of these as v1.0) and the rise of secondary cities like Oakland and Newark (the new and improved 2.0 versions). And rather than betting the farm on being able to catch up in infrastructure and niche cloud computing, IBM saw an opportunity to lean into its service-based business because service-based businesses tend to have lower, but more stable and higher margins, especially versus a capex-intensive computing business. With their purchase of Red Hat, one of the largest implementers of Kubernetes, IBM is effectively betting on the commoditization of the cloud vendors while maintaining their long-standing business relationships to sell more (high-margin) cloud consulting services. IBM is essentially building the port to the new cloud where everything is optimized for delivery of digital products and Red Hat is the key piece of the puzzle to service the ships coming in and out of these “digital ports”. A commoditized cloud As the consumerization of everything spreads to Enterprise IT, expectations for business challenges to be solved faster and cheaper are not just nice-to-haves core requirements. Just like standard shipping containers created the foundation for massive international commerce, the standardization of the cloud has the potential to drive a similar explosion of digital commerce. but This will allow businesses to build, deliver, buy, and sell technology products like never before, and while the big guys will likely try and resist it, in the long-haul, standards typically lead to a market where everyone wins.

IBM’s Big Bet on Standardized Shipping (of bits)

Stingrays are on the loose in Washington D.C. It has been widely reported this week ( , , , ) that Washington D.C. and other undisclosed cities are exhibiting anomalies that appear to be due to unauthorized and unknown IMSI catchers (such as the notorious “ ” devices). These are often to track individuals, intercept texts, and listen to calls. (The ACLU keeps an for domestic surveillance.) AP NPR Washington Post BBC stingray spying devices used by law enforcement updated list of federal agencies known to employ IMSI catchers The suspected existence of was disclosed in a (and its ) from the Department of Homeland Security to Oregon Senator Ron Wyden, dated 26-March 2018. rogue IMSI catchers with unknown operators in American cities letter attachment The letter acknowledges that the and admits that the U.S. is unprepared for detecting such a threat: “use of IMSI catchers by foreign governments may threaten U.S. national and economic security,” “[The Department of Homeland Security does currently have] the technical capability to detect IMSI catchers. To support such a capability, DHS would require funding to procure, deploy, operate and maintain the capability, which includes the costs of hardware, software, and labor.” not We need a net to catch these stingrays In this article, I propose a simple “net” that legitimate federal agencies could cast over Washington D.C. (or any other area) to map the locations of unauthorized IMSI catchers. This undetectable counterattack is nonintrusive, inexpensive, and would require no new technology. A grid of honeypot devices that appear to be victims’ cell phones should be placed in a grid throughout the region of interest. A blacklist of the honeypots’ identification information (IMSI/ESN) would be provided to all authorized service providers in the area. At a predetermined coordinated time, the legitimate cell towers implement the blacklist and drop all connections to the honeypot devices. Once all legitimate cell tower connections are denied, the honeypots that are still receiving service must be physically near unauthorized IMSI catchers that are unaware of the blacklist. Any honeypot cell phones that appear to stay connected to a “cell tower” are actually interacting with an ISMI catcher! To better locate the source of the rogue signals, the net controller can slowly lower the signal broadcast power on the devices. The positions of the ISMI catchers can then be pinpointed from the honeypots that stay connected longest due to stingray proximity. Keeping it safe to swim The net described above should be quickly implemented using extant inexpensive technology to definitively map the scale of the rogue stingray problem. A honeypot outside the fence of each embassy would quickly identify which foreign governments are scooping up data in this way. Since updating and activating a device ID blacklist is not a burdensome task for authorized cell tower operators, this could be implemented as a routine procedure. In fact, cooperating law enforcement and telecommunications companies could easily crowdsource the net to any any phone on a regional network! When a device is not actively in use, the service providers could momentarily add it to a blacklist and drop all legitimate connections for a few seconds. If the device found and connected to a “cell tower” during the blackout, then it must have been ensnared by a nearby rogue stingray. By routinely detecting nearby IMSI catchers with idle devices, this stingray net could be nondisruptively cast over an entire country. Thanks @Dad for sending an article about rogue IMSI catchers, which caused me to ponder methods for addressing the current situation in D.C. and elsewhere. References , Frank Bajak, 2018.04.04: Associated Press: US suspects cellphone spying devices in DC https://apnews.com/d716aac4ad744b4cae3c6b13dce12d7e/APNewsBreak:-US-suspects-cellphone-spying-devices-in-DC , Merrit Kennedy, 2018.04.04: NPR: Feds Say They’ve Detected Apparent Rogue Spy Devices In D.C. https://www.npr.org/sections/thetwo-way/2018/04/04/599428495/feds-say-theyve-detected-apparent-rogue-spy-devices-in-d-c , Matt Zapotosky, 2018.04.03: Washington Post: DHS has detected possible cellphone surveillance in D.C. — and doesn’t know who’s doing it https://www.washingtonpost.com/world/national-security/dhs-says-it-has-detected-possible-cellphone-surveillance-in-dc--and-doesnt-know-whos-doing-it/2018/04/03/f69fbe36-3785-11e8-acd5-35eac230e514_story.html , 2018.04.04: BBC: Mystery Stingray devices discovered in Washington http://www.bbc.com/news/technology-43639709 , Curtis Waltman, 2016.12.02: MuckRock: Rochester police release unredacted list of Harris Corp StingRay and KingFish products https://www.muckrock.com/news/archives/2016/dec/07/rochester-police-release-unredacted-list-harris-co/ , Electronic Frontier Foundation: One Pager on Cell Site Simulators https://www.eff.org/document/eff-one-pager-cell-site-simulators , Joseph Goldstein, 2016.02.11: New York Times: New York Police are Using Covert Cellphone Trackers, Civil Liberties Group Says https://www.nytimes.com/2016/02/12/nyregion/new-york-police-dept-cellphone-tracking-stingrays.html American Civil Liberties Union: Stingray tracking devices: who’s got them? Updated March 2018: https://www.aclu.org/issues/privacy-technology/surveillance-technologies/stingray-tracking-devices-whos-got-them DHS Letter Cover: https://www.documentcloud.org/documents/4429966-DHS-response-to-Wyden-3-26-18.html DHS Letter Attachment: https://www.documentcloud.org/documents/4430049-DHS-attachment-in-response-to-Wyden-3-26-18.html

A proposed method for triangulation of rogue IMSI catchers (a.k.a. “Stingray” devices)

The price of performance over cognition There are two versions of mathematics. The first is the mathematics of schooling, a collection of closed problems and hard truths to be learned for exams. We’ve all experienced it, few of us have enjoyed or excelled at it. The second version is a more open, beautiful and empowering representation of the subject, often the focus of my writing. Why the disconnect? What leads us to privilege narrow outcomes at the expense of deep and meaningful learning experiences? Garry Kasparov has a few thoughts. In his latest book , Kasparov recounts the story of the so-called ultimate battle of man vs machine. He was the man to IBM’s Deep Blue machine, contesting a 6-game chess match with the ultimate prize of intelligence bragging rights. We all know how that went: Deep Blue prevailed 3 ½–2 ½. The watershed moment had arrived for . Deep Thinking Artificial Intelligence Except, that’s not quite how Kasparov sees it. While Chess was long considered the holy grail for AI, the nature of Deep Blue’s programming was hardly the quantum leap forward many imagined it would be. Deep Blue was built on brute force computation. By 1997, the combination of computing power and IBM’s search algorithms was more than sufficient to best the world’s dominant chess player. Deep Blue’s victory may have revealed less about the nature of AI and more about the relatively closed nature of chess. Deep Blue adopted a playing style that scarcely resembled the strategic gameplay of Kasparov. Rather than reasoning through end game strategies, for example, Deep Blue could just look up the optimal next move from a table. IBM had no concern for their machine played a particular move; the result was all that mattered. why The match was marked as a triumph for IBM (both its reputation and stock prices rocketed), but for Kasparov the brute-force computational approach was a betrayal of science. IBM had shunned the ambition of developing human-like chess machines. Instead they assumed a win-at-all-costs mindset that put performance over method. It was a victory for engineering and a missed opportunity for science. Fast-forward twenty years, and the machines have risen further. Google DeepMind’s . The game of Go is characterised by its openness; it cannot be tamed by the brute-force search algorithms of Deep Blue. Instead, AlphaGo called on advanced Machine techniques such as and . The names alone presume that these machines think in more human-like ways. Such presumptions are far from justified. In a brilliant critique of Deep Learning, : AlphaGo sent shockwaves through the scientific community by defeating world Go champion Lee Sedol Learning Deep Learning Neural Networks Francois Chollet writes The only real success of deep learning so far has been the ability to map space X to space Y using a continuous geometric transform, given large amounts of human-annotated data. Doing this well is a game-changer for essentially every industry, but it is still a very long way from human-level AI. So what would ‘human-level AI’ look like? He goes on: The ability to handle hypotheticals, to expand our mental model space far beyond what we can experience directly, in a word, to perform and , is arguably the defining characteristic of human cognition. abstraction reasoning This stands in sharp contrast with what deep nets do…the mapping from inputs to outputs performed by deep nets quickly stops making sense if new inputs differ even slightly from what they saw at training time. There is a tendency to confuse performance with methods. Just because a machine can win at or , it does not mean they play the game as humans do. We have too much reverence for black-box algorithms. Go Chess The parallels with education are striking. , whereas the brute-force memorisation of facts and procedures reign supreme. Students are trained to perform mathematical operations, to swallow the black-box and to act as paltry oracles who can churn out answers without a second thought. This is not the same as doing maths, because to do maths is to question, to explore, to reason. Maths is the most open of domains and can never be reduced to algorithmic form. Those fundamental skills of abstraction and reasoning are often marginalised in the curriculum The quest for Chess machines was well intended, but failed in ambition due to the pressures of performance. So it goes with much of school mathematics, which is underpinned by performance-based assessment. The goals of assessment — to measure students’ thinking and provide feedback — are laudable. The commoditisation of high-stakes testing has put paid to those goals, reducing most of education to a performance act. Just as IBM betrayed science for the sake of winning, education has betrayed learning for the sake of measurement. I was once called an ‘exam machine’ by my undergraduate tutor. He meant it as a compliment and I certainly took it as one. But to pass exams does not a mathematician make. Exams are bounded by time, changing the fundamental nature of problem solving. Just as deprives humans of their intuitions, exams are not an appropriate format for capturing our inner mathematicians. Bullet Chess Educators must rise above the machine-like tendency to focus exclusively on outcomes. At a time when and other digital innovations are sinking their claws into Education, we must demand emphasis on deeper thinking. IBM’s latest showpiece Watson Our track record with artificial intelligence exposes the things value as humans; performance over cognition. The same is true for how we have approached education. If education is to develop students into productive and engaged citizens, then educators must flip the narrative. Method is everything. I am a research mathematician turned educator working at the nexus of mathematics, education and innovation. Come say hello on Twitter or LinkedIn . If you liked this article you might want to check out my following pieces: _As the quest for strong AI unfolds, are we losing our grip on human intelligence?_hackernoon.com Maths students are trapped in Searle’s Chinese room _An educator’s warning to Elon Musk_hackernoon.com Thinking in the age of cyborgs _Reasoning is the language of mathematics_mystudentvoices.com When maths screws you over

What educators must learn from IBM’s ‘betrayal of science’

The First Amendment Implications of TikTok's Ban

Virtual Meetings have become an essential part of corporate collaboration, serving as the de facto way that ideas are exchanged, decisions are made, and strategies are devised. However, the true value of meetings is often diluted by their length and the complexity of the discussions. This is why note-taking and effective summaries and action points are so important. Converting long and often pointless discussions into short (actionable) summaries, meeting attendees can quickly catch up on meetings they missed, review decisions that were made, and understand discussions without having to sift through hours and hours of recordings. We thought it would be cool to create our summarizer. If you don't have one already, keep reading. This technical tutorial will guide you through creating a simple web application that summarizes daily meeting Transcripts using ApyHub’s AI Summarize Document API using NodeJS. Pre-requisites: Access to Google Meet and permission to access meeting transcripts.
A preferred programming language environment (e.g., Python).
ApyHub Account.
GitHub CLI is installed on your computer. Step 1: Clone the GitHub repository Open your terminal and run this command: git clone https://github.com/iamspathan/AI-Transcript-Summarizer.git This command will clone the project in your local environment. Once the project is cloned, you can open the repository in the code editor. Step 2. Install Required Packages: Here, in Node Package Manager (npm), we will install all the dependencies that our application needs to summarize the meeting transcribe. npm install Step 3: Add your API Key to the index.js file. Here, we will add our Secret API key from ApyHub. To generate an API key, you can visit the documentation page of AI Summarize Document API. Your secret looks like this ➡️
apy-token: APY****************************************** Copy this token and paste it in as shown in the code comment below. const express = require('express');
const fileUpload = require('express-fileupload');
const cors = require('cors');
const axios = require('axios');
const FormData = require('form-data');
const open = require('open');
const app = express();
const port = 3000;

app.use(cors());
app.use(fileUpload());

// Serve static files from the 'public' directory
app.use(express.static('public'));

app.post('/summarize', (req, res) => {
    console.log("summarixe called", req.files.file);
    if (!req.files || Object.keys(req.files).length === 0) {
        return res.status(400).send('No files were uploaded.');
    }

    // Assuming the file is attached to the request under the key 'file'
    const file = req.files.file;

    // Prepare the file to be sent using form-data
    const formData = new FormData();
    formData.append('file', file.data, file.name);

    // Set up the request headers, including the dynamic headers from form-data and the secret-apy token.
    const requestHeaders = {
        ...formData.getHeaders(),
        'apy-token': 'ADD YOUR OWN APY-TOKEN HERE'
    };

    // Call the AI Summarize API
    axios.post('https://api.apyhub.com/ai/summarize-documents/file', formData, { headers: requestHeaders })
        .then(apiResponse => {
            // Assuming the API returns JSON with a summary field
            console.log(apiResponse.data.data.summary);
            res.send({ summary: apiResponse.data.data.summary });
        })
        .catch(error => {
            console.error('Error calling the AI Summarize API:', error);
            res.status(500).send('Failed to summarize the document.');
        });
});

app.listen(port, () => {
    console.log(`Server running at http://localhost:${port}`);
    // Open the index.html file in the default browser
    open(`http://localhost:${port}`);
}); Once you’ve added the API key. Save the changes using the Ctrl+S Key. Step 4: Running Your Application Once you’ve added the API key. Save the changes using Ctrl+S in your terminal, and run this command.: node index.js That’s it :) As you can see, Now you can generate a meeting transcript anytime you want :) Virtual Meetings have become an essential part of corporate collaboration, serving as the de facto way that ideas are exchanged, decisions are made, and strategies are devised. However, the true value of meetings is often diluted by their length and the complexity of the discussions. This is why note-taking and effective summaries and action points are so important. Converting long and often pointless discussions into short (actionable) summaries, meeting attendees can quickly catch up on meetings they missed, review decisions that were made, and understand discussions without having to sift through hours and hours of recordings. We thought it would be cool to create our summarizer. If you don't have one already, keep reading. This technical tutorial will guide you through creating a simple web application that summarizes daily meeting Transcripts using ApyHub’s AI Summarize Document API using NodeJS. ApyHub’s AI Summarize Document API Pre-requisites: Access to Google Meet and permission to access meeting transcripts. A preferred programming language environment (e.g., Python). ApyHub Account. GitHub CLI is installed on your computer. Access to Google Meet and permission to access meeting transcripts. Google Meet A preferred programming language environment (e.g., Python). ApyHub Account . ApyHub Account GitHub CLI is installed on your computer. Step 1: Clone the GitHub repository Open your terminal and run this command: git clone https://github.com/iamspathan/AI-Transcript-Summarizer.git git clone https://github.com/iamspathan/AI-Transcript-Summarizer.git This command will clone the project in your local environment. Once the project is cloned, you can open the repository in the code editor. Step 2. Install Required Packages: Here, in Node Package Manager (npm), we will install all the dependencies that our application needs to summarize the meeting transcribe. npm install npm install Step 3: Add your API Key to the index.js file. Here, we will add our Secret API key from ApyHub. To generate an API key, you can visit the documentation page of AI Summarize Document API . Your secret looks like this ➡️ apy-token: APY****************************************** AI Summarize Document API apy-token: APY****************************************** Copy this token and paste it in as shown in the code comment below. const express = require('express');
const fileUpload = require('express-fileupload');
const cors = require('cors');
const axios = require('axios');
const FormData = require('form-data');
const open = require('open');
const app = express();
const port = 3000;

app.use(cors());
app.use(fileUpload());

// Serve static files from the 'public' directory
app.use(express.static('public'));

app.post('/summarize', (req, res) => {
    console.log("summarixe called", req.files.file);
    if (!req.files || Object.keys(req.files).length === 0) {
        return res.status(400).send('No files were uploaded.');
    }

    // Assuming the file is attached to the request under the key 'file'
    const file = req.files.file;

    // Prepare the file to be sent using form-data
    const formData = new FormData();
    formData.append('file', file.data, file.name);

    // Set up the request headers, including the dynamic headers from form-data and the secret-apy token.
    const requestHeaders = {
        ...formData.getHeaders(),
        'apy-token': 'ADD YOUR OWN APY-TOKEN HERE'
    };

    // Call the AI Summarize API
    axios.post('https://api.apyhub.com/ai/summarize-documents/file', formData, { headers: requestHeaders })
        .then(apiResponse => {
            // Assuming the API returns JSON with a summary field
            console.log(apiResponse.data.data.summary);
            res.send({ summary: apiResponse.data.data.summary });
        })
        .catch(error => {
            console.error('Error calling the AI Summarize API:', error);
            res.status(500).send('Failed to summarize the document.');
        });
});

app.listen(port, () => {
    console.log(`Server running at http://localhost:${port}`);
    // Open the index.html file in the default browser
    open(`http://localhost:${port}`);
}); const express = require('express');
const fileUpload = require('express-fileupload');
const cors = require('cors');
const axios = require('axios');
const FormData = require('form-data');
const open = require('open');
const app = express();
const port = 3000;

app.use(cors());
app.use(fileUpload());

// Serve static files from the 'public' directory
app.use(express.static('public'));

app.post('/summarize', (req, res) => {
    console.log("summarixe called", req.files.file);
    if (!req.files || Object.keys(req.files).length === 0) {
        return res.status(400).send('No files were uploaded.');
    }

    // Assuming the file is attached to the request under the key 'file'
    const file = req.files.file;

    // Prepare the file to be sent using form-data
    const formData = new FormData();
    formData.append('file', file.data, file.name);

    // Set up the request headers, including the dynamic headers from form-data and the secret-apy token.
    const requestHeaders = {
        ...formData.getHeaders(),
        'apy-token': 'ADD YOUR OWN APY-TOKEN HERE'
    };

    // Call the AI Summarize API
    axios.post('https://api.apyhub.com/ai/summarize-documents/file', formData, { headers: requestHeaders })
        .then(apiResponse => {
            // Assuming the API returns JSON with a summary field
            console.log(apiResponse.data.data.summary);
            res.send({ summary: apiResponse.data.data.summary });
        })
        .catch(error => {
            console.error('Error calling the AI Summarize API:', error);
            res.status(500).send('Failed to summarize the document.');
        });
});

app.listen(port, () => {
    console.log(`Server running at http://localhost:${port}`);
    // Open the index.html file in the default browser
    open(`http://localhost:${port}`);
}); Once you’ve added the API key. Save the changes using the Ctrl+S Key. Ctrl+S Step 4: Running Your Application Once you’ve added the API key. Save the changes using Ctrl+S in your terminal, and run this command.: node index.js node index.js That’s it :) As you can see, Now you can generate a meeting transcript anytime you want :)

Building an AI-Powered Summarizer using NodeJS and ApyHub API To Make Meetings Easy

A few days ago, I underwent an MRI scan. They slid me into a large tube, and for 15 minutes, the machine around me buzzed, hummed, and clicked. At the end of the examination, I received a CD containing the data. What does a good developer do in such a situation? Of course, as soon as they get home, they start examining the data and thinking about how they might extract it using . Python The CD contained a bunch of DLLs, an EXE, and a few additional files for a Windows viewer, which are obviously useless on Linux. The crux was in a folder named DICOM. It held a series of extension-less files across eight folders. ChatGPT helped me figure out that is a standard format typically used for storing MRI, CT, and X-ray images. Essentially, it's a simple packaging format containing grayscale images along with some metadata. DICOM The allows you to easily export the files in PNG format: following code import os
import pydicom
from PIL import Image
import sys

def save_image(pixel_array, output_path):
    if pixel_array.dtype != 'uint8':
        pixel_array = ((pixel_array - pixel_array.min()) / (pixel_array.max() - pixel_array.min()) * 255).astype('uint8')

    img = Image.fromarray(pixel_array)
    img.save(output_path)
    print(f"Saved image to {output_path}")

def process_dicom_directory(dicomdir_path, save_directory):
    if not os.path.exists(save_directory):
        os.makedirs(save_directory)

    dicomdir = pydicom.dcmread(dicomdir_path)

    for patient_record in dicomdir.patient_records:
        if 'PatientName' in patient_record:
            print(f"Patient: {patient_record.PatientName}")

        for study_record in patient_record.children:
            if 'StudyDate' in study_record:
                print(f"Study: {study_record.StudyDate}")

            for series_record in study_record.children:
                for image_record in series_record.children:
                    if 'ReferencedFileID' in image_record:
                        file_id = list(map(str, image_record.ReferencedFileID))
                        file_id_path = os.path.join(*file_id)
                        print(f"Image: {file_id_path}")

                        image_path = os.path.join(os.path.dirname(dicomdir_path), file_id_path)
                        
                        modified_filename = '_'.join(file_id) + '.png'
                        image_save_path = os.path.join(save_directory, modified_filename)

                        try:
                            img_data = pydicom.dcmread(image_path)
                            print("DICOM image loaded successfully.")
                            save_image(img_data.pixel_array, image_save_path)
                        except FileNotFoundError as e:
                            print(f"Failed to read DICOM file at {image_path}: {e}")
                        except Exception as e:
                            print(f"An error occurred: {e}")

if __name__ == "__main__":
    if len(sys.argv) < 3:
        print("Usage: python dicomsave.py <path_to_DICOMDIR> <path_to_save_images>")
        sys.exit(1)
    
    dicomdir_path = sys.argv[1]
    save_directory = sys.argv[2]
    process_dicom_directory(dicomdir_path, save_directory) The code expects two parameters. The first is the path to the DICOMDIR file, and the second is a directory where the images will be saved in PNG format. To read the DICOM files, we use the library. The structure is loaded using the function, from which metadata (such as the patient's name) and studies containing the images can be extracted. The image data can also be read with . The raw data are accessible through the field, which the function converts to PNG. It's not too complicated. Pydicom pydicom.dcmread dcmread pixelarray save_image The result is a few squares (typically 512x512) grayscale images, which can be easily utilized later on. Why did I think it was important to write this short story about my adventure using the DICOM format? When a programmer hears about processing medical data, they might think it's something serious, something that only universities and research institutes can handle (at least, that's what I thought). As you can see, we're talking about simple grayscale images, which are very easy to process and ideal for things like neural network processing. Consider the possibilities this opens up. For something like a simple tumor detector, all you need is a relatively straightforward convolutional network and a sufficient number of samples. In reality, the task isn't much different from recognizing dogs or cats in images. To illustrate how true this is, let me provide an example. After a brief search on Kaggle, where brain tumors are classified based on MRI data (grayscale images). The dataset categorizes the images into four groups: three types of brain tumors and a fourth category with images of healthy brains. The architecture of the network is as follows: I found a notebook ┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ conv2d (Conv2D)                 │ (None, 164, 164, 64)   │         1,664 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ max_pooling2d (MaxPooling2D)    │ (None, 54, 54, 64)     │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ conv2d_1 (Conv2D)               │ (None, 50, 50, 64)     │       102,464 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ max_pooling2d_1 (MaxPooling2D)  │ (None, 16, 16, 64)     │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ conv2d_2 (Conv2D)               │ (None, 13, 13, 128)    │       131,200 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ max_pooling2d_2 (MaxPooling2D)  │ (None, 6, 6, 128)      │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ conv2d_3 (Conv2D)               │ (None, 3, 3, 128)      │       262,272 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ max_pooling2d_3 (MaxPooling2D)  │ (None, 1, 1, 128)      │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ flatten (Flatten)               │ (None, 128)            │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dense (Dense)                   │ (None, 512)            │        66,048 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dense_1 (Dense)                 │ (None, 4)              │         2,052 │
└─────────────────────────────────┴────────────────────────┴───────────────┘ As you can see, the first few layers consist of a convolution and max pooling sandwich, which extracts patterns of tumors, followed by two dense layers that perform the classification. This is exactly the same architecture used in that uses the CIFAR-10 dataset. I remember it well, as it was one of the first neural networks I encountered. The dataset contains 60,000 images categorized into ten classes, including two classes for dogs and cats, as I mentioned earlier. The architecture of the network looks like this: TensorFlow's CNN sample code CIFAR-10 Model: “sequential”
_________________________________________________________________
Layer (type) Output Shape Param # 
=================================================================
conv2d (Conv2D) (None, 30, 30, 32) 896 
_________________________________________________________________
max_pooling2d (MaxPooling2D) (None, 15, 15, 32) 0 
_________________________________________________________________
conv2d_1 (Conv2D) (None, 13, 13, 64) 18496 
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 6, 6, 64) 0 
_________________________________________________________________
conv2d_2 (Conv2D) (None, 4, 4, 64) 36928 
_________________________________________________________________
flatten (Flatten) (None, 1024) 0 
_________________________________________________________________
dense (Dense) (None, 64) 65600 
_________________________________________________________________
dense_1 (Dense) (None, 10) 650 
=================================================================
Total params: 122,570
Trainable params: 122,570
Non-trainable params: 0
_________________________________________________________________ It's clear that we are dealing with the same architecture, just with slightly different parameters, so recognizing brain tumors in MRI images is indeed not much more difficult than identifying cats or dogs in pictures. Furthermore, the mentioned Kaggle notebook is capable of classifying tumors with 99% effectiveness! I just want to point out how simple it can be to extract and process medical data in certain cases and how problems that seem complex, like detecting brain tumors, can often be quite effectively addressed with simple, traditional solutions. Therefore, I would encourage everyone not to shy away from medical data. As you can see, we are dealing with relatively simple formats, and using relatively simple, well-established technologies (convolutional networks, vision transformers, etc.), a significant impact can be achieved here. If you join an open-source healthcare project in your spare time just as a hobby and can make even a slight improvement to the neural network used, you could potentially save lives!

Can You Open Medical Data (MR, CT, X-Ray) in Python and Find Tumors With AI?! Maybe

আপনি কি পাইথনে মেডিকেল ডেটা (এমআর, সিটি, এক্স-রে) খুলতে পারেন এবং এআই দিয়ে টিউমার খুঁজে পেতে পারেন?! হতে পারে

Können Sie medizinische Daten (MR, CT, Röntgen) in Python öffnen und Tumore mit KI finden?! Vielleicht

¿Se pueden abrir datos médicos (RM, tomografía computarizada, rayos X) en Python y encontrar tumores con IA? Tal vez

Pouvez-vous ouvrir des données médicales (IRM, CT, rayons X) en Python et rechercher des tumeurs avec l'IA ?! Peut être

क्या आप पाइथन में मेडिकल डेटा (एमआर, सीटी, एक्स-रे) खोल सकते हैं और एआई के साथ ट्यूमर ढूंढ सकते हैं?! शायद

Pythonで医療データ（MR、CT、X線）を開き、AIで腫瘍を見つけることができるか？！ おそらく

의료 데이터(MR, CT, X-Ray)를 Python으로 열고 AI로 종양을 찾을 수 있습니까?! 아마도

Você pode abrir dados médicos (ressonância magnética, tomografia computadorizada, raio-X) em Python e encontrar tumores com IA?! Talvez

Можете ли вы открыть медицинские данные (МР, КТ, рентген) на Python и найти опухоли с помощью ИИ?! Может быть

Python'da Tıbbi Verileri (MR, CT, X-Ray) Açabilir ve Yapay Zekayla Tümörleri Bulabilir misiniz?! Belki

Bạn có thể mở dữ liệu y tế (MR, CT, X-Ray) bằng Python và tìm khối u bằng AI không?! Có lẽ

你能用 Python 打开医疗数据（MR、CT、X 射线）并用 AI 查找肿瘤吗？！也许吧

Analysis of Network Graphs: Visualizing Hamilton Characters as a Social Network

নেটওয়ার্ক গ্রাফের বিশ্লেষণ: একটি সামাজিক নেটওয়ার্ক হিসাবে হ্যামিল্টন চরিত্রগুলিকে ভিজ্যুয়ালাইজ করা

Analyse von Netzwerkgraphen: Visualisierung der Hamilton-Charaktere als soziales Netzwerk

Análisis de gráficos de red: visualización de personajes de Hamilton como una red social

Analyse des graphiques de réseau : visualiser les personnages de Hamilton en tant que réseau social

नेटवर्क ग्राफ़ का विश्लेषण: हैमिल्टन के पात्रों को एक सामाजिक नेटवर्क के रूप में देखना

ネットワーク グラフの分析: ハミルトンの登場人物をソーシャル ネットワークとして視覚化する

네트워크 그래프 분석: 해밀턴 캐릭터를 소셜 네트워크로 시각화

Análise de gráficos de rede: visualizando personagens de Hamilton como uma rede social

Анализ сетевых графов: визуализация персонажей Гамильтона как социальной сети

Ağ Grafiklerinin Analizi: Hamilton Karakterlerinin Sosyal Ağ Olarak Görselleştirilmesi

Phân tích biểu đồ mạng: Trực quan hóa các nhân vật Hamilton như một mạng xã hội

网络图分析：将汉密尔顿特征可视化为社交网络

Deep Learning: Edge Devices With mmWave FMCW Radars Part 1 - Signal Processing

ডিপ লার্নিং: mmWave FMCW রাডার সহ এজ ডিভাইস পার্ট 1 - সিগন্যাল প্রসেসিং

Deep Learning: Edge-Geräte mit mmWave-FMCW-Radaren, Teil 1 – Signalverarbeitung

Aprendizaje profundo: dispositivos perimetrales con radares mmWave FMCW Parte 1: Procesamiento de señales

Apprentissage profond : appareils Edge avec radars mmWave FMCW, partie 1 - Traitement du signal

डीप लर्निंग: एमएमवेव एफएमसीडब्लू रडार के साथ एज डिवाइस भाग 1 - सिग्नल प्रोसेसिंग

ディープラーニング: mmWave FMCW レーダーを搭載したエッジデバイス パート 1 - 信号処理

딥 러닝: mmWave FMCW 레이더를 사용한 엣지 장치 1부 - 신호 처리

Aprendizado profundo: dispositivos de borda com radares FMCW mmWave Parte 1 - Processamento de sinal

Глубокое обучение: периферийные устройства с радарами mmWave FMCW. Часть 1. Обработка сигналов

Derin Öğrenme: mmWave FMCW Radarlarına Sahip Uç Cihazlar Bölüm 1 - Sinyal İşleme

Học sâu: Thiết bị biên có radar mmWave FMCW Phần 1 - Xử lý tín hiệu

深度学习：配备毫米波 FMCW 雷达的边缘设备第 1 部分 - 信号处理

As an AI expert, let me be blunt - cyber threats are a massive, unrelenting risk that no business with an online presence can afford to ignore these days. Whether you're running an e-commerce site, logistics operation, or tech firm, phishing, ransomware attacks, or data breaches - these scourges can cripple a company, leading to devastating financial losses, irreparable brand damage, and even regulatory penalties that could bury you. I've personally seen the aftermath of cyber strikes on SMBs with limited security resources and tight budgets. In those cases, traditional cybersecurity just doesn't cut it against today's attack of threats. But that's exactly where artificial intelligence (AI) emerges as a total game-changer. discovered that organizations leveraging AI and automation extensively saved a mind-blowing $1.76 million on average compared to their less AI-savvy counterparts. IBM's 2023 Cost of Data Breach Report And I can testify that AI-powered cyber defense solutions truly earn those savings. By unleashing cutting-edge AI techniques like machine learning, deep learning models, and natural language processing, modern AI cybersecurity acts like an indispensable digital force multiplier reinforcing our defenses against even the wiliest adversaries. As an AI expert, I've deployed these capabilities for clients - it's like having an entire squad of cybersecurity sentries patrolling the digital premises 24/7 to keep the bad actors at bay. Moving forward, I don't believe adopting advanced AI will be a luxury for organizations - it's a flat-out necessity we can't ignore. Whether you're a small business or a giant enterprise, you'd better get proactive and start leveraging AI's offensive cybersecurity potential to safeguard your vital digital assets and ensure continuous operations. In my opinion, AI is quickly separating the cybersecurity haves from the have-nots. AI's Cyber Offense: How It Turbocharges Threat Detection I can't overstate how AI is revolutionizing cybersecurity by unleashing cutting-edge threat detection and response capabilities never before possible. Just look at the rapidly growing market - projects that AI in the cybersecurity sector will explode from $22.4 billion in 2023 to $60.6 billion by 2028. And there are good reasons behind that meteoric growth. MarketsandMarkets Machine learning algorithms excel at quickly identifying patterns and anomalies within massive datasets - making them invaluable assets for recognizing potential cyber threats amid tons of network traffic, user activity logs, and other data. By training these algorithms on historical data, we can have them recognize known attack signatures and deviations signaling new threats before they can wreak havoc. One study I find particularly compelling is from MDPI, showing machine learning models achieved up to 99% malware detection accuracy using techniques like Decision Trees, Convolutional Neural Networks, and Support Vector Machines. That's the level of precision AI can deliver against emerging threats. There are deep learning models that I've deployed to rapidly analyze and classify malware samples with incredible accuracy. The latest deep-learning architectures can see patterns invisible to the naked eye. However, some of the most exciting AI cybersecurity applications my team has tested involve reinforcement learning for adaptive threat response. These self-learning systems can dynamically adjust defensive actions on the fly based on their experiences against evolving attack vectors. Allied Market Research predicts reinforcement learning will see explosive 41.5% annual growth from 2023 to 2032, with cybersecurity as a prime use case. Let's not overlook natural language processing (NLP) for automating incident analysis. I've personally overseen NLP deployments that can rapidly comprehend human language data from reports, intelligence feeds, and more - streamlining our incident response workflows and prioritizing genuine threats over false positives. Combining all these AI disciplines is delivering incredible offensive capabilities to counter even the trickiest cyber adversaries. As an expert and founder in this space, I truly believe AI's ability to autonomously detect and shut down threats before impact will utterly transform cybersecurity over the coming years. Why UEBA and User Behavior Monitoring Matter (And How AI Excels) The cyber risk from malicious insiders or compromised user accounts is one we can't overlook either. That's why I consider user and entity behavior analytics (UEBA) powered by advanced AI/ML models to be paramount for comprehensive, 360-degree security visibility. At a basic level, these AI-driven UEBA solutions leverage machine learning to establish baselines modeling each user's normal behavior based on their activity patterns. Once those baselines are established, the AI can continuously monitor for deviations that may indicate insider threats, privilege abuse, compromised accounts, and other insider risk vectors. What makes this application of AI so powerful is its ability to dynamically score the risk level of unusual user actions based on contextual factors like their role, access privileges, the sensitivity of data/systems involved, and more. This enables real-time flagging of potentially malicious insider activity for further investigation - something that was highly prone to human error with traditional, rigid rule-based approaches. Another area where I've seen UEBA with AI shine is detecting compromised privileged user accounts, which are prime targets for external threat actors seeking a foothold. By understanding the unique behavior patterns of different privileged user roles, AI can rapidly identify the subtle anomalies of a privileged account under hostile control - giving our teams a chance to shut down that breach before catastrophic damage occurs. In my opinion, deploying AI for insider and privileged user threat detection by understanding human behavior is an absolute game-changer. Monitoring our people and accounts is just as vital as external threat monitoring - without it, we're leaving a gaping hole in our defenses that skilled adversaries will inevitably find and exploit. Of course, my teams always emphasize that AI-powered UEBA is just one layer in a comprehensive, defense-in-depth strategy. But it's a crucial layer that lets us get in front of insider incidents before they escalate - buying time that can mean the difference between a contained issue and a full-blown crisis. The Flip Side: Defending Against AI-Powered Threats As amazing as AI's cybersecurity offensive capabilities are, I have to address the flip side too: hackers are actively working on ways to weaponize AI against us. Adversarial attacks designed to bypass, poison, or steal our AI models are a clear and present danger we can't ignore. One disturbing forecast from research analysts indicates: Up to 30% of AI cyberattacks will leverage training data poisoning, model stealing, or adversarial examples to attack AI-powered systems. But we're not defenseless - there are proven ways to harden AI systems against these tactics if we invest in robust AI security controls from the start. Approaches like adversarial training, where models are intentionally exposed to deceptive inputs during the learning process, can improve resilience against evasion. Differential privacy techniques can also obscure model behavior to thwart extraction attacks. We follow best practices around secure AI development Life Cycle, subjecting our models to rigorous adversarial testing and employing defensive AI techniques to stay ahead of emerging threats. I don't mean to sound alarmist, but the cybersecurity industry at large needs to prioritize battling AI-powered threats just as much as leveraging AI for defense. It's a two-way street - we must secure the AI models underpinning our cyber defenses with the same vigor we apply AI offensively. Neglecting AI security WILL be exploited by sophisticated hackers. So while I'm incredibly confident about AI's potential to revolutionize cyber threat detection and response, I'm also pragmatic. We simply can't ignore the dark side and must proactively invest in developing and deploying AI securely to maintain a decisive strategic advantage. Integrating AI Across Security Operations Of course, AI alone is not a silver bullet for cybersecurity. Its true power comes from thoughtful integration across existing processes, teams, and technology stacks. As an enthusiastic AI Expert, I emphasize this force-multiplier effect to clients constantly. AI should augment and empower human expertise, not replace it entirely. That's why the most successful deployments I've seen use AI to offload tedious, repetitive tasks to machines - freeing up skilled personnel to focus on higher-level analysis, investigation, and decision-making that requires human judgment. That's also why AI is rapidly becoming essential for SOC analysts and incident response teams: by automating alert triage, log analysis and basic response workflows, AI drastically reduces burnout from low-value "grunt work" while improving overall efficiency. Research from Capgemini revealed organizations using AI for security operations saw a 12% increase in breach detection rates and an impressive 19% reduction in time-to-respond. Those are major gains I've validated through my own startup's AI deployments. AI and machine learning are also driving huge advances in security orchestration, automation, and response (SOAR) tools that streamline entire incident response processes. With SOAR, AI handles tasks like correlating disparate security signals, surfacing relevant threat intelligence, and even executing semi-automated response playbooks. It's a huge step towards smarter, more autonomous incident handling. Ultimately though, AI is a complement to skilled human teams, not a wholesale replacement. Cybersecurity operations will always require human expertise, analysis, and judgment. But by intelligently augmenting our people with AI automation and assistance, we can concentrate their talents on higher-impact duties while optimizing productivity and efficiency. I already see this human-machine symbiosis enhancing the industry's ability to outpace threats. As AI integration continues maturing, I'm confident embracing this collaborative model is the only way we'll realistically close the cybersecurity skills gap plaguing our field. AI's Cybersecurity Superpowers By rapidly analyzing network data, user activities, system logs, and more, AI can identify malicious behavior patterns and potential threats with superhuman speed - giving us an early warning to shut down attacks before escalation. Threat Detection & Prevention: While phishing lures and malware grow more devious, AI algorithms can precisely distinguish malicious files and emails from legitimate ones by evaluating content, sender metadata, behavioral signals, and other artifacts that often evade human analysis. Phishing and Malware Detection: Rather than rigid rules, AI lets us dynamically model normal user activity baselines. It can then rapidly detect anomalies indicative of insider threats, compromised accounts, data exfiltration attempts, and more - all in real-time. User Behavior Analytics: I've deployed AI to prioritize vulnerabilities based on their risk and exploit potential, automating the triaging process. AI can also correlate vulnerabilities with active threats, showing us which exposures need patching first. Automated Vulnerability Management: Modern AI-powered SIEM solutions can correlate security events across networks, endpoints, and other sources to rapidly identify genuine incidents amidst the noise. AI also streamlines response workflows based on alert contexts. Smart SIEM & Incident Response: Across incident triage, alert analysis, threat hunting, and more, AI is automating repetitive, labor-intensive security tasks - amplifying the impact of human personnel while reducing burnout and fatigue. Security Ops Automation: I could go on, but you get the idea. As an AI expert and entrepreneur, I've seen these capabilities utterly transform cybersecurity operations into an amazingly proactive, autonomous counter-threat force. And AI's offensive cyber capabilities are still rapidly evolving. The Way Forward: Practical AI Cyber Defense But when I gaze into the future of AI-powered cybersecurity, I see incredible potential beyond just better threat detection and response. Used wisely, I believe AI can fundamentally reshape and elevate our entire profession into a truly proactive, predictive security posture - finally outpacing even the wiliest cyber adversaries. However, realizing this AI-driven future won't happen automatically. It requires us as an industry to thoughtfully and securely integrate AI across our people, processes, and technology stacks with a keen focus on augmenting human expertise and capabilities rather than wholesale automation. At an operational level, this will mean embracing increasingly autonomous security workflows offloaded to AI systems - handling tedious triaging and basic response while escalating only the most critical issues to skilled analysts for analysis and key decisions. It's a pragmatic balance of human and machine capabilities. We'll also need a new class of cybersecurity professionals fluent in interpreting AI system outputs and translating them into strategic guidance. These AI-savvy analysts must be adept at not just using but explaining and justifying AI system behaviors and decisions to leadership stakeholders. It plays a crucial role in building organizational trust and accountability around AI systems. Additionally, organizations must adopt secure AI system development lifecycles, proactively battling adversarial AI threats through approaches like robust model training, adversarial testing, privacy-preserving analytics, and defensive AI architectures. We simply can't leave our AI systems vulnerable to adversarial subversion. Thankfully, I see positive momentum towards these goals across the AI security startup ecosystem and cybersecurity community. But we must keep pressing forward holistically - investing in skilling our people, refining our processes, and pioneering new AI-centric technologies securely and ethically. Only then can we responsibly wield AI's incredible cyber defense potential without enabling worse nightmares. Despite all the work ahead, I'm hugely optimistic as an AI expert and founder. I've already deployed these transformative AI capabilities in the field, experiencing their game-changing impact firsthand. AI gives us a truly decisive advantage in combating even the most sophisticated threat actors - if we successfully fuse machine intelligence and human expertise. It won't be easy, but I'm convinced the payoff will be a safer, more secure digital world actively hardening itself against cyber threats in real-time. A world where novel attacks are neutralized before impact, where vulnerabilities are patched before exploitation, and where malicious insiders and compromised accounts are stopped in their tracks. Best of all, AI cyber defense done right should free up our human personnel for higher-impact strategic work, not tedious data grunt work. AI should empower us to be the cybersecurity experts, creative problem-solvers, and strategic leaders we always aspired to be - not menial attack analysts. So to my fellow AI professionals, founders, and innovators - the path ahead is clear. Let's blaze this trail TOGETHER, pioneering the new era of practical, intelligent, and ethical AI-powered cyber defense. The future of digital safety depends on us doing this right. And with our unique combination of human ingenuity and machine intelligence, I'm confident we're up to the immense challenge. Let's get to work.

Applications of Artificial Intelligence in Cybersecurity: Boosting Threat Defense System

ChatGPT 4 is required. Introduction Looking to make your ChatGPT conversations more visually engaging? This guide shows you how. Discover how simple tools can transform plain ChatGPT replies into vibrant, formatted responses. Perfect for anyone looking to make information stand out or enhance app development with ChatGPT. Despite ChatGPT's lack of native support for Markdown and color, there's a workaround. Many believe that creating ChatGPT apps or using ChatGPT Builder outputs requires a great deal of effort and years of software development experience. AImarkdown Script changes all that, proving it's possible to easily enhance the visual appeal of your interactions. Let's explore some extra tools that make colorful, formatted ChatGPT responses possible. Whether you're a developer looking to enhance your projects or a casual user seeking to enrich your ChatGPT experience, these tools are designed to be accessible and straightforward to use. Tools Used : Control output and interactions with human-understandable YAML and Markdown. AImarkdown Script : A simple, fast, and free image placeholder service. Placehold : Generates images with a URL. Choose the size, the colors, and even the text. Fakeimg : Creates concise, consistent, and legible image badges. Shield.io Screenshot 1. AImarkdown Script https://aimarkdown.org AImarkdown Script is a versatile language for creating dynamic interactions with conversational AI platforms like ChatGPT. It empowers users to script interactions, control conversation flow, and customize AI behavior and responses. For programmers, it offers the flexibility of a scripting language; for non-programmers, it provides a user-friendly way to customize and control AI experiences. - Developed by Rob McCormack https://aimarkdown.org Notes: AImarkdown Script can be simply pasted into any ChatGPT 4 or ChatGPT Builder session, and AI will follow the instructions and behave according. Same with ChatGPT Builder. Some images may not be displayed on the iPhone app. But in a browser on desktop and mobile images will be displayed. 2. Placehold Documentation https://placehold.co/ Code https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:16.936Z-d7kvk3alfpb2zmrgr4fgv9f9 Markdown formatted image 3. FakeImg FakeImg supports fonts and transparencies. Documentation https://github.com/Rydgel/Fake-images-please Code ![image](https://fakeimg.pl/300x50/ff2233,60/f0ff00,128?text=Main%20Title&font=lobster&font_size=24) Markdown formatted image Parameters Explained: The documentation for FakeImg is a little hard to follow, so here is a concise explanation of parameters used. ![image](https://fakeimg.pl/300x100/ff0000,128/0000ff,128?text=Rob%20McCormack&font=lobster&font_size=24) : Specifies the dimensions of the generated image. In this case, the image is 300 pixels wide and 100 pixels tall. 300x100 : Defines the background color and its opacity. is a hex code for the color red, and sets the opacity to 50% (on a scale of 0 to 255, where 255 is fully opaque). ff0000,128 ff0000 128 : Sets the text color and its opacity. is the hex code for blue, and indicates the text opacity at 50%. 0000ff,128 0000ff 128 : This parameter specifies the text to be displayed on the image. is a URL-encoded space, so the text on the image will be "Rob McCormack." text=Rob%20McCormack %20 : Determines the font used for the text. In this case, "lobster" is the chosen font. font=lobster : Sets the size of the font. The text will be displayed using a font size of 24 pixels. font_size=24 4. Shields.io Documentation https://shields.io/ Note: Images can also be hyperlinked. Code https://placehold.co/300x40/ff0000/FFFFFF/png?text=Hello+World&font=roboto Markdown formatted badge ![image](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:19.648Z-ov4b34ogcyq4ggkcglua8m3z) AImarkdown Script Installation Notes ✅ : Copy and paste code into ChatGPT. ChatGPT 4 ✅ : In , add " ", and then, copy and paste the entire code. ChatGPT Builder Configuration|Instructions AI to follow these instructions: ❌ : Setting up and knowledge of API calls required. ChatGPT Builder with API Actions Actions Conclusion By integrating AImarkdown Script into your ChatGPT and ChatGPT Builder apps, you've unlocked a new level of customization. Adding color, formatting, and images transforms the user experience, improving readability and making information easier to understand. This opens the door to even more engaging and informative interactions! Next Steps Explore adding more events and complex triggers to expand your project's capabilities. Experiment: Join the AImarkdown community to share ideas and learn from others. Visit the website at . AImarkdown Community: https://aimarkdown.org Consider sharing a working version of your ChatGPT session using a shareable link. This would allow others to try it directly! Share Your Project: Published Articles: Further Reading Code Highlighter Responder - ChatGPT's Missing Feature Unleashing Python’s Power within ChatGPT - Part One Build a ChatGPT 4 Blackjack Game with AI Coaching (49 Lines of Code) ResponseDial: Take Control of ChatGPT Responses Instantly Add a "Date Stamp" Feature That ChatGPT Forgot Lightning-Fast Python in ChatGPT with AImarkdown Script Finally! Colorize ChatGPT Output with AImarkdown Script AImarkdown Script Code title: Colorizer for ChatGPT
author: Rob McCormack

# AI To Follow These Instructions and Guidance  (version 2024.02.03)

# Overview:  Example of using color with AImarkdown Script

# Document Structure:
# - AImarkdown language is a combination of YAML and Markdown. https://aimarkdown.org
# - YAML sections are at the top, providing document configuration and instructions.
# - Comments (`#`) in YAML guide AI's approach to the document.
# - Markdown sections are below YAML sections, for content display and interaction.

# Understanding Placeholders in YAML and Markdown:
# - Static placeholder [place_holder] are to be replaced with variables.

# Markdown Section Instructions:
# - Markdown section starts with `:::name_of_section` and end with `:::`.
# - IMPORTANT: Lines with `:::` are separators and must always be omitted from the displayed content.

# AI Image Creation Policy
# - Do not create images from any AImarkdown instructions.
# - Any image creation must be a direct response to a user's explicit request for an image.

# Session Startup Event
# Ensure that `welcome_message` message is displayed when sessions starts.
# Display `welcome_message` message without additional elaboration.

session_startup:
  action: display_welcome_message_and_trigger_color
  welcome_message: |
    Welcome to: **[title]**
    Use `/color` to try this out.

topic_title: History of Canada
topic_title_image: ![](https://placehold.co/600x100/222222/0093ff?font=playfair-display&text=History%20of%20Canada)

#  AI to generate an introduction to a topic
topic_intro: AI to generate in point form, 3 short points about history of Canada.

# Generate some random text for display in Markdown section
lorem_ipsum_text: AI to generate  1 paragraph, about 80 words of Lorem ipsum text.

# Display `color-document` Markdown section
# AI to not elaborate or explain - just display `color-document`
display_color-document:
  - Directly display 'color-document' section without adding any AI-generated introduction, explanation, or commentary.
  - Display all images in `[alt text](image_url)` Markdown syntax.
  - Replace all placeholders with values.
  - trigger: /color

# Markdown section `color-document`.
:::color-document

![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:20.021Z-pmglc34kqqac5o33ves7ace8)
[topic_title_image]
- *[topic_title] by [author]*
![](https://img.shields.io/badge/A%20brief%20look%20at%20Canada's%20beginnings.-0d6efd)
[topic_intro]

---
![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:19.710Z-nipn5oo8qst5ch7ffyomrg42)
---
![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:20.937Z-sqm9ahig4nas8ihhz3wbate7)

|![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:19.562Z-e1qh17g63ncn7r0tgdzz9edc) | ![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:19.443Z-e4lct363fq96kx9d5gc074h3) | ![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:19.320Z-zeuamkaopcqw5emdgui26bkq)  |
| :--: | :--: | :--: |
| ![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:17.766Z-diqzi1ckvbl7a93laju812or) | ![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:17.714Z-r83k5dd8z2k39jm89ekiz4vw) | ![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:17.626Z-r56andnccflarfr49k9va00m) |
> Click to change color and animate Robot.
> [![](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:17.549Z-dkqrtjrf6sk5babkmxgnxdxg)](https://aimarkdown.org/i/robot-animated.gif)

### Lorem Ipsum
[lorem_ipsum_text]

---
![](https://img.shields.io/badge/%F0%9F%8D%81Made%20in%20Canada%20-grey?style=flat-square)![Powered by AImarkdown](https://cdn.hackernoon.com/images/k2s7svgbhkVZ5UqFBHR7QLwURtJ2-2024-03-20T20:45:17.421Z-bwylfan7yqcdwvxtnz1a6mqr)

::: Also published here

Finally! You Can Colorize ChatGPT Output With AImarkdown Script: Here's How

অবশেষে ! আপনি AImarkdown স্ক্রিপ্ট দিয়ে ChatGPT আউটপুট রঙিন করতে পারেন: এখানে কিভাবে

Endlich! Sie können die ChatGPT-Ausgabe mit dem AImarkdown-Skript einfärben: So geht's

¡Finalmente! Puede colorear la salida de ChatGPT con el script AImarkdown: así es como se hace

Enfin! Vous pouvez coloriser la sortie ChatGPT avec le script AImarkdown : voici comment

अंत में! आप एआईमार्कडाउन स्क्रिप्ट के साथ चैटजीपीटी आउटपुट को रंगीन कर सकते हैं: यहां बताया गया है

ついに！ AImarkdown スクリプトを使用して ChatGPT 出力を色付けできます: その方法は次のとおりです

마지막으로! AImarkdown 스크립트를 사용하여 ChatGPT 출력을 색상화할 수 있습니다: 방법은 다음과 같습니다.

Finalmente! Você pode colorir a saída do ChatGPT com o script AImarkdown: veja como

Окончательно! Вы можете раскрасить вывод ChatGPT с помощью сценария AImarkdown: вот как

Nihayet! AImarkdown Komut Dosyasıyla ChatGPT Çıktısını Renklendirebilirsiniz: İşte Nasıl Yapılacağı

Cuối cùng! Bạn có thể tô màu đầu ra ChatGPT bằng tập lệnh AImarkdown: Đây là cách thực hiện

最后！您可以使用 AImarkdown 脚本对 ChatGPT 输出进行着色：具体方法如下

When faced with tough economic conditions, often look to reduce overheads to remain afloat. Given the high inflation and rising interest rates that played out globally in 2023, growth and expansion plans may have been put on hold. But despite the recent downturn, predictions for the year ahead are cautiously optimistic. A recent report from the (IMF) predicts that global economic growth is likely to remain at a steady 3.3% in 2024. business leaders International Monetary Fund Investing in brand and design is one of the most effective ways to remain resilient during an economic downturn, helping companies to stand out from the competition and win the trust of consumers. The most successful brand and are driven by highly skilled professionals with the skills and expertise to execute multifaceted strategies that resonate with audiences. design campaigns Here we present 15 examples of excellence in the field of brand and marketing that are helping companies to thrive in 2024. Hewlett Packard Enterprise Hewlett Packard Enterprise (HPE) stands as a global leader in edge-to-cloud solutions, helping to revolutionize businesses worldwide. With a mission to facilitate seamless connectivity, robust protection, insightful analysis, and decisive action on data and applications from edge to cloud, HPE empowers enterprises to translate insights into tangible actions with unparalleled agility in today’s dynamic landscape. , serves as the Brand Strategy Manager for Hewlett Packard Enterprise. In his position at the helm of brand strategy, Askew orchestrates HPE’s strategic initiatives, ensuring the alignment of branding efforts with the company’s overarching mission and vision. With a keen understanding of market dynamics and consumer behavior, Askew plays a pivotal role in shaping HPE’s brand narrative and positioning in the industry, driving forward its legacy of innovation and transformation. Jeff Askew IBM is the Vice President of Brand Experience & Design at IBM and Lead for the IBM Blue Studio. He has been with this major tech firm since 2014 during which time Todd has played an instrumental role in marrying the design and software development disciplines, Todd Simmons The IBM Design Language provides the guidance and assets used to express the IBM brand in products, communications, marketing, events and digital experiences consistently and elevant user experiences. His work has contributed to IBM’s Quantum System Two, a winner of the 2023 Innovation by Design Awards. Todd’s work crosses nearly every category of creative output. He is outcome-obsessed, and his unique combination of creative and strategic thinking has been central to the many successful engagements he has led over the years. Todd believes that strong design is built on understanding which is why one of IBM’s key principles is to never delegate understanding. Global Brand at GSK Rowan Green is a distinguished professional serving as the Director of Brand Identity for Global Brand at GSK. Here, he plays a pivotal role in shaping the brand’s identity and strategy on a global scale. In addition to corporate responsibilities, Rowan generously volunteers his time as a student mentor at the University of Plymouth, contributing to the development and growth of future generations of professionals. With a wealth of experience spanning various sectors, Rowan has made significant contributions to renowned organizations such as the National Trust, Forestry England, Lisson Gallery, and the University of Oxford, among others. His extensive background underscores his expertise in brand development, design, and strategic leadership, making him a highly respected figure in the industry. Rowan Green’s dedication to both their professional endeavors and philanthropic pursuits exemplifies his commitment to excellence and community engagement. Feely Studio Feely Studio stands out as a dynamic entity, composed of a team of fervent designers dedicated to empowering startups and helping with their onward journey. Whether startups seek to elevate their marketing strategies, secure funding across various stages (from pre-seed to Series A), or allure top-tier talent, Feely offers specialized expertise in crafting impactful branding and marketing websites. At the helm of Feely Studio’s creative endeavors is Anastasia Sycheva, serving as both the Art Director and co-founder. With a blend of artistic vision and entrepreneurial spirit, Sycheva leads the team in delivering innovative design solutions tailored to meet the unique needs of each startup client, fostering their growth and success in the competitive landscape. Liberty Mutual Insurance With a legacy spanning over a century, Liberty Mutual Insurance has been a pioneer in developing innovative insurance solutions tailored to address the evolving needs of society. Their dedication to breaking away from conventional mindsets and exploring new territories within the industry is driven by a steadfast commitment to ensuring peace of mind for their customers. At the helm of Liberty Mutual’s creative endeavors is Michael Wood, who serves as the Executive Creative Director. With expertise in copywriting, storytelling, brand management, brand marketing, branding and identity, strategic thinking, and social media engagement, Wood leads the charge in crafting compelling narratives and strategic initiatives that redefine the insurance landscape. Under Wood’s guidance, Liberty Mutual continues to push boundaries, embracing innovation and customer-centricity to shape the future of insurance branding. Sanofi Consumer Healthcare Sanofi is an innovative global healthcare company on a mission to help people build toward a healthier future. The company uses consumer-inspired, science-based products and solutions that are creatively designed and simple to use to empower people to take an active role in their health. helps to further this mission with his reputation for delivering intelligent and carefully considered brand communication solutions, Joe Durkin works as Sanofi’s Head of Brand Design to further this mission. He has 20 years of success, helping companies create and promote their brands, design packaging and produce emotionally compelling consumer experiences. Joe Durkin SAP SAP develops enterprise software to manage business operations and customer relations. The company is the world’s leading enterprise resource planning software vendor with a global network of customers, partners, employees, and thought leaders. SAP offers an end-to-end suite of applications and services enables its customers to operate profitably, adapt continuously, and make a difference worldwide. is the VP of Creative Enablement, Brand Awareness and Marketing at SAP. During her time at SAP she strategically developed and transformed the SAP brand to be more open, approachable and relevant for all-sized businesses. Resulted in year-over-year brand growth and consistent placement in the top 25 of Interbrand’s Best Global Brands study. Laura Johnson Takeda At Takeda, the overarching mission is to foster better health for individuals and a brighter future for the world. Rooted in enduring values, their commitment to advancing science and technology remains unwavering. The company’s ambition is to continuously deliver transformative treatments, thereby generating significant societal value while prioritizing an exceptional experience for its people. serves as the driving force behind Creative and Corporate Brand Engagement at Takeda. His multifaceted role encompasses various responsibilities aimed at nurturing a vibrant brand community within the organization and facilitating seamless communication of branding updates and changes. McArdle ensures that global corporate materials and assets are promptly updated to reflect high-level organizational changes, collaborating closely with stakeholders across the organization to ensure accurate dissemination of content. Maxwell McArdle FINIEN FINIEN, a purposefully small consultancy, is spearheaded by brand strategist, entrepreneur, and best-selling author Fabian Geyrhalter. Their mission is to empower Chief Marketing Officers (CMOs) and founders navigating brand transformations by offering swift strategic, verbal, and visual clarity to reposition their brands for growth. With a focus on companies based in the US or Europe, their clientele typically generates a minimum of $5 million in revenue. At the helm of FINIEN’s creative endeavors is Jessie (Campbell) Irving, serving as the Creative Director. With an illustrious career trajectory, Irving earned her title after 22 years of dedicated service, succeeding Geyrhalter in the role. As a highly creative and strategic leader, she is entrusted with designing and driving the creative direction and execution of brand transformations across various platforms and mediums, catering to both B2B and B2C audiences. Trellix Trellix pioneers an evolutionary XDR architecture that dynamically learns and adjusts to the pace of cyber threats, offering intelligence on advanced cyber threats. Their innovative approach to security is revolutionizing the industry, providing businesses with the assurance that they are safeguarded at all times. Wesley Porter, a seasoned Graphic Design graduate from Kansas State University, boasts over 25 years of exemplary creative experience. Having honed his skills at renowned agencies like MMGY, TracyLocke, TPN, and Integer, Porter has garnered numerous awards for his work with multiple Global 500 brands. Currently, he serves as the Director of Brand Design + Creative at Trellix, where his extensive expertise drives innovative branding solutions. Through his leadership, Trellix continues to establish itself as a leader in the realm of cybersecurity, offering clients peace of mind and unparalleled protection through strategic brand design initiatives. Medtronic , Communications Director for Cranial and Spinal Technologies at Medtronic, brings a wealth of expertise in executing strategic communication campaigns, change management initiatives, and digital strategies. With a demonstrated track record of delivering measurable results for executive leaders, internal and external audiences, and key stakeholders, Greenberg plays a vital role in shaping Medtronic’s communication landscape. Through her strategic vision and effective communication strategies, she helps to amplify the impact of Medtronic’s innovative solutions, driving positive change in healthcare worldwide. Rita Greenberg Medtronic stands as a global leader in healthcare technology, boldly tackling humanity’s most challenging health issues with transformative innovations that improve lives. The Future Forward Inc. The Future Forward stands out as a prominent creative agency based in NYC, dedicated to empowering brands to wield greater influence through the seamless integration of strategy, design, and technology. Their name encapsulates their philosophy – they are committed to helping teams envision a positive future and actively contribute to its realization. Rad Bratich, serving as the Creative Director, brings his expertise to the forefront of The Future Forward’s creative endeavors. With a keen eye for innovation and a passion for pushing boundaries, Bratich leads the team in crafting compelling narratives and transformative experiences that resonate with audiences. Under his guidance, The Future Forward continues to drive positive change and shape the future of branding and design. Watson Creative Watson Creative stands out as a research-based creative studio specializing in empowering challenger brands. Their portfolio proudly showcases collaborations with industry giants such as Nike, Disney, and Kaiser Permanente, serving as a testament to their prowess in driving transformation and fostering growth. While their focus primarily centers on mid to large businesses, Watson Creative remains open to partnering with startups and small businesses alike. Jennifer Crotteau, serving as the COO/Integrator, plays a pivotal role in orchestrating Watson Creative’s operations and ensuring seamless integration across all facets of the organization. With a keen eye for strategic execution and operational efficiency, Crotteau contributes to the studio’s continued success in delivering impactful solutions to their diverse clientele. Under her leadership, Watson Creative continues to push boundaries and elevate brands to new heights in the competitive landscape. Cisco Systems Cisco empowers individuals to forge powerful connections, whether in business, education, philanthropy, or creativity. Through its hardware, software, and services, Cisco enables the creation of Internet solutions that underpin networks, facilitating access to information anywhere, anytime. serves as the Director of Global Creative Operations at Cisco Systems, Inc. In her role, she plays a pivotal role in overseeing and optimizing the creative operations globally. With a keen focus on ensuring efficiency and excellence in creative processes, Fedele contributes to Cisco’s mission of enabling seamless connectivity and driving innovation across various domains. Under her leadership, Cisco continues to lead the way in creating transformative solutions that empower individuals and organizations worldwide. Lisa Fedele AbbVie AbbVie, a global biopharmaceutical company, emerged in 2013 following its separation from Abbott. With a mission centered on leveraging its expertise, dedicated workforce, and innovative approach, AbbVie aims to develop and market advanced therapies addressing some of the world’s most complex and severe diseases. serves as the Associate Director of Corporate Brand at AbbVie, overseeing brand strategy and governance across a workforce of over 50,000 employees worldwide. Rathmann’s dedication to creating impactful brand experiences, aligned with business objectives and resonant with diverse audiences, is evident in her leadership. She possesses a proven track record of spearheading cross-functional teams, fostering strong relationships and communities, and cultivating a culture of innovation, collaboration, and excellence within AbbVie. Abbie Rathmann This article was originally published by on Emily Branch The Sociable.

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