Tortoises (/ˈtɔːr.təs.ɪz/) are reptiles of the family Testudinidae of the order Testudines (Latin for &quot;tortoise&quot;). Like other turtles, tortoises have a shell to protect from predation and other threats. The shell in tortoises is generally hard, and like other members of the suborder ...

Tortoise - Wikipedia

View credits, reviews, tracks and shop for the 1994 CD release of &quot;Tortoise&quot; on Discogs.

Tortoise – Tortoise (1994, CD) - Discogs

What do you call a walking vegetarian turtle that isn’t fond of water?

What’s the Difference Between a Turtle and a Tortoise? | Britannica

How much damage could it do to the company? Charlotte Owen’s elevation to the Lords is hard to explain, but speaks volumes about how British democracy works. ... From Xavier Greenwood’s account of converting to Judaism to Rosie Blunt’s story about a lost religious masterpiece, many of the pieces in Tortoise...

Tortoise. Slower, wiser news.

At worst, Tortoise’s rather rapid pivots might be viewed as the lurchings of a company that can’t deliver on its stated business goals. At best, however, they demonstrate the agility of startups to explore new spaces quickly and as the market demands.

Tortoise pivots away from robotic delivery toward mobile stores ...

Tortoise | 3,327 followers on LinkedIn. Automated Retail &amp; Commerce | Automated Commerce &amp; Logistics

Tortoise | LinkedIn

In his review for AllMusic, Glenn Swan writes that Tortoise &quot;share equal responsibility and trust in each other, pouring out a thick stew of meditative grooves, light production experiments, and rusty guitar-string ambience -- the likes of which have rarely sounded so approachable, but this ...

Tortoise (album) - Wikipedia

Hit by an oil price war between Russia and Saudi Arabia, combined with the financial impact of COVID-19, Leawood-based Tortoise Capital Advisors LLC laid off 39 people, about 20% of the company&#x27;s 205 employees.

Amid oil price war, Tortoise Capital Advisors lays off 39 - Kansas ...

Tortoise Capital Advisors | 2,291 followers on LinkedIn. Tortoise specializes in essential assets and income. Tortoise invests in assets and services that serve essential needs in society and can also serve essential client needs, such as diversification and income.

Tortoise Capital Advisors | LinkedIn

Tortoise by Tortoise, released 01 September 1994 1. Magnet Pulls Through 2. Night Air 3. Ry Cooder 4. Onions Wrapped in Rubber 5. Tin Cans &amp; Twine 6. Spiderwebbed 7. His Second Story Island 8. On Noble 9. Flyrod 10. Cornpone Brunch Tortoise&#x27;s self-titled debut incorporates many musical styles ...

Tortoise, by Tortoise

Tortoise

tortoise

Table of Links Abstract and 1 Introduction 2 Related Work 2.1 Neural Codec Language Models and 2.2 Non-autoregressive Models 2.3 Diffusion Models and 2.4 Zero-shot Voice Cloning 3 Hierspeech++ and 3.1 Speech Representations 3.2 Hierarchical Speech Synthesizer 3.3 Text-to-Vec 3.4 Speech Super-resolution 3.5 Model Architecture 4 Speech Synthesis Tasks 4.1 Voice Conversion and 4.2 Text-to-Speech 4.3 Style Prompt Replication 5 Experiment and Result, and Dataset 5.2 Preprocessing and 5.3 Training 5.4 Evaluation Metrics 5.5 Ablation Study 5.6 Zero-shot Voice Conversion 5.7 High-diversity but High-fidelity Speech Synthesis 5.8 Zero-shot Text-to-Speech 5.9 Zero-shot Text-to-Speech with 1s Prompt 5.10 Speech Super-resolution 5.11 Additional Experiments with Other Baselines 6 Limitation and Quick Fix 7 Conclusion, Acknowledgement and References 5.8 Zero-shot Text-to-Speech We compared the zero-shot TTS performance of HierSpeech++ with other baselines: 1) YourTTS, VITS-based end-to-end TTS model, 2) HierSpeech, an end-to-end TTS model using hierarchical VAE, 3) VALL-E-X, a neural codec language models-based multi-lingual zero-shot TTS model and we utilize an unofficial implementation which has an improved audio quality with Vocos decoder, 4) XTTS[12] , a TTS product XTTS v1 from Coqui Corp., and XTTS is built on a open-source TTS model, TorToise [5] which was trained with unprecedented large-scale speech dataset for the first time. For zero-shot TTS, we utilized a noisy speech prompt from the test-clean and test-other subsets of LibriTTS. HierSpeech++ synthesizes the speech with Tttv of 0.333 and Th of 0.333 in TABLE 7 and 8. The results demonstrate that our model is a strong zeroshot TTS model in terms of all subjective and objective metrics. We conducted three MOS experiments for naturalness, prosody, and similarity. Our model beats all models significantly, and our model has even surpassed the groundtruth in terms of naturalness. However, XTTS has a better performance in pMOS, and this means learning prosody requires more datasets to improve expressiveness. Although other models show limitations in synthesizing speech with noisy prompts, our model synthesizes a speech robustly. Furthermore, our model has a better CER and WER than ground-truth, and this also demonstrates the robustness of our model. In summary, all results demonstrate the superiority of our model in naturalness, expressiveness, and robustness for zero-shot TTS. obustness for zero-shot TTS. In addition, we could further improve the zero-shot TTS performance by introducing a style prompt replication (SPR) in the following subsection. Note that we do not apply the SPR in TABLE 2-8. The audio could be upsampled to 48 kHz. Lastly, we could also synthesize noise-free speech even with noisy speech. The details will be described in Section 6. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. [12]. https://github.com/coqui-ai/TTS Authors:
(1) Sang-Hoon Lee, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea;
(2) Ha-Yeong Choi, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea;
(3) Seung-Bin Kim, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea;
(4) Seong-Whan Lee, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea and a Corresponding author. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Related Work 2.1 Neural Codec Language Models and 2.2 Non-autoregressive Models 2.1 Neural Codec Language Models and 2.2 Non-autoregressive Models 2.3 Diffusion Models and 2.4 Zero-shot Voice Cloning 2.3 Diffusion Models and 2.4 Zero-shot Voice Cloning 3 Hierspeech++ and 3.1 Speech Representations 3 Hierspeech++ and 3.1 Speech Representations 3.2 Hierarchical Speech Synthesizer 3.2 Hierarchical Speech Synthesizer 3.3 Text-to-Vec 3.3 Text-to-Vec 3.4 Speech Super-resolution 3.4 Speech Super-resolution 3.5 Model Architecture 3.5 Model Architecture 4 Speech Synthesis Tasks 4.1 Voice Conversion and 4.2 Text-to-Speech 4.1 Voice Conversion and 4.2 Text-to-Speech 4.3 Style Prompt Replication 4.3 Style Prompt Replication 5 Experiment and Result, and Dataset 5 Experiment and Result, and Dataset 5.2 Preprocessing and 5.3 Training 5.2 Preprocessing and 5.3 Training 5.4 Evaluation Metrics 5.4 Evaluation Metrics 5.5 Ablation Study 5.5 Ablation Study 5.6 Zero-shot Voice Conversion 5.6 Zero-shot Voice Conversion 5.7 High-diversity but High-fidelity Speech Synthesis 5.7 High-diversity but High-fidelity Speech Synthesis 5.8 Zero-shot Text-to-Speech 5.8 Zero-shot Text-to-Speech 5.9 Zero-shot Text-to-Speech with 1s Prompt 5.9 Zero-shot Text-to-Speech with 1s Prompt 5.10 Speech Super-resolution 5.10 Speech Super-resolution 5.11 Additional Experiments with Other Baselines 5.11 Additional Experiments with Other Baselines 6 Limitation and Quick Fix 6 Limitation and Quick Fix 7 Conclusion, Acknowledgement and References 7 Conclusion, Acknowledgement and References 5.8 Zero-shot Text-to-Speech We compared the zero-shot TTS performance of HierSpeech++ with other baselines: 1) YourTTS, VITS-based end-to-end TTS model, 2) HierSpeech, an end-to-end TTS model using hierarchical VAE, 3) VALL-E-X, a neural codec language models-based multi-lingual zero-shot TTS model and we utilize an unofficial implementation which has an improved audio quality with Vocos decoder, 4) XTTS[12] , a TTS product XTTS v1 from Coqui Corp., and XTTS is built on a open-source TTS model, TorToise [5] which was trained with unprecedented large-scale speech dataset for the first time. For zero-shot TTS, we utilized a noisy speech prompt from the test-clean and test-other subsets of LibriTTS. HierSpeech++ synthesizes the speech with Tttv of 0.333 and Th of 0.333 in TABLE 7 and 8. The results demonstrate that our model is a strong zeroshot TTS model in terms of all subjective and objective metrics. We conducted three MOS experiments for naturalness, prosody, and similarity. Our model beats all models significantly, and our model has even surpassed the groundtruth in terms of naturalness. However, XTTS has a better performance in pMOS, and this means learning prosody requires more datasets to improve expressiveness. Although other models show limitations in synthesizing speech with noisy prompts, our model synthesizes a speech robustly. Furthermore, our model has a better CER and WER than ground-truth, and this also demonstrates the robustness of our model. In summary, all results demonstrate the superiority of our model in naturalness, expressiveness, and robustness for zero-shot TTS. obustness for zero-shot TTS. In addition, we could further improve the zero-shot TTS performance by introducing a style prompt replication (SPR) in the following subsection. Note that we do not apply the SPR in TABLE 2-8. The audio could be upsampled to 48 kHz. Lastly, we could also synthesize noise-free speech even with noisy speech. The details will be described in Section 6. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. This paper is available on arxiv under CC BY-NC-SA 4.0 DEED license. available on arxiv [12]. https://github.com/coqui-ai/TTS Authors: (1) Sang-Hoon Lee, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea; (2) Ha-Yeong Choi, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea; (3) Seung-Bin Kim, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea; (4) Seong-Whan Lee, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea and a Corresponding author. Authors: Authors: (1) Sang-Hoon Lee, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea; (2) Ha-Yeong Choi, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea; (3) Seung-Bin Kim, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea; (4) Seong-Whan Lee, Fellow, IEEE with the Department of Artificial Intelligence, Korea University, Seoul 02841, South Korea and a Corresponding author.

Zero-shot Text-to-Speech: How Does the Performance of HierSpeech++ Fare With Other Baselines?

Society might be learning tech, or not, but that is not MY concern. What my concern is my human on that computer who leaves me looking like the above photo. is She is addicted and I am ignored. Introduce Yourself Sisu I am a . I am 5 years old. Although my mom used to know for sure. Now she thinks this is how old I am. I am happy for the most part. I am happy when I am soaking in the bath with candles and jazz playing. I’ve been living with my human since I was 8 months old. She is pretty cool until ……. sulcata tortoise Until What? She is the victim of from a data breach. I know this because she has told me all about it 500 times. identity fraud How Has This Affected Your Life? She started learning all she could about tech stuff, from data breaches and ID fraud to crell reports. Do You Mean Credit Reports? Sisu gave no answer! What Is a Good Thing About Computers You’ve Noticed? Well, she does take some awesome pictures of me. We were walking down by Lake Michigan last Sunday and people stopped me to take my photo. I started to sorta pose. I am sure that now I am  a viral sensation. Internet sensation at the very least. Also, my human has started to learn so much about tech. She is learning code now. She is 54 and a widow. This shows me that learning begins at any age by will and determination even at the expense of the tortoise that lives with you. What Do You Want to Say About ID Fraud That You Didn’t Know Before? Before?? Before my life was easy peasy. My human would humor me all day. Now???? she cries and gets mad and tells me she promises to spend time tomorrow but she is too tired the nest day and her brain is fried. Although the data breach wasn’t her fault because it was from Equifax. She said to me that they are supposed to protect not destroy and deny. I say if you don’t want your tortoise to look like the above picture.. then be viligent…I mean vigilant. Right? I never used to second guess myself before this fraud…. Anyway…. Do not think it can’t happen to your human. Talk to your human. Tell them how important it is to check crell reports frequently. To open an account at my social security online. Check, follow up and be suspicious. Because the alternative is me walking around with calcium all over my face and no one cares.

What Its Like for Me, Sisu the Tortoise, to Live With a Human Who Is Learning Tech

Realistic Text-to-Speech Voice Synthesis: Comparing Tortoise and Bark

If you’ve subscribed to my newsletter, , you know that I’m more tortoise, less hare. Steady persistence rather than bursts of frenetic activity. Marathons, not sprints. Crypto is Easy Most people are here to make as much money as possible as quickly as they can. What’s the next 100x altcoin? Is the bottom in? What on-chain data can predict the future? I’m here to squeeze the most juice out of the market. Buy low and grow. Sell only when the market forces you to do so (hopefully not at all). Build slowly and safely. Let the market do the hard work for you. Mark, that’s so dumb. THE WHOLE POINT IS TO SELL! Maybe. Be careful about that. I’ve lost a lot of money from selling crypto. I’ve lost far less from buying it. Down 99% No. It’s all about pace and patience. When you buy only after bitcoin’s price crashes 30% (50–70% drops for altcoins), you don’t need to take profits. You’ve limited your downside while still giving yourself all of the upside or more. As the market falls further, you get better value for each new dollar you put in. You can stop buying once the market goes up and the hares come hopping back into the market, chasing prices upward. That’s when you save your money for the next crash. Sometimes, those crashes last a week. Sometimes, they last a year. For example, if you followed my plan, you’d have sat on your hands for most of 2021, buying only from mid-May to early August and again for 10 days at the end of September. See My Plan That may seem lame because everybody else was getting rich at the beginning and end of the year. But were they? Most traders lost money. With dollar-cost averaging, you would have finished the year down 3% on your investment. With my plan, you would have finished the year up at least 17%, with money to spare. That spare cash came in handy for buying as the market went down in 2022. (With altcoins, the results are all over the place. On some, I’m down +90%. On others, I’m up 1,200% as of this post.) Once the market turns around, you can enjoy the fruits of the hard work you’ve put in. If you need cash, sell your crypto. Or, spend it. You won’t need to be tactical or defensive. You can just treat it like everything else you own. Let the hares tire themselves out chasing after a market that’s running away from them. They can fuss about taking profits, buying with leverage, catching the dips, timing the peaks, and finding the moonshots. You can relax and appreciate your good fortune. Win-win When you have an asset class with so much upside and massive tailwinds, you don’t need to push too hard. Buy when you need to, let the market go up, and save cash for the next opportunity. You win either way: When prices go up, the value of your crypto does, too. When prices go down low enough, you get to buy more, usually at a steep discount. While dollar-cost averaging has its advantages and a good trader will do far better, sometimes “good enough” is good enough. Once in a while, you might get an altseason. Use that time to shed dead altcoins and good projects that didn’t work out the way you expected. Hang on to the rest. They’ll crash 80–95% as everything else does. Buy them on their way down or after the dust settles. Wait for the bull market? Some say friends don’t let friends buy altcoins during bear markets. Others say to save cash for new projects that will come along in the next few years. “Never buy a falling knife, only buy on the way up.” Fair enough. When does the bull market start? What price? What date? If you wait for the bull market, the only guarantee is you will buy at higher prices. For example, if you bought random cryptos in 2019, a true crypto winter, you would have peaked at a 3,000% gain. If you waited until December 2020, once everybody agreed the bull market was back, you would have peaked at a 450% gain. You can see that on this chart of the total crypto market cap. Given the same risk and volatility, would you rather wager the same amount of money for a bigger gain or a smaller gain? Once you wait for the bull market, you’ll wager the same amount of money for a smaller gain. Even if the market only goes up 200% from now until the bull market starts, that means you’ll have to bring 200% more money into the market compared to today. Also, if you wait, you will still suffer 30–50% crashes after you buy. These are more common in bull markets than bear markets, as you can see below. Today’s market is awesome. You can find lots of interesting projects at low prices. You get to interact with earnest teams and communities that care about their projects. You can stake their tokens for rewards, delegate them for profit, or deposit them into liquidity pools for a share of the fees. You can buy metaverse land for pennies on the dollar and your smart contract fees are lower than ever. If you wait for confirmation that the bottom’s in, consider the money you will lose from waiting. You can make up for bad timing. Complacency kills. No risk it, no biscuit Cash is losing value at the fastest rate in years. The US government is trying to destroy the price of everything, everywhere. China’s property market will implode without stimulus and subsidies. England and Japan need extensive government interventions to keep their currency and debt markets from collapsing. The European Central Bank remains ambiguous about whether to raise rates into an energy crisis and possibly trigger sovereign debt defaults for some of its member countries or let inflation run wild and possibly watch the Eurozone collapse. Meanwhile, the crypto market is down 70% since November 2021. Does it seem reckless to put money into crypto when it’s dangling off the edge of a cliff and the world’s largest economies seem destined for a catastrophe? Maybe. At least bitcoin works when your banks, governments, businesses, and credit card companies don’t. You can’t eat it, but you can mine it for heat in the winter. That’s more than you can say for stocks and bonds. Altcoins are far more volatile but not necessarily riskier at these prices. Your downside is still capped at 100% while your upside is limitless. For tokens that offer staking rewards, you get free crypto while you wait for the market to recover. Why risk that upside to avoid the same 100% loss you can get at higher prices? No need to wait, no time to rush Some people will always wait for confirmation that “the bottom’s in,” central banks start printing money again, and the “macro” situation improves. Let them. That will give us more time to accumulate tokens and participate in their related projects. After 3AC, Luna, and lending platforms collapsed, we need to give the crypto market time to rebuild its foundation. Your favorite stock will probably never return 500% in five years. Some altcoins will, and they’ll do far better over time. Let their prices rise and wait for the next crash to give you another chance to buy, maybe even at today’s prices. Many of the best projects have actual development, experience, and genuine community growth — something that altcoins never had before. Bitcoin’s in a 13-year uptrend with massive tailwinds. The technology now supports actual real-world usage (though it still lacks engagement). When you put your money on the line for a chance to grow your stakes in the financial networks of the future, you also suffer whatever consequences come your way. Is it wrong to accept some loss in exchange for a much larger gain, over time? The hares work in frantic bursts of energy, with urgency and haste. That serves them well in life, but not necessarily in crypto. Tortoises understand that crypto is a long race that takes courage, patience, and persistence. One day, possibly sooner than you think, the hares will have their moment again. For now, let them sleep. They need their rest. We tortoises will continue to plug along, pace ourselves, and ultimately, win the race. This post is also available as an NFT on the following platforms: SolType Mirror Mark Helfman publishes the newsletter. He is also the author of three books and a top bitcoin writer on and . Learn more about him in his . Crypto is Easy Medium Hacker Noon bio

Make Way for the Crypto Tortoise

AI and RAG in Knowledge Graph Enlightenment 

is an online community that covers the latest international AI/ML developments. We are fascinated by technological progress and strive to bring a worldwide perspective to AI discussions. Check out our first big project! AIport AIport has put together Volume 1 of the . This is the first generative AI landscape analysis to emphasize regional attributes and encompass nations than other similar editions. Global Generative AI Landscape 2024 four times more Our goal at is to offer a balanced overview of the GenAI sector, showcasing contributions from across the globe, beyond the usual focus on North American and European entities. AIport How We Came Up With the Idea We noticed that many generative AI landscapes tend to focus either on the Silicon Valley giants or the tech powerhouses of Europe, covering no more than 10 countries on average. While this approach does serve its purpose, it can’t really offer a complete picture. To address this, we decided to dig deeper, and this is what we came up with after weeks of research. We believe Volume 1 of our Global Generative AI Landscape 2024 provides an objectively international outlook. About the Research We examined all countries that invest in the AI market, as featured in the by Tortoise. In-house model developers were identified, filtered by the team of editors and data scientists, and subsequently cross-referenced with current GenAI landscapes from , , , and others, before being segmented into ten GenAI categories. 62 Global AI Index Sequoia Capital Antler Base10 As the final step, the data was divided into continental regions: North America, South America, Europe, Asia, Oceania, and Africa. The landscape details which players are developing GenAI solutions, their locations, and the specific nature of their contributions. It contains a total of generative models from companies. 128 107 Key Highlights Of the 62 countries listed in the , only 35 develop their GenAI solutions in-house. Roughly 90% of them focus on one model type. Global AI Index Among the top five nations in the Index, South Korea and Singapore are notably absent from our list of top GenAI developers, suggesting these nations prioritize investment in other AI domains. Conversely, Israel, ranked seventh by Tortoise, has secured a spot on our GenAI development shortlist. Regional leaders by the number of active GenAI companies are North America – USA; South America – Argentina; Europe – UK and France; Asia – China and Israel; Oceania – Australia and New Zealand; Africa – South Africa. The average number of GenAI models per company is the highest in North America, being the only region to have at least one model from each of the 10 model categories. Approximately 10% of all companies covered in the study have implemented multimodality in their GenAI models, with a majority of these developers located in the US. This indicates that while multimodality represents an emerging trend, its adoption outside North America still remains in the nascent stages. A total of 11 companies worldwide have developed more than one type of GenAI model. Stability AI leads with five distinct GenAI model types (image, video, audio, 3D, and code), followed closely by OpenAI (chatbot, audio, video, and multimodal) and Google (text, image, audio, and multimodal) – both with four model types. Microsoft, Meta, Tencent, Baidu, and Yandex are among those companies that developed between two to three types of distinct GenAI models. 13 companies have developed multiple models within a single GenAI category. AssemblyAI has two speech-to-text models, MosaicML offers two iterations of its MPT for code generation, while IPOXCap has introduced two chatbots designed for business intelligence applications. to get more insights from the global AI/ML landscape! Subscribe to AIport

Global GenAI Landscape 2024: Roughly Half of Nations That Invest in AI Develop Generative Models

গ্লোবাল GenAI ল্যান্ডস্কেপ 2024: প্রায় অর্ধেক দেশ যারা AI তে বিনিয়োগ করে জেনারেটিভ মডেল তৈরি করে

Globale GenAI-Landschaft 2024: Etwa die Hälfte der Nationen, die in KI investieren, entwickeln generative Modelle

Panorama global de GenAI 2024: Aproximadamente la mitad de las naciones que invierten en IA desarrollan modelos generativos

Paysage mondial de GenAI 2024 : environ la moitié des pays qui investissent dans l’IA développent des modèles génératifs

ग्लोबल जेनएआई लैंडस्केप 2024: एआई में निवेश करने वाले लगभग आधे देश जेनरेटिव मॉडल विकसित करते हैं

Global GenAI Landscape 2024: AI に投資する国の約半数が生成モデルを開発

2024년 글로벌 GenAI 환경: AI에 투자하는 국가의 약 절반이 생성 모델 개발

Cenário global da GenAI 2024: Aproximadamente metade das nações que investem em IA desenvolvem modelos generativos

Глобальный ландшафт генИИ в 2024 году: примерно половина стран, инвестирующих в ИИ, разрабатывают генеративные модели

Küresel Yapay Zeka Görünümü 2024: Yapay Zekaya Yatırım Yapan Ülkelerin Yaklaşık Yarısı Üretken Modeller Geliştiriyor

Bối cảnh GenAI toàn cầu năm 2024: Khoảng một nửa số quốc gia đầu tư vào AI phát triển các mô hình sáng tạo

2024 年全球 GenAI 格局：大约一半投资人工智能的国家开发生成模型

In an exciting development for cryptocurrency enthusiasts and fans alike, Blastoise has been officially recognized as the mascot meme coin of Blast, the cutting-edge Layer 2  blockchain. meme coin The Appeal Of Blastoise Since its launch in January as one of the pioneering meme coins to kickstart marketing efforts on Blast, Blastoise has rapidly grown to become a top token within the crypto ecosystem. It stands out in the meme coin space, which is often driven by hype and community engagement. Factors Behind Blastoise Success The rise of Blastoise can be attributed to several factors. Firstly, the meme coin market is known for repetitive designs, with numerous dog-themed memes flooding the market and needing more imagination. Blastoise provides a change from the norm with its meme designs heavily influenced by turtles and tortoises, which has resonated with a broad audience, giving it a unique position in the crowded memecoin space. Secondly, Blastoise provides an ecosystem where users can use their tortoise-themed NFT cards to play battle royale games, get rewarded, and enjoy the full gamefi experience. This ensures an active community of users that are invested in its ecosystem beyond the thrill of just owning a meme coin. Lastly, Six weeks after its debut, Blastoise made a significant impact by collaborating with Bitconnect token, the official meme decentralized exchange (DEX) on Blast. Together, they unveiled BlastList, an innovative that serves as a developer-first API for querying Blast deposits directly onchain. This tool, which is free for any project to utilize, exemplifies Blastoise's commitment to fostering a developer-friendly environment on Blast. smart contract Built on Blast: An Innovative Layer 2 Blockchain Blastoise is built on the Blast, regarded as one of the fastest-growing Layer-2 blockchain platforms. Blast stands out as the first L2 solution to incorporate native yield, supported by industry giants such as Paradigm and led by the visionary Pacman, the founder of Blur, the leading NFT marketplace protocol on Ethereum. Blast aims to expand the on-chain economy by providing the highest-yield L2 possible, offering a default interest rate of 4% for ETH and 5% for stablecoins, compared to the 0% standard on other L2s. This initiative is further enhanced by the opportunity for community members to earn through the Blast Airdrop. Blastoise Continues To Make Key Moves Blastoise's journey is further boosted by strategic partnerships with influential market makers and Blast native protocols, including Bitconnect and Fantasy Fantasy, a SocialFi Trading Card Game (TCG). These collaborations aim to cement Blastoise's position as the central figure in Blast's meme culture and build a comprehensive ecosystem within this vibrant blockchain space. The excitement surrounding Blastoise as the top mascot token on Blast is visible, with endorsements from key players like OSF rekt, Blast angel investors, and influential market movers. Drawing parallels with other successful first-mover mascot tokens such as Pepe on Ethereum and Dogwifhat on Solana, Blastoise is set to grow in trading volume and market presence. Looking ahead, Blastoise has set its sights on dominating the meme coin sector on Blast, leveraging its partnerships to create a robust ecosystem that rewards Blastoise holders with Blast native rewards. The goal is clear: to achieve the largest market share on Blast and foster a community where meme culture thrives alongside innovative DeFi solutions. Blastoise Social Media Links | Twitter (X) Website This story was distributed as a release by BTCWire under HackerNoon’s Business Blogging Program. Learn more about the program here: https://business.hackernoon.com/

Blastoise: The Official Mascot Meme Coin of Blast's Cutting-Edge Layer 2 Blockchain

Blastoise: ব্লাস্টের কাটিং-এজ লেয়ার 2 ব্লকচেইনের অফিসিয়াল মাসকট মেম মুদ্রা

Blastoise: Die offizielle Maskottchen-Meme-Münze der hochmodernen Layer-2-Blockchain von Blast

Blastoise: la moneda meme mascota oficial de la innovadora cadena de bloques de capa 2 de Blast

Blastoise : la pièce mème mascotte officielle de la blockchain de pointe de couche 2 de Blast

ब्लास्टोइस: ब्लास्ट की अत्याधुनिक परत 2 ब्लॉकचेन का आधिकारिक शुभंकर मेम सिक्का

Blastoise: Blast の最先端のレイヤー 2 ブロックチェーンの公式マスコット ミーム コイン

Blastoise: Blast의 최첨단 레이어 2 블록체인의 공식 마스코트 Meme 코인

Blastoise: a moeda meme mascote oficial do blockchain de camada 2 de última geração da Blast

Blastoise: официальная монета-талисман передового блокчейна второго уровня Blast

Blastoise: Blast'ın Son Teknoloji Katman 2 Blockchain'inin Resmi Maskot Meme Parası

Blastoise: Đồng xu Meme linh vật chính thức của Blockchain lớp 2 tiên tiến của Blast

Blastoise：Blast 尖端第 2 层区块链的官方吉祥物模因币

Page Curves of Reissner-Nordström Black Hole in HD Gravity

If you're familiar with Git's powerful features and prefer using it for your development process, but your company uses SVN (specifically ) for version control, you might wonder if you can use both. Good news: you can. They can work independently without conflict. We'll guide you on how to use Git alongside SVN. TortoiseSVN The 4 Steps to Follow Step 1: : Checkout Project with SVN Start by checking out the project from SVN. Once you've done this, you will notice a hidden folder in your project directory. This is where SVN keeps track of its version control information. .svn Step 2: : Initialize Git Navigate to the root of your project directory using your terminal, and initiate a Git repository by running the command. This creates a hidden folder, where Git stores its version control information. git init .git Step 3: : Configure Git to Ignore SVN Create a file in your project root directory to instruct Git to ignore certain files. To do this, use the command, and open it for editing. Add to the file. This line tells Git to ignore the SVN version control files. You can check for success with the command . .gitignore touch .gitignore /.svn/ .gitignore git status --ignored Step 4: : Configure SVN to Ignore Git Similarly, you need to tell SVN to ignore Git's version control files. To do this, add the folder and the file to SVN's ignore list. This can be done through the TortoiseSVN context menu. Refer to Figures 1 and 2 for detailed steps. .git .gitignore Now, you have successfully set up your project to use both Git and SVN simultaneously, each ignoring the version control files of the other. You can now enjoy the features of Git during development while still adhering to your company's version control regulations. Also published here

Stories, News & Mentions about TORTOISE

Tortoise’s Stories on HackerNoon

Tortoise's News & Mentions