NYCE.

nyce

An Initial Coin Offering, also commonly referred to as an , is a fundraising mechanism in which new projects sell their underlying crypto tokens in exchange for bitcoin and ether. It is somehow similar to an Initial Public Offering (IPO) in which investors purchase shares of a company. ICO This form of blockchain fundraising has existed since July 2013. Over the last two years, the ICO model has been used by hundreds of organizations to raise billions of dollars. ICOs are booming despite the price collapse of cryptocurrencies and the volume reached new record highs in the first half of 2018. However, ICOs (for now) have a sordid history and little regulatory insight. Investors are often buying coins or tokens for a project that does not even fully exist yet. In most cases, the team will have some degree of code to show what the project will look like. However, there is no guarantee of projects ever being completed or even being embraced by mainstream users. This is a risk people need to be willing to take, as it may take years until there is an actual market for the project in question. STO: Bringing the trendsetter to the market Security Token Offerings, or STOs, are financial securities because they mimic traditional shares. With STOs it’s an upgrade whereby you can purchase tokens during the offering that you can then trade, sell, or hold. However, since security tokens are actual financial securities, your tokens are backed by something tangible like the assets, profits, or revenue of the company[4]. In order to start an STO, a business must complete the traditional registration process of an IPO. As these projects become the next “topic of the day”, you need a right talent to create a buzz in the audience. are helpful for your Pre and Post ICO marketing strategies. They are more efficient to develop the right , , s, , and many more . Finding the right and suitable is a really complicated task so here’s a list of the that can handle your STO projects very well. Marketing Companies and Agencies Content marketing social media marketing PR Service Display Marketing marketing strategies STO marketing agency TOP ICO Marketing agencies Top 30+ STO Security Token Offering Marketing Agencies Crowdcreate Crowdcreate is a top-ranked global ICO marketing agency. Over $106 million crowdfunded across 40+ campaigns. . The world’s largest tech companies choose Crowdcreate to raise more investor funds and grow their online community. They’re experienced growth marketing experts and have the case studies to prove it. They also have more than 35 successful raises with over 7.1 million subscribers 2. Amazix They are a group of professional crypto ICO mods who have technical expertise, are excellent at support and led by an elite team of managers. They have managed some of the largest ICOs in history including Bancor, BANKEX, and Hdac. 3. Element Group Element group is among the leading ICO marketing agencies which seem to provide a range of comprehensive services. The company executes token sales and ICOs; it facilitates the relationship between issuers and buyers and structures marketing processes in a concise and effective way. 4. FoxTail Marketing FoxTail Marketing is a US-based digital marketing company which has successfully completed a range of ICO campaigns. Amongst other things, it also provides lead generation services for mid-market companies. Unlike a lot of specialized agencies of the kind, this one also provides regular marketing services to companies outside of the ICO market. 5. ICOBOX It’s amongst the first ones to emerge on the market. It’s a Russian company with capabilities which encompass a broad range of potential necessities for any ICO project. From whitepaper writing to legal assistance, the marketing agency claims to be able to provide ICOs with the assistance they need from start to end. However, the company is best known for its PR capabilities. 6. 7MARKETZ 7MARKETZ is a global FinTech marketing agency, delivering creative business solutions for startups and enterprises throughout Europe and North America since 2010. Meet 7MARKETZ where the most passionate and skillful professionals join their forces to create uplifting marketing experience! 7MARKETZ Team combines various marketing approaches to lead client’s ICO to strategic objectives and tackle complex development challenges. They infuse client’s ICO with their expertise, fresh vision and a full spectrum of analytical tools. 7. Applicature Applicature is a blockchain development agency working on projects in the blockchain and cryptocurrency industries. They review companies’ business models and help clients adjust their businesses within the growing blockchain ecosystem. They offer a wide range of custom blockchain development services. 8. IBC Group IBC is an international blockchain consulting group spanning 40 countries facilitating end to end ICO support, enterprise blockchain development, capital raising, consulting and institutional training. Their team has supported startups, existing companies and institutions/governments executing long-term strategies. 9. Priority Token They are an international ICO advisory and promotion agency incorporated in the UK with offices in London, Singapore, Moscow, and Dubai. They have fostered a wide network of connections and expertise which can transform a client’s ICO project from good to great. 10. Byzantium Comprised by a team of blockchain, PR, marketing, and investment experts, Byzantium is an ICO marketing company which offers a broad range of services. It crafts tailored marketing strategies and executes them accordingly. The company also promises to provide relationship management, introducing the project to the right investors, advisors, and overall crypto professionals. 11. Ambisafe Ambisafe’s founding team has been pioneering cryptocurrency development since 2010. Their experience ranges from development of alternative consensus algorithms in 2010 to launch the first multi-currency wallet in 2014. Some of their recent achievements include going through the first bitcoin class of silicon valley startup accelerator, breaking to the finals of the SWIFT Innotribe Startup Competition and being the first digital wallet to implement MasterProtocol. 12. MaZee MaZee provides End — to — End ICO Community Management and Marketing service, with an eye for quality delivery. Their focus is on building strategies with the teams that will work for hand — in — hand with client’s project, to help with client’s success. It is a company which has explicitly stated that it places the emphasis on community management. Understanding the necessity for community trust, MaZee executes excellent bounty campaigns and drives successful community engagement throughout the possible channels. 13. InboundJunction InboundJunction is a complete blockchain marketing and ICO making solution for ICOs and Blockchain projects. InboundJunction has worked with more than 70 successful ICOs and top crypto coins and therefore knows the industry, influencers, funds, and community extremely well. Their team is extremely experienced with both Blockchain and marketing so it has the ingredients and capabilities to support, market, advise and promote ICOs successfully. 14. ICO Angels ICO Angels are a specialist advisory & marketing service positioning blockchain related projects for ICO funding. They have boosted the normal crowdfunding process by converting their own network of Angel investors into evangelists of the emerging crypto-currency market. 15. Sparkchain Sparkchain harbors a team of blockchain and digital currency marketers which bring highly technical and complex solutions. The company has expertise in developing protocols, smart contracts, and community development, amid a range of fairly technical capabilities with solutions such as open source technologies, permissioned ledgers, exchanges, wallets, mining applications, and others of the kind. 16. TSM Global TSM Global is UK registered company working via its shells in Macedonia and Moldova. It offers full-service ICO support. With its beginnings in marketing, TSM has raised more than $270 million for its clients. TSM’s international team can offer support in English, Japanese, Chinese, Koran, Russian, German and other languages customizing the campaign to the needs of every client. 17. Searched Bridging The Gap Between Web Development, Search, PR And Content Marketing For Blockchain Startups and ICO’s, They are a crypto-currency marketing agency constructed by entrepreneurs who love to build and create. With experience in growing Startups from the ground up using their advanced SEO and digital marketing strategies and development skills, they have naturally navigated towards Blockchain Startups and ICO’s to support launch and growth as a dedicated Blockchain marketing agency like no other. Their love of seeing their clients grow ensures ultimate performance in a time-constrained industry. 18. Key Difference Media KEY Difference Media focuses uniquely on the crucial stage of ICO marketing. They bridge the gap between their clients and investors — giving them the tools to bring in leads dedicated to their client’s cause. They have a team of experts who are well known in the blockchain community. They help you build the engaging, trustworthy online brand that the client’s audience wants to get behind. 19. MLG Blockchain Consulting MLG Blockchain is a global blockchain development and consulting firm headquartered in Toronto with a distributed team across North America, Europe and Asia that is focused on building next-generation applications using blockchain and smart contract technology. They speed up the client and his team’s understanding of the blockchain and its potential opportunities for the clients business and help them to create a blockchain strategy that client can use today. 20. Belkin Marketing Belkin Marketing is a global digital marketing agency. They provide services that include market, search and media strategy, SMM and experience marketing. Most noteworthy, content marketing and lead generation. Founded in 2007 in San Diego, California, Belkin Marketing Team currently works out of three offices: San Diego, Moscow, and Hong Kong. A unique team of digital creators, they go through an extensive hiring process to eliminate all but the best. In addition, Agency is currently partnered with several global marketing and retail professional brands — including JosDeVries (Holland), DOING (Italy), Think Kong (Poland). 21. Crynet Crynet started as a data-driven digital marketing agency but has quickly grown to be full-service marketing agency with representatives in 3 continents. Crynet offers a wide range of support services for ICOs and Blockchain Driven Business, such as Multinational Legal Support, Blockchain Development, and Tech Support, Payment Gateway crypto-cash, Blockchain HR, Advisor Support, SMM across all Social Media, Telegram, etc. Crynet also has unique coverage of Asia — Japan, Korea, and China allows us to reach out to crypto-communities worldwide. 22. Zerion Zerion is a fintech company with an expertise in creating blockchain-based applications. They have experience in smart contract development on Ethereum blockchain and their focus is on executing ICOs. Zerion believes in a decentralized future. They help innovative companies to create blockchain-based products that disrupt and disintermediate and they empower the individual investor over The Man. They are dedicated, experienced technologists with the knowledge, network, and integrity to help companies go from an idea to success. They power Initial Coin Offerings. Founders secure the infrastructure to issue their tokens. Investors get an intuitive investment interface, which makes building and managing a portfolio easy. 23. CoinFabric CoinFabric is a full-service launchpad for ITOs (Initial Token Offerings) & ICOs (Initial Coin Offerings), advising on overall strategy and implementing it through a variety of services from content marketing, paid advertising and community building, to investor & influencer outreach and more. With a team of industry experts, in their respective fields, CoinFabric has all of the parts to successfully help companies to achieve successful Presale, PreICO & Public Crowdsale events. 24. Official Startups Official Startups is a full-service strategic business consulting, brand management, and marketing agency dedicated to inspiring the entrepreneurial spirit and bringing business dreams to life. The company is a brick and mortar physical business with an established reputation in the Canadian Blockchain Community. The ICO Blockchain team is piloted by Audrey Nesbitt who leads a large team that covers every stage required to have a successful ICO. 25. TokenAsia Equipped with a team of industry experts in technology, marketing & consultancy solutions, TokenAsia offers a full-stack, highly customizable token sale platform. Their primary focus is launching a comprehensive crowdfunding campaign by designing & implementing the overall strategy through integrated promotional services aimed at building Community, Investor, and influencer outreach. 26. IBC Group IBC is an international blockchain consulting group spanning 40 countries facilitating an end to end ICO support, enterprise blockchain development, capital raising, consulting and institutional training. Their team has supported startups, existing companies and institutions/governments executing long-term strategies. 27. Argon Group The Argon Group is an investment bank with a focus on digital finance — the emerging crypto-currency and token-based capital markets. They provide financial advisory, placement, and technology services to companies seeking to raise equity, debt, and non-dilutive capital. The Group develops technical placement solutions including digital tokens powered by advanced smart contracts, which they operate through a digital asset placement and brokerage platform called TokenHub.com. They are developing NYCEX.com, a digital asset and crypto-currency exchange, which will be on the cutting edge of technology and compliance. 28. Pro-Crypto Group The Pro-Crypto Group is a passionate Seoul, South Korea(Top 2 ICO marketplace) based growth marketing agency providing ICO Marketing, design and video production, release publications, and PR outreach, SNS Marketing, Community Management Marketing and influencer marketing. Focusing on a data-driven approach for every blockchain, branding, and crowdfunding campaign, we have successfully funded 29+ crowdfunding campaigns raising over $67 million averagely in 2 years. 29. Olshansky and partners The digital consulting agency “Olshansky and partners”. They offer ICO-consulting. This service will help correctly position client’s project, evaluate competitors, prepare the necessary internal documentation, take into account legal and financial aspects, carry out technical implementation (from tokens to site development), develop a marketing strategy, correctly allocate budgets, prepare the product for launch and accompany the project at all stages of the passage of the ICO to the achievement of the project objectives. 30. CryptoDex Cryptodex is founded on the principle that blockchain technology is changing the fundamental structure of not only our economy and banking systems but also the way we connect and engage as human beings. As we move further into a world that fully implements the utility of blockchain technology, new opportunities to create sustainable independent communities emerge. In the infancy of the blockchain movement, we have been experiencing radical shifts in the way we transact, invest, and allocate our energy, which we have called money. 31. Modern Token Modern Token is a company that provides blockchain consulting for VC-funded projects. Their clients are international companies that are willing to embed blockchain technology into client’s projects and to attract additional funding from private investors. Their team is continuously growing, and they are looking for English-speaking experienced professionals and young talents that show initiative, analytical thinking and are able to work without supervision both independently and in a team. 32. ICO Launch Malta ICO Launch Malta is a full stack ICO platform that services every aspect of a company’s ICO process from incorporation and tax planning, to token creation, smart contract development, and deployment, marketing and PR through to exchange listing. 33. CrowdFundX CrowdfundX is a FinTech marketing firm that markets Reg A+ IPOs and Security Token offerings (STOs.) We provide our clients with the tools and resources necessary to execute successful and compliant offerings while reducing the cost and complexity of acquiring both institutional and retail investors. — — — — — — — — — — — This list is based on my research and experiences only. You can use this only for reference and always do your own research before partnering to the right . STO Marketing Agency

Top 30+ STO Security Token Offering Marketing Agencies

Top 65+ STO Agencies | STO Service Providers

Top 30+ ICO Marketing Agencies & ICO Development Companies | Cryptocurrency Marketing Services

New York City plans to support electric vehicle (EV) adoption with a $15 million initiative to install 600 new curbside chargers. Can the city’s current grid infrastructure keep pace? New York City is ramping up its efforts to support electric vehicle (EV) adoption as it plans to install 600 new curbside EV chargers. Mayor Eric Adams recently announced that the initiative is part of a $15 million federal grant being awarded to the city to bolster its EV charging infrastructure — with a focus on underserved and low-income communities. “We’re building a cleaner, greener, and more affordable city for all New Yorkers, and through initiatives like this, we’re making sure that no New Yorkers are left behind,” wrote Mayor Adams in a blog post. “This $15 million grant will let us build the nation’s largest EV charging program, focused on low-income and disadvantaged areas so people living in all five boroughs can afford to drive and charge electric vehicles.” By 2050, New York City aims to get 20% of all new vehicles registered as electric. Thanks to incentives like the Inflation Reduction Act tax credits and Drive Clean rebates, a growing number of NYC drivers are switching to EVs. Despite these efforts, the city's grid is already struggling to keep up with the power and infrastructural requirements of current EV owners. Can NYC’s Electrical Grid Keep Up with the Growing Demand for EV Charging? NYC is currently grappling with two key challenges to scale its charging infrastructure — space and available power. For commercial transportation, charging hubs require significant space for infrastructure and larger electric trucks. In dense urban areas, especially NYC, real estate is limited and expensive, making it difficult to find suitable locations to accommodate charging stations and vehicles without disrupting city traffic. “Most of the federal EV infrastructure grants are for chargers deployed along highways (not buildings), limiting monetary incentives available to building developers deploying EV chargers,” Akshay Singh, Industrial and Automotive Industries Principal at PwC Strategy&, told me. “City planners need to work closely with utilities to make sure upgrades are being planned & performed timely, especially to supply dense urban areas with the highest EV adoption.” New York’s grid is already strained as the city attempts to electrify not only its transportation but also its buildings. Singh asserts that developers often do not understand the level of grid upgrades required due to a lack of available information. Moreover, these challenges are expected to become more prevalent with charging sites located in high-rise buildings that have not had capacity upgrades in years. “Major challenges with EV charging today are around how to make the economics of operating EV chargers feasible. DC fast chargers that operate at 100kW+ power output (to charge EVs within 30-45 mins) can cost upwards of $50k per unit which makes upfront costs of a multi-unit charging site very expensive,” added Singh. Electric Vehicles as Untapped Grid Assets? As New York pushes toward its ambitious goal of having 400,000 EVs on the road by 2030 as part of the "Green Rides" initiative, it’s clear that the city needs more fast-charging sites. Conglomerates like Revel are already making strides with its "superhub" in Brooklyn, boasting 25 high-speed chargers. But even with their success, the company faces a significant challenge: finding enough grid power to keep these large fast-charging stations running smoothly. While the city grapples with its grid limitations, some startups are stepping in to offer innovative solutions through A.I. and edge computing. Brooklyn-based Synop, for instance, aims to help stabilize the grid by integrating data from grid operators, EV charging stations, and EV fleet operators. “We focus on edge computing to enhance charging management,” Gagan Dhillon, CEO of Synop, told me. By bringing cloud-based functionality closer to the charging site, the company says it can increase reliability and reduce latency, “which is critical in areas with constrained grids or complex microgrid setups.” Dhillon added that one overlooked aspect of EV adoption is that electric vehicles are essentially batteries on wheels, and with the right infrastructure, they can serve as valuable assets rather than just power consumers. “EVs can act as backup power sources during times of high grid demand, providing energy back to the grid or even powering homes when needed,” he said. “With the integration of smart charging technology, EVs can be programmed to charge during off-peak times when energy is more abundant. This flexibility makes them less of a strain on the grid than often imagined.” With more people driving EVs and a grid under a lot of strain, NYC's EV goal success will hinge on how open it is to new technologies, speeding up infrastructure projects, and investing in sustainable energy solutions. “There will be a need for higher powered EV chargers that will further increase the grid upgrade requirements. Developers need to work together with local utilities from the start to successfully deploy EV projects,” Singh told me. “Along with that, additional [capital expenditure] needed to sustain the grid for more demand needs to be laid out and discussions on who will bear the cost burden.” New York City plans to support electric vehicle (EV) adoption with a $15 million initiative to install 600 new curbside chargers. Can the city’s current grid infrastructure keep pace? New York City plans to support electric vehicle (EV) adoption with a $15 million initiative to install 600 new curbside chargers. Can the city’s current grid infrastructure keep pace? New York City plans to support electric vehicle (EV) adoption with a $15 million initiative to install 600 new curbside chargers. Can the city’s current grid infrastructure keep pace? New York City is ramping up its efforts to support electric vehicle (EV) adoption as it plans to install 600 new curbside EV chargers. Mayor Eric Adams recently announced that the initiative is part of a $15 million federal grant being awarded to the city to bolster its EV charging infrastructure — with a focus on underserved and low-income communities. “We’re building a cleaner, greener, and more affordable city for all New Yorkers, and through initiatives like this, we’re making sure that no New Yorkers are left behind,” wrote Mayor Adams in a blog post . “This $15 million grant will let us build the nation’s largest EV charging program, focused on low-income and disadvantaged areas so people living in all five boroughs can afford to drive and charge electric vehicles.” By 2050, New York City aims to get 20% of all new vehicles registered as electric. Thanks to incentives like the Inflation Reduction Act tax credits and Drive Clean rebates, a growing number of NYC drivers are switching to EVs. Despite these efforts, the city's grid is already struggling to keep up with the power and infrastructural requirements of current EV owners. blog post blog post Inflation Reduction Act Inflation Reduction Act switching switching Can NYC’s Electrical Grid Keep Up with the Growing Demand for EV Charging? NYC is currently grappling with two key challenges to scale its charging infrastructure — space and available power. For commercial transportation, charging hubs require significant space for infrastructure and larger electric trucks. In dense urban areas, especially NYC, real estate is limited and expensive, making it difficult to find suitable locations to accommodate charging stations and vehicles without disrupting city traffic. “Most of the federal EV infrastructure grants are for chargers deployed along highways (not buildings), limiting monetary incentives available to building developers deploying EV chargers,” Akshay Singh , Industrial and Automotive Industries Principal at PwC Strategy&, told me. “City planners need to work closely with utilities to make sure upgrades are being planned & performed timely, especially to supply dense urban areas with the highest EV adoption.” Akshay Singh Akshay Singh New York’s grid is already strained as the city attempts to electrify not only its transportation but also its buildings. Singh asserts that developers often do not understand the level of grid upgrades required due to a lack of available information. Moreover, these challenges are expected to become more prevalent with charging sites located in high-rise buildings that have not had capacity upgrades in years. “Major challenges with EV charging today are around how to make the economics of operating EV chargers feasible. DC fast chargers that operate at 100kW+ power output (to charge EVs within 30-45 mins) can cost upwards of $50k per unit which makes upfront costs of a multi-unit charging site very expensive,” added Singh. Electric Vehicles as Untapped Grid Assets? As New York pushes toward its ambitious goal of having 400,000 EVs on the road by 2030 as part of the " Green Rides " initiative, it’s clear that the city needs more fast-charging sites. Conglomerates like Revel are already making strides with its " superhub " in Brooklyn, boasting 25 high-speed chargers. But even with their success, the company faces a significant challenge: finding enough grid power to keep these large fast-charging stations running smoothly. Green Rides Green Rides superhub superhub While the city grapples with its grid limitations, some startups are stepping in to offer innovative solutions through A.I. and edge computing. Brooklyn-based Synop, for instance, aims to help stabilize the grid by integrating data from grid operators, EV charging stations, and EV fleet operators. “We focus on edge computing to enhance charging management,” Gagan Dhillon , CEO of Synop, told me. By bringing cloud-based functionality closer to the charging site, the company says it can increase reliability and reduce latency, “which is critical in areas with constrained grids or complex microgrid setups.” Gagan Dhillon Gagan Dhillon Dhillon added that one overlooked aspect of EV adoption is that electric vehicles are essentially batteries on wheels, and with the right infrastructure, they can serve as valuable assets rather than just power consumers. “EVs can act as backup power sources during times of high grid demand, providing energy back to the grid or even powering homes when needed,” he said. “With the integration of smart charging technology, EVs can be programmed to charge during off-peak times when energy is more abundant. This flexibility makes them less of a strain on the grid than often imagined.” With more people driving EVs and a grid under a lot of strain, NYC's EV goal success will hinge on how open it is to new technologies, speeding up infrastructure projects, and investing in sustainable energy solutions. “There will be a need for higher powered EV chargers that will further increase the grid upgrade requirements. Developers need to work together with local utilities from the start to successfully deploy EV projects,” Singh told me. “Along with that, additional [capital expenditure] needed to sustain the grid for more demand needs to be laid out and discussions on who will bear the cost burden.”

NYC's $15 Million EV Charger Initiative: Can the City Grid Handle Rising Energy Demands?

CAYMAN ISLANDS, Cayman Islands, November 14th, 2024/Chainwire/--Prosper, a decentralized protocol bridging institutional-grade Bitcoin mining power on-chain and aiming to unlock the potential of Bitcoin through liquidity farming, today announced a new investment in its native project token PROS by one of the leading cryptocurrency mining companies Bit Mining Limited(NYSE:BTCM). Prosper's new strategic focus on Bitcoin mining and the broader Bitcoin ecosystem has been well-received by the community. As part of this strategic change, Prosper partners with prominent industry players to obtain various services and products to deliver institutional-grade execution in managing its mining hashrate. This investment from BIT Mining represents another significant validation of Prosper’s thesis by institutional backers. In addition to Prosper's growing roster of top-tier industry partners and sophisticated financial investors (including a recently announced investment by Waterdrip Capital), Prosper’s value proposition also resonates with cryptocurrency mining companies that bring extensive experience in mining operations and a strong understanding of the ecosystem. This investment aligns with Prosper’s strategic direction and supports its new vision. About BIT Mining Limited BIT Mining (NYSE: BTCM) is a leading technology-driven cryptocurrency mining company with operations in cryptocurrency mining, data center operation, and mining machine manufacturing. The company is strategically creating long-term value across the industry with its cryptocurrency ecosystem. Anchored by its cost-efficient data centers that strengthen its profitability with steady cash flow, the company also conducts self-mining operations that enhance its marketplace resilience by leveraging self-developed and purchased mining machines to seamlessly adapt to dynamic cryptocurrency pricing. The company also owns 7-nanometer BTC chips and has strong capabilities in the development of LTC/DOGE miners and ETC miners. About Prosper Prosper is a decentralized protocol for a community that truly believes in Bitcoin, providing full exposure across Bitcoin hashrate and Bitcoin through bridging institutional-grade Bitcoin mining power on-chain, and aims to fully unlock the potential of Bitcoin. For more information, users can visit prosper-fi.com or follow on X (formerly Twitter). Contact Prosper contact@prosper-fi.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here CAYMAN ISLANDS, Cayman Islands, November 14th, 2024/Chainwire/--Prosper, a decentralized protocol bridging institutional-grade Bitcoin mining power on-chain and aiming to unlock the potential of Bitcoin through liquidity farming, today announced a new investment in its native project token PROS by one of the leading cryptocurrency mining companies Bit Mining Limited(NYSE:BTCM). Prosper's new strategic focus on Bitcoin mining and the broader Bitcoin ecosystem has been well-received by the community. As part of this strategic change, Prosper partners with prominent industry players to obtain various services and products to deliver institutional-grade execution in managing its mining hashrate. This investment from BIT Mining represents another significant validation of Prosper’s thesis by institutional backers. In addition to Prosper's growing roster of top-tier industry partners and sophisticated financial investors (including a recently announced investment by Waterdrip Capital ), Prosper’s value proposition also resonates with cryptocurrency mining companies that bring extensive experience in mining operations and a strong understanding of the ecosystem. Waterdrip Capital Waterdrip Capital This investment aligns with Prosper’s strategic direction and supports its new vision. About BIT Mining Limited BIT Mining (NYSE: BTCM) is a leading technology-driven cryptocurrency mining company with operations in cryptocurrency mining, data center operation, and mining machine manufacturing. The company is strategically creating long-term value across the industry with its cryptocurrency ecosystem. BIT Mining BIT Mining Anchored by its cost-efficient data centers that strengthen its profitability with steady cash flow, the company also conducts self-mining operations that enhance its marketplace resilience by leveraging self-developed and purchased mining machines to seamlessly adapt to dynamic cryptocurrency pricing. The company also owns 7-nanometer BTC chips and has strong capabilities in the development of LTC/DOGE miners and ETC miners. About Prosper Prosper is a decentralized protocol for a community that truly believes in Bitcoin, providing full exposure across Bitcoin hashrate and Bitcoin through bridging institutional-grade Bitcoin mining power on-chain, and aims to fully unlock the potential of Bitcoin. For more information, users can visit prosper-fi.com or follow on X (formerly Twitter) . Prosper Prosper prosper-fi.com prosper-fi.com X (formerly Twitter) X (formerly Twitter) Contact Prosper contact@prosper-fi.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

BIT Mining (NYSE: BTCM) Invests In Prosper’s Native Tokens To Support New Focus On Bitcoin Mining

BIT Mining (NYSE: BTCM) ukax Prosper’s Native Tokens ukar qullqichrantawayi, machaq Foco Bitcoin Mining ukar yanapt’añataki

BIT Mining (NYSE: BTCM) інвесціруе ў натыўныя токены Prosper, каб падтрымаць новы фокус на здабычы біткойнаў

BIT Mining (NYSE: BTCM) invierte en tokens nativos de Prosper para respaldar un nuevo enfoque en la minería de Bitcoin

BIT Mining (NYSE: BTCM) investe nei token nativi di Prosper per supportare il nuovo focus sul mining di Bitcoin

BIT Mining (NYSE: BTCM) は、ビットコインマイニングへの新たな焦点をサポートするために Prosper のネイティブトークンに投資します。

BIT Mining (NYSE: BTCM) биткоинді өндіруге жаңа назар аударуды қолдау үшін Prosper-тің жергілікті токендеріне инвестиция жасайды

BIT Mining(NYSE: BTCM), 비트코인 채굴에 대한 새로운 초점을 지원하기 위해 Prosper의 네이티브 토큰에 투자

ການຂຸດຄົ້ນ BIT (NYSE: BTCM) ລົງທຶນໃນ Tokens ພື້ນເມືອງຂອງ Prosper ເພື່ອສະຫນັບສະຫນູນຈຸດສຸມໃຫມ່ກ່ຽວກັບການຂຸດຄົ້ນ Bitcoin

BIT Mining (NYSE: BTCM) investerar i Prospers inhemska tokens för att stödja nytt fokus på Bitcoin Mining

BIT Mining (NYSE: BTCM) ลงทุนในโทเค็นดั้งเดิมของ Prosper เพื่อสนับสนุนการเน้นใหม่ในการขุด Bitcoin

BIT Mining (NYSE: BTCM) Yi Vekisa Eka Prosper’s Native Tokens Ku Seketela Ku Tiyisisa Letintshwa Eka Bitcoin Mining

BIT مائننگ (NYSE: BTCM) بٹ کوائن مائننگ پر نئے فوکس کو سپورٹ کرنے کے لیے پراسپر کے مقامی ٹوکنز میں سرمایہ کاری کرتا ہے۔

The rapid advancement of AI has offered powerful tools for malware detection, but it has also introduced new avenues for adversarial attacks. As an example, recently OpenAI reported threat actors abusing ChatGPT to execute reconnaissance, help fixing code, write partial code, or look at vulnerabilities. These are to me examples of AI aiding “basic” steps, but would threat actors invest and use more advanced applications? Universal Adversarial Perturbations (UAPs) have gained attention due to their potential to bypass machine learning models in various domains, including malware detection. UAPs can manipulate malware in ways that evade AI-based detection systems without altering the malware's core functionality. However, despite this capability, cybercriminals have not widely adopted AI-driven techniques like UAPs. This blog delves into the complexity and effort required to generate UAPs for malware and explains why it might not be worth the trouble for attackers. Just to be clear on definitions: Artificial Intelligence (AI) is a broad field that aims to create machines or software capable of performing tasks that typically require human intelligence, such as understanding language, recognizing images, problem-solving, and decision-making. AI encompasses various techniques and approaches, from rule-based systems to learning algorithms. Machine Learning (ML) is a subset of AI that focuses on building systems that learn from data. Instead of being explicitly programmed for each task, ML models identify patterns in data to make predictions or decisions, improving over time with more experience. UAPs: A Brief Overview Universal Adversarial Perturbations (UAPs) are subtle modifications applied to input data (such as malware samples) to mislead AI models. What makes UAPs particularly interesting is that a single perturbation (one ring rules them all) can be applied to many inputs, causing the AI model to misclassify them. Think of it as changing just a few pixels in a picture to make a powerful facial recognition system mistake someone for someone else. In the below example, a single bit of random code is added to multiple different images, resulting in the classifying model going completely wrong on the identification. When we look at the example of the platypus, the model identifies the animal partially right based on the training on the beak with other images, but due to the interference with the added “noise” in the pixels, it classifies it wrong. That is exactly the interesting space when it comes to malware detection and evasion. You want malicious files to be classified wrong. In the context of malware detection, UAPs allow attackers to evade detection without having to create entirely new malware variants. While this seems like a low-effort, high-reward strategy, generating effective UAPs is far more challenging than it appears, particularly in the malware domain. Complexity in Crafting UAPs for Malware In their paper, "Realizable Universal Adversarial Perturbations for Malware," Labaca-Castro et al. demonstrate that crafting UAPs for malware requires an intricate balance between manipulating feature space (abstract representations of malware) and problem space (real-world executable malware). Unlike image or text data, where perturbations may be easily applied without affecting functionality, malware is far more delicate. A slight misstep in the perturbation process can corrupt the malware sample, rendering it unusable. You need to respect (with regards to Windows malware) the PE structure of a file. A modification to that structure will  break its functionality and the malware will not execute. It may have bypassed detection but it is useless to the attacker. The process requires attackers to perform a series of careful transformations to avoid breaking the executable while still evading detection. This is a far cry from simply adding noise to an image or text dataset. As a result, the time and expertise required to create UAPs that both fool AI/ML malware detection models and preserve malware functionality is significant. UAPs vs. New Malware Variants Given the complexity of generating UAPs, cybercriminals face a dilemma: Should they invest time and resources into crafting these perturbations, or is it easier to create entirely new strains of malware? Developing a new malware strain might involve reusing code from previous versions, applying known obfuscation techniques, or modifying payloads. This process is often faster, less risky, and more predictable compared to the complex sequence of transformations required to generate UAPs. As a result, many attackers prefer to invest in creating new strains of malware, which are more likely to achieve the desired outcome without the same level of effort and risk. Challenges One of the major hurdles in applying UAPs to malware is the real-world execution environment. Malware operates in dynamic, unpredictable conditions, and UAPs crafted in controlled environments may not perform as expected once deployed. Small changes in the operating system, file structure, or antivirus defenses can render the UAP ineffective. This fragility is a key reason why UAPs remain largely theoretical for malware attacks rather than a widely adopted technique in practice. Additionally, defenders are not standing still. Adversarial training—where AI models are retrained using adversarial examples—can harden systems against UAPs, making it even harder for attackers to succeed. Mitigation strategies will raise the cost and effort required for attackers to generate successful UAPs, further reducing their appeal. Conclusion The idea of using AI to defeat AI, particularly through Universal Adversarial Perturbations, may seem like a natural progression in the ongoing battle between attackers and defenders. However, the reality is that the complexity and risk associated with developing UAPs for malware make this approach unattractive for most cybercriminals. Instead, attackers tend to rely on more straightforward methods like creating new malware variants, which offer a better return on investment with less risk of failure. If you examine some of the latest ransomware campaigns, none of them highlight the use of AI-based techniques. Instead, as shown in recent coverage of ransomware tactics here, attackers consistently focus on tried-and-tested approaches that maximize impact and minimize operational complexity. As long as the development of UAPs remains fraught with difficulties—such as maintaining functionality and overcoming problem-space constraints—it’s unlikely that we will see widespread adoption of these techniques in the cybercriminal world. Instead, traditional malware development and deployment methods will continue to dominate the landscape, while defenders must remain vigilant and adaptive to the evolving AI threat landscape. The rapid advancement of AI has offered powerful tools for malware detection, but it has also introduced new avenues for adversarial attacks. As an example, recently OpenAI reported threat actors abusing ChatGPT to execute reconnaissance, help fixing code, write partial code, or look at vulnerabilities. These are to me examples of AI aiding “basic” steps, but would threat actors invest and use more advanced applications? Universal Adversarial Perturbations (UAPs) have gained attention due to their potential to bypass machine learning models in various domains, including malware detection. UAPs can manipulate malware in ways that evade AI-based detection systems without altering the malware's core functionality. However, despite this capability, cybercriminals have not widely adopted AI-driven techniques like UAPs. This blog delves into the complexity and effort required to generate UAPs for malware and explains why it might not be worth the trouble for attackers. Just to be clear on definitions: Artificial Intelligence (AI) is a broad field that aims to create machines or software capable of performing tasks that typically require human intelligence, such as understanding language, recognizing images, problem-solving, and decision-making. AI encompasses various techniques and approaches, from rule-based systems to learning algorithms. Artificial Intelligence (AI) Machine Learning (ML) is a subset of AI that focuses on building systems that learn from data. Instead of being explicitly programmed for each task, ML models identify patterns in data to make predictions or decisions, improving over time with more experience. Machine Learning (ML) UAPs: A Brief Overview Universal Adversarial Perturbations (UAPs) are subtle modifications applied to input data (such as malware samples) to mislead AI models. What makes UAPs particularly interesting is that a single perturbation (one ring rules them all) can be applied to many inputs, causing the AI model to misclassify them. Think of it as changing just a few pixels in a picture to make a powerful facial recognition system mistake someone for someone else. In the below example, a single bit of random code is added to multiple different images, resulting in the classifying model going completely wrong on the identification. When we look at the example of the platypus, the model identifies the animal partially right based on the training on the beak with other images, but due to the interference with the added “noise” in the pixels, it classifies it wrong. That is exactly the interesting space when it comes to malware detection and evasion. You want malicious files to be classified wrong. In the context of malware detection, UAPs allow attackers to evade detection without having to create entirely new malware variants. While this seems like a low-effort, high-reward strategy, generating effective UAPs is far more challenging than it appears, particularly in the malware domain. Complexity in Crafting UAPs for Malware In their paper, "Realizable Universal Adversarial Perturbations for Malware ," Labaca-Castro et al. demonstrate that crafting UAPs for malware requires an intricate balance between manipulating feature space (abstract representations of malware) and problem space (real-world executable malware). Unlike image or text data, where perturbations may be easily applied without affecting functionality, malware is far more delicate. A slight misstep in the perturbation process can corrupt the malware sample, rendering it unusable. You need to respect (with regards to Windows malware) the PE structure of a file. A modification to that structure will  break its functionality and the malware will not execute. It may have bypassed detection but it is useless to the attacker. "Realizable Universal Adversarial Perturbations for Malware "Realizable Universal Adversarial Perturbations for Malware The process requires attackers to perform a series of careful transformations to avoid breaking the executable while still evading detection. This is a far cry from simply adding noise to an image or text dataset. As a result, the time and expertise required to create UAPs that both fool AI/ML malware detection models and preserve malware functionality is significant. UAPs vs. New Malware Variants Given the complexity of generating UAPs, cybercriminals face a dilemma: Should they invest time and resources into crafting these perturbations, or is it easier to create entirely new strains of malware? Developing a new malware strain might involve reusing code from previous versions, applying known obfuscation techniques, or modifying payloads. This process is often faster, less risky, and more predictable compared to the complex sequence of transformations required to generate UAPs. As a result, many attackers prefer to invest in creating new strains of malware, which are more likely to achieve the desired outcome without the same level of effort and risk. Challenges One of the major hurdles in applying UAPs to malware is the real-world execution environment. Malware operates in dynamic, unpredictable conditions, and UAPs crafted in controlled environments may not perform as expected once deployed. Small changes in the operating system, file structure, or antivirus defenses can render the UAP ineffective. This fragility is a key reason why UAPs remain largely theoretical for malware attacks rather than a widely adopted technique in practice. Additionally, defenders are not standing still. Adversarial training —where AI models are retrained using adversarial examples—can harden systems against UAPs, making it even harder for attackers to succeed. Mitigation strategies will raise the cost and effort required for attackers to generate successful UAPs, further reducing their appeal. Adversarial training Adversarial training Conclusion Conclusion The idea of using AI to defeat AI, particularly through Universal Adversarial Perturbations, may seem like a natural progression in the ongoing battle between attackers and defenders. However, the reality is that the complexity and risk associated with developing UAPs for malware make this approach unattractive for most cybercriminals. Instead, attackers tend to rely on more straightforward methods like creating new malware variants, which offer a better return on investment with less risk of failure. If you examine some of the latest ransomware campaigns, none of them highlight the use of AI-based techniques. Instead, as shown in recent coverage of ransomware tactics here , attackers consistently focus on tried-and-tested approaches that maximize impact and minimize operational complexity. here here As long as the development of UAPs remains fraught with difficulties—such as maintaining functionality and overcoming problem-space constraints—it’s unlikely that we will see widespread adoption of these techniques in the cybercriminal world. Instead, traditional malware development and deployment methods will continue to dominate the landscape, while defenders must remain vigilant and adaptive to the evolving AI threat landscape.

Why Cybercriminals Are Not Necessarily Embracing AI

Slovenia's hashrate marketplace NiceHash has announced its first Bitcoin conference, NiceHashX, in the historic city of Maribor. The event, scheduled for November 8-9, 2024, arrives at a crucial juncture when India and other emerging markets closely monitor global cryptocurrency developments. The conference marks NiceHash's decade-long journey since its inception by two Slovenian students in 2014. According to industry data, Slovenia has emerged as a notable cryptocurrency hub, second only to Switzerland in blockchain startup density within Europe. This positions the country as a potential model for developing nations exploring cryptocurrency infrastructure. "Slovenia's journey in cryptocurrency adoption offers valuable insights for emerging markets," Vladimir Hozjan, CEO of NiceHash, told Hackernoon in an exclusive interview. "With over 1,000 businesses already accepting Bitcoin payments, Slovenia demonstrates how digital currency integration can function at a national scale." The conference's speaker lineup features prominent blockchain experts, including Saifedean Ammous, author of The Bitcoin Standard, and CASA CTO Jameson Lopp. Of particular interest to the Indian market are the planned discussions on regulatory frameworks and cryptocurrency adoption in traditional banking systems. Sources familiar with the matter indicate that NiceHash plans to showcase a new Bitcoin payment solution during the conference. This development comes when Indian businesses increasingly explore cryptocurrency payment integrations, despite regulatory uncertainties. Statistical projections reveal that Slovenia's cryptocurrency user base may reach 385,700 by 2028, representing approximately 20% of its population. These adoption rates present interesting parallels for Indian market observers, considering India's growing cryptocurrency user base. The conference agenda spans European Bitcoin adoption strategies, mining operations, and regulatory compliance - topics particularly relevant as India and other Asian markets navigate their cryptocurrency policies. "The regulatory discussions at NiceHashX could provide valuable frameworks for emerging markets," notes a senior cryptocurrency analyst who requested anonymity due to institutional policies. Slovenia's cryptocurrency landscape includes notable initiatives such as BTC City in Ljubljana and the Satoshi monument, demonstrating the country's commitment to blockchain technology. The conference venue, Maribor, hosts numerous businesses already integrating Bitcoin payments, from retail establishments to hospitality services. NiceHash's evolution from a hashrate marketplace to organizing a major Bitcoin conference reflects the broader maturation of cryptocurrency markets. The platform recently launched automated Lightning payouts for miners in 2024, indicating growing sophistication in mining infrastructure. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Slovenia's hashrate marketplace NiceHash has announced its first Bitcoin conference, NiceHashX , in the historic city of Maribor. The event, scheduled for November 8-9, 2024, arrives at a crucial juncture when India and other emerging markets closely monitor global cryptocurrency developments. The conference marks NiceHash's decade-long journey since its inception by two Slovenian students in 2014. According to industry data, Slovenia has emerged as a notable cryptocurrency hub, second only to Switzerland in blockchain startup density within Europe. This positions the country as a potential model for developing nations exploring cryptocurrency infrastructure. NiceHash NiceHashX "Slovenia's journey in cryptocurrency adoption offers valuable insights for emerging markets," Vladimir Hozjan, CEO of NiceHash, told Hackernoon in an exclusive interview. "With over 1,000 businesses already accepting Bitcoin payments, Slovenia demonstrates how digital currency integration can function at a national scale." The conference's speaker lineup features prominent blockchain experts, including Saifedean Ammous, author of The Bitcoin Standard, and CASA CTO Jameson Lopp. Of particular interest to the Indian market are the planned discussions on regulatory frameworks and cryptocurrency adoption in traditional banking systems. Sources familiar with the matter indicate that NiceHash plans to showcase a new Bitcoin payment solution during the conference. This development comes when Indian businesses increasingly explore cryptocurrency payment integrations, despite regulatory uncertainties. Statistical projections reveal that Slovenia's cryptocurrency user base may reach 385,700 by 2028, representing approximately 20% of its population. These adoption rates present interesting parallels for Indian market observers, considering India's growing cryptocurrency user base. The conference agenda spans European Bitcoin adoption strategies, mining operations, and regulatory compliance - topics particularly relevant as India and other Asian markets navigate their cryptocurrency policies. "The regulatory discussions at NiceHashX could provide valuable frameworks for emerging markets," notes a senior cryptocurrency analyst who requested anonymity due to institutional policies. Slovenia's cryptocurrency landscape includes notable initiatives such as BTC City in Ljubljana and the Satoshi monument, demonstrating the country's commitment to blockchain technology. The conference venue, Maribor, hosts numerous businesses already integrating Bitcoin payments, from retail establishments to hospitality services. NiceHash's evolution from a hashrate marketplace to organizing a major Bitcoin conference reflects the broader maturation of cryptocurrency markets. The platform recently launched automated Lightning payouts for miners in 2024, indicating growing sophistication in mining infrastructure. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: business blogging program business blogging program

NiceHash Sets Bitcoin-focused Conference in Maribor, Positioning Slovenia as Crypto Hub

NiceHash estableix una conferència centrada en Bitcoin a Maribor, posicionant Eslovènia com a Crypto Hub

NiceHash organiza una conferencia centrada en Bitcoin en Maribor, posicionando a Eslovenia como centro de criptomonedas

NiceHash establece unha conferencia centrada en Bitcoin en Maribor, posicionando a Eslovenia como Crypto Hub

NiceHash Gelar Konferensi Berfokus Bitcoin di Maribor, Posisikan Slovenia sebagai Pusat Kripto

NiceHash organizza una conferenza incentrata su Bitcoin a Maribor, posizionando la Slovenia come hub delle criptovalute

NiceHash がマリボルでビットコインに焦点を当てたカンファレンスを開催、スロベニアを暗号通貨の中心地として位置付ける

NiceHash აწყობს ბიტკოინზე ორიენტირებულ კონფერენციას მარიბორში, ათავსებს სლოვენიას კრიპტო ჰაბად

NiceHash dia mametraka fihaonambe mifantoka amin'ny Bitcoin ao Maribor, mametraka an'i Slovenia ho Crypto Hub

NiceHash vendos një konferencë të fokusuar në Bitcoin në Maribor, duke e pozicionuar Slloveninë si qendër kripto

НицеХасх одржава конференцију фокусирану на Битцоин у Марибору, позиционирајући Словенију као Црипто Хуб

NiceHash Inaweka Mkutano unaozingatia Bitcoin huko Maribor, Kuweka Slovenia kama Crypto Hub

I-NiceHash Isetha Ingqungquthela egxile ku-Bitcoin e-Maribor, Ibeka iSlovenia njenge-Crypto Hub

NiceHash, a leading cryptocurrency mining platform, has announced the release of custom firmware for Antminer Kaspa ASICs, marking a significant development in the Kaspa mining ecosystem. This firmware, reportedly the first of its kind for Kaspa miners, aims to enhance the performance and efficiency of Antminer KS series devices. Performance and Efficiency Gains According to NiceHash, real-world tests have shown that their custom firmware can increase ASIC performance by up to 20%. The company also claims improvements in energy efficiency, potentially lowering operational costs for miners. Additionally, the firmware includes thermal protection features designed to prevent overheating, which could extend the lifespan of mining hardware. Supported Hardware and Installation The firmware is compatible with several Antminer models, including the KS5 Pro, KS5, and two variants of the KS3. However, installation is not straightforward due to recent manufacturer updates. Many Kaspa Antminers now run stock firmware versions that block custom upgrades, necessitating the use of additional hardware. To address this, NiceHash has introduced the "Cracker Card," a hardware add-on that enables custom firmware installation on CVITech control boards. This card must be physically attached to the miner's control board before firmware installation can proceed. NiceHash is currently offering the Cracker Card and custom firmware exclusively to its users. Large-scale mining operations can request the hardware directly from NiceHash, while smaller operators with fewer than 100 machines may soon be able to purchase the cards through NiceHash's online shop. Industry Impact and Considerations The introduction of custom firmware for Kaspa ASICs could have significant implications for the mining community. Improved efficiency and performance may lead to increased profitability for miners, potentially attracting more participants to the Kaspa network. However, the requirement for additional hardware and the firmware's exclusivity to NiceHash's platform may limit its immediate adoption. Miners will need to weigh the potential benefits against the costs and complexities of implementation. Fee Structure and Compatibility NiceHash has implemented a dynamic fee structure for the firmware, ranging from 1% to 4% based on the level of overclocking applied. This tiered approach allows miners to balance performance gains with associated costs. It's worth noting that the firmware is currently compatible only with NiceHash's mining pool, which may influence miners' decisions to adopt the technology. As the cryptocurrency mining landscape continues to evolve, developments like NiceHash's custom firmware highlight the ongoing efforts to optimize mining operations and improve hardware efficiency. The long-term impact of such innovations on the Kaspa network and broader mining ecosystem remains to be seen. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR NiceHash, a leading cryptocurrency mining platform, has announced the release of custom firmware for Antminer Kaspa ASICs, marking a significant development in the Kaspa mining ecosystem. This firmware, reportedly the first of its kind for Kaspa miners, aims to enhance the performance and efficiency of Antminer KS series devices. Performance and Efficiency Gains According to NiceHash , real-world tests have shown that their custom firmware can increase ASIC performance by up to 20%. The company also claims improvements in energy efficiency, potentially lowering operational costs for miners. Additionally, the firmware includes thermal protection features designed to prevent overheating, which could extend the lifespan of mining hardware. NiceHash Supported Hardware and Installation The firmware is compatible with several Antminer models, including the KS5 Pro, KS5, and two variants of the KS3. However, installation is not straightforward due to recent manufacturer updates. Many Kaspa Antminers now run stock firmware versions that block custom upgrades, necessitating the use of additional hardware. To address this, NiceHash has introduced the "Cracker Card," a hardware add-on that enables custom firmware installation on CVITech control boards. This card must be physically attached to the miner's control board before firmware installation can proceed. NiceHash NiceHash is currently offering the Cracker Card and custom firmware exclusively to its users. Large-scale mining operations can request the hardware directly from NiceHash, while smaller operators with fewer than 100 machines may soon be able to purchase the cards through NiceHash's online shop. Industry Impact and Considerations The introduction of custom firmware for Kaspa ASICs could have significant implications for the mining community. Improved efficiency and performance may lead to increased profitability for miners, potentially attracting more participants to the Kaspa network. However, the requirement for additional hardware and the firmware's exclusivity to NiceHash's platform may limit its immediate adoption. Miners will need to weigh the potential benefits against the costs and complexities of implementation. Fee Structure and Compatibility NiceHash has implemented a dynamic fee structure for the firmware, ranging from 1% to 4% based on the level of overclocking applied. This tiered approach allows miners to balance performance gains with associated costs. It's worth noting that the firmware is currently compatible only with NiceHash's mining pool, which may influence miners' decisions to adopt the technology. As the cryptocurrency mining landscape continues to evolve, developments like NiceHash's custom firmware highlight the ongoing efforts to optimize mining operations and improve hardware efficiency. The long-term impact of such innovations on the Kaspa network and broader mining ecosystem remains to be seen. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR Vested Interest Disclosure: business blogging program business blogging program

NiceHash Unveils Custom Firmware for Kaspa ASIC Miners

NiceHash predstavlja prilagođeni firmver za Kaspa ASIC rudare

NiceHash afslører brugerdefineret firmware til Kaspa ASIC Miners

NiceHash presenta un firmware personalizado para los mineros ASIC de Kaspa

NiceHash devwale mikrolojisyèl koutim pou minè Kaspa ASIC

NiceHash Luncurkan Firmware Khusus untuk Penambang ASIC Kaspa

NiceHash、Kaspa ASIC マイナー向けカスタムファームウェアを発表

NiceHash, Kaspa ASIC 마이너를 위한 맞춤형 펌웨어 공개

NiceHash ເປີດເຜີຍເຟີມແວທີ່ກໍາຫນົດເອງສໍາລັບ Kaspa ASIC Miners

NiceHash го претстави прилагодениот фирмвер за Kaspa ASIC рударите

НицеХасх представља прилагођени фирмвер за Каспа АСИЦ рударе

NiceHash, Kaspa ASIC Madencileri için Özel Ürün Yazılımını Tanıttı

NiceHash Kaspa ASIC konchilari uchun maxsus proshivkani taqdim etadi

Authors:
(1) Liang Wang, Microsoft Corporation, and Correspondence to (wangliang@microsoft.com);
(2) Nan Yang, Microsoft Corporation, and correspondence to (nanya@microsoft.com);
(3) Xiaolong Huang, Microsoft Corporation;
(4) Linjun Yang, Microsoft Corporation;
(5) Rangan Majumder, Microsoft Corporation;
(6) Furu Wei, Microsoft Corporation and Correspondence to (fuwei@microsoft.com). Table of Links Abstract and 1 Introduction 2 Related Work 3 Method 3.1 Synthetic Data Generation 3.2 Training 4 Experiments 4.1 Statistics of the Synthetic Data 4.2 Model Fine-tuning and Evaluation 4.3 Main Results 4.4 Multilingual Retrieval 5 Analysis 5.1 Is Contrastive Pre-training Necessary? 5.2 Extending to Long Text Embeddings and 5.3 Analysis of Training Hyperparameters 6 Conclusion and References A Implementation Details B Test Set Contamination Analysis C Prompts for Synthetic Data Generation D Instructions for Training and Evaluation 5 Analysis 5.1 Is Contrastive Pre-training Necessary? Weakly-supervised contrastive pre-training is one of the key factors behind the success of existing text embedding models. For instance, Contriever [18] treats random cropped spans as positive pairs for pre-training, while E5 [46] and BGE [48] collect and filter text pairs from various sources. This paper is available on arxiv under CC0 1.0 DEED license. Authors: (1) Liang Wang, Microsoft Corporation, and Correspondence to (wangliang@microsoft.com); (2) Nan Yang, Microsoft Corporation, and correspondence to (nanya@microsoft.com); (3) Xiaolong Huang, Microsoft Corporation; (4) Linjun Yang, Microsoft Corporation; (5) Rangan Majumder, Microsoft Corporation; (6) Furu Wei, Microsoft Corporation and Correspondence to (fuwei@microsoft.com). Authors: Authors: (1) Liang Wang, Microsoft Corporation, and Correspondence to (wangliang@microsoft.com); (2) Nan Yang, Microsoft Corporation, and correspondence to (nanya@microsoft.com); (3) Xiaolong Huang, Microsoft Corporation; (4) Linjun Yang, Microsoft Corporation; (5) Rangan Majumder, Microsoft Corporation; (6) Furu Wei, Microsoft Corporation and Correspondence to (fuwei@microsoft.com). Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Related Work 2 Related Work 3 Method 3.1 Synthetic Data Generation 3.1 Synthetic Data Generation 3.2 Training 3.2 Training 4 Experiments 4.1 Statistics of the Synthetic Data 4.1 Statistics of the Synthetic Data 4.2 Model Fine-tuning and Evaluation 4.2 Model Fine-tuning and Evaluation 4.3 Main Results 4.3 Main Results 4.4 Multilingual Retrieval 4.4 Multilingual Retrieval 5 Analysis 5.1 Is Contrastive Pre-training Necessary? 5.1 Is Contrastive Pre-training Necessary? 5.2 Extending to Long Text Embeddings and 5.3 Analysis of Training Hyperparameters 5.2 Extending to Long Text Embeddings and 5.3 Analysis of Training Hyperparameters 6 Conclusion and References 6 Conclusion and References A Implementation Details A Implementation Details B Test Set Contamination Analysis B Test Set Contamination Analysis C Prompts for Synthetic Data Generation C Prompts for Synthetic Data Generation D Instructions for Training and Evaluation D Instructions for Training and Evaluation 5 Analysis 5.1 Is Contrastive Pre-training Necessary? Weakly-supervised contrastive pre-training is one of the key factors behind the success of existing text embedding models. For instance, Contriever [18] treats random cropped spans as positive pairs for pre-training, while E5 [46] and BGE [48] collect and filter text pairs from various sources. This paper is available on arxiv under CC0 1.0 DEED license. This paper is available on arxiv under CC0 1.0 DEED license. available on arxiv

Improving Text Embeddings with
Large Language Models: Is Contrastive Pre-training Necessary?

Bias is a problem in large language models [LLMs]. But how can bias be solved, or tapered? This question means what can be done about training base models or fine-tuning assistant models to solve bias—technically—in LLMs? There are various disadvantages of AI bias in several use cases. This may indicate that there are organizations with interests in mitigating bias. However, is there a place they can go to find technical research paths to explore solving bias in AI? There is a lot of vacillation around what is open source in LLMs—maybe weights, datasets or codes—but even if everything that is used to train a language model is open source, how much can be technically gleaned there to solve bias, since closed source LLMs have teams with access to everything yet are unable to solve it. What can be done about bias—technically—that can be made available on a list, for those interested to go at it, could be a more important open source path, for problems in AI, than debating if weights or others are open source. The same applies to AI safety, alignment, ethics, governance and regulation. What is technically doable to make AI less misused and harmful, in the present and in future, available on a forum for those who want to find options to approach problems? The US has an AI safety institute, which also has an AI safety consortium. The UK has an AI safety institute. The EU has an AI office. Japan and Singapore also have their own AI safety teams. They can host forums for technical approaches as options that other labs may explore, which they may or may not also be exploring. These paths must not be extensively defined, but must have a technical entry port as well as anchorsto some existing approaches. The objective is to open source possible solutions around AI challenges with technical paths that can be seen in a public forum or safety marketplace—so to speak, so that those interested in building would see what is available, and use that to pursue advances. There is so much that has to be done about AI, and the few teams at the front have benchmarks and commercial ends too as priorities [OpenAI o1], making safety sometimes confined around a few of their core approaches. Open source for what can be done may instead redefine everything, more what LLM is open source, or which one is closed source. There is a recent update from Open Source Initiative, The Open Source AI Definition – draft v. 0.0.9, stating that, "When we refer to a “system,” we are speaking both broadly about a fully functional structure and its discrete structural elements. To be considered Open Source, the requirements are the same, whether applied to a system, a model, weights and parameters, or other structural elements. An Open Source AI is an AI system made available under terms and in a way that grant the freedoms to: Use the system for any purpose and without having to ask for permission. Study how the system works and inspect its components. Modify the system for any purpose, including to change its output. Share the system for others to use with or without modifications, for any purpose. These freedoms apply both to a fully functional system and to discrete elements of a system. A precondition to exercising these freedoms is to have access to the preferred form to make modifications to the system." There is a recent story from The NYTimes, OpenAI’s Fund-Raising Talks Could Value Company at $150 Billion, stating that, "OpenAI is in talks to raise about $6.5 billion as part of a deal that would value the company in the vicinity of $150 billion, a nearly $70 billion increase from its valuation nine months ago, according to five people with knowledge of the conversations. OpenAI is also working to transform its A.I. technologies into products that pull in revenue. Building this kind of technology requires billions of dollars in raw computing power, and by some estimates the company is burning through $7 billion every year. OpenAI is pulling in more than $2 billion a year through subscriptions to ChatGPT and other technologies, according to a person familiar with its finances." There is a new story on Reuters, US to convene global AI safety summit in November, stating that, “The Biden administration plans to convene a global safety summit on artificial intelligence, it said on Wednesday, as Congress continues to struggle with regulating the technology. The network members include Australia, Canada, the European Union, France, Japan, Kenya, South Korea, Singapore, Britain, and the United States. Generative AI - which can create text, photos and videos in response to open-ended prompts - has spurred excitement as well as fears it could make some jobs obsolete, upend elections and potentially overpower humans and have catastrophic effects. The goal of the San Francisco meeting is to jumpstart technical collaboration before the AI Action Summit in Paris in February.“ Feature image source Bias is a problem in large language models [LLMs]. But how can bias be solved, or tapered? This question means what can be done about training base models or fine-tuning assistant models to solve bias—technically—in LLMs? There are various disadvantages of AI bias in several use cases. This may indicate that there are organizations with interests in mitigating bias. However, is there a place they can go to find technical research paths to explore solving bias in AI? There is a lot of vacillation around what is open source in LLMs—maybe weights, datasets or codes—but even if everything that is used to train a language model is open source, how much can be technically gleaned there to solve bias, since closed source LLMs have teams with access to everything yet are unable to solve it. What can be done about bias—technically—that can be made available on a list, for those interested to go at it, could be a more important open source path, for problems in AI, than debating if weights or others are open source. The same applies to AI safety, alignment, ethics, governance and regulation. What is technically doable to make AI less misused and harmful, in the present and in future , available on a forum for those who want to find options to approach problems? the present and in future The US has an AI safety institute, which also has an AI safety consortium. The UK has an AI safety institute. The EU has an AI office. Japan and Singapore also have their own AI safety teams. They can host forums for technical approaches as options that other labs may explore, which they may or may not also be exploring. These paths must not be extensively defined, but must have a technical entry port as well as anchors to some existing approaches. as anchors The objective is to open source possible solutions around AI challenges with technical paths that can be seen in a public forum or safety marketplace—so to speak, so that those interested in building would see what is available, and use that to pursue advances. There is so much that has to be done about AI, and the few teams at the front have benchmarks and commercial ends too as priorities [ OpenAI o1 ], making safety sometimes confined around a few of their core approaches. Open source for what can be done may instead redefine everything, more what LLM is open source, or which one is closed source. OpenAI o1 There is a recent update from Open Source Initiative , The Open Source AI Definition – draft v. 0.0.9 , stating that, "When we refer to a “system,” we are speaking both broadly about a fully functional structure and its discrete structural elements. To be considered Open Source, the requirements are the same, whether applied to a system, a model, weights and parameters, or other structural elements. An Open Source AI is an AI system made available under terms and in a way that grant the freedoms to: Use the system for any purpose and without having to ask for permission. Study how the system works and inspect its components. Modify the system for any purpose, including to change its output. Share the system for others to use with or without modifications, for any purpose. These freedoms apply both to a fully functional system and to discrete elements of a system. A precondition to exercising these freedoms is to have access to the preferred form to make modifications to the system." Open Source Initiative The Open Source AI Definition – draft v. 0.0.9 There is a recent story from The NYTimes , OpenAI’s Fund-Raising Talks Could Value Company at $150 Billion , stating that, "OpenAI is in talks to raise about $6.5 billion as part of a deal that would value the company in the vicinity of $150 billion, a nearly $70 billion increase from its valuation nine months ago, according to five people with knowledge of the conversations. OpenAI is also working to transform its A.I. technologies into products that pull in revenue. Building this kind of technology requires billions of dollars in raw computing power, and by some estimates the company is burning through $7 billion every year. OpenAI is pulling in more than $2 billion a year through subscriptions to ChatGPT and other technologies, according to a person familiar with its finances." The NYTimes OpenAI’s Fund-Raising Talks Could Value Company at $150 Billion There is a new story on Reuters , US to convene global AI safety summit in November , stating that, “The Biden administration plans to convene a global safety summit on artificial intelligence, it said on Wednesday, as Congress continues to struggle with regulating the technology. The network members include Australia, Canada, the European Union, France, Japan, Kenya, South Korea, Singapore, Britain, and the United States. Generative AI - which can create text, photos and videos in response to open-ended prompts - has spurred excitement as well as fears it could make some jobs obsolete, upend elections and potentially overpower humans and have catastrophic effects. The goal of the San Francisco meeting is to jumpstart technical collaboration before the AI Action Summit in Paris in February.“ Reuters US to convene global AI safety summit in November Feature image source Feature image source source

AI Alignment: What Open Source, for LLMs Safety, Ethics and Governance, Is Necessary?

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